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1
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Han D, Sojic N, Jiang D. Spatial Profiling of Multiple Enzymatic Activities at Single Tissue Sections via Fenton-Promoted Electrochemiluminescence. J Am Chem Soc 2025; 147:9610-9619. [PMID: 40063963 DOI: 10.1021/jacs.4c17749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2025]
Abstract
Profiling multiple enzymatic activities in tissue is crucial for understanding complex metabolic and signaling networks, yet remains a challenge with existing optical microscopies. Here, we developed a Fenton-promoted luminol electrochemiluminescence (ECL) imaging method to achieve the spatial mapping of multiple enzymatic activities within a single tissue section. This method quantitatively visualizes individual enzymatic activity by combining the enzymatic conversion of substrates with the chemical confinement of the locally produced hydrogen peroxide. To achieve high-resolution spatial imaging by limiting the diffusion (∼500 μm) of hydrogen peroxide, iron oxide nanoparticles were coated on the tissue surface to initiate the Fenton process, locally converting hydrogen peroxide into short-lived hydroxyl radicals with a nanometer-scale diffusion range. The Fenton-promoted ECL emission is confined at the enzymatic conversion sites, offering unprecedented spatial visualization of four tumor-associated oxidases within a single tissue section. Colocalization revealed a synergistic effect between lysyl oxidase and quiescin sulfhydryl oxidase on post-translational modifications of tumor extracellular matrix proteins, along with a previously undiscovered interaction with amiloride-sensitive amine oxidase, which could not be distinguished based on expressions or single enzymatic activity alone. This approach offers a novel activity-based protein profiling tool at the tissue level, providing new data for future enzynomic research and multimodal imaging.
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Affiliation(s)
- Dongni Han
- State Key Laboratory of Analytical Chemistry for Life Science and School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210093, China
| | - Neso Sojic
- University of Bordeaux, CNRS, Bordeaux INP, ISM, UMR, 5255, F-33400 Talence, France
| | - Dechen Jiang
- State Key Laboratory of Analytical Chemistry for Life Science and School of Chemistry and Chemical Engineering, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210093, China
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2
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Nguyen T, Pelletier G, Bednaršek N, Gracey A. Single-Larva RNA Sequencing Reveals That Red Sea Urchin Larvae Are Vulnerable to Co-Occurring Ocean Acidification and Hypoxia. Mol Ecol 2025; 34:e17658. [PMID: 39822122 DOI: 10.1111/mec.17658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 01/02/2025] [Accepted: 01/06/2025] [Indexed: 01/19/2025]
Abstract
Anthropogenic carbon dioxide emissions have been increasing rapidly in recent years, driving pH and oxygen levels to record low concentrations in the oceans. Eastern boundary upwelling systems such as the California Current System (CCS) experience exacerbated ocean acidification and hypoxia (OAH) due to the physical and chemical properties of the transported deeper waters. Research efforts have significantly increased in recent years to investigate the deleterious effects of climate change on marine species, but have not focused on the impacts of simultaneous OAH stressor exposure. Additionally, few studies have explored the physiological impacts of these environmental stressors on the earliest life stages, which are more vulnerable and represent natural population bottlenecks in organismal life cycles. The physiological response of the ecologically and commercially important red sea urchin (Mesocentrotus franciscanus) was assessed by exposing larvae to a variety of OAH conditions, mimicking the range of ecologically relevant conditions encountered currently and in the near future along the CCS. Skeleton dissolution, larval development, and gene expression show a response with clearly delineated thresholds that were related to OAH severity. Skeletal dissolution and the induction of Acid-sensing Ion Channel 1A at pH 7.94/5.70 DO mg/L provide particularly sensitive markers of OAH, with dramatic shifts in larval morphology and gene expression detected at the pH/DO transition of 7.71/3.71-7.27/2.72 mg/L. Experimental simulations that describe physiological thresholds and establish molecular markers of OAH exposure will provide fishery management with the tools to predict patterns of larval recruitment and forecast population dynamics.
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Affiliation(s)
- Tina Nguyen
- Marine and Environmental Biology, University of Southern California, Los Angeles, California, USA
| | - Greg Pelletier
- Washington Department of Ecology, Olympia, Washington, USA
| | - Nina Bednaršek
- Cooperative Institute for Marine Resources Studies, Hatfield Marine Science Center, Oregon State University, Corvallis, Oregon, USA
- Department of Environmental Sciences, Jozef Stefan Institute, Ljubljana, Slovenia
| | - Andrew Gracey
- Marine and Environmental Biology, University of Southern California, Los Angeles, California, USA
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3
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Li X, Xue C, Zhu Z, Yu X, Yang Q, Cui L, Li M. Application of GWAS summary data and drug-induced gene expression profiles of neural progenitor cells in psychiatric drug prioritization analysis. Mol Psychiatry 2025; 30:111-121. [PMID: 39003413 DOI: 10.1038/s41380-024-02660-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 06/24/2024] [Accepted: 07/02/2024] [Indexed: 07/15/2024]
Abstract
Common psychiatric disorders constitute one of the most substantial healthcare burdens worldwide. However, drug development in psychiatry remains hampered partially due to the lack of approaches to estimating drugs that can simultaneously modulate the expression of a nontrivial fraction of disease susceptibility genes. We proposed a new drug prioritization strategy under the framework of our previously proposed phenotype-associated tissues estimation approach (DESE) by investigating the drugs' selective perturbation effect on disease susceptibility genes. Based on the genome-wide association study summary data and drug-induced gene expression profiles of neural progenitor cells, we applied this strategy to prioritize candidate drugs for schizophrenia, depression and bipolar I disorder and identified several known therapeutic drugs among the top-ranked drug candidates. Also, our results revealed that the disease susceptibility genes involved in the selective gene perturbation analysis were enriched with many biologically sensible function terms and interacted with known therapeutic drugs. Our results suggested that selective gene perturbation analysis could be a promising starting point to prioritize biologically sensible drug candidates under the "one drug, multiple targets" paradigm for the drug development of common psychiatric disorders.
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Affiliation(s)
- Xiangyi Li
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
- Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, Guangdong, China
| | - Chao Xue
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Zheng Zhu
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Xuegao Yu
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Qi Yang
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Liqian Cui
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China.
- Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, Guangzhou, 510080, Guangdong, China.
- National Key Clinical Department and Key Discipline of Neurology, Guangzhou, 510080, Guangdong, China.
| | - Miaoxin Li
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China.
- Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, Guangdong, China.
- Research Center of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong, Guangzhou, 510080, China.
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China.
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, 519000, Guangdong, China.
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Alqabandi JA, David R, Abdel-Motal UM, ElAbd RO, Youcef-Toumi K. An innovative cellular medicine approach via the utilization of novel nanotechnology-based biomechatronic platforms as a label-free biomarker for early melanoma diagnosis. Sci Rep 2024; 14:30107. [PMID: 39627312 PMCID: PMC11615046 DOI: 10.1038/s41598-024-79154-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 11/06/2024] [Indexed: 12/06/2024] Open
Abstract
Innovative cellular medicine (ICM) is an exponentially emerging field with a promising approach to combating complex and ubiquitous life-threatening diseases such as multiple sclerosis (MS), arthritis, Parkinson's disease, Alzheimer's, heart disease, and cancer. Together with the advancement of nanotechnology and bio-mechatronics, ICM revolutionizes cellular therapy in understanding the essence and nature of the disease initiated at a single-cell level. This paper focuses on the intricate nature of cancer that requires multi-disciplinary efforts to characterize it well in order to achieve the objectives of modern world contemporary medicine in the early detection of the disease at a cellular level and potentially arrest its proliferation mechanism. This justifies the multidisciplinary research backgrounds of the authors of this paper in advancing cellular medicine by bridging the gap between experimental biology and the engineering field. Thus, in pursuing this approach, two novel miniaturized and highly versatile biomechatronic platforms with dedicated operating software and microelectronics are designed, modeled, nanofabricated, and tested in numerous in vitro experiments to investigate a hypothesis and arrive at a proven theorem in carcinogenesis by interrelating cellular contractile force, membrane potential, and cellular morphology for early detection and characterization of melanoma cancer cells. The novelties that flourished within this work are manifested in sixfold: (1) developing a mathematical model that utilizes a Heaviside step function, as well as a pin-force model to compute the contractile force of a living cell, (2) deriving an expression of cell-membrane potential based on Laplace and Fourier Transform and their Inverse Transform functions by encountering Warburg diffusion impedance factor, (3) nano-fabricating novel biomechatronic platforms with associated microelectronics and customized software that extract cellular physics and mechanics, (4) developing a label-free biomarker, (5) arrive at a proved theorem in developing a mathematical expression in relating cancer cell mechanobiology to its biophysics in connection to the stage of the disease, and (6) to the first time in literature, and to the best of the authors' knowledge, discriminating different stages and morphology of cancer cell melanoma based on their cell-membrane potentials, and associated contractile forces that could introduce a new venue of cellular therapeutic modalities, preclinical early cancer diagnosis, and a novel approach in immunotherapy drug development. The proposed innovative technology-based versatile bio-mechatronic platforms shall be extended for future studies, investigating the role of electrochemical signaling of the nervous system in cancer formation that will significantly impact modern oncology by pursuing a targeted immunotherapy approach. This work also provides a robust platform for immunotherapy practitioners in extending the study of cellular biophysics in stalling neural-cancer interactions, of which the FDA-approved chimeric antigen receptor (CAR)-T cell therapies can be enhanced (genetically engineered) in a lab by improving its receptors to capture cancer antigens. This work amplifies the importance of studying neurotransmitters and electrochemical signaling molecules in shaping the immune T-cell function and its effectiveness in arresting cancer proliferation rate (mechanobiology mechanism).
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Affiliation(s)
- Jassim A Alqabandi
- Mechatronics Research Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
- Mechatronics in Medicine Laboratory, Imperial College London, London, UK.
- Department of Manufacturing Engineering Technology (Bio-Mechatronics) Department, PAAET, Kuwait, State of Kuwait.
| | - Rhiannon David
- Division of Computational and Systems Medicine (CSM), Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, London, UK
| | - Ussama M Abdel-Motal
- Department of Cancer Immunology and AIDS, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Rawan O ElAbd
- McGill University Health Center, Montreal, QC, Canada
| | - Kamal Youcef-Toumi
- Mechatronics Research Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
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5
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Abdulsahib S, Boswell W, Boswell M, Savage M, Schartl M, Lu Y. Transcriptional background effects on a tumor driver gene in different pigment cell types of medaka. JOURNAL OF EXPERIMENTAL ZOOLOGY. PART B, MOLECULAR AND DEVELOPMENTAL EVOLUTION 2024; 342:252-259. [PMID: 37877158 PMCID: PMC11043209 DOI: 10.1002/jez.b.23224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/28/2023] [Accepted: 09/14/2023] [Indexed: 10/26/2023]
Abstract
The Xiphophorus melanoma receptor kinase gene, xmrk, is a bona fide oncogene driving melanocyte tumorigenesis of Xiphophorus fish. When ectopically expressed in medaka, it not only induces development of several pigment cell tumor types in different strains of medaka but also induces different tumor types within the same animal, suggesting its oncogenic activity has a transcriptomic background effect. Although the central pathways that xmrk utilizes to lead to melanomagenesis are well documented, genes and genetic pathways that modulate the oncogenic effect and alter the course of disease have not been studied so far. To understand how the genetic networks between different histocytes of xmrk-driven tumors are composed, we isolated two types of tumors, melanoma and xanthoerythrophoroma, from the same xmrk transgenic medaka individuals, established the transcriptional profiles of both xmrk-driven tumors, and compared (1) genes that are co-expressed with xmrk in both tumor types, and (2) differentially expressed genes and their associated molecular functions, between the two tumor types. Transcriptomic comparisons between the two tumor types show melanoma and xanthoerythrophoroma are characterized by transcriptional features representing varied functions, indicating distinct molecular interactions between the driving oncogene and the cell-type-specific transcriptomes. Melanoma tumors exhibit gene signatures that are relevant to proliferation and invasion, while xanthoerythrophoroma tumors are characterized by expression profiles related to metabolism and DNA repair. We conclude the transcriptomic backgrounds, exemplified by cell-type-specific genes that are downstream of xmrk effected signaling pathways, contribute the potential to change the course of tumor development and may affect overall tumor outcomes.
