Transcriptome profiling reveals an integrated mRNA–lncRNA signature with predictive value of early relapse in colon cancer

Abstract

The purpose of our study was to develop a multigene signature based on transcriptome profiles of both mRNAs and lncRNAs to identify a group of patients who are at high risk of early relapse in stages II-III colon cancer. Firstly, propensity score matching was conducted between patients in early relapse group and long-term survival group from GSE39582 training series (N = 359) and patients were matched 1:1. Global transcriptome analysis was then performed between the paired groups to identify tumor specific mRNAs and lncRNAs. Finally, using LASSO Cox regression model, we built a multigene early relapse classifier incorporating 15 mRNAs and three lncRNAs. The prognostic and predictive accuracy of the signature was internally validated in 102 colon cancer patients and externally validated in other 241 patients. In the training set, patients with high risk score were more likely to suffer from relapse than those with low risk score (HR: 2.67, 95% CI: 2.07-3.46, P < 0.001). The results were validated in the internal validation set (HR: 2.23, 95% CI: 1.23-3.78, P = 0.003) and external validation (HR 1.88, 95% CI 1.42-2.48; P < 0.001) set. Time-dependent receiver operating curve at 1 year showed that the integrated mRNA-lncRNA signature [area under curve (AUC) = 0.742] had better prognostic accuracy than AJCC TNM stage (AUC = 0.615) in the entire 702 patients. In addition, survival decision curve analyses at 12 months revealed a good clinical usefulness of the integrated mRNA-lncRNA signature. In conclusion, we successfully developed an integrated mRNA-lncRNA signature that can accurately predict early relapse.

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

“…For example, the 4‐lncRNA signature proposed by Wang et al, the 2‐lncRNA signature built by Xue et al and the 15‐lncRNA signature developed by Wang et al were all reported to be an ideal tool to identify colon cancer patients with a high mortality risk. Most recently, Cai's group developed an integrated mRNA‐lncRNA signature with predictive values specially for early colon cancer relapse (recurrence between 3 months and 1 year after initial primary resection) and found that the prognostic ability of the model was stronger than that of the TNM stage system . However, the current available signatures only provide prognosis‐related information; none of these studies discussed the role of these signatures in treatment guidance.…”

“…Among them, lncRNAs, which possess tissue-specific and cancer-specific expression patterns and play essential roles in tumorigenesis and cancer progression, 11 and 1 year after initial primary resection) and found that the prognostic ability of the model was stronger than that of the TNM stage system. 12 However, the current available signatures only provide prognosis-related information; none of these studies discussed the role of these signatures in treatment guidance. The clinical practicality of these signatures was therefore limited.…”

“…LncRNA is a transcript longer than 200 nucleotides that cannot be translated into proteins and is among the most prevalent transcriptional changes in tumour . In colon cancer, several prognostic predictive models have been developed based on lncRNAs . However, as none of them has been reported to provide potential treatment guidance, these models may not meet clinical needs.…”

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma

“…Published studies have revealed that lncRNAs have key roles in vital biological functions of cancers. However, only few studies have described the role of lncRNA profiles in tumor recurrence of CA [19][20][21][22]. In this study, we focused on the identification of novel prognostic markers for the tumor recurrence of CA based on the RNA sequencing data from the TCGA database.…”

“…Few studies have focused on the ceRNA network related to tumor recurrence in CA [19][20][21][22]. Thus, in this study, we aim to establish the lncRNA-miRNA-mRNA ceRNA network for the tumor recurrence of CA to identify novel prognostic lncRNA biomarkers for the prediction of tumor recurrence in CA and to achieve better understanding of the role of lncRNAs in CA based on the RNA sequencing data obtained from The Cancer Genome Atlas (TCGA) database.…”