Dataset Information

Novel Multiple miRNA-Based Signatures for Predicting Overall Survival and Recurrence-Free Survival of Colorectal Cancer Patients.

ABSTRACT: BACKGROUND Colorectal cancer (CRC) has become a heavy health burden around the world, accounting for about 10% of newly diagnosed cancer cases. In the present study, we aimed to establish the miRNA-based prediction signature to assess the prognosis of CRC patients. MATERIAL AND METHODS A total of 451 CRC patients' expression profiles and clinical information were download from the TCGA database. LASSO Cox regression was conducted to construct the overall survival (OS)- and recurrence-free survival (RFS)-associated prediction signatures, by which CRC patients were divided into low- and high-risk groups. Kaplan-Meier (K-M) curve and receiver operating characteristic (ROC) curves were used to explore the discriminatory ability and stability of the signatures. Functional enrichment analyses were performed to identify the probable mechanisms. RESULTS miRNA-216a, miRNA-887, miRNA-376b, and miRNA-891a were used to build the prediction formula associated with OS, while miR-1343, miR-149, miR-181a-1, miR-217, miR-3130-1, miR-378a, miR-542, miR-6716, miR-7-3, miR-7702, miR-677, and miR-891a were obtained to construct the formula related to RFS. K-M curve and ROC curve revealed the good discrimination and efficiency of OS in the training (P<0.001, AUC=0.712) and validation cohorts (P=0.019, AUC=0.657), as well as the results of RFS in the training (P<0.001, AUC=0.714) and validation cohorts (P=0.042, AUC=0.651). The function annotations for the targeted genes of these miRNAs show the potential mechanisms of CRC. CONCLUSIONS We established 2 novel miRNA-based prediction signatures of OS and RFS, which are reliable tools to assess the prognosis of CRC patients.

SUBMITTER: Qian J

PROVIDER: S-EPMC6778412 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Novel Multiple miRNA-Based Signatures for Predicting Overall Survival and Recurrence-Free Survival of Colorectal Cancer Patients.

Qian Jinrong J Zeng Lifeng L Jiang Xiaohua X Zhang Zhiyong Z Luo Xiaojiang X

Medical science monitor : international medical journal of experimental and clinical research 20190927

BACKGROUND Colorectal cancer (CRC) has become a heavy health burden around the world, accounting for about 10% of newly diagnosed cancer cases. In the present study, we aimed to establish the miRNA-based prediction signature to assess the prognosis of CRC patients. MATERIAL AND METHODS A total of 451 CRC patients' expression profiles and clinical information were download from the TCGA database. LASSO Cox regression was conducted to construct the overall survival (OS)- and recurrence-free surviv ...[more]

PMID: 31560680

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Project description:BackgroundFew studies have focused on the prognosis of patients with hepatocellular carcinoma (HCC) of Barcelona Clinic Liver Cancer (BCLC) stage 0‒C in terms of early recurrence and 5-years overall survival (OS). We sought to develop nomograms for predicting 5-year OS and early recurrence after curative resection of HCC, based on a clinicopathological‒radiological model. We also investigated whether different treatment methods influenced the OS of patients with early recurrence.MethodsRetrospective data, including clinical pathology, radiology, and follow-up data, were collected for 494 patients with HCC who underwent hepatectomy. Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. OS curves of different treatments for patients who had recurrence within 2 years after curative surgery were depicted and compared using the Kaplan-Meier method and the log-rank test.ResultsMultivariate Cox regression revealed that BCLC stage, non-smooth margin, maximum tumor diameter, age, aspartate aminotransferase levels, microvascular invasion, and differentiation were prognostic factors for OS and were incorporated into the nomogram with good predictive performance in the training (C-index: 0.787) and testing cohorts (C-index: 0.711). A nomogram for recurrence-free survival was also developed based on four prognostic factors (BCLC stage, non-smooth margin, maximum tumor diameter, and microvascular invasion) with good predictive performance in the training (C-index: 0.717) and testing cohorts (C-index: 0.701). In comparison to the BCLC staging system, the C-index (training cohort: 0.787 vs. 0.678, 0.717 vs. 0.675; external cohort 2: 0.748 vs. 0.624, 0.729 vs. 0.587 respectively, for OS and RFS; external cohort1:0.716 vs. 0.627 for RFS, all p value<0.05), and model calibration curves all showed improved performance. Patients who underwent surgery after tumor recurrence had a higher reOS than those who underwent comprehensive treatments and supportive care.ConclusionsThe nomogram, based on clinical, pathological, and radiological factors, demonstrated good accuracy in estimating OS and recurrence, which can guide follow-up and treatment of individual patients. Reoperation may be the best option for patients with recurrence in good condition.

Dataset Information

Novel Multiple miRNA-Based Signatures for Predicting Overall Survival and Recurrence-Free Survival of Colorectal Cancer Patients.

Publications

Novel Multiple miRNA-Based Signatures for Predicting Overall Survival and Recurrence-Free Survival of Colorectal Cancer Patients.

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