Susanne Malander

All identified pathogenic variants in the samples analyzed.

Background: Ovarian cancer is often diagnosed in advanced stages, resulting in poor outcomes. There is an unmet need for a sensitive and specific screening tool for early-stage detection of ovarian cancer. Methods: Recognizing that high-grade serous ovarian carcinoma (HGSC) is driven by copy number alterations (CNAs) and that tumor DNA can be detected in cervical samples, we analyzed CNAs from shallow whole genome sequencing of 212 cervical samples from 128 women with/without HGSC, including 29 germline BRCA1/2 mutation carriers. Using a machine-learning classifier, we developed H igh-grade serous ovarian cancer C ervical copy number sig nature (HCsig), a predictor for HGSC detection. Results: HGSC-derived CNAs were detectable with HCsig in cervical samples collected several years before diagnosis. Importantly, HCsig correctly identified HGSC in 79% of archival cervical samples, including 91% stage I-II (0-27 months pre-diagnosis), and 77% stage III-IV (0-65 months pre-diagnosis). Among patients with HGSC who had multiple pre-diagnostic samples collected during the pre-symptomatic phase, 85% had at least one HCpositive cervical sample before surgery (up to 65 months before diagnosis). Detection rates were 90% and 76% for BRCA1/2 -mutated and wildtype HGSC, respectively. Validation in 172 independent samples (0-98 months pre-diagnosis) showed 76% sensitivity and 94% specificity (AUC=0.83), including high sensitivity for early-stage cancers. Conclusions: We show that applying the HCsig classifier to cervical samples, including from non-symptomatic women several years before diagnosis, holds promise for early-stage detection and secondary prevention of HGSC. Moreover, it may serve as a screening tool to aid decision-making regarding timing of risk-reducing surgery in high-risk populations.

All identified pathogenic variants in the samples analyzed.

Oncoplot showing pathogenic gene alterations. The plot is split into groups by cellular pathways affected by the alteration on the vertical axis and clinical outcome (clinical benefit: PFS ≥12 months, no benefit: PFS ≤6 months) on the horizontal axis. Each column represents one patient. In total, 81 patient samples. See color guide reflecting specific alterations below the plot. # = Reason of “end of treatment” other than progressive disease. Integer “HRD-status and GIS” = the exact GIS reported by MyChoice.

Flowchart showing patients included in final gene panel analysis. * Formalin-fixed paraffin-embedded. ** TSO500 gene panel by Illumina.

BRCA1 (top) and BRCA2 (bottom) with variants found in AVANOVA1&2 colored by treatment response (see legend). BRCA1: Transcript NM_007294.4. In total, 1,863 aa. RING domain (aa 2–101), PALB2-binding domain (also called coiled-coil domain; aa 1,391–1,424), BRCT repeats (aa 1,650–1857), and exon 11 (aa 224–1,366). BRCA2: Transcript NM_000059.4. In total, 3,418 aa. PALB2-binding domain (aa 10–40), DNA-binding domain (aa 2,481–3,186), and exons 10 and 11 (aa 266–2,281).

Table 1 from Beyond HRD Status: Unraveling Genetic Variants Impacting PARP Inhibitor Sensitivity in Advanced Ovarian Cancer