Development and validation of prognostic model based on the analysis of autophagy-related genes in colon cancer

Abstract

Background: Autophagy, a process of self-digestion, is closely related to multiple biological processes of colon cancer. This study aimed to construct and evaluate prognostic signature of autophagy-related genes (ARGs) to predict overall survival (OS) in colon cancer patients. Materials and Methods: First, a total of 234 ARGs were downloaded via The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, differentially expressed ARGs were identified in colon cancer. The univariate and multivariate Cox regression analysis was performed to screen prognostic ARGs to construct the prognostic model. The feasibility of the prognostic model was evaluated using receiver operating characteristic curves and Kaplan-Meier curves. A prognostic model integrating the gene signature with clinical parameters was established with a nomogram. Results: We developed an autophagy risk signature based on the 6 ARGs ( ULK3, ATG101, MAP1LC3C, TSC1, DAPK1, and SERPINA1 ). The risk score was positively correlated with poor outcome and could independently predict prognosis. Furthermore, the autophagy-related signature could effectively reflect the levels of immune cell type fractions and indicate an immunosuppressive microenvironment. Conclusion: We innovatively identified and validated 6 autophagy-related gene signature that can independently predict prognosis and reflect overall immune response intensity in the colon cancer microenvironment.

Immunotherapeutic Value of MAP1LC3C and Its Candidate FDA-Approved Drugs Identified by Pan-Cancer Analysis, Virtual Screening and Sensitivity Analysis

“…Consistent with previously reported results, differentially expressed MAP1LC3C has certain prognostic values in some cancers, especially COAD, LGG and LUAD. MAP1LC3C is a marker that indicates poor prognosis in patients with colon cancer, low-grade glioma and lung adenocarcinoma ( Xu et al, 2020 ; Guo et al, 2021 ; Wang et al, 2021 ).…”

Identification and validation of prognostic autophagy-related genes associated with immune microenvironment in human gastric cancer

“…Few existing studies have shown that the human Atg8-family protein- MAP1LC3C may be essential in particular biological responses, including cell autophagy, motility and invasion [ 36 , 37 ]. Some bioinformatics analyses have revealed the potential value of MAP1LC3C in cancer [ 38 , 39 ], but its role and mechanism in GC has seldom been discussed systematically up to now. The present study filled some gaps in the existing research, which identified higher expression of MAP1LC3C to be significantly associated with poorer prognoses and more advanced tumor grade 3.…”

PANoptosis-based molecular clustering and prognostic signature predicts patient survival and immune landscape in colon cancer

“…In recent years, genes and non-coding RNA related to various forms of cell death have been explored in many studies, including autophagy-, ferroptosis-, pyroptosis-, necroptosisrelated genes and lncRNAs. Wang et al (2021) (Zhao et al, 2021) also used necroptosis-related lncRNAs to predict prognosis and identify molecular classifications to distinguish between cold and hot tumors in gastric cancer. However, genes related to the crosstalk and coordination between different types of cell death have not been well studied.…”

“…In recent years, genes and non-coding RNA related to various forms of cell death have been explored in many studies, including autophagy-, ferroptosis-, pyroptosis-, necroptosis-related genes and lncRNAs. Wang et al (2021) identified six autophagy-related genes and developed a prognostic signature that can independently predict prognosis and reflect overall immune response intensity in the colon cancer microenvironment. Nie et al (2021) constructed a novel ferroptosis-related gene signature to predict the prognosis and immune status of patients with colon cancer.…”