A comprehensively characterized cell line panel highly representative of clinical ovarian high-grade serous carcinomas

Abstract

Recent literature suggests that most widely used ovarian cancer (OVCA) cell models do not recapitulate the molecular features of clinical tumors. To address this limitation, we generated 18 cell lines and 3 corresponding patient-derived xenografts predominantly from high-grade serous carcinoma (HGSOC) peritoneal effusions. Comprehensive genomic characterization and comparison of each model to its parental tumor demonstrated a high degree of molecular similarity. Our characterization included whole exome-sequencing and copy number profiling for cell lines, xenografts, and matched non-malignant tissues, and DNA methylation, gene expression, and spectral karyotyping for a subset of specimens. Compared to the Cancer Genome Atlas (TCGA), our models more closely resembled HGSOC than any other tumor type, justifying their validity as OVCA models. Our meticulously characterized models provide a crucial resource for the OVCA research community that will advance translational findings and ultimately lead to clinical applications.

Keywords: cell models; exome-sequencing; genomic characterization; high-grade serous ovarian carcinoma; patient-derived xenograft.

Figure 1. Representative histologies and cell lines generated from OVCA malignant effusions

A. Histological appearances of tumors. High-grade serous ovarian carcinoma HCC5012 tumor (upper left) and corresponding xenograft (upper right). The appearance of the xenograft is identical to the original tumor. Low-grade serous ovarian carcinoma HCC5075 (lower left). HCC5011 (right lower), high-grade serous ovarian carcinoma (right part of figure) arising from a low-grade serous ovarian carcinoma (left part of figure). This is a rare but well documented occurrence [41]. B. Tumor enrichment and established cell lines. Cell lines were generated from tumor cell-containing ascites obtained from malignant effusions. Images of cell preparations at various stages of cell line generation are shown.

Figure 2. UTSW cell line and xenograft models recapitulate the genomic features of their parental tumors

Copy number alteration profiles were unique for each OVCA case, and highly similar between samples derived from the same patient (e.g. tumor, cell line, and xenograft). A. Examples of the high level of concordance in copy number alterations detected in primary tumors and their associated models for the HCC5012 and HCC5023 cases. Each dot represents 30 smoothed SNP array probes. Genomic coordinates are plotted on the horizontal axis versus the number of copies for each smoothed data point on the vertical axis. B. CNA profiles are plotted against genomic coordinates (horizontal axis) for each UTSW OVCA case. Correlation coefficients representing the similarity between cell lines and the tumors they were derived from are indicated.

Figure 3. UTSW cell lines highly resemble the TCGA HGSOC cohort across multiple genomic dimensions

A. The fraction of genome altered (FGA) was compared between the 18 UTSW cell lines, 11 UTSW tumors, 3 UTSW xenografts, and 583 TCGA HGSOC tumors. No significant differences in the extent of FGA between UTSW samples and TCGA tumors were found (Student's t-test, p>0.05). B., C. Comparison of somatic mutation counts and frequencies in UTSW samples versus TCGA tumors. Only functional somatic mutations (i.e. those predicted to have a biological effect on protein function) were considered. We observed no significant differences in the number of somatic mutations detected between UTSW samples and the TCGA tumors (B, Student's t-test, p>0.05). The UTSW cell lines and tumors had slightly lower mutational frequencies (ie. mutations per megabase) of DNA compared to the TCGA tumors (C, Student's t-test, p<0.05), however, given the large number of samples profiled in the TCGA cohort (n=316), the variability in mutational load of TCGA tumors is much larger than the UTSW samples. D. Comparison of the mean copy number profiles for UTSW cell lines and tumors with the TCGA HGSOC tumors for chromosomes 5 and 8. Tissue-matched TCGA non-malignant profiles are plotted as a copy-neutral (e.g. diploid) reference (black). UTSW cell line copy number patterns (blue) resemble the UTSW tumors (red), and are highly concordant with those of the TCGA tumors (green). Each plotted dot represents the copy number for an individual gene. Supplementary Figure 7 illustrates copy number patterns for UTSW samples and TCGA HGSOCs for all autosomal chromosomes.

Figure 4. Pan-cancer genomic comparisons of UTSW OVCA cell lines and TCGA tumor types

Correlation analyses to assess the similarity between UTSW cell lines and the mean genomic profiles of various TCGA tumor types were conducted for copy number, DNA methylation, gene expression, and mutation data. The 2000 most variably methylated or expressed genes were assessed. For copy number, methylation, and expression plots, the horizontal dotted line indicates the average correlation coefficient observed between the TCGA OVCA tumors and UTSW cell line comparison. For mutation data, functional, somatic mutation frequencies were compared. The TCGA tumor types are indicated as follows: OVCA, bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), and uterine corpus endometrial carcinoma (UCEC).