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Development of RNA binding proteins expression signature for prognosis prediction in gastric cancer patients.

ABSTRACT: It was reported that the expression of RNA binding proteins (RBPs) in malignant tumors is dysregulated and is closely related to tumorigenesis. However, some studies have confirmed the role of RBPs in gastric cancer (GC). We obtained data on gastric cancer in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and identified RBPs that are dysregulated between gastric normal and cancer tissues. Then, we systematically investigated the expression characteristics and clinical prognostic potential of these RBPs through bioinformatics methods. We found 278 dysregulated RBPs in the GC, 91 of which were up-regulated and 181 were down-regulated. We detected 4 hub RBPs (HNRNPL, PABPN1, PCF, SNRPN) are related to overall survival (OS), and 3 hub RBPs (EEF1A2, MRPS5, PCF1) are related to disease-specific survival (DSS), and furthermore, we constructed prognostic signatures. Analysis of the OS and DSS signature showed that the GC patients with high-risk groups have worse OS and DSS than the low-risk groups. The receiver operator characteristic (ROC) curves of the 5-year survival rate of OS and DSS prognosis signature were drawn, and the areas under the two curves were 0.62 and 0.64, respectively. We constructed nomograms to predict OS and DSS, and evaluated by the calibration curve, which showed the GC prediction ability of these two models. Furthermore, the expression of the above six genes was verified by PCR, which is consistent with our results.

SUBMITTER: Zhou L

PROVIDER: S-EPMC7653620 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Development of RNA binding proteins expression signature for prognosis prediction in gastric cancer patients.

Zhou Liqiang L Wu You Y Xin Lin L Zhou Qi Q Li Shihao S Yuan Yiwu Y Wang Jinliang J Wu Dengzhong D

American journal of translational research 20201015 10

It was reported that the expression of RNA binding proteins (RBPs) in malignant tumors is dysregulated and is closely related to tumorigenesis. However, some studies have confirmed the role of RBPs in gastric cancer (GC). We obtained data on gastric cancer in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and identified RBPs that are dysregulated between gastric normal and cancer tissues. Then, we systematically investigated the expression characteristics and clinical prog ...[more]

PMID: 33194072

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Project description:BackgroundProstate cancer (PCa) is one of the most prevalent cancers that occur in men worldwide. Autophagy-related genes (ARGs) may play an essential role in multiple biological processes of prostate cancer. However, ARGs expression signature has rarely been used to investigate the association between autophagy and prognosis in PCa. This study aimed to identify and assess prognostic ARGs signature to predict overall survival (OS) and disease-free survival (DFS) in PCa patients.MethodsFirst, a total of 234 autophagy-related genes were obtained from The Human Autophagy Database. Then, differentially expressed ARGs were identified in prostate cancer patients based on The Cancer Genome Atlas (TCGA) database. The univariate and multivariate Cox regression analysis was performed to screen hub prognostic ARGs for overall survival and disease-free survival, and the prognostic model was constructed. Finally, the correlation between the prognostic model and clinicopathological parameters was further analyzed, including age, T status, N status, and Gleason score.ResultsThe OS-related prognostic model was constructed based on the five ARGs (FAM215A, FDD, MYC, RHEB, and ATG16L1) and significantly stratified prostate cancer patients into high- and low-risk groups in terms of OS (HR = 6.391, 95% CI = 1.581- 25.840, P < 0.001). The area under the receiver operating characteristic curve (AUC) of the prediction model was 0.84. The OS-related prediction model values were higher in T3-4 than in T1-2 (P = 0.008), and higher in Gleason score > 7 than ≤ 7 (P = 0.015). In addition, the DFS-related prognostic model was constructed based on the 22 ARGs (ULK2, NLRC4, MAPK1, ATG4D, MAPK3, ATG2A, ATG9B, FOXO1, PTEN, HDAC6, PRKN, HSPB8, P4HB, MAP2K7, MTOR, RHEB, TSC1, BIRC5, RGS19, RAB24, PTK6, and NRG2), with AUC of 0.85 (HR = 7.407, 95% CI = 4.850-11.320, P < 0.001), which were firmly related to T status (P < 0.001), N status (P = 0.001), and Gleason score (P < 0.001).ConclusionsOur ARGs based prediction models are a reliable prognostic and predictive tool for overall survival and disease-free survival in prostate cancer patients.

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Development of RNA binding proteins expression signature for prognosis prediction in gastric cancer patients.

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Development of RNA binding proteins expression signature for prognosis prediction in gastric cancer patients.

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