1. Novel biomarkers to predict treatment response and prognosis in locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy
- Author
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Bingjie Guan, Meifang Xu, Rong Zheng, Guoxian Guan, and Benhua Xu
- Subjects
Locally advanced rectal cancer ,Neoadjuvant chemoradiotherapy ,Treatment response ,Prognosis ,Immune infiltration ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Purpose To identify genes associated with treatment response and prognosis for locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (NCRT). Methods In our cohort, gene expression profiles of 64 tumor biopsy samples before NCRT were examined and generated. Weighted gene co-expression network analysis was performed to identify gene modules. External validation datasets included GSE3493, GSE119409, and GSE133057. The expression of candidate genes was evaluated using immunohistochemistry (IHC). TIMER was used to assess immune infiltration. Results We identified and validated the capability to predict the treatment response of CCT5 and ELF1 using our data and external validation datasets. The trends of survival differences of candidate genes in the GSE133057 dataset were similar to our cohort. High levels of CCT5 and ELF1 expression were associated with NCRT resistance and poor prognosis. Furthermore, the expression of CCT5 and ELF1 were also assessed in 117 LARC patients’ samples by the IHC method. Based on IHC results and Cox analysis, the risk score model with CCT5 and ELF1 was constructed and performed well. The risk score was an independent prognostic factor for progression-free survival and overall survival in LARC patients and was then used to build nomogram models. The underlying mechanisms of CCT5 and ELF1 were explored using gene set enrichment analysis. The underlying pathway including apoptosis, cell cycle, and other processes. CCT5 and ELF1 expressions were significantly correlated with immune cell infiltration. Conclusion CCT5 and ELF1 were determined as biomarkers for treatment response and prognosis in LARC patients. The risk score model and nomograms helped predict treatment response and survival outcomes for LARC patients undergoing NCRT.
- Published
- 2023
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