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Tang X, Zhang H, Ke J, Luan X, Li Z, Luan T, Zhai J. Localized DNA Logic Circuit Equipped with Cascade Amplifiers for Precise Identification of Cancer Cells. Anal Chem 2025; 97:6258-6267. [PMID: 40091166 DOI: 10.1021/acs.analchem.5c00247] [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: 03/19/2025]
Abstract
Precise and highly sensitive identification of cancer cells plays a pivotal role in early cancer detection, diagnosis, and effective treatment. While DNA logic circuits have shown great promise as diagnostic tools, their practical application has been hindered by inadequate sensitivity arising from limited signal amplification capabilities in complex biological matrices. To address this issue, we constructed a localized DNA circuit (LDC) equipped with cascaded amplifiers by introducing a Y-shaped AND-gate circuit module and three hairpin amplifier modules into a DNA tetrahedron. The Y-shaped logic gate is activated only in the simultaneous presence of two cancer-specific biomarkers: intracellular microRNA-21 (miR-21) and flap endonuclease 1 (FEN1). Upon activation, the logic gate releases output strands that trigger the assembly of hairpin amplifiers, initiating a localized strand displacement amplification cascade that generates a significantly enhanced fluorescent signal. The LDC exhibits remarkable sensitivity with detection limits of 82.5 pM for miR-21 and 0.015 U/mL for FEN1. Fluorescence assays demonstrate that the LDC achieves a 15.5-fold improvement over circuits without amplifiers and a 5.2-fold enhanced sensitivity compared to nonlocalized circuits. The LDC enables simultaneous detection of the dual biomarkers, generating significantly amplified fluorescent signals exclusively in tumor cells expressing both miR-21 and FEN1, thus allowing precise discrimination between cancerous and healthy cells. Furthermore, we demonstrated that the LDC system enables in vivo tumor imaging, effectively differentiating between normal and tumor tissues. This work highlights the potential of the proposed localized cascade-amplification DNA circuit strategy for tumor-specific imaging, paving the way for precise cancer diagnosis and treatment.
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Affiliation(s)
- Xiaoyan Tang
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Han Zhang
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Jiajun Ke
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Xinyu Luan
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Ziqing Li
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Tiangang Luan
- School of Environmental and Chemical Engineering, Wuyi University, Jiangmen 529020, China
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Junqiu Zhai
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
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Huang H, Zhang M, Lu H, Chen Y, Sun W, Zhu J, Chen Z. Identification and evaluation of plasma exosome RNA biomarkers for non-invasive diagnosis of hepatocellular carcinoma using RNA-seq. BMC Cancer 2024; 24:1552. [PMID: 39696145 DOI: 10.1186/s12885-024-13332-0] [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: 05/04/2024] [Accepted: 12/11/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND Non-invasive diagnostic methods, including medical imaging techniques and blood biomarkers such as alpha-fetoprotein (AFP), have been crucial in detecting hepatocellular carcinoma (HCC). However, imaging techniques are only effective for tumor size larger than 2 cm. AFP measurement remains unsatisfactory due to high rate of misdiagnosis and underdiagnosis. Therefore, new reliable biomarkers and better non-invasive diagnostic approach are necessary for HCC identification. METHODS The differentially expressed genes were identified using multiple public RNA-seq data of liver tissues from healthy individuals and HCC patients including peritumoral and tumor tissues. The hub genes for HCC diagnosis were identified combining pathway enrichment analysis and protein-protein interaction network analysis. The performance of hub genes for non-invasive HCC diagnosis was analyzed in plasma of healthy individuals, HBV infected patients, and HCC patients based on exosomal RNA-seq data. A multi-layer perceptron (MLP) model based on exosomal hub genes was developed for non-invasive HCC diagnosis. RESULTS Through differential gene expression and pathway enrichment analysis on multiple public RNA-seq datasets, we first identified 30 dysregulated genes in HCC tissues. Protein-protein interaction analysis further narrowed down this list to 10 key genes: BRCA2, CDK1, MCM4, PLK1, DNA2, BLM, PCNA, POLD1, BRCA1 and FEN1. By further evaluation using additional public HCC tissue datasets, POLD1 and MCM4 were excluded from consideration as potential biomarkers due to their suboptimal performance. Notably, CDK1, FEN1, and PCNA gene were found to be significantly elevated in the plasma exosomes of HCC patients compared to non-HCC individuals, including those with HBV-infected hepatitis and healthy controls. The MLP model, based on three biomarkers, showed an area under the curve (AUC) of 0.85 and 0.84 in training and test dataset respectively, after adjusting for the covariates sex and age. CONCLUSION We identified three key genes, CDK1, FEN1, and PCNA, as exosomal biomarkers for non-invasive diagnosis of HCC. The MLP model utilizing three biomarkers showed good differentiation between non-HCC individuals and HCC patients, which exhibits promising potential as a non-invasive diagnostic tool for detecting HCC. Additional validation with a larger sample size is essential to thoroughly assess the reliability of the biomarkers and the model's performance.
