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Qin K, Luo JY, Zeng DT, Huang WY, Li B, Li Q, Zhan YT, He RQ, Huang WJ, Chen G, Chen ZY, Chi BT, Tang YX, Tang RX, Li H. Kinesin family member 14 expression and its clinical implications in colorectal cancer. World J Gastrointest Oncol 2025; 17:102696. [PMID: 40092935 PMCID: PMC11866231 DOI: 10.4251/wjgo.v17.i3.102696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 11/22/2024] [Accepted: 12/25/2024] [Indexed: 02/14/2025] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is the third most common cancer globally, causing over 900000 deaths annually. Risk factors include aging, diet, obesity, sedentary lifestyle, tobacco use, genetic predisposition, and inflammatory bowel disease. Despite current treatments, survival rates for advanced CRC remain low, highlighting the need for better therapeutic strategies. AIM To evaluate both the clinical significance and the pathological implications of the Kinesin family member 14 (KIF14) expression within CRC specimens. Additionally, this study aims to investigate the interaction between nitidine chloride (NC) and KIF14, considering their potential as therapeutic targets. METHODS The expression of the KIF14 protein in CRC was analyzed using immunohistochemical staining. The integration of multicenter high-throughput data facilitated the calculation of the standardized mean difference (SMD) for KIF14 mRNA levels. The assessment of clinical and pathological impact was enhanced by analyzing combined receiver operating characteristic curves, along with measures of sensitivity, specificity, and likelihood ratios. Additionally, clustered regularly interspaced short palindromic repeats knockout screening for cell growth and single-cell sequencing were employed to validate the significance of KIF14 expression in CRC. Survival analysis established the prognostic value of KIF14 in CRC. The molecular mechanism of NC against CRC was elucidated through whole-genome sequencing and enrichment analysis, and molecular docking was utilized to explore the targeting affinity between NC and KIF14. RESULTS KIF14 was highly expressed in 208 CRC patients. Data from 17 platforms involving 2436 CRC samples and 1320 noncancerous colorectal tissue controls indicated that KIF14 expression was significantly higher in CRC samples, with an SMD of 1.92 (95%CI: 1.49-2.35). The area under the curve was 0.94 (95%CI: 0.92-0.96), with a sensitivity of 0.85 (95%CI: 0.78-0.90) and a specificity of 0.90 (95%CI: 0.85-0.93). The positive and negative likelihood ratios were 8.38 (95%CI: 5.39-13.02) and 0.17 (95%CI: 0.11-0.26), respectively. At the single-cell level, significant overexpression of KIF14 was observed in CRC cells (P < 0.001), with 35 CRC cell lines dependent on KIF14 for growth. The K-M plots demonstrated that KIF14 possesses prognostic value in CRC patients within the GSE71187 and GSE103679 datasets (P < 0.05). Binding energy calculations indicated that KIF14 is a potential target for NC (binding energy: 10.3 kcal/mol). CONCLUSION KIF14 promotes the growth of CRC cells and acts as an oncogenic factor, potentially serving as a therapeutic target for NC in the treatment of CRC.
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Affiliation(s)
- Kai Qin
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Jia-Yuan Luo
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Da-Tong Zeng
- Department of Pathology, Redcross Hospital of Yulin City, Yulin 537000, Guangxi Zhuang Autonomous Region, China
| | - Wan-Ying Huang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Bin Li
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Qi Li
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Yan-Ting Zhan
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Rong-Quan He
- Department of Medical Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Wei-Jian Huang
- Department of Pathology, Redcross Hospital of Yulin City, Yulin 537000, Guangxi Zhuang Autonomous Region, China
| | - Gang Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Zu-Yuan Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Bang-Teng Chi
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Yu-Xing Tang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Rui-Xue Tang
- Department of Pathology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250000, Shandong Province, China
| | - Hui Li
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
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Alam MS, Sultana A, Kibria MK, Khanam A, Wang G, Mollah MNH. Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer. Bioinform Biol Insights 2024; 18:11779322241272386. [PMID: 39239087 PMCID: PMC11375675 DOI: 10.1177/11779322241272386] [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: 01/01/2024] [Accepted: 07/09/2024] [Indexed: 09/07/2024] Open
Abstract
Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.