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Affiliation(s)
- Shahad Abdulsahib
- Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, 419 Centennial Hall, Texas State University, San Marcos, TX, USA
| | - William Boswell
- Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, 419 Centennial Hall, Texas State University, San Marcos, TX, USA
| | - Mikki Boswell
- Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, 419 Centennial Hall, Texas State University, San Marcos, TX, USA
| | - Markita Savage
- Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, 419 Centennial Hall, Texas State University, San Marcos, TX, USA
| | - Manfred Schartl
- Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, 419 Centennial Hall, Texas State University, San Marcos, TX, USA
- Developmental Biochemistry, Biozentrum, University of Würzburg, Würzburg, Germany
| | - Yuan Lu
- Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, 419 Centennial Hall, Texas State University, San Marcos, TX, USA
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Makowska A, Weiskirchen R. Nasopharyngeal Carcinoma Cell Lines: Reliable Alternatives to Primary Nasopharyngeal Cells? Cells 2024; 13:559. [PMID: 38606998 PMCID: PMC11011377 DOI: 10.3390/cells13070559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 03/17/2024] [Accepted: 03/20/2024] [Indexed: 04/13/2024] Open
Abstract
Nasopharyngeal carcinoma (NPC) is a type of cancer that originates from the mucosal lining of the nasopharynx and can invade and spread. Although contemporary chemoradiotherapy effectively manages the disease locally, there are still challenges with locoregional recurrence and distant failure. Therefore, it is crucial to have a deeper understanding of the molecular basis of NPC cell movement in order to develop a more effective treatment and to improve patient survival rates. Cancer cell line models are invaluable in studying health and disease and it is not surprising that they play a critical role in NPC research. Consequently, scientists have established around 80 immortalized human NPC lines that are commonly used as in vitro models. However, over the years, it has been observed that many cell lines are misidentified or contaminated by other cells. This cross-contamination leads to the creation of false cell lines that no longer match the original donor. In this commentary, we discuss the impact of misidentified NPC cell lines on the scientific literature. We found 1159 articles from 2000 to 2023 that used NPC cell lines contaminated with HeLa cells. Alarmingly, the number of publications and citations using these contaminated cell lines continued to increase, even after information about the contamination was officially published. These articles were most commonly published in the fields of oncology, pharmacology, and experimental medicine research. These findings highlight the importance of science policy and support the need for journals to require authentication testing before publication.
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Affiliation(s)
- Anna Makowska
- Division of Pediatric Hematology, Oncology and Stem Cell Transplantation, RWTH University Hospital Aachen, D-52074 Aachen, Germany
| | - Ralf Weiskirchen
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), RWTH University Hospital Aachen, D-52074 Aachen, Germany
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7
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Zhou J, Wu Q, Zhou M, Wen J, Al-Turki Y, Abusorrah A. LAGAM: A Length-Adaptive Genetic Algorithm With Markov Blanket for High-Dimensional Feature Selection in Classification. IEEE TRANSACTIONS ON CYBERNETICS 2023; 53:6858-6869. [PMID: 36374903 DOI: 10.1109/tcyb.2022.3163577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Feature selection (FS) is an essential technique widely applied in data mining. Recent studies have shown that evolutionary computing (EC) is very promising for FS due to its powerful search capability. However, most existing EC-based FS methods use a length-fixed encoding to represent feature subsets. This inflexible encoding turns ineffective when high-dimension data are handled, because it results in a huge search space, as well as a large amount of training time and memory overhead. In this article, we propose a length-adaptive genetic algorithm with Markov blanket (LAGAM), which adopts a length-variable individual encoding and enables individuals to evolve in their own search space. In LAGAM, features are rearranged decreasingly based on their relevance, and an adaptive length changing operator is introduced, which extends or shortens an individual to guide it to explore in a better search space. Local search based on Markov blanket (MB) is embedded to further improve individuals. Experiments are conducted on 12 high-dimensional datasets and results reveal that LAGAM performs better than existing methods. Specifically, it achieves a higher classification accuracy by using fewer features.
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8
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Yang D, Zhang S, Zheng C, Zhou G, Hu Y, Hao Q. Refractive index tomography with a physics-based optical neural network. BIOMEDICAL OPTICS EXPRESS 2023; 14:5886-5903. [PMID: 38021108 PMCID: PMC10659804 DOI: 10.1364/boe.504242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/27/2023] [Accepted: 09/27/2023] [Indexed: 12/01/2023]
Abstract
The non-interference three-dimensional refractive index (RI) tomography has attracted extensive attention in the life science field for its simple system implementation and robust imaging performance. However, the complexity inherent in the physical propagation process poses significant challenges when the sample under study deviates from the weak scattering approximation. Such conditions complicate the task of achieving global optimization with conventional algorithms, rendering the reconstruction process both time-consuming and potentially ineffective. To address such limitations, this paper proposes an untrained multi-slice neural network (MSNN) with an optical structure, in which each layer has a clear corresponding physical meaning according to the beam propagation model. The network does not require pre-training and performs good generalization and can be recovered through the optimization of a set of intensity images. Concurrently, MSNN can calibrate the intensity of different illumination by learnable parameters, and the multiple backscattering effects have also been taken into consideration by integrating a "scattering attenuation layer" between adjacent "RI" layers in the MSNN. Both simulations and experiments have been conducted carefully to demonstrate the effectiveness and feasibility of the proposed method. Experimental results reveal that MSNN can enhance clarity with increased efficiency in RI tomography. The implementation of MSNN introduces a novel paradigm for RI tomography.
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Affiliation(s)
- Delong Yang
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
| | - Shaohui Zhang
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, China
| | - Chuanjian Zheng
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
| | - Guocheng Zhou
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
| | - Yao Hu
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
| | - Qun Hao
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, China
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9
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M S K, Rajaguru H, Nair AR. Evaluation and Exploration of Machine Learning and Convolutional Neural Network Classifiers in Detection of Lung Cancer from Microarray Gene-A Paradigm Shift. Bioengineering (Basel) 2023; 10:933. [PMID: 37627818 PMCID: PMC10451477 DOI: 10.3390/bioengineering10080933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/03/2023] [Accepted: 08/04/2023] [Indexed: 08/27/2023] Open
Abstract
Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. The dataset used for the research is the Lung Harvard 2 Dataset (LH2) which consists of 150 Adenocarcinoma subjects and 31 Mesothelioma subjects. The paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Nonlinear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.
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Affiliation(s)
- Karthika M S
- Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam 638401, India;
| | - Harikumar Rajaguru
- Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam 638401, India;
| | - Ajin R. Nair
- Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam 638401, India;
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10
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Shi M, Liu X, Pan W, Li N, Tang B. Anti-inflammatory strategies for photothermal therapy of cancer. J Mater Chem B 2023. [PMID: 37326239 DOI: 10.1039/d3tb00839h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
High temperature generated by photothermal therapy (PTT) can trigger an inflammatory response at the tumor site, which not only limits the efficacy of PTT but also increases the risk of tumor metastasis and recurrence. In light of the current limitations posed by inflammation in PTT, several studies have revealed that inhibiting PTT-induced inflammation can significantly improve the efficacy of cancer treatment. In this review, we summarize the research progress made in combining anti-inflammatory strategies to enhance the effectiveness of PTT. The goal is to offer valuable insights for developing better-designed photothermal agents in clinical cancer therapy.
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Affiliation(s)
- Mingwan Shi
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Institute of Molecular and Nano Science, Shandong Normal University, Jinan 250014, P. R. China.
| | - Xiaohan Liu
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Institute of Molecular and Nano Science, Shandong Normal University, Jinan 250014, P. R. China.
| | - Wei Pan
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Institute of Molecular and Nano Science, Shandong Normal University, Jinan 250014, P. R. China.
| | - Na Li
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Institute of Molecular and Nano Science, Shandong Normal University, Jinan 250014, P. R. China.
| | - Bo Tang
- College of Chemistry, Chemical Engineering and Materials Science, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Institute of Molecular and Nano Science, Shandong Normal University, Jinan 250014, P. R. China.
- Laoshan Laboratory, Qingdao 266237, P. R. China
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11
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Phon BWS, Bhuvanendran S, Ayub Q, Radhakrishnan AK, Kamarudin MNA. Identification of Prominent Genes between 3D Glioblastoma Models and Clinical Samples via GEO/TCGA/CGGA Data Analysis. BIOLOGY 2023; 12:biology12050648. [PMID: 37237462 DOI: 10.3390/biology12050648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/28/2023]
Abstract
A paradigm shift in preclinical evaluations of new anticancer GBM drugs should occur in favour of 3D cultures. This study leveraged the vast genomic data banks to investigate the suitability of 3D cultures as cell-based models for GBM. We hypothesised that correlating genes that are highly upregulated in 3D GBM models will have an impact in GBM patients, which will support 3D cultures as more reliable preclinical models for GBM. Using clinical samples of brain tissue from healthy individuals and GBM patients from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases, several genes related to pathways such as epithelial-to-mesenchymal transition (EMT)-related genes (CD44, TWIST1, SNAI1, CDH2, FN1, VIM), angiogenesis/migration-related genes (MMP1, MMP2, MMP9, VEGFA), hypoxia-related genes (HIF1A, PLAT), stemness-related genes (SOX2, PROM1, NES, FOS), and genes involved in the Wnt signalling pathway (DKK1, FZD7) were found to be upregulated in brain samples from GBM patients, and the expression of these genes were also enhanced in 3D GBM cells. Additionally, EMT-related genes were upregulated in GBM archetypes (wild-type IDH1R132 ) that historically have poorer treatment responses, with said genes being significant predictors of poorer survival in the TCGA cohort. These findings reinforced the hypothesis that 3D GBM cultures can be used as reliable models to study increased epithelial-to-mesenchymal transitions in clinical GBM samples.
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Affiliation(s)
- Brandon Wee Siang Phon
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway 47500, Malaysia
| | - Saatheeyavaane Bhuvanendran
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway 47500, Malaysia
| | - Qasim Ayub
- School of Science, Monash University Malaysia, Bandar Sunway 47500, Malaysia
- Monash University Malaysia Genomics Facility, Monash University, Bandar Sunway 47500, Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, Bandar Sunway 47500, Malaysia
| | - Ammu Kutty Radhakrishnan
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway 47500, Malaysia
| | - Muhamad Noor Alfarizal Kamarudin
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway 47500, Malaysia
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12
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Claeys T, Menu M, Bouwmeester R, Gevaert K, Martens L. Machine Learning on Large-Scale Proteomics Data Identifies Tissue and Cell-Type Specific Proteins. J Proteome Res 2023; 22:1181-1192. [PMID: 36963412 PMCID: PMC10088018 DOI: 10.1021/acs.jproteome.2c00644] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2023]
Abstract
Using data from 183 public human data sets from PRIDE, a machine learning model was trained to identify tissue and cell-type specific protein patterns. PRIDE projects were searched with ionbot and tissue/cell type annotation was manually added. Data from physiological samples were used to train a Random Forest model on protein abundances to classify samples into tissues and cell types. Subsequently, a one-vs-all classification and feature importance were used to analyze the most discriminating protein abundances per class. Based on protein abundance alone, the model was able to predict tissues with 98% accuracy, and cell types with 99% accuracy. The F-scores describe a clear view on tissue-specific proteins and tissue-specific protein expression patterns. In-depth feature analysis shows slight confusion between physiologically similar tissues, demonstrating the capacity of the algorithm to detect biologically relevant patterns. These results can in turn inform downstream uses, from identification of the tissue of origin of proteins in complex samples such as liquid biopsies, to studying the proteome of tissue-like samples such as organoids and cell lines.
