Deriving tumor purity from cancer next generation sequencing data: applications for quantitative ERBB2 (HER2) copy number analysis and germline inference of BRCA1 and BRCA2 mutations.
Stephanie E SiegmundDanielle K ManningPhani K DavineniFei DongPublished in: Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc (2022)
Tumor purity, or the relative contribution of tumor cells out of all cells in a pathological specimen, influences mutation identification and clinical interpretation of cancer panel next generation sequencing results. Here, we describe a method of calculating tumor purity using pathologist-guided copy number analysis from sequencing data. Molecular calculation of tumor purity showed strong linear correlation with purity derived from driver KRAS or BRAF variant allele fractions in colorectal cancers (R 2 = 0.79) compared to histological estimation in the same set of colorectal cancers (R 2 = 0.01) and in a broader dataset of cancers with various diagnoses (R 2 = 0.35). We used calculated tumor purity to quantitate ERBB2 copy number in breast carcinomas with equivocal immunohistochemical staining and demonstrated strong correlation with fluorescence in situ hybridization (R 2 = 0.88). Finally, we used calculated tumor purity to infer the germline status of variants in breast and ovarian carcinomas with concurrent germline testing. Tumor-only next generation sequencing correctly predicted the somatic versus germline nature of 26 of 26 (100%) pathogenic TP53, BRCA1 and BRCA2 variants. In this article, we describe a framework for calculating tumor purity from cancer next generation sequencing data. Accurate tumor purity assessment can be assimilated into interpretation pipelines to derive clinically useful information from cancer genomic panels.
Keyphrases
- copy number
- mitochondrial dna
- genome wide
- dna methylation
- papillary thyroid
- gene expression
- squamous cell
- dna repair
- healthcare
- radiation therapy
- high grade
- social media
- induced apoptosis
- big data
- dna damage
- childhood cancer
- single cell
- circulating tumor
- young adults
- single molecule
- cell proliferation
- flow cytometry
- health information