Explore the prognostic characteristics of immunogenic cell death-related genes in colon carcinoma based on multi-constraint canonical correlation analysis combined with multi-omics

Author:

Xiong Xinyi1,Cao Qian1,Tang Jiangnan1,He Lan2,Shi Hongjian1,Zhou Fangliang1,He Yingchun1

Affiliation:

1. Hunan University of Chinese Medicine

2. The First Hospital of Hunan University of Chinese Medicine

Abstract

Abstract Colon carcinoma is a highly malignant tumor, its early symptoms are not obvious, and its prognosis is poor. Therefore, it is urgent to develop more prognostic markers of colon cancer. Many long non-coding RNAs (lncRNAs) have been proven to play an active role in tumor diagnosis, prognosis, and immunotherapy. On the other hand, the crucial role of immunogenic cell death (ICD) is in tumor inhibition. This paper aims to integrate ICD-related genes with lncRNAs and explore the mechanism of action of ICD-related lncRNAs in colon cancer. Therefore, this paper proposes a multi-constraint canonical correlation analysis to explore ICD-related lncRNAs. Furthermore, this paper uses univariate and Lasso-Cox regression to construct and verify the prognosis model of the top important lncRNAs. In this paper, according to the model's risk score, colon cancer samples are divided into a high-risk group and a low-risk group, and the effect of the model is verified based on the TCGA queue and GEO queue, respectively. In addition, we analyzed the similarities and differences in functional enrichment, immune infiltration, and drug sensitivity between the two risk groups in detail. There was a significant difference in the infiltrating abundance of T cells CD8 between high- and low-risk groups. Therefore, this article re-clusters T cell clusters based on single-cell sequencing (scRNA-seq) data of colon cancer. The unique pathways involved in the genes of the CD8 subpopulation of T cells and their communication with other T cell subpopulations were explored. In summary, the ICD-related lncRNAs risk model determined in this paper can provide a reference for predicting colon cancer patients' prognosis and drug sensitivity.

Publisher

Research Square Platform LLC

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