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A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

ABSTRACT: A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ?8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ?8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of factors such as "overexpression" and "shorter survival" is vital, as poor definition may lead to mis-estimations. To eliminate this possibility, we defined an expression cutoff value using an algorithm calculated by a Cox regression model, and the hazard ratio for each gene was set so as to identify genes whose expression levels were associated with shorter survival. Next, genes associated with shorter survival were entered into pathway analysis to identify pathways that were altered in a shorter survival cohort. We identified pathways involving upregulation of GRB2. Overexpression of GRB2 was linked to shorter survival in the TCGA dataset, a finding validated by histological examination of biopsy samples taken from the patients for diagnostic purposes. Thus, GRB2 is a novel biomarker that predicts shorter survival of patients with aggressive prostate cancer (GS ?8).

SUBMITTER: Iwata T

PROVIDER: S-EPMC7952695 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

Iwata Teppei T Sedukhina Anna S AS Kubota Manabu M Oonuma Shigeko S Maeda Ichiro I Yoshiike Miki M Usuba Wataru W Minagawa Kimino K Hames Eleina E Meguro Rei R Cho Sunny S Chien Stephen H H SHH Urabe Shiro S Pae Sookhee S Palanisamy Kishore K Kumai Toshio T Yudo Kazuo K Kikuchi Eiji E Sato Ko K

Scientific reports 20210311 1

A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ≧8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of facto ...[more]

PMID: 33707553

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Project description:To screen target gene cluster by bioinformatics analysis and verify them by in vitro experiment and clinicopathological correlation analysis. We try to find a new biomarker with prognostic value for prostate cancer (PCa). 42 candidate marker genes were constructed by protein protein interaction (PPI) network and enriched by KEGG pathway to find out the gene cluster we are interested in. Prognostic model was established to preliminarily analyze the prognostic value of this gene cluster in PCa, and Cox risk regression was used for comparative analysis. Immunohistochemistry was used to detect the expression of each gene in clinical tissue microarray. Finally, we analyzed the correlation between each gene and their clinicopathological features of PCa combined with TCGA clinical data. Based on the analysis of PPI and KEGG, we found the target gene cluster (FCGR3A, HAVCR2, CCR7 and CD28). Prognostic model analysis showed that this gene cluster had the ability to predict biochemical recurrence, and the survival rate and ROC analysis showed favorable prediction effect. Univariate Cox regression analysis showed that the risk scores of Gleason score (GS), T stage, N stage and PSA were significantly different (P<0.05), and the risk ratio of high expression was 2.30 times that of low expression (P=0.004). However, it was not statistically significant in multivariate Cox regression analysis (P>0.05). The results of tissue microarray showed that FCGR3A and HAVCR2 were highly expressed in PCa (P<0.01), while the expression of CCR7 and CD28 had no significant difference (P>0.05). Kaplan-Meier analysis showed that there was significant difference in BCR free survival of FCGR3A and HAVCR2 (FCGR3A, P=0.010; HAVCR2, P=0.018), while the expression of CCR7 and CD28 had no significant difference on the survival and prognosis of PCa patients (P>0.05). TCGA clinical data analysis found that the expression of FCGR3A had a unique correlation with the clinicopathological features of PCa, which was closely related to the tumor stage. The expression of FCGR3A is related to BCR free survival of PCa patients. Therefore, FCGR3A is a new biomarker with potential prognostic value of PCa.

Project description:BACKGROUND:Recently, many potential prognostic biomarkers for gastric cancer (GC) have been identified, but the prognosis of advanced GC patients remains poor. Chloride channels are promising cancer biomarkers, and their family member chloride channel-3 (CLC-3) is involved in multiple biological behaviors. However, whether CLC-3 is a prognostic biomarker for GC patients is rarely reported. The molecular mechanisms by which CLC-3 is regulated in GC are unclear. METHODS:The expression of CLC-3 and XRCC5 in human specimens was analyzed using immunohistochemistry. The primary biological functions and pathways related to CLC-3 were enriched by RNA sequencing. A 5'-biotin-labeled DNA probe with a promoter region between -?248 and +?226 was synthesized to pull down CLC-3 promoter-binding proteins. Functional studies were detected by MTS, clone formation, wound scratch, transwell, and xenograft mice model. Mechanistic studies were investigated by streptavidin-agarose-mediated DNA pull-down, mass spectrometry, ChIP, dual-luciferase reporter assay system, Co-IP, and immunofluorescence. RESULTS:The results showed that CLC-3 was overexpressed in human GC tissues and that overexpression of CLC-3 was a poor prognostic biomarker for GC patients (P?=?0.012). Furthermore, higher expression of CLC-3 was correlated with deeper tumor invasion (P?=?0.006) and increased lymph node metastasis (P?=?0.016), and knockdown of CLC-3 inhibited cell proliferation and migration in vitro. In addition, X-ray repair cross-complementing 5 (XRCC5) was identified as a CLC-3 promoter-binding protein, and both CLC-3 (HR 1.671; 95% CI 1.012-2.758; P?=?0.045) and XRCC5 (HR 1.795; 95% CI 1.076-2.994; P?=?0.025) were prognostic factors of overall survival in GC patients. The in vitro and in vivo results showed that the expression and function of CLC-3 were inhibited after XRCC5 knockdown, and the inhibition effects were rescued by CLC-3 overexpression. Meanwhile, the expression and function of CLC-3 were promoted after XRCC5 overexpression, and the promotion effects were reversed by the CLC-3 knockdown. The mechanistic study revealed that knockdown of XRCC5 suppressed the binding of XRCC5 to the CLC-3 promoter and subsequent promoter activity, thus regulating CLC-3 expression at the transcriptional level by interacting with PARP1. CONCLUSIONS:Our findings indicate that overexpression of CLC-3 is regulated by XRCC5 and is a poor prognostic biomarker for gastric cancer. Double targeting CLC-3 and XRCC5 may provide the promising therapeutic potential for GC treatment.

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A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

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A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

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