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Affiliation(s)
- Tine Claeys
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
| | - Maxime Menu
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
| | - Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
| | - Kris Gevaert
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
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Petrikaite V, D'Avanzo N, Celia C, Fresta M. Nanocarriers overcoming biological barriers induced by multidrug resistance of chemotherapeutics in 2D and 3D cancer models. Drug Resist Updat 2023; 68:100956. [PMID: 36958083 DOI: 10.1016/j.drup.2023.100956] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 02/28/2023] [Accepted: 03/07/2023] [Indexed: 03/14/2023]
Abstract
Multidrug resistance (MDR) is currently a big challenge in cancer therapy and limits its success in several patients. Tumors use the MDR mechanisms to colonize the host and reduce the efficacy of chemotherapeutics that are injected as single agents or combinations. MDR mechanisms are responsible for inactivation of drugs and formbiological barriers in cancer like the drug efflux pumps, aberrant extracellular matrix, hypoxic areas, altered cell death mechanisms, etc. Nanocarriers have some potential to overcome these barriers and improve the efficacy of chemotherapeutics. In fact, they are versatile and can deliver natural and synthetic biomolecules, as well as RNAi/DNAi, thus providing a controlled release of drugs and a synergistic effect in tumor tissues. Biocompatible and safe multifunctional biopolymers, with or without specific targeting molecules, modify the surface and interface properties of nanocarriers. These modifications affect the interaction of nanocarriers with cellular models as well as the selection of suitable models for in vitro experiments. MDR cancer cells, and particularly their 2D and 3D models, in combination with anatomical and physiological structures of tumor tissues, can boost the design and preparation of nanomedicines for anticancer therapy. 2D and 3D cancer cell cultures are suitable models to study the interaction, internalization, and efficacy of nanocarriers, the mechanisms of MDR in cancer cells and tissues, and they are used to tailor a personalized medicine and improve the efficacy of anticancer treatment in patients. The description of molecular mechanisms and physio-pathological pathways of these models further allow the design of nanomedicine that can efficiently overcome biological barriers involved in MDR and test the activity of nanocarriers in 2D and 3D models of MDR cancer cells.
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Affiliation(s)
- Vilma Petrikaite
- Laboratory of Drug Targets Histopathology, Institute of Cardiology, Lithuanian University of Health Sciences, Sukilėlių pr. 13, LT-50162 Kaunas, Lithuania; Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania.
| | - Nicola D'Avanzo
- Department of Pharmacy, University of Chieti - Pescara "G. d'Annunzio", Via dei Vestini 31, 66100 Chieti, Italy; Department of Experimental and Clinical Medicine, University "Magna Græcia" of Catanzaro Campus Universitario-Germaneto, Viale Europa, 88100 Catanzaro, Italy
| | - Christian Celia
- Laboratory of Drug Targets Histopathology, Institute of Cardiology, Lithuanian University of Health Sciences, Sukilėlių pr. 13, LT-50162 Kaunas, Lithuania; Department of Pharmacy, University of Chieti - Pescara "G. d'Annunzio", Via dei Vestini 31, 66100 Chieti, Italy
| | - Massimo Fresta
- Department of Health Sciences, University of Catanzaro "Magna Graecia", Viale "S. Venuta" s.n.c., 88100 Catanzaro, Italy
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Chen H, Peng F, Xu J, Wang G, Zhao Y. Increased expression of GPX4 promotes the tumorigenesis of thyroid cancer by inhibiting ferroptosis and predicts poor clinical outcomes. Aging (Albany NY) 2023; 15:230-245. [PMID: 36626251 PMCID: PMC9876627 DOI: 10.18632/aging.204473] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 12/16/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Ferroptosis plays a critical role in suppressing cancer progression, and its essential regulator is glutathione peroxidase 4 (GPX4). High GPX4 expression can inhibit accumulation of iron, thus suppressing ferroptosis. However, its function in thyroid cancer has not been fully illuminated. Here, we explore the effect of GPX4 on thyroid cancer tumorigenesis and prognosis. METHODS Based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, GPX4 expression was investigated in cancer tissues and adjacent tissues. We determined the biological functions of GPX4-associated differentially expressed genes (DEGs) by using the "clusterProfiler" R package. In addition, the predictive value of GPX4 in thyroid cancer was assessed by using Cox regression analysis and nomograms. Finally, we conducted several in vitro experiments to determine the influence of GPX4 expression on proliferation and ferroptosis in thyroid cancer cells. RESULTS GPX4 expression was obviously elevated in thyroid cancer tissues compared with normal tissues. Biological function analysis indicated enrichment in muscle contraction, contractile fiber, metal ion transmembrane transporter activity, and complement and coagulation cascades. GPX4 overexpression was associated with stage T3-T4 and pathologic stage III-IV in thyroid cancer patients. Cox regression analysis indicated that GPX4 may be a risk factor for the overall survival of thyroid cancer patients. In vitro research showed that knockdown of GPX4 suppressed proliferation and induced ferroptosis in thyroid cancer cells. CONCLUSIONS GPX4 overexpression in thyroid cancer might play an essential role in tumorigenesis and may have prognostic value for thyroid cancer patients.
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Affiliation(s)
- Huanjie Chen
- Department of General Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, People’s Republic of China
| | - Fang Peng
- Department of Pathology, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, People’s Republic of China
| | - Jingchao Xu
- Department of General Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, People’s Republic of China
| | - Guangzhi Wang
- Department of General Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, People’s Republic of China
| | - Yongfu Zhao
- Department of General Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, People’s Republic of China
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Mobashir M, Turunen SP, Izhari MA, Ashankyty IM, Helleday T, Lehti K. An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation. Cells 2022; 11:4121. [PMID: 36552885 PMCID: PMC9777290 DOI: 10.3390/cells11244121] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 12/14/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
To understand complex diseases, high-throughput data are generated at large and multiple levels. However, extracting meaningful information from large datasets for comprehensive understanding of cell phenotypes and disease pathophysiology remains a major challenge. Despite tremendous advances in understanding molecular mechanisms of cancer and its progression, current knowledge appears discrete and fragmented. In order to render this wealth of data more integrated and thus informative, we have developed a GECIP toolbox to investigate the crosstalk and the responsible genes'/proteins' connectivity of enriched pathways from gene expression data. To implement this toolbox, we used mainly gene expression datasets of prostate cancer, and the three datasets were GSE17951, GSE8218, and GSE1431. The raw samples were processed for normalization, prediction of differentially expressed genes, and the prediction of enriched pathways for the differentially expressed genes. The enriched pathways have been processed for crosstalk degree calculations for which number connections per gene, the frequency of genes in the pathways, sharing frequency, and the connectivity have been used. For network prediction, protein-protein interaction network database FunCoup2.0 was used, and cytoscape software was used for the network visualization. In our results, we found that there were enriched pathways 27, 45, and 22 for GSE17951, GSE8218, and GSE1431, respectively, and 11 pathways in common between all of them. From the crosstalk results, we observe that focal adhesion and PI3K pathways, both experimentally proven central for cellular output upon perturbation of numerous individual/distinct signaling pathways, displayed highest crosstalk degree. Moreover, we also observe that there were more critical pathways which appear to be highly significant, and these pathways are HIF1a, hippo, AMPK, and Ras. In terms of the pathways' components, GSK3B, YWHAE, HIF1A, ATP1A3, and PRKCA are shared between the aforementioned pathways and have higher connectivity with the pathways and the other pathway components. Finally, we conclude that the focal adhesion and PI3K pathways are the most critical pathways, and since for many other pathways, high-rank enrichment did not translate to high crosstalk degree, the global impact of one pathway on others appears distinct from enrichment.
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Affiliation(s)
- Mohammad Mobashir
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solnavägen 9, Solna 17165, Sweden
| | - S. Pauliina Turunen
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solnavägen 9, Solna 17165, Sweden
| | - Mohammad Asrar Izhari
- Faculty of Applied Medical Sciences, University of Al-Baha, Al-Baha 65528, Saudi Arabia
| | - Ibraheem Mohammed Ashankyty
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 22233, Saudi Arabia
| | - Thomas Helleday
- SciLifeLab, Department of Oncology and Pathology, Karolinska Institutet, P.O. Box 1031, 17121 Stockholm, Sweden
| | - Kaisa Lehti
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solnavägen 9, Solna 17165, Sweden
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Helmi N, Alammari D, Mobashir M. Role of Potential COVID-19 Immune System Associated Genes and the Potential Pathways Linkage with Type-2 Diabetes. Comb Chem High Throughput Screen 2022; 25:2452-2462. [PMID: 34348612 DOI: 10.2174/1386207324666210804124416] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 05/30/2021] [Accepted: 06/06/2021] [Indexed: 01/27/2023]
Abstract
BACKGROUND Coronavirus is an enclosed positive-sense RNA virus with club-like spikes extending from its surface. It is most typically associated with acute respiratory infections in humans, but its capacity to infect many host species and cause multiple illnesses makes it a complicated pathogen. The frequent encounters between wild animals and humans are a typical cause of infection. The zoonotic infections SARS-CoV and MERS-CoV are among the most common causes of serious respiratory illnesses in humans. AIM The main goal of this research was to look at gene expression profiles in human samples that were either infected with coronavirus or were not, and compare the varied expression patterns and their functional implications. METHODS The previously researched samples were acquired from a public database for this purpose, and the study was conducted, which included gene expression analysis, pathway analysis, and network-level comprehension. The results for differentially expressed genes, enriched pathways, and networks for prospective genes and gene sets are presented in the analysis. In terms of COVID-19 gene expression and its relationship to type 2 diabetes. RESULTS We see a lot of genes that have different gene expression patterns than normal for coronavirus infection, but in terms of pathways, it appears that there are only a few sets of functions that are affected by altered gene expression, and they are related to infection, inflammation, and the immune system. CONCLUSION Based on our study, we conclude that the potential genes which are affected due to infection are NFKBIA, MYC, FOXO3, BIRC3, ICAM1, IL8, CXCL1/2/5, GADD45A, RELB, SGK1, AREG, BBC3, DDIT3/4, EGR1, MTHFD2, and SESN2 and the functional changes are mainly associated with these pathways: TNF, cytokine, NF-kB, TLR, TCR, BCR, Foxo, and TGF signaling pathways are among them and there are additional pathways such as hippo signaling, apoptosis, estrogen signaling, regulating pluropotency of stem cells, ErbB, Wnt, p53, cAMP, MAPK, PI3K-AKT, oxidative phosphorylation, protein processing in endoplasmic reticulum, prolactin signaling, adipocytokine, neurotrophine signaling, and longevity regulating pathways. SMARCD3, PARL, GLIPR1, STAT2, PMAIP1, GP1BA, and TOX genes and PI3K-Akt, focal adhesion, Foxo, phagosome, adrenergic, osteoclast differentiation, platelet activation, insulin, cytokine- cytokine interaction, apoptosis, ECM, JAK-STAT, and oxytocin signaling appear as the linkage between COVID-19 and Type-2 diabetes.
