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Epihet for intra-tumoral epigenetic heterogeneity analysis and visualization.

ABSTRACT: Intra-tumoral epigenetic heterogeneity is an indicator of tumor population fitness and is linked to the deregulation of transcription. However, there is no published computational tool to automate the measurement of intra-tumoral epigenetic allelic heterogeneity. We developed an R/Bioconductor package, epihet, to calculate the intra-tumoral epigenetic heterogeneity and to perform differential epigenetic heterogeneity analysis. Furthermore, epihet can implement a biological network analysis workflow for transforming cancer-specific differential epigenetic heterogeneity loci into cancer-related biological function and clinical biomarkers. Finally, we demonstrated epihet utility on acute myeloid leukemia. We found statistically significant differential epigenetic heterogeneity (DEH) loci compared to normal controls and constructed co-epigenetic heterogeneity network and modules. epihet is available at https://bioconductor.org/packages/release/bioc/html/epihet.html .

SUBMITTER: Chen X

PROVIDER: S-EPMC7801679 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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epihet for intra-tumoral epigenetic heterogeneity analysis and visualization.

Chen Xiaowen X Ashoor Haitham H Musich Ryan R Wang Jiahui J Zhang Mingsheng M Zhang Chao C Lu Mingyang M Li Sheng S

Scientific reports 20210111 1

Intra-tumoral epigenetic heterogeneity is an indicator of tumor population fitness and is linked to the deregulation of transcription. However, there is no published computational tool to automate the measurement of intra-tumoral epigenetic allelic heterogeneity. We developed an R/Bioconductor package, epihet, to calculate the intra-tumoral epigenetic heterogeneity and to perform differential epigenetic heterogeneity analysis. Furthermore, epihet can implement a biological network analysis workf ...[more]

PMID: 33432081

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Project description:Intra-individual tumoral heterogeneity (ITH) is a hallmark of solid tumors and impedes accurate genomic diagnosis and selection of proper therapy. The purpose of this study was to identify ITH of ovarian serous adenocarcinomas (OSAs) and to determine the utility of ascitic cancer cells as a resource for mutation profiling in spite of ITH. We performed whole-exome sequencing, copy number profiling, and DNA methylation profiling of four OSA genomes using multiregional biopsies from 13 intraovarian lesions, 12 extraovarian tumor lesions (omentum/peritoneum), and ascitic cells. We observed substantial levels of heterogeneity in mutations and copy number alterations (CNAs) of the OSAs. We categorized the mutations into 'common', 'shared' and 'private' according to the regional distribution. Six common, 8 shared, and 24 private mutations were observed in known cancer-related genes,. but common mutations had a higher mutant allele frequency and included TP53 mutations in all four OSAs. Region-specific chromosomal amplifications and deletions involving BRCA1, PIK3CA, and RB1 were also identified. Of note, the mutations detected in ascitic cancer cells represented 92.3-100% of overall somatic mutations in the given case. Phylogenetic analyses of ascitic genomes predicted a polyseeding origin of somatic mutations in ascitic cells. Our results demonstrate that despite ITH, somatic mutations, CNAs, and DNA methylations in both â??commonâ?? category and cancer-related genes were highly conserved in ascitic cells of OSAs, highlighting the clinical relevance of genome analysis of ascitic cells. Ascitic tumor cells may serve as a potential resource to discover somatic mutations of primary OSA with diagnostic and therapeutic relevance. Genome wide DNA methylation profiling of ascitic cells as well as biopsies from ovarian serous adenocarcinomas cases obtained by Illumina Infinium 450k Human DNA methylation Beadchip Bisulphite converted DNA from the 16 samples were hybridized to the Illumina Infinium 450k Human Methylation Beadchip

Dataset Information

Epihet for intra-tumoral epigenetic heterogeneity analysis and visualization.

Publications

epihet for intra-tumoral epigenetic heterogeneity analysis and visualization.

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