Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA.

Drug resistance is the major cause of therapeutic failure in high-grade serous ovarian cancer (HGSOC). Yet, the mechanisms by which tumors evolve to drug resistant states remains largely unknown. To address this, we aimed to exploit clone-specific genomic structural variations by combining scaled single-cell whole genome sequencing with longitudinally collected cell-free DNA (cfDNA), enabling clonal tracking before, during and after treatment. We developed a cfDNA hybrid capture, deep sequencing approach based on leveraging clone-specific structural variants as endogenous barcodes, with orders of magnitude lower error rates than single nucleotide variants in ctDNA (circulating tumor DNA) detection, demonstrated on 19 patients at baseline. We then applied this to monitor and model clonal evolution over several years in ten HGSOC patients treated with systemic therapy from diagnosis through recurrence. We found drug resistance to be polyclonal in most cases, but frequently dominated by a single high-fitness and expanding clone, reducing clonal diversity in the relapsed disease state in most patients. Drug-resistant clones frequently displayed notable genomic features, including high-level amplifications of oncogenes such as CCNE1, RAB25, NOTCH3, and ERBB2. Using a population genetics Wright-Fisher model, we found evolutionary trajectories of these features were consistent with drug-induced positive selection. In select cases, these alterations impacted selection of secondary lines of therapy with positive patient outcomes. For cases with matched single-cell RNA sequencing data, pre-existing and genomically encoded phenotypic states such as upregulation of EMT and VEGF were linked to drug resistance. Together, our findings indicate that drug resistant states in HGSOC pre-exist at diagnosis and lead to dramatic clonal expansions that alter clonal composition at the time of relapse. We suggest that combining tumor single cell sequencing with cfDNA enables clonal tracking in patients and harbors potential for evolution-informed adaptive treatment decisions.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer.

Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity. We studied WGD evolution in 65 high-grade serous ovarian cancer (HGSOC) tissue samples from 40 patients, yielding 29,481 tumor cell genomes. We found near-ubiquitous evidence of WGD as an ongoing mutational process promoting cell-cell diversity, high rates of chromosomal missegregation, and consequent micronucleation. Using a novel mutation-based WGD timing method, doubleTime , we delineated specific modes by which WGD can drive tumor evolution: (i) unitary evolutionary origin followed by significant diversification, (ii) independent WGD events on a pre-existing background of copy number diversity, and (iii) evolutionarily late clonal expansions of WGD populations. Additionally, through integrated single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signaling and cGAS-STING pathway activation result from ongoing chromosomal instability and are restricted to tumors that remain predominantly diploid. This contrasted with predominantly WGD tumors, which exhibited significant quiescent and immunosuppressive phenotypic states. Together, these findings establish WGD as an evolutionarily 'active' mutational process that promotes evolvability and dysregulated immunity in late stage ovarian cancer.

Mainstreaming in parallel with ovarian cancer tumor testing to improve genetic testing uptake.

OBJECTIVES: Although genetic testing (GT) is universally recommended for patients with epithelial ovarian cancer (EOC), rates are low (34%). In 1/2019, we implemented mainstreaming-GT in parallel with tumor testing via MSK-IMPACT within oncology clinics. We sought to determine GT rates pre/post-mainstreaming and patient characteristics associated with GT. METHODS: Patients with newly diagnosed EOC seen at our institution from 7/1/2015-3/31/2022 were included. Clinical data were abstracted including social determinants of health (SDOH) variables, race/ethnicity, marital status, insurance, language, comorbidities, employment, and Yost index, a measure of socioeconomic status. GT rates were calculated overall and pre-/post-mainstreaming (1/2019). Logistic regression models were fit to identify variables associated with GT. RESULTS: Of 1742 patients with EOC, 1591 (91%) underwent GT. Rates of GT increased from 87% to 95% after mainstreaming (p < 0.001). Among 151 patients not undergoing GT, major reasons were lack of provider recommendation (n = 76, 50%) and logistical issues (n = 38, 25%) with few declining (n = 14, 9%) or having medical complications preventing GT (n = 7, 4.6%). High-grade serous histology, advanced stage (III/IV), and having a spouse/partner were associated with increased GT uptake (p < 0.01). Among SDOH variables, there were no differences by insurance, Yost score, language, comorbidities, employment, or race/ethnicity. In multivariable models, likelihood of GT increased with mainstreaming, even after adjustment for histology, stage, and marital status (OR 3.77; 95% CI: 2.56-5.66). CONCLUSIONS: Mainstreaming increased the likelihood of GT in patients with EOC. We found lower testing rates in patients without partners/spouses, non-high-grade serous histology, and early-stage disease, representing potential areas for future interventions.