Literature DB >> 34184132

Transcriptomic analysis of castration, chemo-resistant and metastatic prostate cancer elucidates complex genetic crosstalk leading to disease progression.

Sayani Mukherjee1, C Sudandiradoss2.   

Abstract

Prostate adenocarcinoma, with its rising numbers and high fatality rate, is a daunting healthcare challenge to clinicians and researchers alike. The mainstay of our meta-analysis was to decipher differentially expressed genes (DEGs), their corresponding transcription factors (TFs), miRNAs (microRNA) and interacting pathways underlying the progression of prostate cancer (PCa). We have chosen multiple datasets from primary, castration-resistant, chemo-resistant and metastatic prostate cancer stages for investigation. From our tissue-specific and disease-specific co-expression networks, fifteen hub genes such as ACTB, ACTN1, CDH1, CDKN1A, DDX21, ELF3, FLNA, FLNC, IKZF1, ILK, KRT13, KRT18, KRT19, SVIL and TRIM29 were identified and validated by molecular complex detection analysis as well as survival analysis. In our attempt to highlight hub gene-associated mutations and drug interactions, FLNC was found to be most commonly mutated and CDKN1A gene was found to have highest druggability. Moreover, from DAVID and gene set enrichment analysis, the focal adhesion and oestrogen signalling pathways were found enriched which indicates the involvement of hub genes in tumour invasiveness and metastasis. Finally by Enrichr tool and miRNet, we identified transcriptional factors SNAI2, TP63, CEBPB and KLF11 and microRNAs, namely hsa-mir-1-3p, hsa-mir-145-5p, hsa-mir-124-3p and hsa-mir-218-5p significantly controlling the hub gene expressions. In a nutshell, our report will help to gain a deeper insight into complex molecular intricacies and thereby unveil the probable biomarkers and therapeutic targets involved with PCa progression.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Castration resistance; Chemoresistance; Hub genes; Metastasis; Prostate cancer; Transcriptomic analysis

Mesh:

Substances:

Year:  2021        PMID: 34184132     DOI: 10.1007/s10142-021-00789-6

Source DB:  PubMed          Journal:  Funct Integr Genomics        ISSN: 1438-793X            Impact factor:   3.410


  49 in total

1.  Integrin-linked kinase expression increases with prostate tumor grade.

Authors:  J R Graff; J A Deddens; B W Konicek; B M Colligan; B M Hurst; H W Carter; J H Carter
Journal:  Clin Cancer Res       Date:  2001-07       Impact factor: 12.531

2.  The Gene Expression Omnibus Database.

Authors:  Emily Clough; Tanya Barrett
Journal:  Methods Mol Biol       Date:  2016

3.  ERG induces androgen receptor-mediated regulation of SOX9 in prostate cancer.

Authors:  Changmeng Cai; Hongyun Wang; Housheng Hansen He; Sen Chen; Lingfeng He; Fen Ma; Lorelei Mucci; Qianben Wang; Christopher Fiore; Adam G Sowalsky; Massimo Loda; X Shirley Liu; Myles Brown; Steven P Balk; Xin Yuan
Journal:  J Clin Invest       Date:  2013-02-15       Impact factor: 14.808

Review 4.  The role of estrogen receptor β in prostate cancer.

Authors:  Paraskevi Christoforou; Panagiotis F Christopoulos; Michael Koutsilieris
Journal:  Mol Med       Date:  2014-10-02       Impact factor: 6.354

Review 5.  Taxane mechanisms of action: potential implications for treatment sequencing in metastatic castration-resistant prostate cancer.

Authors:  John M Fitzpatrick; Ronald de Wit
Journal:  Eur Urol       Date:  2013-07-25       Impact factor: 20.096

6.  Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods.

Authors:  Chao Chen; Kay Grennan; Judith Badner; Dandan Zhang; Elliot Gershon; Li Jin; Chunyu Liu
Journal:  PLoS One       Date:  2011-02-28       Impact factor: 3.240

7.  CCAAT/Enhancer binding protein β controls androgen-deprivation-induced senescence in prostate cancer cells.

Authors:  D J Barakat; J Zhang; T Barberi; S R Denmeade; A D Friedman; I Paz-Priel
Journal:  Oncogene       Date:  2015-03-16       Impact factor: 9.867

8.  cytoHubba: identifying hub objects and sub-networks from complex interactome.

Authors:  Chia-Hao Chin; Shu-Hwa Chen; Hsin-Hung Wu; Chin-Wen Ho; Ming-Tat Ko; Chung-Yen Lin
Journal:  BMC Syst Biol       Date:  2014-12-08

9.  Impact of novel miR-145-3p regulatory networks on survival in patients with castration-resistant prostate cancer.

Authors:  Yusuke Goto; Akira Kurozumi; Takayuki Arai; Nijiro Nohata; Satoko Kojima; Atsushi Okato; Mayuko Kato; Kazuto Yamazaki; Yasuo Ishida; Yukio Naya; Tomohiko Ichikawa; Naohiko Seki
Journal:  Br J Cancer       Date:  2017-06-22       Impact factor: 7.640

10.  ER membrane-bending proteins are necessary for de novo nuclear pore formation.

Authors:  T Renee Dawson; Michelle D Lazarus; Martin W Hetzer; Susan R Wente
Journal:  J Cell Biol       Date:  2009-03-09       Impact factor: 10.539

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  1 in total

1.  Transcriptome Analysis Reveals Hub Genes Regulating Autophagy in Patients With Severe COVID-19.

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  1 in total

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