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Affiliation(s)
- Nawal Helmi
- Department of Biochemistry, College of Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Dalia Alammari
- Department of Microbiology and Immunology, Faculty of Medicine, Ibn Sina National College, Jeddah, Saudi Arabia
| | - Mohammad Mobashir
- Department of Microbiology, Tumor and Cell Biology (MTC) Karolinska Institute, Novels väg 16, 17165 Solna, Swedan.,Department of Computer Science and Software Engineering Leader, Data Science Research Group, College of Information Technology (CIT), United Arab Emirate University (UAEU), Al Ain 17551, United Arab Emirates
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17
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Ionizing Radiation and Estrogen Affecting Growth Factor Genes in an Experimental Breast Cancer Model. Int J Mol Sci 2022; 23:ijms232214284. [PMID: 36430763 PMCID: PMC9693528 DOI: 10.3390/ijms232214284] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/26/2022] [Accepted: 11/04/2022] [Indexed: 11/19/2022] Open
Abstract
Genes associated with growth factors were previously analyzed in a radiation- and estrogen-induced experimental breast cancer model. Such in vitro experimental breast cancer model was developed by exposure of the immortalized human breast epithelial cell line, MCF-10F, to low doses of high linear energy transfer (LET) α particle radiation (150 keV/μm) and subsequent growth in the presence or absence of 17β-estradiol. The MCF-10F cell line was analyzed in different stages of transformation after being irradiated with either a single 60 cGy dose or 60/60 cGy doses of alpha particles. In the present report, the profiling of differentially expressed genes associated with growth factors was analyzed in their relationship with clinical parameters. Thus, the results indicated that Fibroblast growth factor2 gene expression levels were higher in cells transformed by radiation or in the presence of ionizing radiation; whereas the fibroblast growth factor-binding protein 1gene expression was higher in the tumor cell line derived from this model. Such expressions were coincident with higher values in normal than malignant tissues and with estrogen receptor (ER) negative samples for both gene types. The results also showed that transforming growth factor alpha gene expression was higher in the tumor cell line than the tumorigenic A5 and the transformed A3 cell line, whereas the transforming growth factor beta receptor 3 gene expression was higher in A3 and A5 than in Tumor2 cell lines and the untreated controls and the E cell lines. Such gene expression was accompanied by results indicating negative and positive receptors for transforming growth factor alpha and the transforming growth factor beta receptor 3, respectively. Such expressions were low in malignant tissues when compared with benign ones. Furthermore, Fibroblast growth factor2, the fibroblast growth factor-binding protein 1, transforming growth factor alpha, the transforming growth factor beta receptor 3, and the insulin growth factor receptor gene expressions were found to be present in all BRCA patients that are BRCA-Basal, BRCA-LumA, and BRCA-LumB, except in BRCA-Her2 patients. The results also indicated that the insulin growth factor receptor gene expression was higher in the tumor cell line Tumor2 than in Alpha3 cells transformed by ionizing radiation only; then, the insulin growth factor receptor was higher in the A5 than E cell line. The insulin growth factor receptor gene expression was higher in breast cancer than in normal tissues in breast cancer patients. Furthermore, Fibroblast growth factor2, the fibroblast growth factor-binding protein 1, transforming growth factor alpha, the transforming growth factor beta receptor 3, and the insulin growth factor receptor gene expression levels were in stages 3 and 4 of breast cancer patients. It can be concluded that, by using gene technology and molecular information, it is possible to improve therapy and reduce the side effects of therapeutic radiation use. Knowing the different genes involved in breast cancer will make possible the improvement of clinical chemotherapy.
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18
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Calaf GM, Crispin LA, Muñoz JP, Aguayo F, Narayan G, Roy D. Cell Adhesion Molecules Affected by Ionizing Radiation and Estrogen in an Experimental Breast Cancer Model. Int J Mol Sci 2022; 23:12674. [PMID: 36293530 PMCID: PMC9604318 DOI: 10.3390/ijms232012674] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/23/2022] [Accepted: 10/09/2022] [Indexed: 11/07/2022] Open
Abstract
Cancer develops in a multi-step process where environmental carcinogenic exposure is a primary etiological component, and where cell-cell communication governs the biological activities of tissues. Identifying the molecular genes that regulate this process is essential to targeting metastatic breast cancer. Ionizing radiation can modify and damage DNA, RNA, and cell membrane components such as lipids and proteins by direct ionization. Comparing differential gene expression can help to determine the effect of radiation and estrogens on cell adhesion. An in vitro experimental breast cancer model was developed by exposure of the immortalized human breast epithelial cell line MCF-10F to low doses of high linear energy transfer α particle radiation and subsequent growth in the presence of 17β-estradiol. The MCF-10F cell line was analyzed in different stages of transformation that showed gradual phenotypic changes including altered morphology, increase in cell proliferation relative to the control, anchorage-independent growth, and invasive capability before becoming tumorigenic in nude mice. This model was used to determine genes associated with cell adhesion and communication such as E-cadherin, the desmocollin 3, the gap junction protein alpha 1, the Integrin alpha 6, the Integrin beta 6, the Keratin 14, Keratin 16, Keratin 17, Keratin 6B, and the laminin beta 3. Results indicated that most genes had greater expression in the tumorigenic cell line Tumor2 derived from the athymic animal than the Alpha3, a non-tumorigenic cell line exposed only to radiation, indicating that altered expression levels of adhesion molecules depended on estrogen. There is a significant need for experimental model systems that facilitate the study of cell plasticity to assess the importance of estrogens in modulating the biology of cancer cells.
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Affiliation(s)
- Gloria M. Calaf
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile
| | - Leodan A. Crispin
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile
| | - Juan P. Muñoz
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile
| | - Francisco Aguayo
- Laboratorio de Oncovirología, Programa de Virología, Instituto de Ciencias Biomédicas (ICBM), Facultad de Medicina, Universidad de Chile, Santiago 8380000, Chile
| | - Gopeshwar Narayan
- Department of Molecular and Human Genetics, Banaras Hindu University, Varanasi 221005, India
| | - Debasish Roy
- Department of Natural Sciences, Hostos College of the City University of New York, Bronx, NY 10451, USA
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19
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Variance-mean mixture of multivariate normal distribution and weighted gamma distribution: properties and applications. J Korean Stat Soc 2022. [DOI: 10.1007/s42952-022-00196-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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20
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Identifying the genes impacted by cell proliferation in proteomics and transcriptomics studies. PLoS Comput Biol 2022; 18:e1010604. [PMID: 36201535 PMCID: PMC9578628 DOI: 10.1371/journal.pcbi.1010604] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/18/2022] [Accepted: 09/26/2022] [Indexed: 11/19/2022] Open
Abstract
Hypothesis-free high-throughput profiling allows relative quantification of thousands of proteins or transcripts across samples and thereby identification of differentially expressed genes. It is used in many biological contexts to characterize differences between cell lines and tissues, identify drug mode of action or drivers of drug resistance, among others. Changes in gene expression can also be due to confounding factors that were not accounted for in the experimental plan, such as change in cell proliferation. We combined the analysis of 1,076 and 1,040 cell lines in five proteomics and three transcriptomics data sets to identify 157 genes that correlate with cell proliferation rates. These include actors in DNA replication and mitosis, and genes periodically expressed during the cell cycle. This signature of cell proliferation is a valuable resource when analyzing high-throughput data showing changes in proliferation across conditions. We show how to use this resource to help in interpretation of in vitro drug screens and tumor samples. It informs on differences of cell proliferation rates between conditions where such information is not directly available. The signature genes also highlight which hits in a screen may be due to proliferation changes; this can either contribute to biological interpretation or help focus on experiment-specific regulation events otherwise buried in the statistical analysis.
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Khan I, Gril B, Hoshino A, Yang HH, Lee MP, Difilippantonio S, Lyden DC, Steeg PS. Metastasis suppressor NME1 in exosomes or liposomes conveys motility and migration inhibition in breast cancer model systems. Clin Exp Metastasis 2022; 39:815-831. [PMID: 35939247 PMCID: PMC10642714 DOI: 10.1007/s10585-022-10182-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 07/27/2022] [Indexed: 11/03/2022]
Abstract
Tumor-derived exosomes have documented roles in accelerating the initiation and outgrowth of metastases, as well as in therapy resistance. Little information supports the converse, that exosomes or similar vesicles can suppress metastasis. We investigated the NME1 (Nm23-H1) metastasis suppressor as a candidate for metastasis suppression by extracellular vesicles. Exosomes derived from two cancer cell lines (MDA-MB-231T and MDA-MB-435), when transfected with the NME1 (Nm23-H1) metastasis suppressor, secreted exosomes with NME1 as the predominant constituent. These exosomes entered recipient tumor cells, altered their endocytic patterns in agreement with NME1 function, and suppressed in vitro tumor cell motility and migration compared to exosomes from control transfectants. Proteomic analysis of exosomes revealed multiple differentially expressed proteins that could exert biological functions. Therefore, we also prepared and investigated liposomes, empty or containing partially purified rNME1. rNME1 containing liposomes recapitulated the effects of exosomes from NME1 transfectants in vitro. In an experimental lung metastasis assay the median lung metastases per histologic section was 158 using control liposomes and 15 in the rNME1 liposome group, 90.5% lower than the control liposome group (P = 0.016). The data expand the exosome/liposome field to include metastasis suppressive functions and describe a new translational approach to prevent metastasis.
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Affiliation(s)
- Imran Khan
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Building 37, Convent Drive, Room 1126, Bethesda, MD, 20892, USA.
| | - Brunilde Gril
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Building 37, Convent Drive, Room 1126, Bethesda, MD, 20892, USA
| | - Ayuko Hoshino
- Children's Cancer and Blood Foundation Laboratories, Departments of Pediatrics, Cell and Developmental Biology, Weill Cornell Medical College, New York, NY, USA
- Department of Pediatrics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
- School of Life Science and Technology, Tokyo Institute of Technology, Yokohama, Japan
| | - Howard H Yang
- Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, USA
| | - Maxwell P Lee
- Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, USA
| | - Simone Difilippantonio
- Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, USA
| | - David C Lyden
- Children's Cancer and Blood Foundation Laboratories, Departments of Pediatrics, Cell and Developmental Biology, Weill Cornell Medical College, New York, NY, USA
- Department of Pediatrics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Patricia S Steeg
- Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Building 37, Convent Drive, Room 1126, Bethesda, MD, 20892, USA
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22
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Peng W, Liu H, Dai W, Yu N, Wang J. Predicting cancer drug response using parallel heterogeneous graph convolutional networks with neighborhood interactions. Bioinformatics 2022; 38:4546-4553. [PMID: 35997568 DOI: 10.1093/bioinformatics/btac574] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/26/2022] [Accepted: 08/22/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Due to cancer heterogeneity, the therapeutic effect may not be the same when a cohort of patients of the same cancer type receive the same treatment. The anticancer drug response prediction may help develop personalized therapy regimens to increase survival and reduce patients' expenses. Recently, graph neural network-based methods have aroused widespread interest and achieved impressive results on the drug response prediction task. However, most of them apply graph convolution to process cell line-drug bipartite graphs while ignoring the intrinsic differences between cell lines and drug nodes. Moreover, most of these methods aggregate node-wise neighbor features but fail to consider the element-wise interaction between cell lines and drugs. RESULTS This work proposes a neighborhood interaction (NI)-based heterogeneous graph convolution network method, namely NIHGCN, for anticancer drug response prediction in an end-to-end way. Firstly, it constructs a heterogeneous network consisting of drugs, cell lines and the known drug response information. Cell line gene expression and drug molecular fingerprints are linearly transformed and input as node attributes into an interaction model. The interaction module consists of a parallel graph convolution network layer and a NI layer, which aggregates node-level features from their neighbors through graph convolution operation and considers the element-level of interactions with their neighbors in the NI layer. Finally, the drug response predictions are made by calculating the linear correlation coefficients of feature representations of cell lines and drugs. We have conducted extensive experiments to assess the effectiveness of our model on Cancer Drug Sensitivity Data (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets. It has achieved the best performance compared with the state-of-the-art algorithms, especially in predicting drug responses for new cell lines, new drugs and targeted drugs. Furthermore, our model that was well trained on the GDSC dataset can be successfully applied to predict samples of PDX and TCGA, which verified the transferability of our model from cell line in vitro to the datasets in vivo. AVAILABILITY AND IMPLEMENTATION The source code can be obtained from https://github.com/weiba/NIHGCN. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Wei Peng
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650050, P.R. China
| | - Hancheng Liu
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650050, P.R. China
| | - Wei Dai
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650050, P.R. China
| | - Ning Yu
- Department of Computing Sciences, The College at Brockport, State University of New York, Brockport, NY 14422, USA
| | - Jianxin Wang
- School of Computer Science and Engineering, Central South University, Changsha 410083, P.R. China.,Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, P. R. China
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23
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Dubey A, Rasool A. Usage of Clustering and Weighted Nearest Neighbors for Efficient Missing Data Imputation of Microarray Gene Expression Dataset. ADVANCED THEORY AND SIMULATIONS 2022. [DOI: 10.1002/adts.202200460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Aditya Dubey
- Department of Computer Science and Engineering Maulana Azad National Institute of Technology Bhopal 462003 India
| | - Akhtar Rasool
- Department of Computer Science and Engineering Maulana Azad National Institute of Technology Bhopal 462003 India
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24
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Deng WQ, Craiu RV. Exploring dimension learning via a penalized probabilistic principal component analysis. J STAT COMPUT SIM 2022. [DOI: 10.1080/00949655.2022.2100890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Affiliation(s)
- Wei Q. Deng
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Canada
| | - Radu V. Craiu
- Department of Statistical Sciences, University of Toronto, Toronto, Canada
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25
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Gelbrich N, Miebach L, Berner J, Freund E, Saadati F, Schmidt A, Stope M, Zimmermann U, Burchardt M, Bekeschus S. Non-invasive medical gas plasma augments bladder cancer cell toxicity in preclinical models and patient-derived tumor tissues. J Adv Res 2022; 47:209-223. [PMID: 35931323 PMCID: PMC10173201 DOI: 10.1016/j.jare.2022.07.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 06/08/2022] [Accepted: 07/29/2022] [Indexed: 12/24/2022] Open
Abstract
INTRODUCTION Medical gas plasma therapy has been successfully applied to several types of cancer in preclinical models. First palliative tumor patients suffering from advanced head and neck cancer benefited from this novel therapeutic modality. The gas plasma-induced biological effects of reactive oxygen and nitrogen species (ROS/RNS) generated in the plasma gas phase result in oxidation-induced lethal damage to tumor cells. OBJECTIVES This study aimed to verify these anti-tumor effects of gas plasma exposure on urinary bladder cancer. METHODS 2D cell culture models, 3D tumor spheroids, 3D vascularized tumors grown on the chicken chorion-allantois-membrane (CAM) in ovo, and patient-derived primary cancer tissue gas plasma-treated ex vivo were used. RESULTS Gas plasma treatment led to oxidation, growth retardation, motility inhibition, and cell death in 2D and 3D tumor models. A marked decline in tumor growth was also observed in the tumors grown in ovo. In addition, results of gas plasma treatment on primary urothelial carcinoma tissues ex vivo highlighted the selective tumor-toxic effects as non-malignant tissue exposed to gas plasma was less affected. Whole-transcriptome gene expression analysis revealed downregulation of tumor-promoting fibroblast growth factor receptor 3 (FGFR3) accompanied by upregulation of apoptosis-inducing factor 2 (AIFm2), which plays a central role in caspase-independent cell death signaling. CONCLUSION Gas plasma treatment induced cytotoxicity in patient-derived cancer tissue and slowed tumor growth in an organoid model of urinary bladder carcinoma, along with less severe effects in non-malignant tissues. Studies on the potential clinical benefits of this local and safe ROS therapy are awaited.