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Affiliation(s)
- Md Shahin Alam
- Center of Translational Medicine, The First People's Hospital of Taicang, Taicang Affiliated Hospital of Soochow University, Suzhou, China
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, China
- Bioinformatics Laboratory (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
| | - Adiba Sultana
- Bioinformatics Laboratory (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Md Kaderi Kibria
- Bioinformatics Laboratory (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
| | - Alima Khanam
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, Bangladesh
| | - Guanghui Wang
- Center of Translational Medicine, The First People's Hospital of Taicang, Taicang Affiliated Hospital of Soochow University, Suzhou, China
| | - Md Nurul Haque Mollah
- Bioinformatics Laboratory (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
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Shornale Akter M, Uddin MH, Atikur Rahman S, Hossain MA, Ashik MAR, Zaman NN, Faruk O, Hossain MS, Parvin A, Rahman MH. Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment. Cancer Rep (Hoboken) 2024; 7:e2009. [PMID: 38717954 PMCID: PMC11078332 DOI: 10.1002/cnr2.2009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/21/2023] [Accepted: 02/12/2024] [Indexed: 05/12/2024] Open
Abstract
Breast cancer (BC) is the most widespread cancer worldwide. Over 2 million new cases of BC were identified in 2020 alone. Despite previous studies, the lack of specific biomarkers and signaling pathways implicated in BC impedes the development of potential therapeutic strategies. We employed several RNAseq datasets to extract differentially expressed genes (DEGs) based on the intersection of all datasets, followed by protein-protein interaction network construction. Using the shared DEGs, we also identified significant gene ontology (GO) and KEGG pathways to understand the signaling pathways involved in BC development. A molecular docking simulation was performed to explore potential interactions between proteins and drugs. The intersection of the four datasets resulted in 146 DEGs common, including AURKB, PLK1, TTK, UBE2C, CDCA8, KIF15, and CDC45 that are significant hub-proteins associated with breastcancer development. These genes are crucial in complement activation, mitotic cytokinesis, aging, and cancer development. We identified key microRNAs (i.e., hsa-miR-16-5p, hsa-miR-1-3p, hsa-miR-147a, hsa-miR-195-5p, and hsa-miR-155-5p) that are associated with aggressive tumor behavior and poor clinical outcomes in BC. Notable transcription factors (TFs) were FOXC1, GATA2, FOXL1, ZNF24 and NR2F6. These biomarkers are involved in regulating cancer cell proliferation, invasion, and migration. Finally, molecular docking suggested Hesperidin, 2-amino-isoxazolopyridines, and NMS-P715 as potential lead compounds against BC progression. We believe that these findings will provide important insight into the BC progression as well as potential biomarkers and drug candidates for therapeutic development.
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Affiliation(s)
- Most Shornale Akter
- Department of Biotechnology and Genetic EngineeringIslamic UniversityKushtiaBangladesh
| | - Md. Helal Uddin
- Department of Biotechnology and Genetic EngineeringIslamic UniversityKushtiaBangladesh
| | - Sheikh Atikur Rahman
- Department of Biotechnology and Genetic EngineeringIslamic UniversityKushtiaBangladesh
| | - Md. Arju Hossain
- Department of Biotechnology and Genetic EngineeringMawlana Bhashani Science and Technology UniversityTangailBangladesh
- Department of MicrobiologyPrimeasia UniversityDhakaBangladesh
| | | | - Nurun Nesa Zaman
- Department of Biotechnology and Genetic EngineeringIslamic UniversityKushtiaBangladesh
| | - Omar Faruk
- Department of Biotechnology and Genetic EngineeringMawlana Bhashani Science and Technology UniversityTangailBangladesh
| | | | - Anzana Parvin
- Department of Biotechnology and Genetic EngineeringIslamic UniversityKushtiaBangladesh
| | - Md Habibur Rahman
- Department of Computer Science and EngineeringIslamic UniversityKushtiaBangladesh
- Center for Advanced Bioinformatics and Artificial Intelligence ResearchIslamic UniversityKushtiaBangladesh
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Tuly KF, Hossen MB, Islam MA, Kibria MK, Alam MS, Harun-Or-Roshid M, Begum AA, Hasan S, Mahumud RA, Mollah MNH. Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1705. [PMID: 37893423 PMCID: PMC10608013 DOI: 10.3390/medicina59101705] [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: 07/21/2023] [Revised: 09/07/2023] [Accepted: 09/20/2023] [Indexed: 10/29/2023]
Abstract
Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.
