Dataset Information

A qualitative transcriptional signature for predicting microsatellite instability status of right-sided Colon Cancer.

ABSTRACT: BACKGROUND:Microsatellite instability (MSI) accounts for about 15% of colorectal cancer and is associated with prognosis. Today, MSI is usually detected by polymerase chain reaction amplification of specific microsatellite markers. However, the instability is identified by comparing the length of microsatellite repeats in tumor and normal samples. In this work, we developed a qualitative transcriptional signature to individually predict MSI status for right-sided colon cancer (RCC) based on tumor samples. RESULTS:Using RCC samples, based on the relative expression orderings (REOs) of gene pairs, we extracted a signature consisting of 10 gene pairs (10-GPS) to predict MSI status for RCC through a feature selection process. A sample is predicted as MSI when the gene expression orderings of at least 7 gene pairs vote for MSI; otherwise the microsatellite stability (MSS). The classification performance reached the largest F-score in the training dataset. This signature was verified in four independent datasets of RCCs with the F-scores of 1, 0.9630, 0.9412 and 0.8798, respectively. Additionally, the hierarchical clustering analyses and molecular features also supported the correctness of the reclassifications of the MSI status by 10-GPS. CONCLUSIONS:The qualitative transcriptional signature can be used to classify MSI status of RCC samples at the individualized level.

SUBMITTER: Fu Y

PROVIDER: S-EPMC6813057 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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A qualitative transcriptional signature for predicting microsatellite instability status of right-sided Colon Cancer.

Fu Yelin Y Qi Lishuang L Guo Wenbing W Jin Liangliang L Song Kai K You Tianyi T Zhang Shuobo S Gu Yunyan Y Zhao Wenyuan W Guo Zheng Z

BMC genomics 20191023 1

<h4>Background</h4>Microsatellite instability (MSI) accounts for about 15% of colorectal cancer and is associated with prognosis. Today, MSI is usually detected by polymerase chain reaction amplification of specific microsatellite markers. However, the instability is identified by comparing the length of microsatellite repeats in tumor and normal samples. In this work, we developed a qualitative transcriptional signature to individually predict MSI status for right-sided colon cancer (RCC) based ...[more]

PMID: 31646964

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Project description:The difference between left- and right-sided colon cancer has become the focus of global attention, and researchers have found differences in the morbidity, molecular biological characteristics, and response to targeted drug therapy between left- and right-sided colon cancer. Therefore, the identification of more effective predictive indicators is critical for providing guidance to future clinical work. We collected samples from different colon sites and regions and analyzed the identities and distributions of differentially expressed species in the microbiota in the left and right sides of the colon to better explore the pathogenesis of colon cancer and provided a basis for individualized drug therapy. We collected samples from different regions in the body of 40 patients with colon cancer, including stool and tissues. The Subjects were classified into four groups, and this classification was mainly based on the colon cancer distribution. The microbiota composition of the left-sided and right-sided colon samples was assessed by specifically amplifying the V3-V4 region of the 16S rDNA gene from DNA extracts from the samples. These amplicons were examined by Illumina HiSeq 2500 sequencing. The microbial taxa in the left-sided colon samples are more abundant than those in the right-sided colon samples. The flora in the left-sided colon samples, such as Clostridium perfringens and Fusobacterium nucleatum, might be associated with VEGF expression and are more likely to promote colon cancer. The microbiota distribution in the right-sided colon samples is less invasive and harmful and particularly rich in Bifidobacterium dentium. In addition, Streptococcus, which is the target of EGFR, was found to be expressed in both the left- and right-sided colon samples but was found at a higher level in the left-sided colon samples. Additionally, the differential pathways involved in the left-sided colon samples mainly mediate DNA damage, methylation, and histone modifications, whereas those in the right-sided colon samples are dominated by DNA synthesis. The comparison of only the geographical differences revealed a significant difference in the distribution of the microbial population. The adherent microbiota composition and structural changes between the left- and right-sided colon samples might contribute to the development of colon cancer, lead to different morbidities, and further affect the prognosis of patients and their sensitivity to targeted drugs. Therefore, the identification of the differential flora in the colon could be used as an indicator for predicting the occurrence and development of colon cancer, which is also beneficial for future individualized drug therapy.

Project description:BackgroundThough colon cancer (CC) is one of the most malignant tumors across the world, CC patients with microsatellite instability-high (MSI-H) in stage II seem to have a better prognosis. However, the molecular mechanisms underlying the phenomena haven't been elucidated yet.MethodsThis study enrolled 322 CCs with known microsatellite status from GSE143985, GSE39582 and GSE92921 in the Gene Expression Omnibus (GEO) database. Robust rank aggregation (RRA) analysis, univariate Cox regression analysis and multivariate Cox stepwise regression analysis were performed to identify genes and construct risk score signature. Kaplan-Meier and receiver operating characteristic (ROC) curves analyses were used to evaluate the prognostic value of the signature. The potential mechanisms underlying this signature were assessed in the Metascape database, gene set enrichment analysis (GSEA) and immune infiltration analysis.ResultsRRA analysis identified 40 differently expressed genes (DEGs). A 3-gene risk score signature (MKQ signature) associated with disease-free survival (DFS) was generated. DFS was significantly longer in CC patients with lower than higher scores (P=0.0046). The areas under curves (AUCs) of the time-dependent ROC curves of MKQ signature at 1-, 3- and 5-year DFS were 1, 0.963 and 0.961 respectively. Recurrence-free survival (RFS) was significantly longer in patients in GSE39582 with lower than higher risk scores (P=0.032). The AUCs for 1-, 3- and 5-year RFS in GSE39582 were 0.63, 0.618 and 0.583, respectively, validating the value of the MKQ signature. Functional annotation and GSEA revealed that the MKQ signature was associated with multiple immune-related pathways. Immune cell infiltration was found to differ in patients differing in the MKQ signature.ConclusionsGene expression and microsatellite status identified a 3-gene signature (MKQ signature) that could facilitate risk-stratified management in patients with stage II CC. Dysregulation of MSMB, KRT23, and QPRT can serve as prognostic markers in stage II CC.

Dataset Information

A qualitative transcriptional signature for predicting microsatellite instability status of right-sided Colon Cancer.

Publications

A qualitative transcriptional signature for predicting microsatellite instability status of right-sided Colon Cancer.

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