<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Objective</bold>: To identify the susceptible single nucleotide polymorphisms (SNPs) loci in HCC patients in Guangxi Region, screen biomarkers from differential SNPs loci by using predictors, and establish risk prediction models for HCC, to provide a basis of screening high-risk individuals of HCC.<bold>Methods</bold>: Blood sample and clinical data of 50 normal participants and 50 hepatic cancer (HCC) patients in Rui Kang Hospital affiliated to Guangxi University of Traditional Chinese Medicine were collected. Normal participants and HCC patients were assigned to training set and testing set, respectively. Whole Exome Sequencing (WES) technique was employed to compare the exon sequence of the normal participants and HCC patients. Five predictors were used to screen the biomarkers and construct HCC prediction models. The prediction models were validated with both training and testing set.<bold>Results</bold>: Two-hundred seventy SNPs were identified to be significantly different from HCC, among which 100 SNPs were selected as biomarkers for prediction models. Five prediction models constructed with the 100 SNPs showed good sensitivity and specificity for HCC prediction among the training set and testing set.<bold>Conclusion</bold>: A series of SNPs were identified as susceptible genes for HCC. Some of these SNPs including CNN2, CD177, KMT2C, and HLADQB1 were consistent with the previously identified polymorphisms by targeted genes examination. The prediction models constructed with part of those SNPs could accurately predict HCC development.</abstract>

Objective: To identify the susceptible single nucleotide polymorphisms (SNPs) loci in HCC patients in Guangxi Region, screen biomarkers from differential SNPs loci by using predictors, and establish risk prediction models for HCC, to provide a basis of screening high-risk individuals of HCC.Methods: Blood sample and clinical data of 50 normal participants and 50 hepatic cancer (HCC) patients in Rui Kang Hospital affiliated to Guangxi University of Traditional Chinese Medicine were collected. Normal participants and HCC patients were assigned to training set and testing set, respectively. Whole Exome Sequencing (WES) technique was employed to compare the exon sequence of the normal participants and HCC patients. Five predictors were used to screen the biomarkers and construct HCC prediction models. The prediction models were validated with both training and testing set.Results: Two-hundred seventy SNPs were identified to be significantly different from HCC, among which 100 SNPs were selected as biomarkers for prediction models. Five prediction models constructed with the 100 SNPs showed good sensitivity and specificity for HCC prediction among the training set and testing set.Conclusion: A series of SNPs were identified as susceptible genes for HCC. Some of these SNPs including CNN2, CD177, KMT2C, and HLADQB1 were consistent with the previously identified polymorphisms by targeted genes examination. The prediction models constructed with part of those SNPs could accurately predict HCC development.

Identification of Susceptibility Genes in Hepatic Cancer Using Whole Exome Sequencing and Risk Prediction Model Construction

Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine

Revista Romana de Medicina de Laborator

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Objective: To identify the susceptible single nucleotide polymorphisms (SNPs) loci in HCC patients in Guangxi Region, screen biomarkers from differential SNPs...

Identification of Susceptibility Genes in Hepatic Cancer Using Whole Exome Sequencing and Risk Prediction Model Construction

Publicado en línea: 07 feb 2020

Páginas: 67 - 74

Recibido: 14 jun 2019

Aceptado: 01 dic 2019

DOI: https://doi.org/10.2478/rrlm-2020-0008

Palabras clave
SNP, biomarkers, HCC

© 2020 Jinghui Zheng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Identification of Susceptibility Genes in Hepatic Cancer Using Whole Exome Sequencing and Risk Prediction Model Construction

Publicado en línea: 07 feb 2020

Páginas: 67 - 74

Recibido: 14 jun 2019

Aceptado: 01 dic 2019

DOI: https://doi.org/10.2478/rrlm-2020-0008

Palabras claveSNP, biomarkers, HCC

© 2020 Jinghui Zheng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
SNP, biomarkers, HCC