An Immune-Related Gene Signature for Predicting Neoadjuvant Chemoradiotherapy Efficacy in Rectal Carcinoma

Abstract

BackgroundLocally advanced rectal cancers (LARC) show a highly variable response to neoadjuvant chemoradiotherapy (nCRT), and the impact of the tumor immune response in this process is poorly understood. This study aimed to characterize the immune-related gene expression profiles (GEP), pathways, and cell types associated with response or resistance to neoadjuvant chemoradiotherapy.MethodsThe transcriptomic and clinical data of Rectal carcinoma from the Gene Expression Omnibus database and Immune-related genes (IRGs) from ImmPort were downloaded to identify the differentially expressed immune-related genes (DEIRGs) between responder and non-responder to neoadjuvant chemoradiotherapy. Gene set enrichment analyses were performed to uncover significantly enriched GO terms and KEGG pathways. Immune cell infiltration was estimated from RNA-sequencing data using ImmuCellAI. Afterward, we constructed an immune-related gene-based predictive model (IRGPM) by Support Vector Machine and validated it in an external cohort.ResultA 15-gene signature (HLA-DPB1, HLA-DQA1, CXCL9, CXCL10, TAP2, INHBB, BMP2, CD74, IL33, CCL11, CXCL11, DEFB1, HLA-DPA1, CCN3, STAT1) was identified as DEIRGs and found to be significantly associated with nCRT outcomes. Gene set enrichment analyses indicated that the 15 genes play active roles in inflammation-related biological processes. In addition, ImmuCellAI revealed that CD4 naive T cells, Tex, Th1 were significantly up-regulated (p=0.035, p=0.02, p=0.0086, respectively), while Tfh were significantly down-regulated (p=0.015) in responder subgroup. Finally, a novel predictive model was developed by SVM based on DEIRGs with an AUC of 80% (internal validation) and 73.5% (external validation).ConclusionOur team conducted a genomic study of the relationship between gene expression profile and response to nCRT in LARC. Our data suggested that the DEIRGs signature could help predict the efficacy of nCRT. And a DEIRGs‐based SVM model was developed to monitor the outcomes of nCRT in LARC.

An immune-related gene prognostic prediction risk model for neoadjuvant chemoradiotherapy in rectal cancer using artificial intelligence

“…Five of 20 genes were shown to be predictive in rectal cancer in previous studies. CXCL10, IL12A, CD247 and ITGB1 were identified as predictive markers for the response to neoadjuvant treatment in rectal cancer in previous studies (15,(41)(42)(43)(44)(45). Tumor IRS1 expression was related to the survival of rectal cancer patients (46).…”

“…Then, intensive or different treatment schemes, as well as different monitoring schemes, can be appropriately selected for these patients. A previous study reported that immune-related genes can be used to predict the response to neoadjuvant therapy (15). However, the relationship between immune-related genes and the long-term prognosis (DFS) of LARC patients receiving neoadjuvant treatment followed by TME and adjuvant chemotherapy is currently unclear.…”

“…It is suggested that immunity has an effect on prognosis. CXCL10 is an interferonstimulated chemokine that attracts T cells (15). IL12A and IRF4 are associated with T-cell differentiation (40).…”

“…Due to the inconsistent results of IHC, it is hoped that further findings could be derived from gene analysis. Qian et al explored the relationship between the gene expression profile and response to nCRT in LARC, and they developed an immune gene predictive model that could predict the response to nCRT by support vector machine (SVM) (15). Therefore, the value of immune-related gene signatures closely related to the TIME in predicting prognosis is worth studying.…”

Construction and validation of prognostic risk model based on radiosensitivity-related immune genes in rectal cancer

“…An increasing number of studies have shown that immune genes can affect radiosensitivity and prognosis by regulating antitumor immune surveillance, antigen presentation and so on. Li et al studied the relationship between gene expression pro les and nCRT response in LARC, and developed a 15-immune gene prediction model to predict the response to nCRT [5]. Carine et al calculated the biopsy-adapted immunoscore (IS B ) based on the in ltration of CD3 + and CD8 + T cells, through which they could predict response to nCRT and better de ne patients eligible to an organ preservation strategy (Watch-and-Wait) [6].…”