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Affiliation(s)
- Khanis Farhana Tuly
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Bayazid Hossen
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Ariful Islam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Kaderi Kibria
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
- Department of Statistics, Hajee Mohammad Danesh Science & Technology University, Dinajpur 5200, Bangladesh
| | - Md. Shahin Alam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Harun-Or-Roshid
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Anjuman Ara Begum
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Sohel Hasan
- Molecular and Biomedical Health Science Lab, Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh;
| | - Rashidul Alam Mahumud
- NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia;
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
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Wang SS, Zhai GQ, Huang ZG, Luo JY, He J, Huang JZ, Yang L, Xiao CN, Li SL, Chen KR, Chen YY, Ji HC, Ding JP, Li SH, Cheng JW, Chen G. Nitidine chloride regulates cell function of bladder cancer in vitro through downregulating Lymphocyte antigen 75. NAUNYN-SCHMIEDEBERG'S ARCHIVES OF PHARMACOLOGY 2023; 396:2071-2085. [PMID: 36914902 DOI: 10.1007/s00210-023-02446-0] [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: 09/23/2022] [Accepted: 02/23/2023] [Indexed: 03/16/2023]
Abstract
Nitidine chloride (NC) is effective on cancer in many tumors, but its effect on bladder cancer (BC) is unknown. We conducted cell function experiments to verify the antineoplastic effect of NC on BC cell lines (5637, T24, and UM-UC-3) in vitro. Then, mRNAs of NC-treated and NC-untreated BC cells were extracted for mRNA sequencing. Differentially expressed genes (DEGs), expression analysis, and drug molecular docking were conducted to discover the target gene of NC. Finally, functional enrichment was analyzed to explore the underlying mechanisms. NC dramatically inhibited proliferation, migration, and invasion, and it induced apoptosis and arrested the S and G2/M phases of BC cell lines. Lymphocyte antigen 75 (LY75) appeared to be the target of NC. LY75 was highly expressed and had the ability to distinguish BC tissue from non-cancerous tissue. Then, drug molecular docking confirmed the targeting relationship between NC and LY75. Gene enrichment analysis showed that the downregulated genes, after being treated with NC, were mainly enriched in pathways relevant to cell pathophysiological processes. NC inhibits BC cell proliferation, migration, and invasion, induces apoptosis, and arrests cell cycles by downregulating the expression of LY75. This study provides molecular and theoretical bases for NC treatment of BC.
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Affiliation(s)
- Shi-Shuo Wang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Gao-Qiang Zhai
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Zhi-Guang Huang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Jia-Yuan Luo
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Juan He
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Jie-Zhuang Huang
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Ling Yang
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Chu-Nan Xiao
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Su-Li Li
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Kai-Rong Chen
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Yan-Yu Chen
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Han-Chu Ji
- Department of Urology, Eighth Affiliated Hospital of Guangxi Medical University (Guigang City People's Hospital), Guigang, 537100, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Jun-Ping Ding
- Department of Urology, Liuzhou Municipal Liutie Central Hospital, Liuzhou, 545007, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Sheng-Hua Li
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Ji-Wen Cheng
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.
