Development and Validation of a Prognostic Nomogram for Gastric Cancer Based on DNA Methylation-Driven Differentially Expressed Genes

Abstract

Background/Aims: The incidence of gastric cancer (GC) ranks fifth among common tumors and GC is the third leading cause of cancer-related death worldwide. The aim of this study was to develop and validate a nomogram for predicting the overall survival (OS) of patients with GC. Methods: DNA methylation (DNAm)-driven genes were identified by integrating DNAm and gene expression profiling analyses from The Cancer Genome Atlas (TCGA) GC cohort. Then, a risk score model was built based on Kaplan-Meier (K-M), least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses. After analyzing the clinical parameters, a nomogram was constructed and assessed. Another cohort (GSE62254) was used for external validation. Results: Thirteen differentially expressed DNAm-driven genes were narrowed down to a six-gene signature (PODN, NPY, MICU3, TUBB6 and RHOJ were hypermethylated, and MYO1A was hypomethylated), which was associated with OS (P < 0.05) after survival and LASSO regression analyses. These differentially expressed genes (DEGs) with altered DNAm statuses were included in the prognostic risk score model. The univariate Cox regression analysis indicated that risk score, age, and number of positive lymph nodes were significantly associated with survival time in GC patients. The multivariate Cox regression analysis also indicated that these variables were significant prognostic factors for GC. A nomogram including these variables was constructed, and its performance in predicting the 1-, 3-and 5-year survival outcomes of GC patients was estimated through time-dependent receiver operating characteristic (ROC) curves. In addition, the clinical benefit of this model was revealed by decision curve analysis (DCA). Pathway enrichment analysis suggested that these DNAm-driven genes might impact tumor progression by affecting signaling pathways such as the "ECM RECEPTOR INTERACTION" and "DNA REPLICATION" pathways. Conclusions: The altered status of the DNAm-driven gene signature (PODN, MYO1A, NPY, MICU3, TUBB6 and RHOJ) was significantly associated with the OS of GC patients. A nomogram incorporating risk score, age and number of positive lymph nodes can be conveniently used to facilitate the individualized prediction of OS in patients with GC.

A Novel Unfolded Protein Response (UPR) Related 6 Genes Signature for Prognosis of Human Gastric Cancer

“…[49] In our study, we presented the batch effect of GSE84437 and the normalized data after overcoming this disadvantage, making our prognostic signature more robust and reliable. Although the 1-,3-,5-year AUC of our 6-URGs prognostic signature are lower than that of former studies [42][43][44][45][46][47][48] (most AUC > 0.7), this doesn't imply a lower prediction performance of it as a big sample size (406 and 431 in our case) can strongly affect the AUC of a model and AUC can even close to 0.5 when sample size is larger than 500. [50] It is necessary to search the underlying mechanisms of the 6 UPR genes identi ed in our study.…”

“…There are several studies having established multi-molecule biomarkers for GC prognosis including mRNAs, non-coding RNAs, DNA methylation, and so on. [42][43][44][45][46][47][48] All these models demonstrated good prediction effect for OS or RFS (Recurrence free survival) of GC. But seldom of them provided a detailed description of normalization process with GEO array express data.…”

Bioinformatics Analysis Discovers Microtubular Tubulin Beta 6 Class V (TUBB6) as a Potential Therapeutic Target in Glioblastoma

“…ROC curves of 1-, 3-, and 5-years survival rates of glioma patients show the accuracy of TUBB6 in the prognostic prediction of glioma patients. TUBB6 is used as a prognostic biomarker in many cancers, such as gastric cancer (Bai et al, 2020), ovarian cancer (Li et al, 2017), prostate cancer (Lin et al, 2019) and triple-negative breast cancer (Chung et al, 2017). However, the key role of TUBB6 in GBM has not been investigated yet.…”

Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients

“…Elaborate search results of prognostic signatures in GC were shown in Table 1 and Figure 2 (Chen et al, 2005 ; Motoori et al, 2005 ; Xu et al, 2009 ; Takeno et al, 2010 ; Cho et al, 2011 ; Bauer et al, 2012 ; Kim et al, 2012 ; Wang et al, 2013 , 2017b , 2018 ; Lee et al, 2014 ; Pasini et al, 2014 ; Li et al, 2016 ; Zhao et al, 2016 , 2019 ; Hou et al, 2017 ; Kuang et al, 2017 ; Lafrenie et al, 2017 ; Liu et al, 2018 , 2019 ; Peng et al, 2018 , 2020 ; Smyth et al, 2018 ; Wu et al, 2018 ; Yuzhalin et al, 2018 ; Chang and Lai, 2019 ; Chang et al, 2019 ; Dai et al, 2019 ; Jiang et al, 2019 , 2020 ; Song et al, 2019 ; Bai et al, 2020 ; Guan et al, 2020 ). Briefly, we got 39 literatures in NCBI PubMed Database following the above procedure ( Figure 1 ).…”