Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer
Precision oncology is an absolute need today due to the emergence of treatment resistance and heterogeneity among cancerous profiles. Target-propelled cancer therapy is one of the treasures of precision oncology which has come together with substantial medical accomplishment. Prostate cancer is one...
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Frontiers Media S.A.
2022-06-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.881246/full |
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author | Taj Mohammad Prithvi Singh Deeba Shamim Jairajpuri Lamya Ahmed Al-Keridis Nawaf Alshammari Mohd. Adnan Ravins Dohare Md Imtaiyaz Hassan |
author_facet | Taj Mohammad Prithvi Singh Deeba Shamim Jairajpuri Lamya Ahmed Al-Keridis Nawaf Alshammari Mohd. Adnan Ravins Dohare Md Imtaiyaz Hassan |
author_sort | Taj Mohammad |
collection | DOAJ |
description | Precision oncology is an absolute need today due to the emergence of treatment resistance and heterogeneity among cancerous profiles. Target-propelled cancer therapy is one of the treasures of precision oncology which has come together with substantial medical accomplishment. Prostate cancer is one of the most common cancers in males, with tremendous biological heterogeneity in molecular and clinical behavior. The spectrum of molecular abnormalities and varying clinical patterns in prostate cancer suggest substantial heterogeneity among different profiles. To identify novel therapeutic targets and precise biomarkers implicated with prostate cancer, we performed a state-of-the-art bioinformatics study, beginning with analyzing high-throughput genomic datasets from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) suggests a set of five dysregulated hub genes (MAF, STAT6, SOX2, FOXO1, and WNT3A) that played crucial roles in biological pathways associated with prostate cancer progression. We found overexpressed STAT6 and SOX2 and proposed them as candidate biomarkers and potential targets in prostate cancer. Furthermore, the alteration frequencies in STAT6 and SOX2 and their impact on the patients’ survival were explored through the cBioPortal platform. The Kaplan-Meier survival analysis suggested that the alterations in the candidate genes were linked to the decreased overall survival of the patients. Altogether, the results signify that STAT6 and SOX2 and their genomic alterations can be explored in therapeutic interventions of prostate cancer for precision oncology, utilizing early diagnosis and target-propelled therapy. |
first_indexed | 2024-04-12T11:11:54Z |
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institution | Directory Open Access Journal |
issn | 2234-943X |
language | English |
last_indexed | 2024-04-12T11:11:54Z |
publishDate | 2022-06-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Oncology |
spelling | doaj.art-0a13df85ef664e1aa82c29e713b88c382022-12-22T03:35:35ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-06-011210.3389/fonc.2022.881246881246Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate CancerTaj Mohammad0Prithvi Singh1Deeba Shamim Jairajpuri2Lamya Ahmed Al-Keridis3Nawaf Alshammari4Mohd. Adnan5Ravins Dohare6Md Imtaiyaz Hassan7Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, IndiaCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, IndiaDepartment of Medical Biochemistry, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, BahrainDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi ArabiaDepartment of Biology, College of Science, University of Hail, Hail, Saudi ArabiaDepartment of Biology, College of Science, University of Hail, Hail, Saudi ArabiaCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, IndiaCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, IndiaPrecision oncology is an absolute need today due to the emergence of treatment resistance and heterogeneity among cancerous profiles. Target-propelled cancer therapy is one of the treasures of precision oncology which has come together with substantial medical accomplishment. Prostate cancer is one of the most common cancers in males, with tremendous biological heterogeneity in molecular and clinical behavior. The spectrum of molecular abnormalities and varying clinical patterns in prostate cancer suggest substantial heterogeneity among different profiles. To identify novel therapeutic targets and precise biomarkers implicated with prostate cancer, we performed a state-of-the-art bioinformatics study, beginning with analyzing high-throughput genomic datasets from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) suggests a set of five dysregulated hub genes (MAF, STAT6, SOX2, FOXO1, and WNT3A) that played crucial roles in biological pathways associated with prostate cancer progression. We found overexpressed STAT6 and SOX2 and proposed them as candidate biomarkers and potential targets in prostate cancer. Furthermore, the alteration frequencies in STAT6 and SOX2 and their impact on the patients’ survival were explored through the cBioPortal platform. The Kaplan-Meier survival analysis suggested that the alterations in the candidate genes were linked to the decreased overall survival of the patients. Altogether, the results signify that STAT6 and SOX2 and their genomic alterations can be explored in therapeutic interventions of prostate cancer for precision oncology, utilizing early diagnosis and target-propelled therapy.https://www.frontiersin.org/articles/10.3389/fonc.2022.881246/fullprostate cancerprecision oncologytarget-propelled therapyThe Cancer Genome Atlasweighted gene co-expression network analysis |
spellingShingle | Taj Mohammad Prithvi Singh Deeba Shamim Jairajpuri Lamya Ahmed Al-Keridis Nawaf Alshammari Mohd. Adnan Ravins Dohare Md Imtaiyaz Hassan Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer Frontiers in Oncology prostate cancer precision oncology target-propelled therapy The Cancer Genome Atlas weighted gene co-expression network analysis |
title | Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer |
title_full | Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer |
title_fullStr | Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer |
title_full_unstemmed | Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer |
title_short | Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer |
title_sort | differential gene expression and weighted correlation network dynamics in high throughput datasets of prostate cancer |
topic | prostate cancer precision oncology target-propelled therapy The Cancer Genome Atlas weighted gene co-expression network analysis |
url | https://www.frontiersin.org/articles/10.3389/fonc.2022.881246/full |
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