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Affiliation(s)
- Heqing Huang
- Infectious Disease Department, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China
| | - Min Zhang
- BamRock Research Department, Suzhou BamRock Biotechnology Ltd., Suzhou, Jiangsu Province, China
| | - Hong Lu
- Infectious Disease Department, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China
| | - Yiling Chen
- Infectious Disease Department, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China
| | - Weijie Sun
- Ulink College of Shanghai, Shanghai, China
| | - Jinghan Zhu
- Infectious Disease Department, The Fourth Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China.
| | - Zutao Chen
- Infectious Disease Department, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China.
- MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Key Laboratory of Pathogen Bioscience and Anti-infective Medicine, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China.
- Infectious Disease Department, The Fourth Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China.
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Peng Z, Wang S, Wen D, Mei Z, Zhang H, Liao S, Lv L, Li C. FEN1 upregulation mediated by SUMO2 via antagonizing proteasomal degradation promotes hepatocellular carcinoma stemness. Transl Oncol 2024; 44:101916. [PMID: 38513457 PMCID: PMC10966306 DOI: 10.1016/j.tranon.2024.101916] [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: 09/24/2023] [Revised: 01/22/2024] [Accepted: 02/15/2024] [Indexed: 03/23/2024] Open
Abstract
PURPOSE Metastasis of hepatocellular carcinoma (HCC) critically impacts the survival prognosis of patients, with the pivotal role of hepatocellular carcinoma stem cells in initiating invasive metastatic behaviors. The Flap Endonuclease 1 (FEN1) is delineated as a metallonuclease, quintessential for myriad cellular processes including DNA replication, DNA synthesis, DNA damage rectification, Okazaki fragment maturation, baseexcision repair, and the preservation of genomic stability. Furthermore, it has been recognized as an oncogene in a diverse range of malignancies. Our antecedent research has highlighted a pronounced overexpression of protein FEN1 in hepatocellular carcinoma, where it amplifies the invasiveness and metastatic potential of liver cancer cells. However, its precise role in liver cancer stem cells (LCSCs) remains an enigma and requires further investigation. METHODS To rigorously evaluate the stemness attributes of LCSCs, we employed sphere formation assays and flow cytometric evaluations. Both CD133+ and CD133- cell populations were discerningly isolated utilizing immunomagnetic bead separation techniques. The expression levels of pertinent genes were assayed via real-time quantitative PCR (RT-qPCR) and western blot analyses, while the expression profiles in hepatocellular carcinoma tissues were gauged using immunohistochemistry. Subsequent immunoprecipitation, in conjunction with mass spectrometry, ascertained the concurrent binding of proteins FEN1 and Small ubiquitin-related modifier 2 (SUMO2) in HCC cells. Lastly, the impact of SUMO2 on proteasomal degradation pathway of FEN1 was validated by supplementing MG132. RESULTS Our empirical findings substantiate that protein FEN1 is profusely expressed in spheroids and CD133+ cells. In vitro investigations demonstrate that the upregulation of protein FEN1 unequivocally augments the stemness of LCSCs. In a congruent in vivo context, elevation of FEN1 noticeably enhances the tumorigenic potential of LCSCs. Conversely, inhibiting