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A qualitative transcriptional signature for predicting microsatellite instability status of right-sided Colon Cancer.
Fu, Yelin; Qi, Lishuang; Guo, Wenbing; Jin, Liangliang; Song, Kai; You, Tianyi; Zhang, Shuobo; Gu, Yunyan; Zhao, Wenyuan; Guo, Zheng.
Afiliación
  • Fu Y; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Qi L; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Guo W; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Jin L; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Song K; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • You T; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Zhang S; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Gu Y; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
  • Zhao W; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China. zhaowenyuan@ems.hrbmu.edu.cn.
  • Guo Z; Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China. guoz@ems.hrbmu.edu.cn.
BMC Genomics ; 20(1): 769, 2019 Oct 23.
Article en En | MEDLINE | ID: mdl-31646964
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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias del Colon / Inestabilidad de Microsatélites / Transcriptoma Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2019 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias del Colon / Inestabilidad de Microsatélites / Transcriptoma Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2019 Tipo del documento: Article País de afiliación: China