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Mirza Z, Ansari MS, Iqbal MS, Ahmad N, Alganmi N, Banjar H, Al-Qahtani MH, Karim S. Identification of Novel Diagnostic and Prognostic Gene Signature Biomarkers for Breast Cancer Using Artificial Intelligence and Machine Learning Assisted Transcriptomics Analysis. Cancers (Basel) 2023; 15:3237. [PMID: 37370847 DOI: 10.3390/cancers15123237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/10/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND Breast cancer (BC) is one of the most common female cancers. Clinical and histopathological information is collectively used for diagnosis, but is often not precise. We applied machine learning (ML) methods to identify the valuable gene signature model based on differentially expressed genes (DEGs) for BC diagnosis and prognosis. METHODS A cohort of 701 samples from 11 GEO BC microarray datasets was used for the identification of significant DEGs. Seven ML methods, including RFECV-LR, RFECV-SVM, LR-L1, SVC-L1, RF, and Extra-Trees were applied for gene reduction and the construction of a diagnostic model for cancer classification. Kaplan-Meier survival analysis was performed for prognostic signature construction. The potential biomarkers were confirmed via qRT-PCR and validated by another set of ML methods including GBDT, XGBoost, AdaBoost, KNN, and MLP. RESULTS We identified 355 DEGs and predicted BC-associated pathways, including kinetochore metaphase signaling, PTEN, senescence, and phagosome-formation pathways. A hub of 28 DEGs and a novel diagnostic nine-gene signature (COL10A, S100P, ADAMTS5, WISP1, COMP, CXCL10, LYVE1, COL11A1, and INHBA) were identified using stringent filter conditions. Similarly, a novel prognostic model consisting of eight-gene signatures (CCNE2, NUSAP1, TPX2, S100P, ITM2A, LIFR, TNXA, and ZBTB16) was also identified using disease-free survival and overall survival analysis. Gene signatures were validated by another set of ML methods. Finally, qRT-PCR results confirmed the expression of the identified gene signatures in BC. CONCLUSION The ML approach helped construct novel diagnostic and prognostic models based on the expression profiling of BC. The identified nine-gene signature and eight-gene signatures showed excellent potential in BC diagnosis and prognosis, respectively.
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Affiliation(s)
- Zeenat Mirza
- King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Department of Medical Laboratory Science, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Md Shahid Ansari
- Department of Clinical Data Analytics, Max Super Speciality Hospital, Saket, New Delhi 110017, India
| | - Md Shahid Iqbal
- Department of Statistics and Computer Applications, Tilka Manjhi Bhagalpur University, Bhagalpur 812007, India
| | - Nesar Ahmad
- Department of Statistics and Computer Applications, Tilka Manjhi Bhagalpur University, Bhagalpur 812007, India
| | - Nofe Alganmi
- Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Centre of Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Haneen Banjar
- Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Centre of Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Mohammed H Al-Qahtani
- Department of Medical Laboratory Science, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Sajjad Karim
- Department of Medical Laboratory Science, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Dong W, Huang Y. Common Genetic Factors and Pathways in Alzheimer's Disease and Ischemic Stroke: Evidences from GWAS. Genes (Basel) 2023; 14:353. [PMID: 36833280 PMCID: PMC9957001 DOI: 10.3390/genes14020353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/19/2023] [Accepted: 01/27/2023] [Indexed: 02/03/2023] Open
Abstract
Alzheimer's disease (AD) and ischemic stroke (IS) are common neurological disorders, and the comorbidity of these two brain diseases is often seen. Although AD and IS were regarded as two distinct disease entities, in terms of different etiologies and clinical presentation, recent genome-wide association studies (GWASs) revealed that there were common risk genes between AD and IS, indicating common molecular pathways and their common pathophysiology. In this review, we summarize AD and IS risk single nucleotide polymorphisms (SNPs) and their representative genes from the GWAS Catalog database, and find thirteen common risk genes, but no common risk SNPs. Furthermore, the common molecular pathways associated with these risk gene products are summarized from the GeneCards database and clustered into inflammation and immunity, G protein-coupled receptor, and signal transduction. At least seven of these thirteen genes can be regulated by 23 microRNAs identified from the TargetScan database. Taken together, the imbalance of these molecular pathways may give rise to these two common brain disorders. This review sheds light on the pathogenesis of comorbidity of AD and IS, and provides molecular targets for disease prevention, manipulation, and brain health maintenance.
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Affiliation(s)
- Wei Dong
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yue Huang
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Department of Pharmacology, School of Medical Sciences, Faculty of Medicine & Health, UNSW, Sydney, NSW 2052, Australia
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Qin YY, Feng S, Zhang XD, Peng B. Screening of traditional Chinese medicine monomers as ribonucleotide reductase M2 inhibitors for tumor treatment. World J Clin Cases 2022; 10:11299-11312. [PMID: 36387821 PMCID: PMC9649558 DOI: 10.12998/wjcc.v10.i31.11299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/14/2022] [Accepted: 09/29/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Ribonucleotide reductase (RR) is a key enzyme in tumor proliferation, especially its subunit-RRM2. Although there are multiple therapeutics for tumors, they all have certain limitations. Given their advantages, traditional Chinese medicine (TCM) monomers have become an important source of anti-tumor drugs. Therefore, screening and analysis of TCM monomers with RRM2 inhibition can provide a reference for further anti-tumor drug development.