protein FEN1 resulted in a marked reduction in LCSC stemness. From a mechanistic perspective, there exists a salient positive correlation between the protein expression of FEN1 and SUMO2 in liver cancer tissues. Furthermore, the level of SUMO2-mediated modification of FEN1 is pronouncedly elevated in LCSCs. Interestingly, SUMO2 has the ability to bind to FEN1, leading to a inhibition in the proteasomal degradation pathway of FEN1 and an enhancement in its protein expression. However, it is noteworthy that this interaction does not affect the mRNA level of FEN1. CONCLUSION In summation, our research elucidates that protein FEN1 is an effector in augmenting the stemness of LCSCs. Consequently, strategic attenuation of protein FEN1 might proffer a pioneering approach for the efficacious elimination of LCSCs.
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Affiliation(s)
- Zhenxiang Peng
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China
| | - Shuling Wang
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China
| | - Diguang Wen
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China
| | - Zhechuan Mei
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China.
| | - Hao Zhang
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China.
| | - Shengtao Liao
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China.
| | - Lin Lv
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China.
| | - Chuanfei Li
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Linjiang Road, Yuzhong District, Chongqing 400010, PR China.
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Wang S, Wang X, Sun J, Yang J, Wu D, Wu F, Zhou H. Down-regulation of DNA key protein-FEN1 inhibits OSCC growth by affecting immunosuppressive phenotypes via IFN-γ/JAK/STAT-1. Int J Oral Sci 2023; 15:17. [PMID: 37185662 PMCID: PMC10130046 DOI: 10.1038/s41368-023-00221-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/13/2023] [Accepted: 03/02/2023] [Indexed: 05/17/2023] Open
Abstract
Oral squamous cell carcinoma (OSCC) escape from the immune system is mediated through several immunosuppressive phenotypes that are critical to the initiation and progression of tumors. As a hallmark of cancer, DNA damage repair is closely related to changes in the immunophenotypes of tumor cells. Although flap endonuclease-1 (FEN1), a pivotal DNA-related enzyme is involved in DNA base excision repair to maintain the stability of the cell genome, the correlation between FEN1 and tumor immunity has been unexplored. In the current study, by analyzing the clinicopathological characteristics of FEN1, we demonstrated that FEN1 overexpressed and that an inhibitory immune microenvironment was established in OSCC. In addition, we found that downregulating FEN1 inhibited the growth of OSCC tumors. In vitro studies provided evidence that FEN1 knockdown inhibited the biological behaviors of OSCC and caused DNA damage. Performing multiplex immunohistochemistry (mIHC), we directly observed that the acquisition of critical immunosuppressive phenotypes was correlated with the expression of FEN1. More importantly, FEN1 directly or indirectly regulated two typical immunosuppressive phenotype-related proteins human leukocyte antigen (HLA-DR) and programmed death receptor ligand 1 (PD-L1), through the interferon-gamma (IFN-γ)/janus kinase (JAK)/signal transducer and activator transcription 1 (STAT1) pathway. Our study highlights a new perspective on FEN1 action for the first time, providing theoretical evidence that it may be a potential immunotherapy target for OSCC.
