Homologous Recombination Pathway Alternation Predicts Prognosis of Colorectal Cancer With Chemotherapy

同源重组途径改变可预测化疗后结直肠癌的预后

阅读:1

Abstract

Background: Chemotherapy is the basic treatment for colorectal cancer (CRC). However, colorectal cancer cells often develop resistance to chemotherapy drugs, leading to recurrence and poor prognosis. More and more studies have shown that the Homologous recombination (HR) pathway plays an important role in chemotherapy treatment for tumors. However, the relationship between HR pathway, chemotherapy sensitivity, and the prognosis of CRC patients is still unclear. Methods: We collected 35 samples of CRC patients after chemotherapy treatment from Guangxi Medical University Cancer Hospital, then collected mutation data and clinical prognosis data from the group. We also downloaded Mondaca-CRC, TCGA-CRC cohorts for chemotherapy treatment. Result: We found that HR mutant-type (HR-MUT) patients are less likely to experience tumor metastasis after receiving chemotherapy. Additionally, our univariate and multivariate cox regression models showed that HR-MUT can be used as an independent predictor of the prognosis of chemotherapy for CRC patients. The KM curve showed that patients with HR-MUT CRC had significantly prolonged overall survival (OS) time (log-rank p = 0.017; hazard ratio (HR) = 0.69). Compared to HR mutant-type (HR-WT), HR-MUT has a significantly lower IC50 value with several chemotherapeutic drugs. Pathway enrichment analysis further revealed that the HR-MUT displayed a significantly lower rate of DNA damage repair ability, tumor growth, metastasis activity, and tumor fatty acid metabolism activity than HR-WT, though its immune response activity was notably higher. Conclusion: These findings indicate that HR-MUT may be a relevant marker for CRC patients receiving chemotherapy, as it is closely related to improving OS time and reducing chemotherapy resistance.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。