Identification of hub genes in bladder cancer based on weighted gene co‐expression network analysis from TCGA database

Abstract

Background Muscular invasive bladder cancer (MIBC) is a common malignant tumor in the world. Because of their heterogeneity in prognosis and response to treatment, biomarkers that can predict survival or help make treatment decisions in patients with MIBC are essential for individualized treatment. Aim We aimed to integrate bioinformatics research methods to identify a set of effective biomarkers capable of predicting, diagnosing, and treating MIBC. To provide a new theoretical basis for the diagnosis and treatment of bladder cancer. Methods and results Gene expression profiles and clinical data of MIBC were obtained by downloading from the Cancer Genome Atlas database. A dataset of 129 MIBC cases and controls was included. 2084 up‐regulated genes and 2961 down‐regulated genes were identified by differentially expressed gene (DEG) analysis. Then, gene ontology analysis was performed to explore the biological functions of DEGs, respectively. The up‐regulated DEGs are mainly enriched in epidermal cell differentiation, mitotic nuclear division, and so forth. They are also involved in the cell cycle, p53 signaling pathway, PPAR signaling pathway, and so forth. The weighted gene co‐expression network analysis yielded five modules related to pathological stages and grading, of which blue and turquoise were the most relevant modules for MIBC. Next, Using Kaplan–Meier survival analysis to identify further hub genes, the screening criteria at p ≤ .05, we found CNKSR1 , HIP1R , CFL2 , TPM1 , CSRP1 , SYNM , POPDC2 , PJA2 , and RBBP8NL genes associated with the progression and prognosis of MIBC patients. Finally, immunohistochemistry experiments further confirmed that CNKSR1 plays a vital role in the tumorigenic context of MIBC. Conclusion The research suggests that CNKSR1 , POPDC2 , and PJA2 may be novel biomarkers as therapeutic targets for MIBC, especially we used immunohistochemical further to validate CNKSR1 as a therapeutic target for MIBC which may help to improve the prognosis for MIBC.

CSRP1 gene: a potential novel prognostic marker in acute myeloid leukemia with implications for immune response

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Aberrant expression of PTPRN2 promotes malignant transformation of colorectal cancer cells through EMT/TRAF2/STAT3 signaling pathway

“…Some studies have shown that PTPRN2 is frequently expressed in temozolomide-resistant glioblastoma [31] , and castration-resistant prostate tumors [32] , suggesting that PTPRN2 is a promising therapeutic target of cancer. Bioinformatics research has found that PTPRN2 differs between the lower (II and III) and high (IV) grade gliomas, with its expression being higher in grade IV glioblastomas [33] , and are linked to bladder cancer [34] , and leiomyosarcoma sarcomagenesis [35] , but detailed research is lacking. In-depth studies, it has been demonstrated that PTPRN2 is strongly related to poor OS in breast cancer patients, through resistance to apoptosis [17] , and promotes the metastatic ability of breast cancer cells [16] .…”

A novel feature selection algorithm for identifying hub genes in lung cancer

“…We utilized the WGCNA package in R to establish co-expressed gene modules and, notably, identified a significant gene module with the most robust correlation to lung cancer, as documented in Refs. 35 , 53 , 54 . Furthermore, we applied WGCNA to the selected genes to explore the intricate expression patterns that existed among them.…”