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Cuproptosis-Associated Lncrna Signature for Colon Cancer Prognosis and Immune Microenvironment Analysis

28 Pages Posted: 25 May 2023 Publication Status: Preprint

See all articles by Shanbo Ma

Shanbo Ma

Government of the People's Republic of China - Xijing Hospital

Rui Zhang

Government of the People's Republic of China - Air Force Medical University

Jin Wang

Government of the People's Republic of China - Xijing Hospital

Long Li

Government of the People's Republic of China - Xijing Hospital

Shan Miao

Government of the People's Republic of China - Xijing Hospital

Wei Quan

Shaanxi University of Chinese Medicine

Fangyao Chen

Xi'an Jiaotong University (XJTU)

Zhao Yang

Government of the People's Republic of China - Air Force Medical University

Xiaopeng Shi

Government of the People's Republic of China - Xijing Hospital

Abstract

Background: Cuproptosis is a novel method of modulating cell death that regulates tumorigenesis and progression processes. Cuproptosis-associated lncRNAs (CALs) are not clearly understood in colon cancer (CC). Furthermore, it is currently unknown how CALs affect prognosis and how they relate to the immune microenvironment of CC. Our study investigated the potential prognostic value of CALs and their association with immune microenvironments in CC patients.

Methods: The RNA of CC patients was sequenced, and medical data were retrieved from The Cancer Genome Atlas (TCGA) portal. A total of 446 participants were randomly assigned to the training and testing cohorts. The Pearson correlation analysis was used to recognize CALs. To choose significant markers in the training cohort, we used univariate regression with the LASSO method, followed by multivariate Cox regression analysis to develop the final prediction model. Therefore, we developed a predictive model based on the cuproptosis signature. The performance of the proposed model was assessed using the receiving operating characteristic (ROC) analysis. We also investigated the relationship between this signature and medication susceptibility, somatic mutations, and immunological infiltration.

Results: CC patients were divided into two risk cohorts using a 5-CAL signature; the patients in the elevated-risk cohort exhibited a poorer prognosis. The ROC analysis revealed the predictive accuracy of the developed risk model. We also detected variations in immune cell infiltration between the two cohorts, such as CD8+ T cells, regulatory T cells, and M0 and M1 macrophages. The high-risk cohort also exhibited lower IC50 values for several chemotherapy drugs.

Conclusion: We recognized a novel CAL signature that accurately predicts the prognosis of CC patients. CALs may be therapeutic targets for CC and may have a function in the antitumor immune system.

Note:
Funding Declaration: This study was supported by National Natural Science Foundation of China(No.81902185), China Postdoctoral Science Foundation (No.2020M673661), and the Key Research and Development Program of Shaanxi Province(No.2021SF-175andNo.2022SF-205).

Conflicts of Interest: None

Keywords: colon cancer, cuproptosis, lncRNAs, signature, prognosis, tumor immune microenvironment.

Suggested Citation

Ma, Shanbo and Zhang, Rui and Wang, Jin and Li, Long and Miao, Shan and Quan, Wei and Chen, Fangyao and Yang, Zhao and Shi, Xiaopeng, Cuproptosis-Associated Lncrna Signature for Colon Cancer Prognosis and Immune Microenvironment Analysis. Available at SSRN: https://ssrn.com/abstract=4447182 or http://dx.doi.org/10.2139/ssrn.4447182

Shanbo Ma (Contact Author)

Government of the People's Republic of China - Xijing Hospital ( email )

Xi'an, 710032
China

Rui Zhang

Government of the People's Republic of China - Air Force Medical University ( email )

No.169, Changlexi Road
Xi'an, 710032
China

Jin Wang

Government of the People's Republic of China - Xijing Hospital ( email )

Xi'an, 710032
China

Long Li

Government of the People's Republic of China - Xijing Hospital ( email )

Xi'an, 710032
China

Shan Miao

Government of the People's Republic of China - Xijing Hospital ( email )

Xi'an, 710032
China

Wei Quan

Shaanxi University of Chinese Medicine ( email )

Xianyang
China

Fangyao Chen

Xi'an Jiaotong University (XJTU) ( email )

Zhao Yang

Government of the People's Republic of China - Air Force Medical University ( email )

No.169, Changlexi Road
Xi'an, 710032
China

Xiaopeng Shi

Government of the People's Republic of China - Xijing Hospital ( email )

Xi'an, 710032
China

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