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Affiliation(s)
- Nadine Gelbrich
- Clinic and Policlinic for Urology, Greifswald University Medical Center, Ferdinand-Sauerbruch-Str., 17475 Greifswald, Germany; ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany
| | - Lea Miebach
- ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany; Clinic and Policlinic for General, Visceral, Thoracic, and Vascular Surgery, Greifswald University Medical Center, Ferdinand-Sauerbruch-Str., 17475 Greifswald, Germany
| | - Julia Berner
- ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany; Clinic and Policlinic for Oral, Maxillofacial, and Plastic Surgery, Greifswald University Medical Center, Ferdinand-Sauerbruch-Str., 17475 Greifswald, Germany
| | - Eric Freund
- ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany; Clinic and Policlinic for General, Visceral, Thoracic, and Vascular Surgery, Greifswald University Medical Center, Ferdinand-Sauerbruch-Str., 17475 Greifswald, Germany
| | - Fariba Saadati
- ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany; Clinic and Policlinic of Dermatology and Venerology, Rostock University Medical Center, Stempelstr. 13, 18057 Rostock, Germany
| | - Anke Schmidt
- ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany
| | - Matthias Stope
- Department of Gynecology and Gynecological Oncology, University Hospital Bonn, 53127 Bonn, Germany
| | - Uwe Zimmermann
- Clinic and Policlinic for Urology, Greifswald University Medical Center, Ferdinand-Sauerbruch-Str., 17475 Greifswald, Germany
| | - Martin Burchardt
- Clinic and Policlinic for Urology, Greifswald University Medical Center, Ferdinand-Sauerbruch-Str., 17475 Greifswald, Germany
| | - Sander Bekeschus
- ZIK plasmatis, Leibniz Institute for Plasma Science and Technology (INP), Felix-Hausdorff-Str. 2, 17489 Greifswald, Germany.
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Bolivar-Cime A, Cortez-Elizalde D. Behavior of Some Hypothesis Tests for the Covariance Matrix of High Dimensional Data. REVISTA COLOMBIANA DE ESTADÍSTICA 2022. [DOI: 10.15446/rce.v45n2.98550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The study of the structure of the covariance matrix when the dimension of the data is much greater than the sample size (high dimensional data) is a complicated problem, since we have many unknown parameters and few data. Several hypothesis tests for the covariance matrix, in the high dimensional context and in the classical case (where the dimension of the data is less than the sample size), can be found in the literature. It has been of interest the tests for the null hypothesis that the covariance matrix of Gaussian data is equal or proportional to the identity matrix, considering the classical case as well as the high dimensional context. Since it is important to have a wide comparison between these tests found in the literature, and for some of them it is difficult to have theoretical results about their powers, in this work we compare several tests by simulations, in terms of the size and power of the test. We also present some examples of application with real high dimensional data found in the literature.
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Sateesh J, Guha K, Dutta A, Sengupta P, Yalamanchili D, Donepudi NS, Surya Manoj M, Sohail SS. A comprehensive review on advancements in tissue engineering and microfluidics toward kidney-on-chip. BIOMICROFLUIDICS 2022; 16:041501. [PMID: 35992641 PMCID: PMC9385224 DOI: 10.1063/5.0087852] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 07/19/2022] [Indexed: 06/15/2023]
Abstract
This review provides a detailed literature survey on microfluidics and its road map toward kidney-on-chip technology. The whole review has been tailored with a clear description of crucial milestones in regenerative medicine, such as bioengineering, tissue engineering, microfluidics, microfluidic applications in biomedical engineering, capabilities of microfluidics in biomimetics, organ-on-chip, kidney-on-chip for disease modeling, drug toxicity, and implantable devices. This paper also presents future scope for research in the bio-microfluidics domain and biomimetics domain.
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Affiliation(s)
| | - Koushik Guha
- Department of Electronics and Communication Engineering, National MEMS Design Centre, National Institute of Technology Silchar, Assam 788010, India
| | - Arindam Dutta
- Urologist, RG Stone Urology and Laparoscopic Hospital, Kolkata, West Bengal, India
| | | | | | - Nanda Sai Donepudi
- Medical Interns, Government Siddhartha Medical College, Vijayawada, India
| | - M. Surya Manoj
- Department of Electronics and Communication Engineering, National MEMS Design Centre, National Institute of Technology Silchar, Assam 788010, India
| | - Sk. Shahrukh Sohail
- Department of Electronics and Communication Engineering, National MEMS Design Centre, National Institute of Technology Silchar, Assam 788010, India
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Thomas DS, Cisneros LH, Anderson ARA, Maley CC. In Silico Investigations of Multi-Drug Adaptive Therapy Protocols. Cancers (Basel) 2022; 14:2699. [PMID: 35681680 PMCID: PMC9179496 DOI: 10.3390/cancers14112699] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/21/2022] [Accepted: 05/25/2022] [Indexed: 11/17/2022] Open
Abstract
The standard of care for cancer patients aims to eradicate the tumor by killing the maximum number of cancer cells using the maximum tolerated dose (MTD) of a drug. MTD causes significant toxicity and selects for resistant cells, eventually making the tumor refractory to treatment. Adaptive therapy aims to maximize time to progression (TTP), by maintaining sensitive cells to compete with resistant cells. We explored both dose modulation (DM) protocols and fixed dose (FD) interspersed with drug holiday protocols. In contrast to previous single drug protocols, we explored the determinants of success of two-drug adaptive therapy protocols, using an agent-based model. In almost all cases, DM protocols (but not FD protocols) increased TTP relative to MTD. DM protocols worked well when there was more competition, with a higher cost of resistance, greater cell turnover, and when crowded proliferating cells could replace their neighbors. The amount that the drug dose was changed, mattered less. The more sensitive the protocol was to tumor burden changes, the better. In general, protocols that used as little drug as possible, worked best. Preclinical experiments should test these predictions, especially dose modulation protocols, with the goal of generating successful clinical trials for greater cancer control.
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Affiliation(s)
- Daniel S. Thomas
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, USA; (D.S.T.); (L.H.C.)
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ 85287, USA
| | - Luis H. Cisneros
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, USA; (D.S.T.); (L.H.C.)
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ 85287, USA
| | | | - Carlo C. Maley
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ 85287, USA; (D.S.T.); (L.H.C.)
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ 85287, USA
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ 85287, USA
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Utility of Serum Ki-67 as a Marker for Malignancy in Dogs. Animals (Basel) 2022; 12:ani12101263. [PMID: 35625109 PMCID: PMC9138135 DOI: 10.3390/ani12101263] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 05/08/2022] [Accepted: 05/12/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Although serum tumour markers offer an uncomplicated, non-invasive examination method and possible therapeutic options, they are still rarely used in veterinary medicine. Our marker of interest, the Ki-67 protein, can only be detected in the active phases of the cell cycle. Therefore, it is a suitable marker for assessing the proliferating cell fraction of an organism and can thus provide information about potentially present, rapid-growing tumour tissue. The purpose of our study was to determine whether Ki-67 could be considered as a possible tumour marker in canine serum for veterinary medicine. We measured serum concentrations of Ki-67 in dogs with various malignant tumours, such as carcinomas, sarcomas, and lymphomas. In the dogs with malignant tumours we determined significantly higher serum Ki-67 concentrations compared with healthy dogs and dogs with non-malignant diseases. No significant difference in serum Ki-67 concentration was observed between the different types of cancer or between benign and malignant mammary tumours. Our investigations also included some inflammatory parameters measured in blood, such as neutrophils, lymphocytes, and monocytes, with mixed results. The results of our study suggest that Ki-67 may be useful as a potential serum tumour marker, providing information about the presence of malignant diseases in a dog. Abstract Tumour markers are scarcely used in veterinary medicine, although they are non-invasive, contribute to a faster diagnosis and new therapeutic options. The nuclear protein Ki-67 is absent in G0-phase but is detectable throughout all active phases of the cell cycle. Consequently, it is used as a marker for the proliferating cell fraction of a cell population and thus could indicate neoplastic tissue present. Our study is designed to show whether Ki-67 can be considered as a potential canine serum tumour marker for veterinary medicine. We measured serum concentrations of Ki-67 in dogs with various malignant tumours (carcinomas (n = 35); sarcomas (n = 26); lymphomas (n = 21)) using a commercially available quantitative sandwich ELISA from mybiosource. Dogs with malignant tumours showed significantly higher serum Ki-67 concentrations compared to healthy dogs (n = 19) and non-neoplastic diseased dogs (n = 26). No significant difference in serum Ki-67 concentration was detected between carcinoma, sarcoma, and lymphoma, nor between mammary adenocarcinoma and adenoma. In our investigations we also included some inflammatory parameters measured in blood, such as neutrophils, lymphocytes, and monocytes, and gained mixed results. The results of our study suggest that Ki-67 may be useful as a potential serum tumour marker, providing information about the presence of malignancies in a dog.
