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

机译:基质相关的lncRNA专家组可预测早期结肠癌患者的复发和辅助化疗获益

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摘要

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 troma‐related ncRNA ignature (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.
机译:具有相似临床特征的结肠癌患者的预后和化疗反应的异质性强调了新的生物标志物的必要性,这些标志物有助于改善生存预测并更合理,更精确地调整治疗方法。在本研究中,我们基于52个lncRNA建立了与染色体相关的ncRNA点火(SLS),以全面预测临床结果。 SLS模型不仅可以通过单因素分析来区分具有不同复发和死亡风险的患者,而且还可以作为无复发和总体生存的独立因素。与常规使用的TNM分级系统相比,SLS模型显然具有更高的预测准确性。此外,SLS模型还可以有效筛查对化疗有反应的患者,因为只有低SLS组的患者可以受益于辅助化疗。随后的细胞浸润和竞争性内源性RNA(ceRNA)网络功能分析进一步证实了SLS模型与基质激活相关的生物学过程之间的关联。此外,这项研究还确定了三种在表型上不同的结肠癌亚型,这些亚型在临床结局和化疗益处方面均存在差异。总之,我们的SLS模型可能是结肠癌生存和化疗决策的重要决定因素,并且可能具有很强的临床转化价值。

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