AIM To screen and analyze potential anti-tumor TCM monomers with a good binding capacity to RRM2.
METHODS The Gene Expression Profiling Interactive Analysis database was used to analyze the level of RRM2 gene expression in normal and tumor tissues as well as RRM2's effect on the overall survival rate of tumor patients. TCM monomers that potentially act on RRM2 were screened via literature mining. Using AutoDock software, the screened monomers were docked with the RRM2 protein.
RESULTS The expression of RRM2 mRNA in multiple tumor tissues was significantly higher than that in normal tissues, and it was negatively correlated with the overall survival rate of patients with the majority of tumor types. Through literature mining, we discovered that berberine, ursolic acid, gambogic acid, cinobufagin, quercetin, daphnetin, and osalmide have inhibitory effects on RRM2. The results of molecular docking identified that the above TCM monomers have a strong binding capacity with RRM2 protein, which mainly interacted through hydrogen bonds and hydrophobic force. The main binding sites were Arg330, Tyr323, Ser263, and Met350.
CONCLUSION RRM2 is an important tumor therapeutic target. The TCM monomers screened have a good binding capacity with the RRM2 protein.
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Affiliation(s)
- Ya-Ya Qin
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Song Feng
- School of Basic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Xiao-Dong Zhang
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Bin Peng
- School of Basic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
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Zhao H, Dang R, Zhu Y, Qu B, Sayyed Y, Wen Y, Liu X, Lin J, Li L. Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets. Cancer Biol Med 2022; 19:j.issn.2095-3941.2021.0586. [PMID: 35819135 PMCID: PMC9500228 DOI: 10.20892/j.issn.2095-3941.2021.0586] [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] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE The aim of this study was to identify hub genes associated with immune cell infiltration in breast cancer through bioinformatic analyses of multiple datasets. METHODS Nonparametric (NOISeq) and robust rank aggregation-ranked parametric (EdgeR) methods were used to assess robust differentially expressed genes across multiple datasets. Protein-protein interaction network, GO, KEGG enrichment, and sub-network analyses were performed to identify immune-associated hub genes in breast cancer. Immune cell infiltration was evaluated with the CIBERSORT, XCELL, and TIMER methods. The association between the hub gene-based risk signature and survival was determined through Kaplan-Meier survival analysis, multivariate Cox analysis, and a nomogram with external verification. RESULTS We identified 163 robust differentially expressed genes in breast cancer through applying both nonparametric and parametric methods to multiple GEO (n = 2,212) and TCGA (n = 1,045) datasets. Integrated bioinformatic analyses further identified 10 hub genes: CXCL10, CXCL9, CXCL11, SPP1, POSTN, MMP9, DPT, COL1A1, ADAMDEC1, and RGS1. The 10 hub-gene-based risk signature significantly correlated with the prognosis of patients with breast cancer. Moreover, these hub genes were strongly associated with the extent of infiltration of CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and myeloid dendritic cells into breast tumors. CONCLUSIONS Integrated analyses of multiple databases led to the discovery of 10 robust hub genes that together may serve as a risk factor characteristic of the immune microenvironment in breast cancer.