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Lee YJ, Ahn YJ, Lee GJ. Cytotoxicity evaluation of sodium lauryl sulfate in a paper-based 3D cell culture system. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:1755-1764. [PMID: 35355024 DOI: 10.1039/d2ay00161f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Because three-dimensional (3D) cell culture is more similar to in vivo cell microenvironments than two-dimensional (2D) cell culture, various 3D cell culture systems have been developed. Recently, paper has been used as a promising material for 3D cell culture and tissue models due to its flexibility, ease of manufacture, low cost, and widespread accessibility. In this study, we fabricated a paper-based 3D cell culture platform consisting of a hydrophilic region for cell attachment and a hydrophobic region printed with wax. Using this paper platform for 3D culture of L929 cells, we evaluated the cytotoxicity of a model substance, sodium lauryl sulfate (SLS), using water-soluble tetrazolium salt, Live/Dead, and luminescence assays. Then we compared those cytotoxicity results with results from a conventional 3D cell culture kit and 2D cell culture. We found that 3D cultured cells on paper responded more sensitively to SLS than 2D cultured cells, and the cytotoxicity of SLS to cells grown on the paper-based 3D cell culture platform was similar to that of cells grown using a commercially available 3D cell culture kit. Therefore, we expect that our paper-based 3D cell culture platform can be applied as a simple and facile tool for cell viability evaluation.
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Affiliation(s)
- Young Ju Lee
- Department of Biomedical Engineering, College of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Seoul 02447, Korea.
| | - Yong Jin Ahn
- Department of Medical Engineering, Kyung Hee University Graduate School, Seoul 02447, Korea
| | - Gi-Ja Lee
- Department of Biomedical Engineering, College of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Seoul 02447, Korea.
- Department of Medical Engineering, Kyung Hee University Graduate School, Seoul 02447, Korea
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31
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Khouja HI, Ashankyty IM, Bajrai LH, Kumar PKP, Kamal MA, Firoz A, Mobashir M. Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer. Sci Rep 2022; 12:7240. [PMID: 35508649 PMCID: PMC9065671 DOI: 10.1038/s41598-022-11143-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 10/11/2021] [Indexed: 02/05/2023] Open
Abstract
Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma and furthermore, the TCGA and cBioPortal database have been utilized for clinical relevance understanding. In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.
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Affiliation(s)
- Hamed Ishaq Khouja
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
| | - Ibraheem Mohammed Ashankyty
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Leena Hussein Bajrai
- Special Infectious Agents Unit-BSL3, King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
- Biochemistry Department, Sciences College, King Abdulaziz University, Jeddah, Saudi Arabia
| | - P K Praveen Kumar
- Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, 602105, India
| | - Mohammad Amjad Kamal
- West China School of Nursing/Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
- King Fahd Medical Research Center, King Abdulaziz University, P. O. Box 80216, Jeddah, 21589, Saudi Arabia
- Enzymoics, Novel Global Community Educational Foundation, 7 Peterlee Place, Hebersham, NSW, 2770, Australia
| | - Ahmad Firoz
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
| | - Mohammad Mobashir
- SciLifeLab, Department of Oncology and Pathology, Karolinska Institutet, Box 1031, 171 21, Stockholm, Sweden.
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Koca HE, Bostancı Durmus A, Yarcı Gursoy A, Candar T, Tokgöz Çakır B, Karahan S, Kucukozkan T, Caglar GS. Human epididymis protein 4 and fetal lung maturity. J Perinat Med 2022; 50:219-224. [PMID: 34534427 DOI: 10.1515/jpm-2021-0034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 09/02/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVES To document the maternal and fetal cord blood levels of human epididymis protein 4 (HE-4) in term and preterm newborns in order to investigate the possible physiological role of HE-4 in fetal lung development. METHODS This cross-sectional study was conducted in a university-affiliated hospital between April 2018 and September 2018. The study population consisted of cesarean section (C-section) deliveries after 24 weeks of pregnancy. Both maternal and umbilical cord HE-4 levels (mHE-4 and uHE-4, respectively) were measured using chemiluminescent microparticle immunoassay. Amniotic fluid was sampled from each case to determine the lamellar body count (LBC) as the gold standard test for lung maturation. All the parameters, including the uHE-4 levels, were compared between the term delivery (≥37 weeks) (n=52) and preterm delivery (24-37th weeks) (n=30) groups. The best cut-off value of uHE-4 was calculated for fetal lung maturity. RESULTS There were no statistically significant differences between the groups regarding the demographic data. The mHE-4 levels did not statistically significantly differ between the groups (p>0.05) whereas the uHE-4 level of the preterm newborns was significantly higher than that of the term newborns (p<0.05). There was a significant negative association between the uHE-4 level and LBC (r=-0.389; p<0.001). The uHE-4 level was the only statistically significant fetal parameter indicating fetal lung maturity confirmed by LBC. At a cut-off value of 281 pmol/L, uHE-4 had 96.8% sensitivity, 45% specificity, 84.5% positive predictive value, and 81.8% negative predictive value for fetal lung maturity. CONCLUSIONS Although the exact physiological role of HE-4 has not yet been elucidated, this preliminary study supports the idea that HE-4 plays a role in fetal lung maturation to some extent.
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Affiliation(s)
- Hande Esra Koca
- Department of Obstetrics and Gynecology, Dr. Sami Ulus Research and Training Hospital, Ankara, Turkey
| | - Arzu Bostancı Durmus
- Department of Obstetrics and Gynecology, Dr. Sami Ulus Research and Training Hospital, Ankara, Turkey
| | - Aslı Yarcı Gursoy
- Department of Obstetrics and Gynecology, Ufuk University School of Medicine, Ankara, Turkey
| | - Tuba Candar
- Department of Biochemistry, Ufuk University Faculty of Medicine, Ankara, Turkey
| | - Betül Tokgöz Çakır
- Department of Obstetrics and Gynecology, Kahraman Kazan Hamdi Eriş State Hospital, Ankara, Turkey
| | - Sevilay Karahan
- Department of Biostatistics, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Tuncay Kucukozkan
- Department of Obstetrics and Gynecology, Dr. Sami Ulus Research and Training Hospital, Ankara, Turkey
| | - Gamze Sinem Caglar
- Department of Obstetrics and Gynecology, Ufuk University School of Medicine, Ankara, Turkey
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Orafa Z, Karimi N, Keyvani S, Oloomi M. Quantitative CK19 biomarker detection in breast cancer cell lines. J Med Life 2022; 15:188-195. [PMID: 35419102 PMCID: PMC8999104 DOI: 10.25122/jml-2021-1101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 05/20/2021] [Indexed: 11/21/2022] Open
Abstract
Cytokeratin19 (CK19) was detected as the most related marker for circulating tumor cells, which was assessed in specific cell lines. MCF7, SKBR3, T47D, and MDA-MB-231, and HeLa cell line as negative control were used. CK19 expression was confirmed by using mouse monoclonal anti-human CK19 antibody. CK19 detection in MDA-MB-231 was not observed. CK19 marker expression was compared in T47D, MCF7, and SKBR3 cell lines. T47D and MCF7 belonged to the luminal subtype of breast cancer (BC) that CK19 expression regulated with an ER marker. SKBR3 belonged to the HER2 positive subtype of BC. However, MDA-MB-231 belonged to the claudin-low subtype of BC that lack of CK19 expression strongly is related to negative ER, PR, and HER2. Therefore, there are not only quantitative differences in CK19 expression, but its expression could also link to the other markers of BC that should be considered in the molecular classification of breast carcinoma. Different expression levels related to cell classification could be useful in the prognosis and treatment of cancers with epithelial origins.
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Affiliation(s)
- Zahra Orafa
- Molecular Biology Department, Pasteur Institute of Iran, Tehran, Iran
| | - Nasrin Karimi
- Molecular Biology Department, Pasteur Institute of Iran, Tehran, Iran
| | - Saeideh Keyvani
- Molecular Biology Department, Pasteur Institute of Iran, Tehran, Iran
| | - Mana Oloomi
- Molecular Biology Department, Pasteur Institute of Iran, Tehran, Iran,Corresponding Author: Mana Oloomi, Molecular Biology Department, Pasteur Institute of Iran, Pasteur Ave., Tehran-Iran 13164. E-mail:
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Who's Who? Discrimination of Human Breast Cancer Cell Lines by Raman and FTIR Microspectroscopy. Cancers (Basel) 2022; 14:cancers14020452. [PMID: 35053613 PMCID: PMC8773714 DOI: 10.3390/cancers14020452] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/05/2022] [Accepted: 01/12/2022] [Indexed: 12/14/2022] Open
Abstract
(1) Breast cancer is presently the leading cause of death in women worldwide. This study aims at identifying molecular biomarkers of cancer in human breast cancer cells, in order to differentiate highly aggressive triple-negative from non-triple-negative cancers, as well as distinct triple-negative subtypes, which is currently an unmet clinical need paramount for an improved patient care. (2) Raman and FTIR (Fourier transform infrared) microspectroscopy state-of-the-art techniques were applied, as highly sensitive, specific and non-invasive methods for probing heterogeneous biological samples such as human cells. (3) Particular biochemical features of malignancy were unveiled based on the cells' vibrational signature, upon principal component analysis of the data. This enabled discrimination between TNBC (triple-negative breast cancer) and non-TNBC, TNBC MSL (mesenchymal stem cell-like) and TNBC BL1 (basal-like 1) and TNBC BL1 highly metastatic and low-metastatic cell lines. This specific differentiation between distinct TNBC subtypes-mesenchymal from basal-like, and basal-like 1 with high-metastatic potential from basal-like 1 with low-metastatic potential-is a pioneer result, of potential high impact in cancer diagnosis and treatment.
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Federico A, Saarimäki LA, Serra A, Del Giudice G, Kinaret PAS, Scala G, Greco D. Microarray Data Preprocessing: From Experimental Design to Differential Analysis. Methods Mol Biol 2022; 2401:79-100. [PMID: 34902124 DOI: 10.1007/978-1-0716-1839-4_7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
DNA microarray data preprocessing is of utmost importance in the analytical path starting from the experimental design and leading to a reliable biological interpretation. In fact, when all relevant aspects regarding the experimental plan have been considered, the following steps from data quality check to differential analysis will lead to robust, trustworthy results. In this chapter, all the relevant aspects and considerations about microarray preprocessing will be discussed. Preprocessing steps are organized in an orderly manner, from experimental design to quality check and batch effect removal, including the most common visualization methods. Furthermore, we will discuss data representation and differential testing methods with a focus on the most common microarray technologies, such as gene expression and DNA methylation.
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Affiliation(s)
- Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Tampere, Finland
| | - Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Tampere, Finland
| | - Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Tampere, Finland
| | - Giusy Del Giudice
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Tampere, Finland
| | - Pia Anneli Sofia Kinaret
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Tampere, Finland
- Institute of Biotechnology,, University of Helsinki, Helsinki, Finland
| | - Giovanni Scala
- Department of Biology, University of Naples Federico II, Naples, Italy
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- BioMediTech Institute, Tampere University, Tampere, Finland.
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Tampere, Finland.
- Institute of Biotechnology,, University of Helsinki, Helsinki, Finland.
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Phon BWS, Kamarudin MNA, Bhuvanendran S, Radhakrishnan AK. Transitioning pre-clinical glioblastoma models to clinical settings with biomarkers identified in 3D cell-based models: A systematic scoping review. Biomed Pharmacother 2022; 145:112396. [PMID: 34775238 DOI: 10.1016/j.biopha.2021.112396] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 10/25/2021] [Accepted: 11/02/2021] [Indexed: 11/02/2022] Open
Abstract
Glioblastoma (GBM) remains incurable despite the overwhelming discovery of 2-dimensional (2D) cell-based potential therapeutics since the majority of them have met unsatisfactory results in animal and clinical settings. Incremental empirical evidence has laid the widespread need of transitioning 2D to 3-dimensional (3D) cultures that better mimic GBM's complex and heterogenic nature to allow better translation of pre-clinical results. This systematic scoping review analyses the transcriptomic data involving 3D models of GBM against 2D models from 22 studies identified from four databases (PubMed, ScienceDirect, Medline, and Embase). From a total of 499 genes reported in these studies, 313 (63%) genes were upregulated across 3D models cultured using different scaffolds. Our analysis showed that 4 of the replicable upregulated genes are associated with GBM stemness, epithelial to mesenchymal transition (EMT), hypoxia, and migration-related genes regardless of the type of scaffolds, displaying close resemblances to primitive undifferentiated tumour phenotypes that are associated with decreased overall survival and increased hazard ratio in GBM patients. The upregulation of drug response and drug efflux genes (e.g. cytochrome P450s and ABC transporters) mirrors the GBM genetic landscape that contributes to in vivo and clinical treatment resistance. These upregulated genes displayed strong protein-protein interactions when analysed using an online bioinformatics software (STRING). These findings reinforce the need for widespread transition to 3D GBM models as a relatively inexpensive humanised pre-clinical tool with suitable genetic biomarkers to bridge clinical gaps in potential therapeutic evaluations.