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Affiliation(s)
- Shimeng Wang
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Xiangjian Wang
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- Department of Oral Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Jun Sun
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China
- Department of Oral Medicine, Stomatological Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Jin Yang
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Deyang Wu
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Fanglong Wu
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
| | - Hongmei Zhou
- State Key Laboratory of Oral Diseases & National Center of Stomatology & National Clinical Research Center for Oral Diseases & Frontier Innovation Center for Dental Medicine Plus & Department of Oral Medicine, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
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Zhu W, Ding M, Chang J, Liao H, Xiao G, Wang Q. A 9-gene prognostic signature for kidney renal clear cell carcinoma overall survival based on co-expression and regression analyses. Chem Biol Drug Des 2023; 101:422-437. [PMID: 36053927 DOI: 10.1111/cbdd.14141] [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: 12/22/2021] [Revised: 08/10/2022] [Accepted: 08/30/2022] [Indexed: 01/18/2023]
Abstract
This research attempted to screen potential signatures associated with KIRC progression and overall survival by weighted gene co-expression network analysis (WGCNA) and Cox regression. The KIRC-associated mRNA expression and clinical data were accessed from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened by differential analysis. A co-expression network was constructed by "WGCNA". Based on WGCNA module, GO and KEGG analyses were performed. Protein-protein interaction (PPI) network was constructed. Prognostic signatures were screened by Lasso-Cox regression. Prognostic model was evaluated by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves. Multivariate Cox and nomogram were introduced to examine whether risk score could be an independent marker. qRT-PCR was introduced to determine expression of 9 hub genes in KIRC clinical tumor tissues and adjacent tissues, respectively. Genes in the green module were highly associated with clinical status, and green module genes were significantly enriched in mitotic nuclear division, cell cycle, and p53 signaling pathway. Twenty-six candidates were subsequently screened out from the green module. Next, a 9-gene prognostic model (DLGAP5, NUF2, TOP2A, RRM2, HJURP, PLK1, AURKB, KIF18A, CCNB2) was constructed. The predicting ability of the model was optimal. Some cancer-related signaling pathways were differently activated between two risk score groups. Additionally, under-expression of some signature genes (AURKB, CCNB2, PLK1, RRM2, TOP2A) was associated with better survival rate for KIRC patients. Meanwhile, all 9 hub genes were substantially overexpressed in KIRC patients. A KIRC prognostic signature was screened in this study, contributing valuable findings to KIRC biomarker development.
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Affiliation(s)
- Wenwen Zhu
- Department of Oncology, the Affiliated Hospital of Shaoxing University, Zhejiang, China
| | - Mengyu Ding
- Department of Oncology, the Affiliated Hospital of Shaoxing University, Zhejiang, China
| | - Jian Chang
- Department of Oncology, the Affiliated Hospital of Shaoxing University, Zhejiang, China
| | - Hui Liao
- Department of Oncology, the Affiliated Hospital of Shaoxing University, Zhejiang, China
| | - Geqiong Xiao
- Department of Oncology, the Affiliated Hospital of Shaoxing University, Zhejiang, China
| | - Qiong Wang
- Department of Oncology, the Affiliated Hospital of Shaoxing University, Zhejiang, China
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Qiao S, Zhang W, Su Y, Jiang Y. Integrated bioinformatics analysis of IFITM1 as a prognostic biomarker and investigation of its immunological role in prostate adenocarcinoma. Front Oncol 2022; 12:1037535. [PMID: 36591519 PMCID: PMC9795034 DOI: 10.3389/fonc.2022.1037535] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
Introduction Prostate adenocarcinoma (PRAD) is a highly aggressive malignancy with high mortality and poor prognosis, and its potential mechanism remains unclear. Our study aimed to identify novel markers for the prognosis of PRAD using bioinformatics technology. Methods The GSE32571 dataset was downloaded from the GEO database, and analyzed via the limma R package to identify differentially expressed genes (DEGs) and differentially expressed immune score-related genes (DEISRGs). The immune-related genes (IRGs) were further obtained by overlapping DEISRGs and DEGs, and the core gene was identified via survival analysis. Furthermore, the expression level, prognostic value, and potential functions of the core gene were evaluated via multiple bioinformatics databases. Results A total of 301 IRGs were identified from the GSE32571 dataset, and IFITM1 was a down-regulated gene in several types of cancer, including PRAD. Besides, low expression of IFITM1 was associated with a poor prognosis in PRAD. GSEA indicated that the vital pathways of IFITM1-associated genes were mainly enriched in primary immunodeficiency, Th17 cell differentiation, Th1, and Th2 cell differentiation, natural killer cell-mediated cytotoxicity, myeloid dendritic cell activation, regulation of leukocyte activation, etc. Furthermore, IFITM1 was closely correlated with 22 types of tumor-infiltrating immune cells. Discussion IFITM1 was a prognostic biomarker for PRAD patients, and it can be acted as a potential immune therapy target in PRAD.
