Deciphering colorectal cancer radioresistance and immune microrenvironment: unraveling the role of EIF5A through single-cell RNA sequencing and machine learning.

Autor:	Zhong Y; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University Fujian Cancer Hospital, (Fujian Branch of Fudan University Shanghai Cancer Center), Fujian Cancer Hospital, Fuzhou, China., Chen X; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University Fujian Cancer Hospital, (Fujian Branch of Fudan University Shanghai Cancer Center), Fujian Cancer Hospital, Fuzhou, China., Wu S; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University Fujian Cancer Hospital, (Fujian Branch of Fudan University Shanghai Cancer Center), Fujian Cancer Hospital, Fuzhou, China., Fang H; Department of Hepatopancreatobiliary Surgery, Clinical Oncology School of Fujian Medical University, (Fujian Branch of Fudan University Shanghai Cancer Center), Fuzhou, China., Hong L; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University Fujian Cancer Hospital, (Fujian Branch of Fudan University Shanghai Cancer Center), Fujian Cancer Hospital, Fuzhou, China., Shao L; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University Fujian Cancer Hospital, (Fujian Branch of Fudan University Shanghai Cancer Center), Fujian Cancer Hospital, Fuzhou, China., Wang L; Department of Radiation Oncology, Jiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China., Wu J; Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University Fujian Cancer Hospital, (Fujian Branch of Fudan University Shanghai Cancer Center), Fujian Cancer Hospital, Fuzhou, China.
Jazyk:	angličtina
Zdroj:	Frontiers in immunology [Front Immunol] 2024 Sep 03; Vol. 15, pp. 1466226. Date of Electronic Publication: 2024 Sep 03 (Print Publication: 2024).
DOI:	10.3389/fimmu.2024.1466226
Abstrakt:	Background: Radiotherapy (RT) is a critical component of treatment for locally advanced rectal cancer (LARC), though patient response varies significantly. The variability in treatment outcomes is partly due to the resistance conferred by cancer stem cells (CSCs) and tumor immune microenvironment (TiME). This study investigates the role of EIF5A in radiotherapy response and its impact on the CSCs and TiME. Methods: Predictive models for preoperative radiotherapy (preRT) response were developed using machine learning, identifying EIF5A as a key gene associated with radioresistance. EIF5A expression was analyzed via bulk RNA-seq and single-cell RNA-seq (scRNA-seq). Functional assays and in vivo experiments validated EIF5A's role in radioresistance and TiME modulation. Results: EIF5A was significantly upregulated in radioresistant colorectal cancer (CRC) tissues. EIF5A knockdown in CRC cell lines reduced cell viability, migration, and invasion after radiation, and increased radiation-induced apoptosis. Mechanistically, EIF5A promoted cancer stem cell (CSC) characteristics through the Hedgehog signaling pathway. Analysis of the TiME revealed that the radiation-resistant group had an immune-desert phenotype, characterized by low immune cell infiltration. In vivo experiments showed that EIF5A knockdown led to increased infiltration of CD8+ T cells and M1 macrophages, and decreased M2 macrophages and Tregs following radiation therapy, thereby enhancing the radiotherapy response. Conclusion: EIF5A contributes to CRC radioresistance by promoting CSC traits via the Hedgehog pathway and modulating the TiME to an immune-suppressive state. Targeting EIF5A could enhance radiation sensitivity and improve immune responses, offering a potential therapeutic strategy to optimize radiotherapy outcomes in CRC patients. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Zhong, Chen, Wu, Fang, Hong, Shao, Wang and Wu.)
Databáze:	MEDLINE
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