Metastatic colorectal adenocarcinoma tumor purity assessment from whole exome sequencing data

Abstract

Tumors rich in stroma are associated with advanced stage and poor prognosis in colorectal adenocarcinoma (CRC). Abundance of stromal cells also has implications for genomic analysis of patient tumors as it may prevent detection of somatic mutations. As part of our efforts to interrogate stroma-cancer cell interactions and to identify actionable therapeutic targets in metastatic CRC, we aimed to determine the proportion of stroma embedded in hepatic CRC metastases by performing computational tumor purity analysis based on whole exome sequencing data (WES). Unlike previous studies focusing on histopathologically prescreened samples, we used an unbiased in-house collection of tumor specimens. WES from CRC liver metastasis samples were utilized to evaluate stromal content and to assess the performance of three in silico tumor purity tools, ABSOLUTE, Sequenza and PureCN. Matching tumor derived organoids were analyzed as a high purity control as they are enriched in cancer cells. Computational purity estimates were compared to those from a histopathological assessment conducted by a board-certified pathologist. According to all computational methods, metastatic specimens had a median tumor purity of 30% whereas the organoids were enriched for cancer cells with a median purity estimate of 94%. In line with this, variant allele frequencies (VAFs) of oncogenes and tumor suppressor genes were undetectable or low in most patient tumors, but higher in matching organoid cultures. Positive correlation was observed between VAFs and in silico tumor purity estimates. Sequenza and PureCN produced concordant results whereas ABSOLUTE yielded lower purity estimates for all samples. Our data shows that unbiased sample selection combined with molecular, computational, and histopathological tumor purity assessment is critical to determine the level of stroma embedded in metastatic colorectal adenocarcinoma.

Fig 1. In silico tumor purity assessment using whole-exome sequencing data and ABSOLUTE, Sequenza and PureCN tools.

ABSOLUTE was run with the max.non.clonal parameter set to either 30% or 50%. CRCLM tumors (A) and tumor-derived organoids (B) from 6 patients for whom matching normal DNA was available were analyzed. (C) Tumor purity estimates of samples with known ratios of normal and tumor DNA from patient CR1121. PDO; patient-derived tumor organoids, PDXO; patient-derived xenograft organoids.

Fig 2. PureCN tumor purity assessment of CRCLM patient tumors from 12 patients using tumor only data.

Fig 3. Representative H&E stained section of the patient CR726 FFPE CRCLM tumor sample.

Tumor area is outlined with cyan and the zoomed in area within it in yellow.

Fig 4

Variant allele frequencies of the pathogenic single nucleotide variants detected in CRCLM tumors (A) from 18 patients and in tumor organoids (B) derived from 6 of these patients. PDO; patient-derived tumor organoids, PDXO; patient-derived xenograft organoids. Amino acid change of each variant is displayed within the heatmap cells.

Fig 5. Correlation between the variant allele frequency (VAF) of the most prevalent pathogenic variant in each sample and of in silico and pathologist tumor purity results.

(A) and (B) ABSOLUTE, (C) Sequenza, (D) PureCN, or (E.) pathologist tumor purity assessment. (F) Correlation between the PureCN in silico tumor purity results and pathologist purity assessment. Each dot represents a patient tumor specimen or a tumor-derived organoid sample.

Fig 6. PureCN tumor purity estimates with mean and standard deviation for all 18 patients grouped by their chemotherapy status prior to hepatectomy.