Christie, E. L. | bioRxiv Science

bioRxiv2025

Targeting ALC1 can safely expand the therapeutic utility of PARP inhibitors across high-grade serous ovarian cancers

Poly (ADP-ribose) polymerase inhibitors (PARPi) are approved for homologous recombination-deficient (HRD) high-grade serous ovarian cancers (HGSOCs), but their long-term effectiveness is limited by the emergence of resistance and hematological toxicity. Moreover, PARPi are largely ineffective in HR-proficient HGSOCs, particularly tumors with CCNE1 amplification, which exhibit marked therapeutic resistance and currently lack effective treatment options. Loss of a chromatin remodeling enzyme, Amplified in Liver Cancer 1 (ALC1), has been shown to enhance PARPi sensitivity. However, the clinical contexts in which ALC1 targeting will be clinically meaningful remain elusive. Here we demonstrate that ALC1 loss enhances PARPi sensitivity across HRD and CCNE1-amplified serous ovarian cancer lines, xenograft and patient-derived cells. ALC1 depletion can overcome clinically relevant mechanisms of PARPi resistance while having minimal effects in BRCA-wild-type or heterozygous non-cancerous cells. Consistent with this therapeutic safety, PARPi sensitivity upon ALC1 loss can be reliably predicted by the endogenous levels of phospho-T21 RPA2, a marker for replication stress which is typically higher in ovarian cancer cells compared to their normal counterparts. Together, our studies define the clinical contexts in which the therapeutic utility of PARPi can be expanded by targeting ALC1, whose inhibitors are currently in Phase I clinical trials.

cancer biology↗

bioRxiv2016

Chemotherapy weakly contributes to predicted neoantigen expression in ovarian cancer

BackgroundPatients with highly mutated tumors, such as melanoma or smoking-related lung cancer, have higher rates of response to immune checkpoint blockade therapy, perhaps due to increased neoantigen expression. Many chemotherapies including platinum compounds are known to be mutagenic, but the impact of standard treatment protocols on mutational burden and resulting neoantigen expression in most human cancers is unknown.\n\nMethodsWe sought to quantify the effect of chemotherapy treatment on computationally predicted neoantigen expression for 12 high grade serous ovarian carcinoma (HGSC) patients with pre- and post-chemotherapy samples collected in the Australian Ovarian Cancer Study. We additionally analyzed 16 patients from the cohort with post-treatment samples only, including five primary surgical samples exposed to neoadjuvant chemotherapy. Our approach integrates tumor whole genome and RNA sequencing with class I MHC binding prediction and mutational signatures of chemotherapy exposure extracted from two preclinical studies.\n\nResultsThe mutational signatures for cisplatin and cyclophosphamide identified in a preclinical model had significant but inexact associations with the relevant exposure in the clinical samples. In an analysis stratified by tissue type (solid tumor or ascites), relapse samples collected after chemotherapy harbored a median of 90% more expressed neoantigens than untreated primary samples, a figure that combines the effects of chemotherapy and other mutagenic processes operative during relapse. Neoadjuvant-treated primary samples showed no detectable increase over untreated samples. The contribution from chemotherapy-associated signatures was small, accounting for a mean of 5% (range 0-16) of the expressed neoantigen burden in relapse samples. In both treated and untreated samples, most neoantigens were attributed to COSMIC Signature (3), associated with BRCA disruption, Signature (1), associated with a slow mutagenic process active in healthy tissue, and Signature (8), of unknown etiology.\n\nConclusionRelapsed HGSC tumors harbor nearly double the predicted expressed neoantigen burden of primary samples, but mutations associated with chemotherapy signatures account for only a small part of this increase. The mutagenic processes responsible for most neoantigens are similar between primary and relapse samples. Our analyses are based on mutations detectable from whole genome sequencing of bulk samples and do not account for neoantigens present in small populations of cells.

cancer biology↗