bioRxivCancer BiologyPreprint
Targeting ALC1 can safely expand the therapeutic utility of PARP inhibitors across high-grade serous ovarian cancers
Lindsey N AubuchoniD, Deanna H. WongiD, Natasha RamakrishnaniD, Samantha F. Greenberg, Rohan Reddy, Elena LomonosovaiD, Amanda J. CompadreiD, Kathleen E. Jackson, Danielle Kemper, Vrutti V. Mehta, Kellen Zoberi, Dineo KhabeleiD, Elizabeth L. ChristieiD, Mary Margaret MulleniD, Priyanka VermaiD
Abstract
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.
- organism: human
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 0
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