Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms

Hao Chi; Jinbang Huang; Yang Yan; Chenglu Jiang; Shengke Zhang; Haiqing Chen; Lai Jiang; Jieying Zhang; Qinghong Zhang; Guanhu Yang; Gang Tian

doi:10.3389/fmolb.2023.1254232

Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms

Front Mol Biosci. 2023 Oct 17:10:1254232. doi: 10.3389/fmolb.2023.1254232. eCollection 2023.

Authors

Hao Chi^#¹, Jinbang Huang^#¹, Yang Yan^#², Chenglu Jiang¹, Shengke Zhang¹, Haiqing Chen¹, Lai Jiang¹, Jieying Zhang³, Qinghong Zhang⁴, Guanhu Yang⁵, Gang Tian⁶

Affiliations

¹ Clinical Medical College, Southwest Medical University, Luzhou, China.
² The Third Affiliated Hospital of Guizhou Medical University, Duyun, China.
³ First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
⁴ Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China.
⁵ Department of Specialty Medicine, Ohio University, Athens, OH, United States.
⁶ Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

^# Contributed equally.

Abstract

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

Keywords: Chemotherapy sensitivity; Colon cancer; Disulfidptosis; Immunotherapy response; LnRNAs; Prognostic markers; Tumor microenvironment.

Grants and funding

This study was supported by grants from the Luzhou Science and Technology Department Applied Basic Research program (No: 2022-JYJ-145), the Sichuan Province Science and Technology Department of foreign (border) high-end talent introduction project (No: 2023JDGD0037), and Sichuan Provincial Medical Association (No: Q22027).