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Liu LJ, Liao JM, Zhu F. Proliferating cell nuclear antigen clamp associated factor, a potential proto-oncogene with increased expression in malignant gastrointestinal tumors. World J Gastrointest Oncol 2021; 13:1425-1439. [PMID: 34721775 PMCID: PMC8529917 DOI: 10.4251/wjgo.v13.i10.1425] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 06/11/2021] [Accepted: 07/23/2021] [Indexed: 02/06/2023] Open
Abstract
Gastrointestinal (GI) cancers, including malignancies in the gastrointestinal tract and accessory organs of digestion, represent the leading cause of death worldwide due to the poor prognosis of most GI cancers. An investigation into the potential molecular targets of prediction, diagnosis, prognosis, and therapy in GI cancers is urgently required. Proliferating cell nuclear antigen (PCNA) clamp associated factor (PCLAF), which plays an essential role in cell proliferation, apoptosis, and cell cycle regulation by binding to PCNA, is a potential molecular target of GI cancers as it contributes to a series of malignant properties, including tumorigenesis, epithelial-mesenchymal transition, migration, and invasion. Furthermore, PCLAF is an underlying plasma prediction target in colorectal cancer and liver cancer. In addition to GI cancers, PCLAF is also involved in other types of cancers and autoimmune diseases. Several pivotal pathways, including the Rb/E2F pathway, NF-κB pathway, and p53-p21 cascade, are implicated in PCLAF-mediated diseases. PCLAF also contributes to some diseases through dysregulation of the p53 pathway, WNT signal pathway, MEK/ERK pathway, and PI3K/AKT/mTOR signal cascade. This review mainly describes in detail the role of PCLAF in physiological status and GI cancers. The signaling pathways involved in PCLAF are also summarized. Suppression of the interaction of PCLAF/PCNA or the expression of PCLAF might be potential biological therapeutic strategies for GI cancers.
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Affiliation(s)
- Li-Juan Liu
- State Key Laboratory of Virology and Hubei Province Key Laboratory of Allergy & Immunology, Department of Medical Microbiology, School of Medicine, Wuhan University, Wuhan 430071, Hubei Province, China
| | - Jian-Ming Liao
- State Key Laboratory of Virology and Hubei Province Key Laboratory of Allergy & Immunology, Department of Medical Microbiology, School of Medicine, Wuhan University, Wuhan 430071, Hubei Province, China
- Department of Neurosurgery, Renmin Hospital, Wuhan University, Wuhan 430060, Hubei Province, China
| | - Fan Zhu
- State Key Laboratory of Virology and Hubei Province Key Laboratory of Allergy & Immunology, Department of Medical Microbiology, School of Medicine, Wuhan University, Wuhan 430071, Hubei Province, China
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Zhang Y, Lin Z, Lin X, Zhang X, Zhao Q, Sun Y. A gene module identification algorithm and its applications to identify gene modules and key genes of hepatocellular carcinoma. Sci Rep 2021; 11:5517. [PMID: 33750838 PMCID: PMC7943822 DOI: 10.1038/s41598-021-84837-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 02/18/2021] [Indexed: 12/19/2022] Open
Abstract
To further improve the effect of gene modules identification, combining the Newman algorithm in community detection and K-means algorithm framework, a new method of gene module identification, GCNA-Kpca algorithm, was proposed. The core idea of the algorithm was to build a gene co-expression network (GCN) based on gene expression data firstly; Then the Newman algorithm was used to initially identify gene modules based on the topology of GCN, and the number of clusters and clustering centers were determined; Finally the number of clusters and clustering centers were input into the K-means algorithm framework, and the secondary clustering was performed based on the gene expression profile to obtain the final gene modules. The algorithm took into account the role of modularity in the clustering process, and could find the optimal membership module for each gene through multiple iterations. Experimental results