A CLRN3-Based CD8+ T-Related Gene Signature Predicts Prognosis and Immunotherapy Response in Colorectal Cancer

被引:3
作者
Gong, Zhiwen [1 ]
Huang, Xiuting [2 ,3 ]
Cao, Qingdong [1 ]
Wu, Yuanquan [4 ]
Zhang, Qunying [5 ]
机构
[1] Sun Yat Sen Univ, Affiliated Hosp 5, Dept Thorac Surg, Zhuhai 519000, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 5, Guangdong Prov Engn Res Ctr Mol Imaging, Zhuhai 519000, Peoples R China
[3] Sun Yat Sen Univ, Guangdong Hong Kong Macao Univ Joint Lab Intervent, Affiliated Hosp 5, Zhuhai 519000, Peoples R China
[4] Sun Yat Sen Univ, Kashi Hosp, Dept Gastrointestinal Surg, Kashi 844000, Peoples R China
[5] Sun Yat Sen Univ, Affiliated Hosp 5, Dept Geriatr, Zhuhai 519000, Peoples R China
关键词
CD8(+) T cells; colorectal cancer; machine learning; prognosis; immunoinfiltration; immune escape;
D O I
10.3390/biom14080891
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background: Colorectal cancer (CRC) ranks among the most prevalent malignancies affecting the gastrointestinal tract. The infiltration of CD8(+) T cells significantly influences the prognosis and progression of tumor patients. Methods: This study establishes a CRC immune risk model based on CD8(+) T cell-related genes. CD8(+) T cell-related genes were identified through Weighted Gene Co-expression Network Analysis (WGCNA), and the enriched gene sets were annotated via Gene Ontology (GO) and Reactome pathway analysis. Employing machine learning methods, including the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Random Forest (RF), we identified nine genes associated with CD8(+) T-cell infiltration. The infiltration levels of immune cells in CRC tissues were assessed using the ssGSEA algorithm. Results: These genes provide a foundation for constructing a prognostic model. The TCGA-CRC sample model's prediction scores were categorized, and the prediction models were validated through Cox regression analysis and Kaplan-Meier curve analysis. Notably, although CRC tissues with higher risk scores exhibited elevated levels of CD8(+) T-cell infiltration, they also demonstrated heightened expression of immune checkpoint genes. Furthermore, comparison of microsatellite instability (MSI) and gene mutations across the immune subgroups revealed notable gene variations, particularly with APC, TP53, and TNNT1 showing higher mutation frequencies. Finally, the predictive model's efficacy was corroborated through the use of Tumor Immune Dysfunction and Exclusion (TIDE), Immune Profiling Score (IPS), and immune escape-related molecular markers. The predictive model was validated through an external cohort of CRC and the Bladder Cancer Immunotherapy Cohort. CLRN3 expression levels in tumor and adjacent normal tissues were assessed using quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Subsequent in vitro and in vivo experiments demonstrated that CLRN3 knockdown significantly attenuated the malignant biological behavior of CRC cells, while overexpression had the opposite effect. Conclusions: This study presents a novel prognostic model for CRC, providing a framework for enhancing the survival rates of CRC patients by targeting CD8(+) T-cell infiltration.
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页数:18
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[1]   The National Burden of Colorectal Cancer in the United States from 1990 to 2019 [J].
Alsakarneh, Saqr ;
Jaber, Fouad ;
Beran, Azizullah ;
Aldiabat, Mohammad ;
Abboud, Yazan ;
Hassan, Noor ;
Abdallah, Mohamed ;
Abdelfattah, Thaer ;
Numan, Laith ;
Clarkston, Wendell ;
Bilal, Mohammad ;
Shaukat, Aasma .
CANCERS, 2024, 16 (01)
[2]   Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models [J].
Belhechmi, Shaima ;
De Bin, Riccardo ;
Rotolo, Federico ;
Michiels, Stefan .
BMC BIOINFORMATICS, 2020, 21 (01)
[3]   Epigenetic profiles associated with major depression in the human brain [J].
Bustamante, Angela C. ;
Armstrong, Don L. ;
Uddin, Monica .
PSYCHIATRY RESEARCH, 2018, 260 :439-442
[4]   International Socioeconomic Predictors of Colon and Rectal Cancer Mortality: Is Colorectal Cancer a First World Problem? [J].
Cui, Christina L. ;
Dornisch, Anna M. ;
Umlauf, Anya E. ;
Cuomo, Raphael E. ;
Murphy, James D. ;
Lopez, Nicole E. .
JCO GLOBAL ONCOLOGY, 2021, 7 :1659-1667
[5]   Consensus molecular subtypes and the evolution of precision medicine in colorectal cancer [J].
Dienstmann, Rodrigo ;
Vermeulen, Louis ;
Guinney, Justin ;
Kopetz, Scott ;
Tejpar, Sabine ;
Tabernero, Josep .
NATURE REVIEWS CANCER, 2017, 17 (02) :79-92
[6]   Emerging Complexity in CD4+T Lineage Programming and Its Implications in Colorectal Cancer [J].
DiToro, Daniel ;
Basu, Rajatava .
FRONTIERS IN IMMUNOLOGY, 2021, 12
[7]   Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data [J].
Finotello, Francesca ;
Mayer, Clemens ;
Plattner, Christina ;
Laschober, Gerhard ;
Rieder, Dietmar ;
Hackl, Hubert ;
Krogsdam, Anne ;
Loncova, Zuzana ;
Posch, Wilfried ;
Wilflingseder, Doris ;
Sopper, Sieghart ;
Ijsselsteijn, Marieke ;
Brouwer, Thomas P. ;
Johnson, Douglas ;
Xu, Yaomin ;
Wang, Yu ;
Sanders, Melinda E. ;
Estrada, Monica V. ;
Ericsson-Gonzalez, Paula ;
Charoentong, Pornpimol ;
Balko, Justin ;
de Miranda, Noel Filipe da Cunha Carvahlo ;
Trajanoski, Zlatko .
GENOME MEDICINE, 2019, 11 (1)
[8]   Identification of the Shared Gene Signatures and Biological Mechanism in Type 2 Diabetes and Pancreatic Cancer [J].
Hu, Yifang ;
Zeng, Ni ;
Ge, Yaoqi ;
Wang, Dan ;
Qin, Xiaoxuan ;
Zhang, Wensong ;
Jiang, Feng ;
Liu, Yun .
FRONTIERS IN ENDOCRINOLOGY, 2022, 13
[9]   Prognosis of lasso-like penalized Cox models with tumor profiling improves prediction over clinical data alone and benefits from bi-dimensional pre-screening [J].
Jardillier, Remy ;
Koca, Dzenis ;
Chatelain, Florent ;
Guyon, Laurent .
BMC CANCER, 2022, 22 (01)
[10]   Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response [J].
Jiang, Peng ;
Gu, Shengqing ;
Pan, Deng ;
Fu, Jingxin ;
Sahu, Avinash ;
Hu, Xihao ;
Li, Ziyi ;
Traugh, Nicole ;
Bu, Xia ;
Li, Bo ;
Liu, Jun ;
Freeman, Gordon J. ;
Brown, Myles A. ;
Wucherpfennig, Kai W. ;
Liu, X. Shirley .
NATURE MEDICINE, 2018, 24 (10) :1550-+