Functional Homologous Recombination (HR) Screening Shows the Majority of -Mutant Breast and Ovarian Cancer Cell Lines Are HR-Proficient.

Tumors with a pathogenic mutation are homologous recombination (HR)-deficient (HRD) and consequently sensitive to platinum-based chemotherapy and Poly-[ADP-Ribose]-Polymerase inhibitors (PARPi). We hypothesized that functional HR status better reflects real-time HR status than mutation status. Therefore, we determined the functional HR status of 53 breast cancer (BC) and 38 ovarian cancer (OC) cell lines by measuring the formation of RAD51 foci after irradiation.

Proof-of-concept study linking ex vivo sensitivity testing to neoadjuvant anthracycline-based chemotherapy response in breast cancer patients.

We developed a functional ex vivo anthracycline-based sensitivity test. Surgical resection material of primary breast cancer (BC) was used to determine criteria for the ex vivo sensitivity assay based on morphology, proliferation and apoptosis. Subsequently, a proof-of-concept study was performed correlating results of this assay on primary BC biopsies with in vivo response after treatment with anthracycline-containing neoadjuvant chemotherapy (NAC).

Functional RECAP (REpair CAPacity) assay identifies homologous recombination deficiency undetected by DNA-based BRCAness tests.

Germline BRCA1/2 mutation status is predictive for response to Poly-[ADP-Ribose]-Polymerase (PARP) inhibitors in breast cancer (BC) patients. However, non-germline BRCA1/2 mutated and homologous recombination repair deficient (HRD) tumors are likely also PARP-inhibitor sensitive. Clinical validity and utility of various HRD biomarkers are under investigation.

Functional Ex Vivo Tissue-Based Chemotherapy Sensitivity Testing for Breast Cancer.

Unlabelled: Background chemotherapy is part of most breast cancer (BC) treatment schedules. However, a substantial fraction of BC tumors does not respond to the treatment. Unfortunately, no standard biomarkers exist for response prediction.

Direct Ex Vivo Observation of Homologous Recombination Defect Reversal After DNA-Damaging Chemotherapy in Patients With Metastatic Breast Cancer.

Purpose: Biomarkers that predict response to poly (ADP-ribose) polymerase inhibitors (PARPis) are required to detect PARPi sensitivity beyond germline -mutated (gBRCAm) cancers and PARPi resistance among reverted gBRCAm cancers. Therefore, we previously developed the Repair Capacity (RECAP) test, a functional homologous recombination (HR) assay that exploits the formation of RAD51 foci in proliferating cells after ex vivo irradiation of fresh primary breast cancer tissue. The aim of the current study was to validate the feasibility of this test on histologic biopsy specimens from metastatic breast cancer and to explore the utility of the RECAP test as a predictive tool for treatment with DNA-damaging agents, such as PARPis.

Ex vivo treatment of prostate tumor tissue recapitulates in vivo therapy response.

Background: In vitro models of prostate cancer (PCa) are not always reliable to evaluate anticancer treatment efficacy. This limitation may be overcome by using viable tumor slice material. Here we report on the establishment of an optimized ex vivo method to culture tissue slices from patient-derived xenografts (PDX) of prostate cancer (PCa), to assess responses to PCa treatments.

Functional Assay Reveals Homologous Recombination Deficiency in Breast Cancer Beyond BRCA Gene Defects.

Purpose: Tumors of germline mutated carriers show homologous recombination (HR) deficiency (HRD), resulting in impaired DNA double-strand break (DSB) repair and high sensitivity to PARP inhibitors. Although this therapy is expected to be effective beyond germline mutated carriers, a robust validated test to detect HRD tumors is lacking. In this study, we therefore evaluated a functional HR assay exploiting the formation of RAD51 foci in proliferating cells after irradiation of fresh breast cancer tissue: the recombination REpair CAPacity (RECAP) test.

tumor culture systems for functional drug testing and therapy response prediction.

Optimal patient stratification is of utmost importance in the era of personalized medicine. Prediction of individual treatment responses by functional assays requires model systems derived from viable tumor samples, which should closely resemble tumor characteristics and microenvironment. This review discusses a broad spectrum of model systems, ranging from classic 2D monolayer culture techniques to more experimental 'cancer-on-chip' procedures.