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.
Highlights
Cancer subtyping has mainly relied on pathological and molecular means
Increased Single nucleotide variation (SNV) load as stratifying criterion for survival When the whole genome sequences (WGS) data of the tumor and blood pairwise samples of the 110-Liver cohort were subjected to SNV analysis, SNV load and its constituent GOH and LOH mutation numbers varied substantially between samples, and there was no significant correlation between SNV load, i.e., the total number of SNVs in each tumor genome, with the clinical parameters of age at operation, viral status or tumor grade (Additional File 2: Figure S1)
In stratifying the 110-Liver and 85-hepatocellular carcinoma (HCC) cohorts employing SNV load, LOH%, Signature α% or survival-associated recurrent copy number variations (CNVs) (srCNV) content as stratifying criterion, the results obtained from WGS data, AluScan-subset data and Exome-subset data indicated that the Exome-subset largely did not provide statistical distinction with sufficiently low p-values between the long-survival and short-survival subgroups, possibly on account of the relative paucity of cancer SNVs in the exomic regions
Summary
Cancer 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. A relatively rare subtype of combined HCC and ICC (viz. HCC/ICC) that harbors both hepatocellular and biliary epithelial cancer pathologies is associated with poorer prognosis than either HCC or ICC. The main overall risk factor for liver cancers is virus infection: both hepatitis B virus (HBV) and hepatitis C virus (HCV) infections lead to chronic liver disease and possible subsequent cancer. HBV infection is associated with about half, and HCV infection with about 25%, of the HCC cases with considerable regional variations [3, 4]. There are a range of non-viral risk factors for liver cancers, including alcohol intake, tobacco use and environmental exposures, which are consistent with variations in etiological and progression mechanisms
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