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Affiliation(s)
- Huanyu Zhao
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Ruoyu Dang
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Yipan Zhu
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Baijian Qu
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Yasra Sayyed
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Ying Wen
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Xicheng Liu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China
| | - Jianping Lin
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China
| | - Luyuan Li
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300350, China,Correspondence to: Luyuan Li E-mail:
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Hao M, Ding C, Sun S, Peng X, Liu W. Chitosan/Sodium Alginate/Velvet Antler Blood Peptides Hydrogel Promotes Diabetic Wound Healing via Regulating Angiogenesis, Inflammatory Response and Skin Flora. J Inflamm Res 2022; 15:4921-4938. [PMID: 36051089 PMCID: PMC9427019 DOI: 10.2147/jir.s376692] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/18/2022] [Indexed: 11/23/2022] Open
Abstract
Background Diabetic ulcer remains a clinical challenge due to impaired angiogenesis and persistent inflammation, requiring new alternative therapies to promote tissue regeneration. Purpose In this study, chitosan/sodium alginate/velvet antler blood peptides (CS/SA/VBPs) hydrogel (CAVBPH) was fabricated and used in the treatment of skin wounds in type 2 diabetes mellitus (T2D) for the first time. Methods VBPs were prepared by hydrolysis and ultrafiltration, and their sequences were identified using LC-MS/MS. The CAVBPH was further fabricated and characterized. A mouse model of T2D was induced by a high-sugar and high-fat diet (HSFD) and streptozotocin (STZ) injection. CAVBPH was applied topically to T2D wounds, and its effects on skin repair and potential biological mechanisms were analyzed by appearance observation, histopathological staining, bioinformatics analysis, Western blot, and 16S rRNA sequencing. Results VBPs had numerous short-chain active peptides, excellent antioxidant activity, and a low hemolysis rate. CAVBPH exhibited desirable biochemical properties and participated in the diabetic wound healing process by promoting cell proliferation (PCNA and α-SMA) and angiogenesis (capillaries and CD31) and alleviating inflammation (CD68). Mechanistically, the therapeutic effect of CAVBPH on chronic wounds might rely on activating the PI3K/AKT/mTOR/HIF-1α/VEGFA pathway and reversing the expression of inflammatory cytokines TNF-α and IL-1β. The results of 16S rRNA sequencing indicated that T2D significantly altered the diversity and structure of skin flora at the wound site. CAVBPH treatment elevated the relative abundance of beneficial microbes (e.g., Corynebacterium_1 and Lactobacillus) and reversed the structural imbalance of skin microbiota. Conclusion These results indicate that CAVBPH is a promising wound dressing, and its repair effect on diabetic wounds by regulating angiogenesis, inflammatory response, and skin flora may depend on the rich small peptides in VBPs.
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Affiliation(s)
- Mingqian Hao
- College of Traditional Chinese Medicine, Jilin Agricultural Science and Technology College, Jilin, People's Republic of China.,School of Chinese Medicinal Materials, Jilin Agricultural University, Changchun, People's Republic of China
| | - Chuanbo Ding
- College of Traditional Chinese Medicine, Jilin Agricultural Science and Technology College, Jilin, People's Republic of China
| | - Shuwen Sun
- School of Chinese Medicinal Materials, Jilin Agricultural University, Changchun, People's Republic of China
| | - Xiaojuan Peng
- School of Chinese Medicinal Materials, Jilin Agricultural University, Changchun, People's Republic of China
| | - Wencong Liu
- School of Chinese Medicinal Materials, Jilin Agricultural University, Changchun, People's Republic of China
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11
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Alam MS, Sultana A, Reza MS, Amanullah M, Kabir SR, Mollah MNH. Integrated bioinformatics and statistical approaches to explore molecular biomarkers for breast cancer diagnosis, prognosis and therapies. PLoS One 2022; 17:e0268967. [PMID: 35617355 PMCID: PMC9135200 DOI: 10.1371/journal.pone.0268967] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 05/11/2022] [Indexed: 02/06/2023] Open
Abstract
Integrated bioinformatics and statistical approaches are now playing the vital role in identifying potential molecular biomarkers more accurately in presence of huge number of alternatives for disease diagnosis, prognosis and therapies by reducing time and cost compared to the wet-lab based experimental procedures. Breast cancer (BC) is one of the leading causes of cancer related deaths for women worldwide. Several dry-lab and wet-lab based studies have identified different sets of molecular biomarkers for BC. But they did not compare their results to each other so much either computationally or experimentally. In this study, an attempt was made to propose a set of molecular biomarkers that might be more effective for BC diagnosis, prognosis and therapies, by using the integrated bioinformatics and statistical approaches. At first, we identified 190 differentially expressed genes (DEGs) between BC and control samples by using the statistical LIMMA approach. Then we identified 13 DEGs (AKR1C1, IRF9, OAS1, OAS3, SLCO2A1, NT5E, NQO1, ANGPT1, FN1, ATF6B, HPGD, BCL11A, and TP53INP1) as the key genes (KGs) by protein-protein interaction (PPI) network analysis. Then we investigated the pathogenetic processes of DEGs highlighting KGs by GO terms and KEGG pathway enrichment analysis. Moreover, we disclosed the transcriptional and post-transcriptional regulatory factors of KGs by their interaction network analysis with the transcription factors (TFs) and micro-RNAs. Both supervised and unsupervised learning's including multivariate survival analysis results confirmed the strong prognostic power of the proposed KGs. Finally, we suggested KGs-guided computationally more effective seven candidate drugs (NVP-BHG712, Nilotinib, GSK2126458, YM201636, TG-02, CX-5461, AP-24534) compared to other published drugs by cross-validation with the state-of-the-art alternatives top-ranked independent receptor proteins. Thus, our findings might be played a vital role in breast cancer diagnosis, prognosis and therapies.
