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Genomic subtyping of liver cancers with prognostic application

Authors
  • Wu, Zhenggang1, 2
  • Long, Xi2
  • Tsang, Shui Ying2
  • Hu, Taobo2
  • Yang, Jian-Feng2
  • Mat, Wai Kin2
  • Wang, Hongyang3
  • Xue, Hong1, 2, 4, 5, 2
  • 1 9 Yuexing First Road, Nanshan, Shenzhen, China , Shenzhen (China)
  • 2 Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China , Hong Kong (China)
  • 3 Second Military Medical University, Shanghai, China , Shanghai (China)
  • 4 School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China , Nanjing (China)
  • 5 Nanjing Medical University, Nanjing, China , Nanjing (China)
Type
Published Article
Journal
BMC Cancer
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Jan 31, 2020
Volume
20
Issue
1
Identifiers
DOI: 10.1186/s12885-020-6546-8
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundCancer subtyping has mainly relied on pathological and molecular means. Massively parallel sequencing-enabled subtyping requires genomic markers to be developed based on global features rather than individual mutations for effective implementation.MethodsIn the present study, the whole genome sequences (WGS) of 110 liver cancers of Japanese patients published with different pathologies were analyzed with respect to their single nucleotide variations (SNVs) comprising both gain-of-heterozygosity (GOH) and loss-of-heterozygosity (LOH) mutations, the signatures of combined GOH and LOH mutations, along with recurrent copy number variations (CNVs).ResultsThe results, obtained based on the WGS sequences as well as the Exome subset within the WGSs that covered ~ 2.0% of the WGS and the AluScan-subset within the WGSs that were amplifiable by Alu element-consensus primers and covered ~ 2.1% of the WGS, indicated that the WGS samples could be employed with the mutational parameters of SNV load, LOH%, the Signature α%, and survival-associated recurrent CNVs (srCNVs) as genomic markers for subtyping to stratify liver cancer patients prognostically into the long and short survival subgroups. The usage of the AluScan-subset data, which could be implemented with sub-micrograms of DNA samples and vastly reduced sequencing analysis task, outperformed the usage of WGS data when LOH% was employed as stratifying criterion.ConclusionsThus genomic subtyping performed with novel genomic markers identified in this study was effective in predicting patient-survival duration, with cohorts of hepatocellular carcinomas alone and those including intrahepatic cholangiocarcinomas. Such relatively heterogeneity-insensitive genomic subtyping merits further studies with a broader spectrum of cancers.

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