showed that the algorithm proposed in this paper had the best performance in error rate, biological significance and CNN classification indicators (Precision, Recall and F-score). The gene module obtained by GCNA-Kpca was used for the task of key gene identification, and these key genes had the highest prognostic significance. Moreover, GCNA-Kpca algorithm was used to identify 10 key genes in hepatocellular carcinoma (HCC): CDC20, CCNB1, EIF4A3, H2AFX, NOP56, RFC4, NOP58, AURKA, PCNA, and FEN1. According to the validation, it was reasonable to speculate that these 10 key genes could be biomarkers for HCC. And NOP56 and NOP58 are key genes for HCC that we discovered for the first time.
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Affiliation(s)
- Yan Zhang
- College of Environmental Science and Engineering, Dalian Martime University, Linghai Road, Dalian, 116026, Liaoning, China
| | - Zhengkui Lin
- College of Information Science and Technology, Dalian Maritime University, Linghai Road, Dalian, 116026, Liaoning, China
| | - Xiaofeng Lin
- College of Information Science and Technology, Dalian Maritime University, Linghai Road, Dalian, 116026, Liaoning, China
| | - Xue Zhang
- College of Information Science and Technology, Dalian Maritime University, Linghai Road, Dalian, 116026, Liaoning, China
| | - Qian Zhao
- College of Information Science and Technology, Dalian Maritime University, Linghai Road, Dalian, 116026, Liaoning, China.
| | - Yeqing Sun
- College of Environmental Science and Engineering, Dalian Martime University, Linghai Road, Dalian, 116026, Liaoning, China.
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Zhao Q, Zhang Y, Shao S, Sun Y, Lin Z. Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis. PeerJ 2021; 9:e10594. [PMID: 33552715 PMCID: PMC7821758 DOI: 10.7717/peerj.10594] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 11/26/2020] [Indexed: 12/18/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC), the main type of liver cancer in human, is one of the most prevalent and deadly malignancies in the world. The present study aimed to identify hub genes and key biological pathways by integrated bioinformatics analysis. Methods A bioinformatics pipeline based on gene co-expression network (GCN) analysis was built to analyze the gene expression profile of HCC. Firstly, differentially expressed genes (DEGs) were identified and a GCN was constructed with Pearson correlation analysis. Then, the gene modules were identified with 3 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Moreover, we used the Search Tool for the Retrieval of Interacting Genes (STRING) database to construct a protein protein interaction (PPI) network of the key gene module, and we identified the hub genes using nine topology analysis algorithms based on this PPI network. Further, we used the Oncomine analysis, survival analysis, GEO data set and random forest algorithm to verify the important roles of hub genes in HCC. Lastly, we explored the methylation changes of hub genes using another GEO data (GSE73003). Results Firstly, among the expression profiles, 4,130 up-regulated genes and 471 down-regulated genes were identified. Next, the multi-level algorithm which had the highest modularity divided the GCN into nine gene modules. Also, a key gene module (m1) was identified. The biological processes of GO enrichment of m1 mainly included the processes of mitosis and meiosis and the functions of catalytic and exodeoxyribonuclease activity. Besides, these genes were enriched in the cell cycle and mitotic pathway. Furthermore, we identified 11 hub genes, MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 which played key roles in HCC. The results of multiple verification methods indicated that the 11 hub genes had highly diagnostic efficiencies to distinguish tumors from normal tissues. Lastly, the methylation changes of gene CDC20, TOP2A, TK1, FEN1 in HCC samples had statistical significance (P-value < 0.05). Conclusion MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, the cell cycle and mitotic pathway might played vital roles in the progression of HCC.
