Abstract
The heterogeneity in prognoses and chemotherapeutic responses of colon cancer patients with similar clinical features emphasized the necessity for new biomarkers that help to improve the survival prediction and tailor therapies more rationally and precisely. In the present study, we established a stroma‐related lncRNA signature (SLS) based on 52 lncRNAs to comprehensively predict clinical outcome. The SLS model could not only distinguish patients with different recurrence and mortality risks through univariate analysis, but also served as an independent factor for relapse‐free and overall survival. Compared with the conventionally used TNM stage system, the SLS model clearly possessed higher predictive accuracy. Moreover, the SLS model also effectively screened chemotherapy‐responsive patients, as only patients in the low‐SLS group could benefit from adjuvant chemotherapy. The following cell infiltration and competing endogenous RNA (ceRNA) network functional analyses further confirmed the association between the SLS model and stromal activation‐related biological processes. Additionally, this study also identified three phenotypically distinct colon cancer subtypes that varied in clinical outcome and chemotherapy benefits. In conclusion, our SLS model may be a significant determinant of survival and chemotherapeutic decision‐making in colon cancer and may have a strong clinical transformation value.
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