Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer

Abstract

Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencing, an autophagy-related risk model was identified. The model was capable of distinguishing the worse prognosis of patients with gastric cancer (GC), which was validated in TCGA and two independent Gene Expression Omnibus cohorts utilizing the survival analysis, and was also independent of other clinical covariates evaluated by multivariable Cox regression. The clinical value of this model was further assessed using a receiver operating characteristic (ROC) and nomogram analysis. Investigation of single-cell RNA sequencing uncovered that this model might act as an indicator of the dysfunctional characteristics of T cells in the high-risk group. Moreover, the high-risk group exhibited the lower expression of immune checkpoint markers (PDCD1 and CTLA4) than the low-risk group, which indicated the potential predictive power to the current immunotherapy response in patients with GC. In conclusion, this autophagy-associated risk model may be a useful tool for prognostic evaluation and will facilitate the potential application of this model as an indicator of the predictive immune checkpoint biomarkers.

Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing

“…ScRNAseq technology focused on gastric cancer and immunemediated mechanisms of carcinogenesis have begun to advance the field greatly in a short period. We have learned that T cells may be important for initiating tissue damage, but after cancer arises, exhaustion limits their protective role (21,24,38,48,54). New findings that NKT cells as a possible long-lasting cell type that promotes antitumor immunity will undoubtedly drive future studies (22,25).…”

“…It was also found that in diffuse gastric tumors there was a higher infiltration of immune cells, with enrichment for an exhaustive profile, than in the prognostically more favorable intestinal adenocarcinoma (24). Tong et al ( 2022) discovered that tumors with a high autophagy signature score had dysfunctional T cell responses compared to low autophagy signature tumors which have a better prognosis; however, in contradiction to previous work, high autophagy score was also associated with low tumor expression of exhaustive transcripts (i.e., CTLA4, PDL1) (38). These combined findings suggest that gastric cancers with better survival outcomes overall have a proinflammatory antitumor phenotype and may be strong candidates for immunotherapy if possessing a low-moderate autophagy signature.…”

“…Autophagy, a self-degradative process, has been associated with tumor progression (60). Tong et al (2021) observed an enhanced autophagy signature in scRNAseq data that increased with gastric disease progression, which could be used to predict patients at high risk of succumbing to the disease (38). On the other hand, a low-risk autophagy score of gastric cancer correlated with an increase in the levels of activated Ths and CTLs, expression of PD-1/CTLA-4 transcripts, and a decrease in the prevalence of Tregs.…”

“…helped researchers to make use of scRNAseq analyses to expand bulk RNAseq findings, utilizing scRNAseq transcriptomic profiles to infer cell-type composition that is lost in the bulk datasets (38,44,103). Wang (35).…”

“…Most groups obtained primary gastric cancer tissues from patients to generate scRNAseq data (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35). Some utilized previously published primary tumor datasets for further analysis (36)(37)(38)(39)(40)(41)(42)(43). Others transcriptionally profiled "liquid biopsies" of metastatic ascites fluid taken from gastric cancer patients (44,45).…”