Molecular and cellular heterogeneity of gastric cancer explained by methylation-driven key regulators

Abstract

Gastric cancer (GC) is a heterogeneous disease of diverse genetic, genomic, and epigenetic alterations. Tumor microenvironment (TME) also contributes to the heterogeneity of GC. To investigate GC heterogeneity, we developed an Integrative Sequential Causality Test (ISCT) to identify key regulators of GC by integrating DNA methylation, copy number variation, and transcriptomic data. Applying ISCT to three GC cohorts containing methylation, CNV and transcriptomic data, 11 common methylation-driven key regulators (ADHFE1, CDO1, CRYAB, FSTL1, GPT, PKP3, PTPRCAP, RAB25, RHOH, SFN, and SORD) were identified. Based on these 11 genes, gastric tumors were clustered into 3 clusters which were associated with known molecular subtypes, Lauren classification, tumor stage, and patient survival, suggesting significance of the methylation-driven key regulators in molecular and histological heterogeneity of GC. We further showed that chemotherapy benefit was different in the 3 GC clusters and varied depending on the tumor stage. Both immune/stromal proportions in TME and tumor cell genomic variations contributed to expression variations of the 11 methylation-driven key regulators and to the GC heterogeneity.

Deep learning based on hematoxylin–eosin staining outperforms immunohistochemistry in predicting molecular subtypes of gastric adenocarcinoma

“…Thus, comparing our error rate of the cNN ensemble (~33%) with that of the full clustering (22-26%), we can see that we are already close to the optimum. Moreover, it is also unclear which molecular classification system is most appropriate for GC as other systems existfor example, the ACRG (Asian Cancer Research Group) system based on mRNA expression [41], systems based on methylation data [42][43][44], or systems that attempt to combine ARCG and TCGA [8,9]. This suggests that there is still be a long way to go to perfectly classify GC into molecular subtypes [45].…”