bioRxivCancer Biology
Breast cancer brain metastases show increased levels of genomic aberration based homologous recombination deficiency scores relative to their corresponding primary tumors
M. Diossy, L. Reiniger, Z. Sztupinszki, M. Krzystanek, K. M. Timms, C. Neff, C. Solimeno, D. Pruss, A. C. Eklund, E. Toth, O. Kiss, O. Rusz, G. Cserni, T. Zombori, B. Szekely, I. Csabai, Z. Szallasi
Abstract
Due to its mechanism of action, PARP inhibitor therapy is expected to benefit mainly tumor cases with homologous recombination deficiency (HRD). Various measures of genomic scarring based HRD scores were developed as a companion diagnostic in order to correlate it with PARP inhibitor sensitivity. We compared a variety of HRD scores in primary tumors and their corresponding brain metastases and found a significant increase in this measure in brain metastases for all measures of HRD that were tested. This discrepancy warrants further investigation to assess whether this observation is common to other metastatic sites, and potentially a significant adjustment of strategy in the application of HRD measures in clinical trials for the prioritization of patients for PARP inhibitor therapy.\n\nKey messageWe quantified homologous recombination deficiency (HRD) in paired primary breast cancer and brain metastases samples based on a previously published data set. We showed that HRD significantly increases in the brain metastases relative to its paired primary tumor. An independent validation was also performed on another set of primary breast cancer and brain metastasis pairs using the \"my choice\" HRD score in collaboration with Myriad Genetics.\n\nThese confirmatory results suggest that brain metastases of breast cancer tend to have significantly higher HRD scores, which would prioritize those patients for PARP inhibitor therapy with those agents that cross the blood brain barrier such as veliparib and niraparib.
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: drug response / drug discovery
- approach: statistical model
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