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Affiliation(s)
- Brandon Wee Siang Phon
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor, Malaysia
| | - Muhamad N A Kamarudin
- Brain Research Institute Monash Sunway, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, 47500 Bandar Sunway, Selangor, Malaysia.
| | - Saatheeyavaane Bhuvanendran
- Brain Research Institute Monash Sunway, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, 47500 Bandar Sunway, Selangor, Malaysia
| | - Ammu K Radhakrishnan
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor, Malaysia
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Hao X, Hu F, Gu Y, Yang H, Li C, Guo C. Molecularly assembled graphdiyne with atomic sites for ultrafast and real-time detection of nitric oxide in cell assays. Biosens Bioelectron 2022; 195:113630. [PMID: 34536724 DOI: 10.1016/j.bios.2021.113630] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 09/06/2021] [Accepted: 09/08/2021] [Indexed: 01/31/2023]
Abstract
Nitric oxide as a signal molecule participates in a variety of physiological and pathological processes but its real-time detection in cell assays still faces challenging because of the trace amount, short half-life and easy conversion to other substances. We report here a rational design by assembling highly π-conjugated and small capacitive gaphdiyne (GDY) with a coordination complex of hemin (HEM) into a molecularly assembled material of GDY/HEM to achieve ultrafast and real-time monitoring of nitric oxide in cell assays. GDY comprising alkynyl C atoms can hybridize with the HEM to enable strong π-π interaction and atomic dispersion of iron sites while avoiding the formation of catalytically inactive dimer for the HEM. These characteristics make the GDY/HEM an excellent sensing material towards nitric oxide, which has an ultrafast response time of 0.95 s, a low detection limit of 7 nM and long linear range up to 151.38 μΜ. The GDY/HEM realizes real-time monitoring nitric oxide released from cancer and normal cells, demonstrating its capability for cell analysis.
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Affiliation(s)
- Xijuan Hao
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China
| | - Fangxin Hu
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China
| | - Yu Gu
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China
| | - Hongbin Yang
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China
| | - Changming Li
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China; Institute for Clean Energy and Advanced Materials, Southwest University, Chongqing, 400715, China
| | - Chunxian Guo
- School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China; Jiangsu Laboratory for Biochemical Sensing and Biochip, Suzhou, 215011, China.
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38
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Zaffino P, Spadea MF. Algorithms to Preprocess Microarray Image Data. Methods Mol Biol 2022; 2401:69-78. [PMID: 34902123 DOI: 10.1007/978-1-0716-1839-4_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Microarray is a powerful technology that enables the monitoring of expression levels for thousands of genes simultaneously, providing scientists with a full overview about DNA and RNA investigation. The process is made of three main phases: interaction with biological samples, data extraction, and data analysis. In particular, the data extraction phase strongly relies on image processing algorithms, since the expression levels are revealed by the interaction of light with fluorescent markers. More in detail, in order to extract quantitative information from probes image, three steps are required: (1) gridding, (2) segmentation, and (3) intensity quantification. Errors in one of these steps can deeply affect the process outcome. In this chapter each of the above mentioned steps will be analyzed and discussed. Software platforms dedicated to this purpose will be reported as well.
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Affiliation(s)
- Paolo Zaffino
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, CZ, Italy.
| | - Maria Francesca Spadea
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, CZ, Italy
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Intestinal Organoids: New Tools to Comprehend the Virulence of Bacterial Foodborne Pathogens. Foods 2022; 11:foods11010108. [PMID: 35010234 PMCID: PMC8750402 DOI: 10.3390/foods11010108] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/18/2021] [Accepted: 12/22/2021] [Indexed: 12/12/2022] Open
Abstract
Foodborne diseases cause high morbidity and mortality worldwide. Understanding the relationships between bacteria and epithelial cells throughout the infection process is essential to setting up preventive and therapeutic solutions. The extensive study of their pathophysiology has mostly been performed on transformed cell cultures that do not fully mirror the complex cell populations, the in vivo architectures, and the genetic profiles of native tissues. Following advances in primary cell culture techniques, organoids have been developed. Such technological breakthroughs have opened a new path in the study of microbial infectious diseases, and thus opened onto new strategies to control foodborne hazards. This review sheds new light on cellular messages from the host–foodborne pathogen crosstalk during in vitro organoid infection by the foodborne pathogenic bacteria with the highest health burden. Finally, future perspectives and current challenges are discussed to provide a better understanding of the potential applications of organoids in the investigation of foodborne infectious diseases.
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40
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Dubey A, Rasool A. Efficient technique of microarray missing data imputation using clustering and weighted nearest neighbour. Sci Rep 2021; 11:24297. [PMID: 34934107 PMCID: PMC8692342 DOI: 10.1038/s41598-021-03438-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 11/22/2021] [Indexed: 02/03/2023] Open
Abstract
For most bioinformatics statistical methods, particularly for gene expression data classification, prognosis, and prediction, a complete dataset is required. The gene sample value can be missing due to hardware failure, software failure, or manual mistakes. The missing data in gene expression research dramatically affects the analysis of the collected data. Consequently, this has become a critical problem that requires an efficient imputation algorithm to resolve the issue. This paper proposed a technique considering the local similarity structure that predicts the missing data using clustering and top K nearest neighbor approaches for imputing the missing value. A similarity-based spectral clustering approach is used that is combined with the K-means. The spectral clustering parameters, cluster size, and weighting factors are optimized, and after that, missing values are predicted. For imputing each cluster’s missing value, the top K nearest neighbor approach utilizes the concept of weighted distance. The evaluation is carried out on numerous datasets from a variety of biological areas, with experimentally inserted missing values varying from 5 to 25%. Experimental results prove that the proposed imputation technique makes accurate predictions as compared to other imputation procedures. In this paper, for performing the imputation experiments, microarray gene expression datasets consisting of information of different cancers and tumors are considered. The main contribution of this research states that local similarity-based techniques can be used for imputation even when the dataset has varying dimensionality and characteristics.
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Affiliation(s)
- Aditya Dubey
- Department of Computer Science & Engineering, Maulana Azad National Institute of Technology, Bhopal, 462003, India.
| | - Akhtar Rasool
- Department of Computer Science & Engineering, Maulana Azad National Institute of Technology, Bhopal, 462003, India
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Zhong L, Meng Q, Chen Y, Du L, Wu P. A laminar augmented cascading flexible neural forest model for classification of cancer subtypes based on gene expression data. BMC Bioinformatics 2021; 22:475. [PMID: 34600466 PMCID: PMC8487515 DOI: 10.1186/s12859-021-04391-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 09/22/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Correctly classifying the subtypes of cancer is of great significance for the in-depth study of cancer pathogenesis and the realization of personalized treatment for cancer patients. In recent years, classification of cancer subtypes using deep neural networks and gene expression data has gradually become a research hotspot. However, most classifiers may face overfitting and low classification accuracy when dealing with small sample size and high-dimensional biology data. RESULTS In this paper, a laminar augmented cascading flexible neural forest (LACFNForest) model was proposed to complete the classification of cancer subtypes. This model is a cascading flexible neural forest using deep flexible neural forest (DFNForest) as the base classifier. A hierarchical broadening ensemble method was proposed, which ensures the robustness of classification results and avoids the waste of model structure and function as much as possible. We also introduced an output judgment mechanism to each layer of the forest to reduce the computational complexity of the model. The deep neural forest was extended to the densely connected deep neural forest to improve the prediction results. The experiments on RNA-seq gene expression data showed that LACFNForest has better performance in the classification of cancer subtypes compared to the conventional methods. CONCLUSION The LACFNForest model effectively improves the accuracy of cancer subtype classification with good robustness. It provides a new approach for the ensemble learning of classifiers in terms of structural design.
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Affiliation(s)
- Lianxin Zhong
- School of Information Science and Engineering, University of Jinan, Jinan, China
- Shandong Provincial Key laboratory of Network Based Intelligent Computing, Jinan, 250022, China
| | - Qingfang Meng
- School of Information Science and Engineering, University of Jinan, Jinan, China.
- Shandong Provincial Key laboratory of Network Based Intelligent Computing, Jinan, 250022, China.
| | - Yuehui Chen
- School of Information Science and Engineering, University of Jinan, Jinan, China
- Shandong Provincial Key laboratory of Network Based Intelligent Computing, Jinan, 250022, China
| | - Lei Du
- School of Information Science and Engineering, University of Jinan, Jinan, China
- Shandong Provincial Key laboratory of Network Based Intelligent Computing, Jinan, 250022, China
| | - Peng Wu
- School of Information Science and Engineering, University of Jinan, Jinan, China
- Shandong Provincial Key laboratory of Network Based Intelligent Computing, Jinan, 250022, China
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Pinkney HR, Black MA, Diermeier SD. Single-Cell RNA-Seq Reveals Heterogeneous lncRNA Expression in Xenografted Triple-Negative Breast Cancer Cells. BIOLOGY 2021; 10:987. [PMID: 34681087 PMCID: PMC8533545 DOI: 10.3390/biology10100987] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/23/2021] [Accepted: 09/26/2021] [Indexed: 12/03/2022]
Abstract
Breast cancer is the most commonly diagnosed cancer in the world, with triple-negative breast cancer (TNBC) making up 12% of these diagnoses. TNBC tumours are highly heterogeneous in both inter-tumour and intra-tumour gene expression profiles, where they form subclonal populations of varying levels of aggressiveness. These aspects make it difficult to study and treat TNBC, requiring further research into tumour heterogeneity as well as potential therapeutic targets and biomarkers. Recently, it was discovered that the majority of the transcribed genome comprises non-coding RNAs, in particular long non-coding RNAs (lncRNAs). LncRNAs are transcripts of >200 nucleotides in length that do not encode a protein. They have been characterised as regulatory molecules and their expression can be associated with a malignant phenotype. We set out to explore TNBC tumour heterogeneity in vivo at a single cell level to investigate whether lncRNA expression varies across different cells within the tumour, even if cells are coming from the same cell line, and whether lncRNA expression is sufficient to define cellular subpopulations. We applied single-cell expression profiling due to its ability to capture expression signals of lncRNAs expressed in small subpopulations of cells. Overall, we observed most lncRNAs to be expressed at low, but detectable levels in TNBC xenografts, with a median of 25 lncRNAs detected per cell. LncRNA expression alone was insufficient to define a subpopulation of cells, and lncRNAs showed highly heterogeneous expression patterns, including ubiquitous expression, subpopulation-specific expression, and a hybrid pattern of lncRNAs expressed in several, but not all subpopulations. These findings reinforce that transcriptionally defined tumour cell subpopulations can be identified in cell-line derived xenografts, and uses single-cell RNA-seq (scRNA-seq) to detect and characterise lncRNA expression across these subpopulations in xenografted tumours. Future studies will aim to investigate the spatial distribution of lncRNAs within xenografts and patient tissues, and study the potential of subclone-specific lncRNAs as new therapeutic targets and/or biomarkers.
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Affiliation(s)
- Holly R. Pinkney
- Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand; (H.R.P.); (M.A.B.)
| | - Michael A. Black
- Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand; (H.R.P.); (M.A.B.)
| | - Sarah D. Diermeier
- Department of Biochemistry, University of Otago, Dunedin 9016, New Zealand; (H.R.P.); (M.A.B.)
