Literature DB >> 35836886

Screening a novel six critical gene-based system of diagnostic and prognostic biomarkers in prostate adenocarcinoma patients with different clinical variables.

Hadia Munir1, Fawad Ahmad2, Sajid Ullah3, Saeedah Musaed Almutairi4, Samra Asghar5, Tehmina Siddique6, Mostafa A Abdel-Maksoud4, Rabab Ahmed Rasheed7, Fatma Alzahraa A Elkhamisy8,9, Mohammed Aufy10, Hamid Yaz4.   

Abstract

The mechanisms behind prostate adenocarcinoma (PRAD) pathogenicity remain to be understood due to tumor heterogeneity. In the current study, we identified by microarray technology six eligible real hub genes from already identified hub genes through a systematic in silico approach that could be useful to lower the heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment. For this purpose, microarray technology-based, already-identified PRAD-associated hub genes were initially explored through extensive literature mining; then, a protein-protein interaction (PPI) network construction of those hub genes and its analysis helped us to identify six most critical genes (real hub genes). Various online available expression databases were then used to explore the tumor driving, diagnostic, and prognostic roles of real hub genes in PRAD patients with different clinicopathologic variables. In total, 124 hub genes were extracted from the literature, and among those genes, six, including CDC20, HMMR, AURKA, CDK1, ASF1B, and CCNB1 were identified as real hub genes by the degree method. Further expression analysis revealed the significant up-regulation of real hub genes in PRAD patients of different races, age groups, and nodal metastasis status relative to controls. Moreover, through correlational analyses, different valuable correlations between treal hub genes expression and different other data (promoter methylation status, genetic alterations, overall survival (OS), tumor purity, CD4+ T, CD8+ T immune cells infiltration, and different other mutant genes and a few more) across PRAD samples were also documented. Ultimately, from this study, a few important transcription factors (TFS), miRNAs, and chemotherapeutic drugs showing a great therapeutic potential were also identified. In conclusion, we have discovered a set of six real hub genes that might be utilized as new biomarkers for lowering heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment. AJTR
Copyright © 2022.

Entities:  

Keywords:  PRAD; biomarker; heterogeneity; overall survival (OS); tissue microarray

Year:  2022        PMID: 35836886      PMCID: PMC9274568     

Source DB:  PubMed          Journal:  Am J Transl Res        ISSN: 1943-8141            Impact factor:   3.940


  122 in total

1.  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

Review 2.  CDK1 in Breast Cancer: Implications for Theranostic Potential.

Authors:  Sepideh Izadi; Afshin Nikkhoo; Mohammad Hojjat-Farsangi; Afshin Namdar; Gholamreza Azizi; Hamed Mohammadi; Mehdi Yousefi; Farhad Jadidi-Niaragh
Journal:  Anticancer Agents Med Chem       Date:  2020       Impact factor: 2.505

3.  Degradation of CCNB1 mediated by APC11 through UBA52 ubiquitination promotes cell cycle progression and proliferation of non-small cell lung cancer cells.

Authors:  Fajiu Wang; Xi Chen; Xiaobo Yu; Qiang Lin
Journal:  Am J Transl Res       Date:  2019-11-15       Impact factor: 4.060

4.  Histone H3.1 and H3.3 complexes mediate nucleosome assembly pathways dependent or independent of DNA synthesis.

Authors:  Hideaki Tagami; Dominique Ray-Gallet; Geneviève Almouzni; Yoshihiro Nakatani
Journal:  Cell       Date:  2004-01-09       Impact factor: 41.582

5.  Restoration of paclitaxel resistance by CDK1 intervention in drug-resistant ovarian cancer.

Authors:  Taejeong Bae; Kwon-Yeon Weon; Jeong-Won Lee; Ki-Hwan Eum; Sungchul Kim; Jin Woo Choi
Journal:  Carcinogenesis       Date:  2015-10-06       Impact factor: 4.944

6.  Identification of hub genes in prostate cancer using robust rank aggregation and weighted gene co-expression network analysis.

Authors:  Zhen-Yu Song; Fan Chao; Zhiyuan Zhuo; Zhe Ma; Wenzhi Li; Gang Chen
Journal:  Aging (Albany NY)       Date:  2019-07-15       Impact factor: 5.682

Review 7.  Risk factors and biomarkers of life-threatening cancers.

Authors:  Philippe Autier
Journal:  Ecancermedicalscience       Date:  2015-11-24

8.  DriverDBv2: a database for human cancer driver gene research.

Authors:  I-Fang Chung; Chen-Yang Chen; Shih-Chieh Su; Chia-Yang Li; Kou-Juey Wu; Hsei-Wei Wang; Wei-Chung Cheng
Journal:  Nucleic Acids Res       Date:  2015-12-03       Impact factor: 16.971

9.  Aurora kinase A (AURKA) interaction with Wnt and Ras-MAPK signalling pathways in colorectal cancer.

Authors:  Annika Jacobsen; Linda J W Bosch; Sanne R Martens-de Kemp; Beatriz Carvalho; Anke H Sillars-Hardebol; Richard J Dobson; Emanuele de Rinaldis; Gerrit A Meijer; Sanne Abeln; Jaap Heringa; Remond J A Fijneman; K Anton Feenstra
Journal:  Sci Rep       Date:  2018-05-14       Impact factor: 4.379

10.  Comprehensive analysis of pan-cancer reveals potential of ASF1B as a prognostic and immunological biomarker.

Authors:  Xinyao Hu; Hua Zhu; Xiaoyu Zhang; Xiaoqin He; Ximing Xu
Journal:  Cancer Med       Date:  2021-09-02       Impact factor: 4.452

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