PARP Inhibition in Prostate Cancer With Homologous Recombination Repair Alterations

Prediction of homologous recombination deficiency from Oncomine Comprehensive Assay Plus correlating with SOPHiA DDM HRD Solution

OBJECTIVE

Poly(ADP-ribose) polymerase (PARP) inhibitors are used for targeted therapy for ovarian cancer with homologous recombination deficiency (HRD). In this study, we aimed to develop a homologous recombination deficiency prediction model to predict the genomic integrity (GI) index of the SOPHiA DDM HRD Solution from the Oncomine Comprehensive Assay (OCA) Plus. We also tried to a find cut-off value of the genomic instability metric (GIM) of the OCA Plus that correlates with the GI index of the SOPHiA DDM HRD Solution.

METHODS

We included 87 cases with high-grade ovarian serous carcinoma from five tertiary referral hospitals in Republic of Korea. We developed an HRD prediction model to predict the GI index of the SOPHiA DDM HRD Solution. As predictor variables in the model, we used the HRD score, which included percent loss of heterozygosity (%LOH), percent telomeric allelic imbalance (%TAI), percent large-scale state transitions (%LST), and the genomic instability metric (GIM). To build the model, we employed a penalized logistic regression technique.

RESULTS

The final model equation is -21.77 + 0.200 × GIM + 0.102 × %LOH + 0.037 × %TAI + 0.261 × %LST. To improve the performance of the prediction model, we added a borderline result category to the GI results. The accuracy of our HRD status prediction model was 0.958 for the test set. The accuracy of HRD status using GIM with a cut-off value of 16 was 0.911.

CONCLUSION

The Oncomine Comprehensive Assay Plus provides a reliable biomarker for homologous recombination deficiency.

IGFBP3 promotes resistance to Olaparib via modulating EGFR signaling in advanced prostate cancer

Olaparib is a pioneering PARP inhibitor (PARPi) approved for treating castration-resistant prostate cancer (CRPC) tumors harboring DNA repair defects, but clinical resistance has been documented. To study acquired resistance, we developed Olaparib-resistant (OlapR) cell lines through chronic Olaparib treatment of LNCaP and C4-2B cell lines. Here, we found that IGFBP3 is highly expressed in acquired (OlapR) and intrinsic (Rv1) models of Olaparib resistance. We show that IGFBP3 expression promotes Olaparib resistance by enhancing DNA repair capacity through activation of EGFR and DNA-PKcs. IGFBP3 depletion enhances efficacy of Olaparib by promoting DNA damage accumulation and subsequently, cell death in resistant models. Mechanistically, we show that silencing IGFBP3 or EGFR expression reduces cell viability and resensitizes OlapR cells to Olaparib treatment. Inhibition of EGFR by Gefitinib suppressed growth of OlapR cells and improved Olaparib sensitivity, thereby phenocopying IGFBP3 inhibition. Collectively, our results highlight IGFBP3 and EGFR as critical mediators of Olaparib resistance.

Potential agnostic role of BRCA alterations in patients with several solid tumors: One for all, all for one?

Germline BRCA1/2 alterations in the Homologous Recombination (HR) pathway are considered as main susceptibility biomarkers to Hereditary Breast and Ovarian Cancers (HBOC). The modern molecular biology technologies allowed to characterize germline and somatic BRCA1/2 alterations in several malignancies, broadening the landscape of BRCA1/2-alterated tumors. In the last years, BRCA genetic testing, beyond the preventive value, also assumed a predictive and prognostic significance for patient management. The approval of molecules with agnostic indication is leading to a new clinical model, defined "mutational". Among these drugs, the Poly (ADP)-Ribose Polymerase inhibitors (PARPi) for BRCA1/2-deficient tumors were widely studied leading to increasing therapeutic implications. In this Review we provided an overview of the main clinical studies describing the association between BRCA-mutated tumors and PARPi response, focusing on the controversial evidence about the potential agnostic indication based on BRCA1/2 alterations in several solid tumors.

Prediction of homologous recombination deficiency from cancer gene expression data

Objective

Homologous recombination deficiency (HRD) is the main mechanism of tumorigenesis in some cancers. HRD causes abnormal double-strand break repair, resulting in genomic scars. Some scoring HRD tests have been approved as companion diagnostics of polyadenosine diphosphate-ribose polymerase (PARP) inhibitor treatment. This study aimed to build an HRD prediction model using gene expression data from various cancer types.

Methods

The cancer genome atlas data were used for HRD prediction modeling. A total of 10,567 cases of 33 cancer types were included, and expression data from 5128 out of 20,502 genes were included as predictors. A penalized logistic regression model was chosen as a modeling technique.

Results

The area under the curve of the receiver operating characteristic curve of HRD status prediction was 0.98 for the training set and 0.93 for the test set. The accuracy of HRD status prediction was 0.93 for the training set and 0.88 for the test set.

Conclusions

Our study suggests that the HRD prediction model based on penalized logistic regression using gene expression data can be used to select patients for treatment with PARP inhibitors.

Clinical implications of homologous recombination repair mutations in prostate cancer

Prostate cancer is a disease with significant interpatient genomics, with a proportion of patients presenting mutations in key homologous recombination repair (HRR) gene aberrations, particularly in late-stage disease. A better understanding of the genomic landscape of prostate cancer and the prognostic and predictive value of HRR mutations could lead to more precise care for prostate cancer patients. BRCA1/2 mutations are associated with a more aggressive disease course and higher risk of developing lethal prostate cancer, but also identify patients who could benefit from directed therapeutic strategies with PARP inhibitors. Other HRR mutations are also frequent but their prognostic and predictive value for prostate cancer patients is less clear. Moreover, a proportion of these mutations are associated with inherited germline defects, being relevant for the patients' risk of second malignancies but also to inform their relatives' risk of cancer through cascade testing. In this manuscript, we review current knowledge of the prognostic and predictive value for different HHR alterations across the different prostate cancer disease states. Additionally, we assess the challenges to implement genomic testing in clinical practice for prostate cancer patients.

Harnessing Synthetic Lethal Interactions for Personalized Medicine

Two genes are said to have synthetic lethal (SL) interactions if the simultaneous mutations in a cell lead to lethality, but each individual mutation does not. Targeting SL partners of mutated cancer genes can kill cancer cells but leave normal cells intact. The applicability of translating this concept into clinics has been demonstrated by three drugs that have been approved by the FDA to target PARP for tumors bearing mutations in BRCA1/2. This article reviews applications of the SL concept to translational cancer medicine over the past five years. Topics are (1) exploiting the SL concept for drug combinations to circumvent tumor resistance, (2) using synthetic lethality to identify prognostic and predictive biomarkers, (3) applying SL interactions to stratify patients for targeted and immunotherapy, and (4) discussions on challenges and future directions.