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Affiliation(s)
- Qian Zhao
- College of Information Science and Technology, Dalian Martime University, Dalian, Liaoning, China
| | - Yan Zhang
- College of Information Science and Technology, Dalian Martime University, Dalian, Liaoning, China
| | - Shichun Shao
- College of Environmental Science and Engineering, Dalian Martime University, Dalian, Liaoning, China
| | - Yeqing Sun
- College of Environmental Science and Engineering, Dalian Martime University, Dalian, Liaoning, China
| | - Zhengkui Lin
- College of Information Science and Technology, Dalian Martime University, Dalian, Liaoning, China
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Li Z, Lin Y, Cheng B, Zhang Q, Cai Y. Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods. Front Genet 2021; 12:571231. [PMID: 33767726 PMCID: PMC7985067 DOI: 10.3389/fgene.2021.571231] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 02/18/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research. METHODS The bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network. RESULTS We ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes. CONCLUSION The present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.
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Affiliation(s)
- Zhuolin Li
- Department of Clinical Laboratory, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Yao Lin
- Department of Plastic Surgery and Burn Center, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Bizhen Cheng
- Department of Clinical Laboratory, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Qiaoxin Zhang
- Department of Clinical Laboratory, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Yingmu Cai
- Department of Clinical Laboratory, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- *Correspondence: Yingmu Cai,
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Feng S, Luo S, Ji C, Shi J. miR-29c-3p regulates proliferation and migration in ovarian cancer by targeting KIF4A. World J Surg Oncol 2020; 18:315. [PMID: 33261630 PMCID: PMC7709319 DOI: 10.1186/s12957-020-02088-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 11/16/2020] [Indexed: 12/27/2022] Open
Abstract
Background Increasing evidence suggested that microRNA and kinesin superfamily proteins play an essential role in ovarian cancer. The association between KIF4A and ovarian cancer (OC) was investigated in this study. Methods We performed bioinformatics analysis in the GEO database to screen out the differentially expressed miRNAs (DEmiRNAs) associated with ovarian cancer prognosis. Upstream targeting prediction for KIF4A was acquired by using the mirDIP database. The potential regulatory factor miR-29c-3p for KIF4A was obtained from the intersection of the above all miRNAs. The prognosis of KIF4A and target-miRNA in OC was obtained in the subsequent analysis. qRT-PCR and Western blot detected KIF4A expression level in IOSE80 (human normal ovarian epithelial cell line). In the meantime, the gene expression level was detected in A2780, HO-8910PM, COC1, and SKOV3 cell lines (human ovarian carcinoma cell line). MTT and colony formation assays were used to detect cell proliferation of SKOV3 cell line. The following assays detected cell migration through the use of transwell and wound heal assays. Targeted binding relationship between KIF4A and miRNA was detected by using the dual-luciferase reporter assay. Results Both high expression of KIF4A and lower expression of miR-29c-3p could be used as biomarkers indicating poor prognosis in OC patients. Cellular function tests confirmed that when KIF4A was silenced, it inhibited the proliferation and migration of OC cells. In addition, 3′-UTR of KIF4A had a direct binding site with miR-29c-3p, which indicated that the expression of KIF4A could be regulated by miR-29c-3p. In subsequent assays, the proliferation and migration of OC cells were inhibited by the overexpression of miR-29c-3p. At the same time, rescue experiments also confirmed that the promotion of KIF4A could be reversed by miR-29c-3p. Conclusion In a word, our data revealed a new mechanism for the role of KIF4A in the occurrence and development of OC.
