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Single-cell analysis of copy-number alterations in serous ovarian cancer reveals substantial heterogeneity in both low- and high-grade tumors.

ABSTRACT: Unusually high aneuploidy is a hallmark of epithelial serous ovarian cancer (SOC). Previous analyses have focused on aneuploidy on average across all tumor cells. With the expansion of single-cell sequencing technologies, however, an analysis of copy number heterogeneity cell-to-cell is now technically feasible. Here, we describe an analysis of single-cell RNA sequencing (scRNA-seq) data to infer arm-level aneuploidy in individual serous ovarian cancer cells. By first clustering high-quality sequenced epithelial versus non-epithelial cells, high-confidence tumor cell populations were identified. InferCNV was used to predict segmented copy-number alterations (CNAs), which were then used to determine arm-level aneuploidy at the single-cell level. Control comparisons of normal cells to normal cells showed zero arm-level aneuploidy, whereas a median of four aneuploid events were detectable in cancer cells. A heterogeneity analysis of high-grade tumor cells compared to low-grade tumor cells showed similar levels of cell-to-cell variation between cancer grades. Metastatic tumors potentially showed selection pressure with reduced cell-to-cell variation compared to cells from primary tumors. Minor cell populations with CNAs similar to metastatic cells were identified within the matched primary tumors. Taken together, these results provide a minimum estimate for single-cell aneuploidy in serous ovarian cancer and demonstrate the utility of single-cell sequencing for CNA analysis.

SUBMITTER: Kumar M

PROVIDER: S-EPMC7714496 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDNA copy number alterations are frequently observed in ovarian cancer, but it remains a challenge to identify the most relevant alterations and the specific causal genes in those regions.MethodsWe obtained high-resolution 500K SNP array data for 52 ovarian tumors and identified the most statistically significant minimal genomic regions with the most prevalent and highest-level copy number alterations (recurrent CNAs). Within a region of recurrent CNA, comparison of expression levels in tumors with a given CNA to tumors lacking that CNA and to whole normal ovary samples was used to select genes with CNA-specific expression patterns. A public expression array data set of laser capture micro-dissected (LCM) non-malignant fallopian tube epithelia and LCM ovarian serous adenocarcinoma was used to evaluate the effect of cell-type mixture biases.ResultsFourteen recurrent deletions were detected on chromosomes 4, 6, 9, 12, 13, 15, 16, 17, 18, 22 and most prevalently on X and 8. Copy number and expression data suggest several apoptosis mediators as candidate drivers of the 8p deletions. Sixteen recurrent gains were identified on chromosomes 1, 2, 3, 5, 8, 10, 12, 15, 17, 19, and 20, with the most prevalent gains localized to 8q and 3q. Within the 8q amplicon, PVT1, but not MYC, was strongly over-expressed relative to tumors lacking this CNA and showed over-expression relative to normal ovary. Likewise, the cell polarity regulators PRKCI and ECT2 were identified as putative drivers of two distinct amplicons on 3q. Co-occurrence analyses suggested potential synergistic or antagonistic relationships between recurrent CNAs. Genes within regions of recurrent CNA showed an enrichment of Cancer Census genes, particularly when filtered for CNA-specific expression.ConclusionThese analyses provide detailed views of ovarian cancer genomic changes and highlight the benefits of using multiple reference sample types for the evaluation of CNA-specific expression changes.

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Single-cell analysis of copy-number alterations in serous ovarian cancer reveals substantial heterogeneity in both low- and high-grade tumors.

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