Dataset Information

Predicting the effect of 5-fluorouracil-based adjuvant chemotherapy on colorectal cancer recurrence: A model using gene expression profiles.

ABSTRACT: It is critical to identify patients with stage II and III colorectal cancer (CRC) who will benefit from adjuvant chemotherapy (ACT) after curative surgery, while the only use of clinical factors is insufficient to predict this beneficial effect. In this study, we performed genetic algorithm (GA) to select ACT candidate genes, and built a predictive model of support vector machine (SVM) using gene expression profiles from the Gene Expression Omnibus database. The model contained four ACT candidate genes (EDEM1, MVD, SEMA5B, and WWP2) and TNM stage (stage II or III). After using Subpopulation Treatment Effect Pattern Plot to determine the optimal cutoff value of predictive scores, the validated patients from The Cancer Genome Atlas database can be divided into the predictive ACT-benefit/-futile groups. Patients in the predictive ACT-benefit group with 5-fluorouracil (5-Fu)-based ACT had significantly longer relapse-free survival (RFS) compared to those without ACT (P = .015); However, the difference in RFS in the predictive ACT-futile group was insignificant (P = .596). The multivariable analysis found that the predictive groups were significantly associated with the effect of ACT (Pinteraction = .011). Consequently, we developed a predictive model based on the SVM and GA algorithm which was further validated to define patients who benefit from ACT on recurrence.

SUBMITTER: Chen Q

PROVIDER: S-EPMC7196071 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Predicting the effect of 5-fluorouracil-based adjuvant chemotherapy on colorectal cancer recurrence: A model using gene expression profiles.

Chen Quan Q Gao Peng P Song Yongxi Y Huang Xuanzhang X Xiao Qiong Q Chen Xiaowan X Lv Xinger X Wang Zhenning Z

Cancer medicine 20200309 9

It is critical to identify patients with stage II and III colorectal cancer (CRC) who will benefit from adjuvant chemotherapy (ACT) after curative surgery, while the only use of clinical factors is insufficient to predict this beneficial effect. In this study, we performed genetic algorithm (GA) to select ACT candidate genes, and built a predictive model of support vector machine (SVM) using gene expression profiles from the Gene Expression Omnibus database. The model contained four ACT candidat ...[more]

PMID: 32150672

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Project description:BackgroundCirculating tumor DNA (ctDNA) has emerged as a biomarker that can define the risk of recurrence after curative-intent surgery for patients with colorectal cancer (CRC). However, beyond the predictive power of postoperative ctDNA detection, the efficacy and potential limitations of ctDNA detection urgently need to be fully elucidated in a large cohort of CRC.ObjectivesTo define potentially cured CRC patients through ctDNA monitoring following surgery.DesignA prospective, multicenter, observational study.MethodsWe enrolled 309 patients with stages I-IV CRC who underwent definitive surgery. Tumor tissues were sequenced by a custom-designed next-generation sequencing panel to identify somatic mutations. Plasma was analyzed using a ctDNA-based molecular residual disease (MRD) assay which integrated tumor-genotype-informed and tumor-genotype-naïve ctDNA analysis. The turnaround time of the assay was 10-14 days.ResultsPostoperative ctDNA was detected in 5.4%, 13.8%, 15%, and 30% of patients with stage I, II, III, and IV disease, respectively, and in 17.5% of all longitudinal samples. Patients with positive postsurgery MRD had a higher recurrence rate than those with negative postsurgery MRD [hazard ratio (HR), 13.17; p < 0.0001], producing a sensitivity of 64.6%, a specificity of 94.8%, a positive predictive value (PPV) of 75.6%, and a negative predictive value (NPV) of 91.5%. Furthermore, patients with positive longitudinal MRD also had a significantly higher recurrence rate (HR, 14.44; p < 0.0001), with increased sensitivity (75.0%), specificity (94.9%), PPV (79.6%), and NPV (93.4%). Subgroup analyses revealed that adjuvant therapy did not confer superior survival for patients with undetectable or detectable MRD. In addition, MRD detection was less effective in identifying lung-only and peritoneal metastases.ConclusionPostoperative ctDNA status is a strong predictor of recurrence independent of stage and microsatellite instability status. Longitudinal undetectable MRD could be used to define the potentially cured population in CRC patients undergoing curative-intent surgery.

Dataset Information

Predicting the effect of 5-fluorouracil-based adjuvant chemotherapy on colorectal cancer recurrence: A model using gene expression profiles.

Publications

Predicting the effect of 5-fluorouracil-based adjuvant chemotherapy on colorectal cancer recurrence: A model using gene expression profiles.

Similar Datasets

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