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Affiliation(s)
- Md. Shahin Alam
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- * E-mail: (MNHM); (MSA)
| | - Adiba Sultana
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- Center for Systems Biology, Soochow University, Suzhou, China
| | - Md. Selim Reza
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
| | - Md Amanullah
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- Department of Respiratory Medicine, Sir Run Run Shaw Hospital and Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Syed Rashel Kabir
- Department of Biochemistry and Molecular Biology, Rajshahi University, Rajshahi, Bangladesh
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- * E-mail: (MNHM); (MSA)
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An C, Wang M, Yao W. Exhausting hsa_circ_0072088 restrains proliferation, motility and angiogenesis of breast carcinoma cells through regulating miR-1236-3p and RRM2 in a ceRNA pathway. Clin Breast Cancer 2022. [DOI: 10.1016/j.clbc.2022.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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13
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Liu K, Chen S, Lu R. Identification of important genes related to ferroptosis and hypoxia in acute myocardial infarction based on WGCNA. Bioengineered 2021; 12:7950-7963. [PMID: 34565282 PMCID: PMC8806940 DOI: 10.1080/21655979.2021.1984004] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Acute myocardial infarction (AMI) tends to cause severe heart failure and the population suffering from AMI gradually become younger. This study aims to determine the key genes associated with AMI, ferroptosis and hypoxia that could serve as novel biomarkers for AMI. There were 522 up-regulated genes and 119 down-regulated genes in GSE4648. Based on the expression of ferroptosis-related genes (FRGs) and hypoxia-related genes, the ferroptosis Z-score and the hypoxia Z-score calculated by ssGSEA were significantly higher in the infarcted area of AMI mice than in the control group, and there was a positive correlation between ferroptosis and hypoxia Z-score. 6 modules were obtained by Weighted Gene Co-Expression Network Analysis (WGCNA), and 2 key modules and 66 key genes were screened out. Genes in the key modules were found mainly related to ERK1 and ERK2 cascade, TNF signaling pathway, and MAPK signaling pathway through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Protein-protein interaction (PPI) network analysis was performed on the key genes and 10 hub genes (Atf3, Ptgs2, Cxcl1, Socs3, Hspa1b, Selp, Cxcl2, Il1b, Myd88, and S100a8) were obtained using STRING and Cytohubba. The expression of 9 hub genes except Cxcl1 was consistent in GSE4648 and GSE775. The transcription factors (TFs)-hub genes interaction network was constructed and 48 TFs were obtained using TRRUST. Finally, it was verified through the animal experiment that these hub genes were up-regulated in AMI mice myocardial tissues. This study offers new ideas for the diagnosis and treatment of AMI.
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Affiliation(s)
- Kai Liu
- Department of Cardio-thoracis Surgery, Zhejiang Hospital, Hangzhou, Zhejiang, China
| | - Shaoxi Chen
- Department of Cardio-thoracis Surgery, Zhejiang Hospital, Hangzhou, Zhejiang, China
| | - Ruoyi Lu
- Department of Cardio-thoracis Surgery, Zhejiang Hospital, Hangzhou, Zhejiang, China
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14
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Jiang F, Mao Y, Lu B, Zhou G, Wang J. A hypoxia risk signature for the tumor immune microenvironment evaluation and prognosis prediction in acute myeloid leukemia. Sci Rep 2021; 11:14657. [PMID: 34282207 PMCID: PMC8289869 DOI: 10.1038/s41598-021-94128-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 07/06/2021] [Indexed: 02/06/2023] Open
Abstract
Acute myeloid leukemia (AML) is the most prevalent form of acute leukemia. Patients with AML often have poor clinical prognoses. Hypoxia can activate a series of immunosuppressive processes in tumors, resulting in diseases and poor clinical prognoses. However, how to evaluate the severity of hypoxia in tumor immune microenvironment remains unknown. In this study, we downloaded the profiles of RNA sequence and clinicopathological data of pediatric AML patients from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, as well as those of AML patients from Gene Expression Omnibus (GEO). In order to explore the immune microenvironment in AML, we established a risk signature to predict clinical prognosis. Our data showed that patients with high hypoxia risk score had shorter overall survival, indicating that higher hypoxia risk scores was significantly linked to immunosuppressive microenvironment in AML. Further analysis showed that the hypoxia could be used to serve as an independent prognostic indicator for AML patients. Moreover, we found gene sets enriched in high-risk AML group participated in the carcinogenesis. In summary, the established hypoxia-related risk model could act as an independent predictor for the clinical prognosis of AML, and also reflect the response intensity of the immune microenvironment in AML.
