A robust panel based on tumour microenvironment genes for prognostic prediction and tailoring therapies in stage I–III colon cancer

Abstract

Background: Tumour microenvironment (TME) is critical for the regulation of cancer development as well as therapy. The objective of the current study was the development of a robust prognostic model based on TMErelevant genes. Methods: Five public microarray datasets providing clinical information were obtained. The least absolute shrinkage and selection operator regression method was used to reduce the dimensionality of robust prognostic genes identified via the bootstrap method. Findings: We established a prognostic panel, designated as tumour microenvironment risk score (TMRS), consisting of 100 genes. With specific risk score formulae, the TMRS panel possesses a strong ability to predict relapse-free survival and overall survival through both univariate and multivariate analyses. Compared with the TNM stage, the TMRS panel showed much higher predictive accuracy. Further analysis revealed that patients with higher TMRS scores exhibited no therapeutic benefits from adjuvant chemotherapy, probably due to the activation of stromal relevant pathways and infiltration of stromal cells. Besides colon cancer, the TMRS panel was also revealed to be a reliable tool for prognostic prediction and chemotherapeutic decision-making in gastric cancer. Its value in predicting immunotherapy outcomes was also confirmed in two other cohorts consisting of metastatic urothelial carcinoma patients and melanoma patients. Interpretation: Our TMRS panel may be an effective tool for survival prediction and treatment guidance in patients with stage I-III colon cancer.

A stroma‐related lncRNA panel for predicting recurrence and adjuvant chemotherapy benefit in patients with early‐stage colon cancer

“…In this study, we also constructed a new colon cancer molecular subtype by SNF‐CC method that aggregates the expression data of 52 lncRNAs and 100 robust prognostic TME genes identified in our previous study . Similar to SLS signature, this derived subtype was also associated with a significant difference in survival outcome and the curative effect of ADJC and FOLFIRI regimens, indicating that such a genomic classification offers insights to the stratified management of patients and further personalized therapeutic decision‐making.…”

Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Oral Squamous Cell Carcinoma

“…To be specific, 70% patients were randomly extracted from the training cohort to evaluate the prognostic value of the initially selected AS events in 1000 iterations. Alternative splicing events with P < 0.05 for over 700 times were considered as robust prognostic AS events ( 14 ). Given that 132 patients died in our OSCC cohort, it is recommended that less than 13 AS events should be included in the constructed model based on the “EPV (events per variable) 1 to 10 rule of thumb” ( 15 , 16 ).…”

Identification of biomarkers predicting the chemotherapeutic outcomes of capecitabine and oxaliplatin in patients with gastric cancer

“…However, in order to facilitate a practical application, the number of genes in the majority of panels is >100. For example, a tumor microenvironment risk score prediction panel could predict whether patients with colon cancer benefit from adjuvant chemotherapy (16). Thus far, no study has reported a model of multiple gene combinations to predict the response of GC to the CapeOX chemotherapy regimens, to the best of our knowledge.…”