- Amaroq Therapeutics Ltd., Dunedin 9016, New Zealand
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43
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Liu S, Yu T. Kernel density estimation in mixture models with known mixture proportions. Stat Med 2021; 40:6360-6372. [PMID: 34474504 DOI: 10.1002/sim.9187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 06/18/2021] [Accepted: 08/17/2021] [Indexed: 11/11/2022]
Abstract
In this article, we consider the density estimation for data with a mixture structure, where the component densities are assumed unknown, but for each observation, the probabilities of its membership to the subpopulations are known or estimable from other resources. Data of this kind arise from practice and have wide applications. Motivated from the classical kernel density estimation method for a single population, we propose a weighted kernel density estimation method to estimate the component density functions nonparametrically. Within the framework of the EM algorithm, we derive an algorithm that computes our proposed estimates effectively. Via extensive simulation studies, we demonstrate that our methods outperform the existing methods in most occasions. We further compare our methods with existing methods by real data examples.
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Affiliation(s)
- Siyun Liu
- Department of Statistics and Data Science, National University of Singapore, Singapore
| | - Tao Yu
- Department of Statistics and Data Science, National University of Singapore, Singapore
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Gupta P, Kumar RV, Kwon CH, Chen ZS. Synthesis and anticancer evaluation of sulfur containing 9-anilinoacridines. Recent Pat Anticancer Drug Discov 2021; 17:102-119. [PMID: 34323200 DOI: 10.2174/1574892816666210728122910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/18/2021] [Accepted: 04/17/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND DNA topoisomerases are a class of enzymes that play a critical role in fundamental biological processes of replication, transcription, recombination, repair and chromatin remodeling. Amsacrine (m-AMSA), the best-known compound of 9-anilinoacridines series was one of the first DNA-intercalating agents to be considered as a Topoisomerase II inhibitor. OBJECTIVE A series of sulfur containing 9-anilinoacridines related to amsacrine were synthesized and evaluated for their anticancer activity. METHODS Cell viability was assessed by the MTT assay. The topoisomerase II inhibitory assay was performed using the Human topoisomerase II Assay kit and flow cytometry was used to evaluate the effects on cell cycle of K562 cells. Molecular docking was performed using Schrödinger Maestro program. RESULTS Compound 36 was found to be the most cytotoxic of the sulfide series against SW620, K562, and MCF-7. The limited SAR suggested the importance of the methansulfonamidoacetamide side chain functionality, the lipophilicity and relative metabolic stability of 36 in contributing to the cytotoxicity. Topoisomerase II α inhibitory activity appeared to be involved in the cytotoxicity of 36 through inhibition of decatenation of kinetoplast DNA (kDNA) in a concentration dependent manner. Cell cycle analysis further showed the Topo II inhibition through accumulation of K562 cells in G2/M phase of cell cycle. Docking of 36 into the Topo II α-DNA complex suggested that it may be an allosteric inhibitor of Topo II α. CONCLUSION Compound 36 exhibits anticancer activity by inhibiting topoisomerase II and it could further be evaluated in in vivo models.
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Affiliation(s)
- Pranav Gupta
- Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, Queens, New York 11439, United States
| | - Radhika V Kumar
- Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, Queens, New York 11439, United States
| | - Chul-Hoon Kwon
- Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, Queens, New York 11439, United States
| | - Zhe-Sheng Chen
- Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, St. John's University, Queens, New York 11439, United States
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46
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Fuchs S, Di Lascio FML, Durante F. Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables. Comput Stat Data Anal 2021. [DOI: 10.1016/j.csda.2021.107201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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47
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Sinha R, Luna A, Schultz N, Sander C. A pan-cancer survey of cell line tumor similarity by feature-weighted molecular profiles. CELL REPORTS METHODS 2021; 1:100039. [PMID: 35475239 PMCID: PMC9017219 DOI: 10.1016/j.crmeth.2021.100039] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 03/31/2021] [Accepted: 05/24/2021] [Indexed: 02/07/2023]
Abstract
Patient-derived cell lines are often used in pre-clinical cancer research, but some cell lines are too different from tumors to be good models. Comparison of genomic and expression profiles can guide the choice of pre-clinical models, but typically not all features are equally relevant. We present TumorComparer, a computational method for comparing cellular profiles with higher weights on functional features of interest. In this pan-cancer application, we compare ∼600 cell lines and ∼8,000 tumor samples of 24 cancer types, using weights to emphasize known oncogenic alterations. We characterize the similarity of cell lines and tumors within and across cancers by using multiple datum types and rank cell lines by their inferred quality as representative models. Beyond the assessment of cell lines, the weighted similarity approach is adaptable to patient stratification in clinical trials and personalized medicine.
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Affiliation(s)
- Rileen Sinha
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Augustin Luna
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Boston, MA 02142, USA
| | - Nikolaus Schultz
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Chris Sander
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Boston, MA 02142, USA
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Petti M, Verrienti A, Paci P, Farina L. SEaCorAl: Identifying and contrasting the regulation-correlation bias in RNA-Seq paired expression data of patient groups. Comput Biol Med 2021; 135:104567. [PMID: 34174761 DOI: 10.1016/j.compbiomed.2021.104567] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 05/27/2021] [Accepted: 06/08/2021] [Indexed: 01/11/2023]
Abstract
The Cancer Genome Atlas database offers the possibility of analyzing genome-wide expression RNA-Seq cancer data using paired counts, that is, studies where expression data are collected in pairs of normal and cancer cells, by taking samples from the same individual. Correlation of gene expression profiles is the most common analysis to study co-expression groups, which is used to find biological interpretation of -omics big data. The aim of the paper is threefold: firstly we show for the first time, the presence of a "regulation-correlation bias" in RNA-Seq paired expression data, that is an artifactual link between the expression status (up- or down-regulation) of a gene pair and the sign of the corresponding correlation coefficient. Secondly, we provide a statistical model able to theoretically explain the reasons for the presence of such a bias. Thirdly, we present a bias-removal algorithm, called SEaCorAl, able to effectively reduce bias effects and improve the biological significance of correlation analysis. Validation of the SEaCorAl algorithm is performed by showing a significant increase in the ability to detect biologically meaningful associations of positive correlations and a significant increase of the modularity of the resulting unbiased correlation network.
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Affiliation(s)
- Manuela Petti
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy
| | - Antonella Verrienti
- Department of Translational and Precision Medicine, Sapienza University of Rome, Italy
| | - Paola Paci
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy
| | - Lorenzo Farina
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy.
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Schirinzi A, Cazzolla AP, Mascolo E, Palmieri G, Pesce F, Gesualdo L, Santacroce L, Ballini A, Lovero R, Di Serio F. Determination of the Upper Reference Limit of Human Epididymis Secretory Protein 4 (HE4) in Healthy Male Individuals and Correlation with Renal and Fertility Markers. Endocr Metab Immune Disord Drug Targets 2021; 21:912-918. [PMID: 32767951 DOI: 10.2174/1871530320666200807121050] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 06/05/2020] [Accepted: 06/08/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Elevated human epididymis secretory protein 4 (HE4) serum levels have been widely investigated in patients with ovarian cancer. However, high levels of HE4 can be also found in other tumors and in renal fibrosis. To date, the HE4 assay manufacturer features the reference value only for the female pre- and post-menopausal population. The aim of this study was to determine the upper reference limit (URL) of HE4 in a well-defined and large cohort of healthy male individuals and investigate potential factors influencing HE4 levels in healthy subjects. METHODS The study included 307 Italian healthy male individuals. HE4 was measured using a chemiluminescent assay (Abbott Laboratories, Wiesbaden, Germany). The URL was calculated using the non-parametric percentile method. Differences in HE4 concentrations according to age, estimated glomerular filtration rate (eGFR), free and bioavailable testosterone were also evaluated. RESULTS The 97.5th percentile URL of serum HE4 in our study population was 57 pmol/L (90% CI). After stratifying subjects according to age, we found that the URL of HE4 was higher in older (> 50 years) than in younger subjects (18-30 years old), and overlapping with the URL in males from 31 to 50 years old (P=4.769e-16, r=0.44). A strong negative correlation between HE4 and eGFR was observed (P=8.412e-12, r=-0.38). Moreover, a statistically significant negative correlation was also found between HE4 and free and bioavailable testosterone. CONCLUSION This study determined the URL of HE4 in a large cohort of healthy male subjects. Our findings indicate that the HE4 age-dependent differences in males need to be taken into account. The definition of the HE4 URL in males and the correlation observed with eGFR and testosterone should foster the clinical use of HE4 beyond gynecologic cancer.
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Affiliation(s)
| | - Angela Pia Cazzolla
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Elisa Mascolo
- Clinic Pathology Unit, Polyclinic University Hospital, Bari, Italy
| | | | - Francesco Pesce
- Nephrology, Dialysis and Transplantation Unit, DETO, University "Aldo Moro", Bari, Italy
| | - Loreto Gesualdo
- Nephrology, Dialysis and Transplantation Unit, DETO, University "Aldo Moro", Bari, Italy
| | - Luigi Santacroce
- Ionian Department (DJSGEM), Microbiology and Virology Laboratory, University of Bari "Aldo Moro", Bari, Italy
| | - Andrea Ballini
- Department of Biosciences, Biotechnologies and Biopharmaceutics, Campus Universitario "Ernesto Quagliariello", University of Bari "Aldo Moro", Bari, Italy
| | - Roberto Lovero
- Clinic Pathology Unit, Polyclinic University Hospital, Bari, Italy
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Li M, Li X, Wang C, Li Q, Zhu S, Zhang Y, Li X, Yang F, Zhu X. Selection and Validation of Reference Genes For qRT-PCR Analysis of Rhopalosiphum padi (Hemiptera: Aphididae). Front Physiol 2021; 12:663338. [PMID: 33935809 PMCID: PMC8079785 DOI: 10.3389/fphys.2021.663338] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 03/22/2021] [Indexed: 11/23/2022] Open
Abstract
Rhopalosiphum padi (L.) (Hemiptera: Aphididae) is an important cosmopolitan pest in cereal crops. Reference genes can significantly affect qRT-PCR results. Therefore, selecting appropriate reference genes is a key prerequisite for qRT-PCR analyses. This study was conducted to identify suitable qRT-PCR reference genes in R. padi. We systematically analyzed the expression profiles of 11 commonly used reference genes. The ΔCt method, the BestKeeper, NormFinder, geNorm algorithms, and the RefFinder online tool were used to evaluate the suitability of these genes under diverse experimental conditions. The data indicated that the most appropriate sets of reference genes were β-actin and GAPDH (for developmental stages), AK and TATA (for populations), RPS18 and RPL13 (for tissues), TATA and GAPDH (for wing dimorphism), EF-1α and RPS6 (for antibiotic treatments), GAPDH and β-actin (for insecticide treatments), GAPDH, TATA, RPS18 (for starvation-induced stress), TATA, RPS6, and AK (for temperatures), and TATA and GAPDH (for all conditions). Our study findings, which revealed the reference genes suitable for various experimental conditions, will facilitate the standardization of qRT-PCR programs, while also improving the accuracy of qRT-PCR analyses, with implications for future research on R. padi gene functions.
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Affiliation(s)
- Mengyi Li
- Heilongjiang Provincial Key Laboratory of Ecological Restoration and Resource Utilization for Cold Region, School of Life Sciences, Heilongjiang University, Harbin, China.,Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
| | - Xinan Li
- School of Resource and Environmental Sciences, Henan Institute of Science and Technology, Xinxiang, China
| | - Chao Wang
- Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
| | - Qiuchi Li
- Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
| | - Saige Zhu
- Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
| | - Yunhui Zhang
- Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
| | - Xiangrui Li
- Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
| | - Fengshan Yang
- Heilongjiang Provincial Key Laboratory of Ecological Restoration and Resource Utilization for Cold Region, School of Life Sciences, Heilongjiang University, Harbin, China
| | - Xun Zhu
- Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.,State Key Laboratory for Biology of Plant Diseases and Insect Pests, Beijing, China
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