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Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

ABSTRACT: Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than those in high-risk group. This finding was further validated in five other independent datasets (GSE14333, GSE17536, GSE17537, GSE33113, and GSE37892). Besides, associations between clinicopathological information and risk score were analyzed. A nomogram including risk score was plotted to facilitate the utilization of risk score. The risk score model is also demonstrated to be effective on predicting both overall and recurrence-free survival of chemotherapy received patients. After performing Gene Set Enrichment Analysis (GSEA) between high and low risk groups, we found that several cell-cell interaction KEGG pathways were identified. Funnel plot results showed that there was no publication bias in these datasets. In summary, by utilizing the regulatory activity in stage II and III colorectal carcinoma, the risk score successfully predicts the survival of 1021 stage II/III CRC patients in six independent datasets.

SUBMITTER: Liu G

PROVIDER: S-EPMC5716735 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

Liu Gang G Dong Chuanpeng C Wang Xing X Hou Guojun G Zheng Yu Y Xu Huilin H Zhan Xiaohui X Liu Lei L

Oncotarget 20170928 58

Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than t ...[more]

PMID: 29228695

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Project description:Distant metastasis is the major causes of death in colorectal cancer (CRC) patients. In order to identify genes influencing the prognosis of patients with CRC, we compared gene expression in primary tumors with and without distant metastasis using an oligonucleotide microarray. We also examined the expression of the candidate gene in 100 CRC patients by quantitative real-time reverse transcription PCR and studied the relationship between its expression and the prognosis of patients with CRC. As a result, we identified MUC12 as a candidate gene involved in metastasis processes by microarray analysis. Quantitative real-time reverse transcription PCR showed that MUC12 expression was significantly lower in cancer tissues than in adjacent normal tissues (P < 0.001). In stage II and stage III CRC, patients with low expression showed worse disease-free survival (P = 0.038). Multivariate analysis disclosed that MUC12 expression status was an independent prognostic factor in stage II and stage III CRC (relative risk, 9.532; 95% confidence interval, 2.303-41.905; P = 0.002). This study revealed the prognostic value of MUC12 expression in CRC patients. Moreover, our result suggests MUC12 expression is a possible candidate gene for assessing postoperative adjuvant therapy for CRC patients. Total of 111 microarray datasets (77 for LCM samples, and 17 pairs for homogenized samples from tumor and adjacent tissues) were normalized using robust multi-array average (RMA) method under R 2.6.2 statistical software together with BioConductor package, as described previously. Then, the gene expression levels were log2-transformed, and 62 control probe sets were removed for further analysis. In order to identify a set of genes associated with development of metastatic recurrence, we performed Wilcoxon rank-sum test for gene expression differences of 54,613 probe sets between recurrence and non-recurrence groups. Similarly, Wilcoxon singed-rank test was conducted to select genes which showed significant expression difference between tumor and adjacent tissue. Then, we selected a set of genes that satisfied both of above two criteria.

Project description:BackgroundColorectal cancer is the second-leading cause of cancer-related mortality in the United States and a leading cause of cancer-related mortality worldwide. Loss of SMAD4, a critical tumor suppressor and the central node of the transforming growth factor-beta superfamily, is associated with worse outcomes for colorectal cancer patients; however, it is unknown whether an RNA-based profile associated with SMAD4 expression could be used to better identify high-risk colorectal cancer patients.AimIdentify a gene expression-based SMAD4-modulated profile and test its association with patient outcome.Methods and resultsUsing a discovery dataset of 250 colorectal cancer patients, we analyzed expression of BMP/Wnt target genes for association with SMAD4 expression. Promoters of the BMP/Wnt genes were interrogated for SMAD-binding elements. Fifteen genes were implicated and three tested for modulation by SMAD4 in patient-derived colorectal cancer tumoroids. Expression of the 15 genes was used for unsupervised hierarchical clustering of a training dataset and two resulting clusters modeled in a centroid model. This model was applied to an independent validation dataset of stage II and III patients. Disease-free survival was analyzed by the Kaplan-Meier method. In vitro analysis of three genes identified in the SMAD4-modulated profile (JAG1, TCF7, and MYC) revealed modulation by SMAD4 consistent with the trend observed in the profile. In the training dataset (n = 553), the profile was not associated with outcome. However, among stage II and III patients (n = 461), distinct clusters were identified by unsupervised hierarchical clustering that were associated with disease-free survival (p = .02, log-rank test). The main model was applied to a validation dataset of stage II/III CRC patients (n = 257) which confirmed the association of clustering with disease-free survival (p = .013, log-rank test).ConclusionsA SMAD4-modulated gene expression profile identified high-risk stage II and III colorectal cancer patients, can predict disease-free survival, and has prognostic potential for stage II and III colorectal cancer patients.

Dataset Information

Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

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Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

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