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Affiliation(s)
- Feng Jiang
- grid.8547.e0000 0001 0125 2443Department of Neonatology, Obstetrics and Gynecology Hospital, Fudan University, No. 419, Fangxie Road, Shanghai, 200011 China
| | - Yan Mao
- grid.412676.00000 0004 1799 0784Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Binbin Lu
- grid.412676.00000 0004 1799 0784Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Guoping Zhou
- grid.412676.00000 0004 1799 0784Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Jimei Wang
- grid.8547.e0000 0001 0125 2443Department of Neonatology, Obstetrics and Gynecology Hospital, Fudan University, No. 419, Fangxie Road, Shanghai, 200011 China
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Madakka M, Jayaraju N, Rajesh N. Evaluating the antimicrobial activity and antitumor screening of green synthesized silver nanoparticles compounds, using Syzygium jambolanum, towards MCF7 cell line (Breast cancer cell line). JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY 2021. [DOI: 10.1016/j.jpap.2021.100028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
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Zhang F, Yu X, Lin Z, Wang X, Gao T, Teng D, Teng W. Using Tumor-Infiltrating Immune Cells and a ceRNA Network Model to Construct a Prognostic Analysis Model of Thyroid Carcinoma. Front Oncol 2021; 11:658165. [PMID: 34141614 PMCID: PMC8204697 DOI: 10.3389/fonc.2021.658165] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 04/13/2021] [Indexed: 12/24/2022] Open
Abstract
Thyroid carcinoma is a solid malignant tumor that has had a fast-growing incidence in recent years. Our research used thyroid carcinoma gene expression profiling from TCGA (The Cancer Genome Atlas) database to identify differentially expressed ceRNAs. Using the gene expression profiling from 502 carcinoma thyroid tissues and 58 normal thyroid tissues from the TCGA database, we established the thyroid carcinoma-specific competitive endogenous RNA (ceRNA) network and found nine overall survival (OS)-associated genes (PRDM1, TGFBR3, E2F1, FGF1, ADAM12, ALPL, RET, AL928654.2, AC128688.2). We quantified the proportions of immune cells using the algorithm “CIBERSORT”, found three OS-associated immune cells (memory B cells, M0 macrophages, and activated dendritic cells), and established a thyroid carcinoma-specific immune cell network based on that. The good reliabilities AUC (area under the curve) of 10-year survival (0.955, 0.944, respectively) were accessed from the nomograms of genes and immune cells. Subsequently, by conducting co-expression analyses, we found a potential regulation network among ceRNAs and immune cells. Besides, we found that ALPL (alkaline phosphatase) and hsa-miR-204-5p were significantly correlated and that ALPL was related to activated dendritic cells. We took advantage of multi-dimensional databases to verify our discovery. Besides, immunohistochemistry (IHC) assays were conducted to detect the expression of a dendritic cell marker (CD11c) and ALPL in thyroid carcinoma (TC) and paracancerous tissues. In summary, our study found a potential mechanism in which hsa-miR-204-5p regulated ALPL in activated dendritic cells, which may allow them to play a critical role in thyroid carcinoma. These findings provide potential prognostic biomarkers and therapeutic targets for thyroid carcinoma.
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Affiliation(s)
- Fan Zhang
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Xiaohui Yu
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Zheyu Lin
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Xichang Wang
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Tiantian Gao
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Di Teng
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
| | - Weiping Teng
- Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, China
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