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Affiliation(s)
- Songwei Feng
- Department of Gynecology, The Second Affiliated Hospital of Soochow University, Suzhou, People's Republic of China
| | - Shanhui Luo
- Department of Gynecology, The Second Affiliated Hospital of Soochow University, Suzhou, People's Republic of China
| | - Chenchen Ji
- Orthopedic Institute, Soochow University, Suzhou, People's Republic of China
| | - Jia Shi
- Department of Laboratory, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, 48 Huaishuxiang, Wuxi, 214002, Jiangsu Province, People's Republic of China.
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Yang DP, Lu HP, Chen G, Yang J, Gao L, Song JH, Chen SW, Mo JX, Kong JL, Tang ZQ, Li CB, Zhou HF, Yang LJ. Integrated expression analysis revealed RUNX2 upregulation in lung squamous cell carcinoma tissues. IET Syst Biol 2020; 14:252-260. [PMID: 33095746 PMCID: PMC8687175 DOI: 10.1049/iet-syb.2020.0063] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 08/01/2020] [Accepted: 08/10/2020] [Indexed: 12/14/2022] Open
Abstract
This study aimed to investigate the clinicopathological significance and prospective molecular mechanism of RUNX family transcription factor 2 (RUNX2) in lung squamous cell carcinoma (LUSC). The authors used immunohistochemistry (IHC), RNA-seq, and microarray data from multi-platforms to conduct a comprehensive analysis of the clinicopathological significance and molecular mechanism of RUNX2 in the occurrence and development of LUSC. RUNX2 expression was significantly higher in 16 LUSC tissues than in paired non-cancerous tissues detected by IHC (P < 0.05). RNA-seq data from the combination of TCGA and genotype-tissue expression (GTEx) revealed significantly higher expression of RUNX2 in 502 LUSC samples than in 476 non-cancer samples. The expression of RUNX2 protein was also significantly higher in pathologic T3-T4 than in T1-T2 samples (P = 0.031). The pooled standardised mean difference (SMD) for RUNX2 was 0.87 (95% CI, 0.58-1.16), including 29 microarrays from GEO and one from ArrayExpress. The co-expression network of RUNX2 revealed complicated connections between RUNX2 and 45 co-expressed genes, which were significantly clustered in pathways including ECM-receptor interaction, focal adhesion, protein digestion and absorption, human papillomavirus infection and PI3K-Akt signalling pathway. Overexpression of RUNX2 plays an essential role in the clinical progression of LUSC.
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Affiliation(s)
- Da-Ping Yang
- Department of Pathology, The Eighth Affiliated Hospital of Guangxi Medical University/Guigang People's Hospital, Guigang, Guangxi, People's Republic of China
| | - Hui-Ping Lu
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Gang Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Jie Yang
- Department of Pharmacology, School of Pharmacy, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Li Gao
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Jian-Hua Song
- Department of Pathology, The Eighth Affiliated Hospital of Guangxi Medical University/Guigang People's Hospital, Guigang, Guangxi, People's Republic of China
| | - Shang-Wei Chen
- Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Jun-Xian Mo
- Department of Cardio-Thoracic Surgery, The Seventh Affiliated Hospital of Guangxi Medical University/Wuzhou Gongren Hospital, Wuzhou, Guangxi, People's Republic of China
| | - Jin-Liang Kong
- Ward of Pulmonary and Critical Care Medicine, Department of Respiratory Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Zhong-Qing Tang
- Department of Pathology, The Seventh Affiliated Hospital of Guangxi Medical University/Wuzhou Gongren Hospital, Wuzhou, Guangxi, People's Republic of China
| | - Chang-Bo Li
- Department of Cardio-Thoracic Surgery, The Seventh Affiliated Hospital of Guangxi Medical University/Wuzhou Gongren Hospital, Wuzhou, Guangxi, People's Republic of China
| | - Hua-Fu Zhou
- Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
| | - Lin-Jie Yang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
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