Comprehensive Analysis of a Cancer-Immunity Cycle–Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer

Abstract

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle–based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle–related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint–associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle–based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

Construction of a Risk Model and Prediction of prognosis and immunotherapy Based on Cuproptosis-Related LncRNAs in the Urinary System Pan-Cancer

“…This demonstrates the scienti c validity and sensitivity of our model. To enable our risk model to be more valid in clinical diagnosis and treatment, we performed immunotherapy analysis as well as drug sensitivity analysis [39] . It is well known that the accumulation of genetic mutations is the main cause of tumor formation [40] .…”

Developing an m5C regulator–mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer

“…TIDE is a reliable surrogate biomarker that could accurately predict immune checkpoint blockade (ICB) response by measuring the tumor immune escape, and it even performed better than PD-L1 expression in melanoma; that is, a higher TIDE score is associated with worse ICB response and worse patient survival under anti-PD1 and anti-CTLA4 therapies (90). According to our previous studies and others, the immune landscape is crucial in assessing the efficacy of immunotherapy and chemotherapy targeting CRC patients (91)(92)(93)(94). However, the role of m 5 C RNA methylation regulators in patients with rectal cancer is still unclear.…”

Characterization of sialylation-related long noncoding RNAs to develop a novel signature for predicting prognosis, immune landscape, and chemotherapy response in colorectal cancer

“…The roles of lncRNAs, a type of RNA that meditates multiple pathways and has a promising future in early cancer diagnosis, remain unclear in sialylation and Siglec interactions. Given the previous evidence that multiple gene-related signatures based on specific biological functions were superior in predicting the prognosis and individualized therapy in patients with CRC ( 53 – 56 ), in the present study, we aimed at exploring the clinical significance of a sialylation lncRNAs-based signature.…”