PURPOSE Olaparib, a poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi), is approved for the treatment of human epidermal growth factor receptor 2 (HER2)–negative metastatic breast cancer (MBC) in germline (g) BRCA1/ 2 mutation carriers. Olaparib Expanded, an investigator-initiated, phase II study, assessed olaparib response in patients with MBC with somatic (s) BRCA1/ 2 mutations or g/s mutations in homologous recombination (HR)–related genes other than BRCA1/2. METHODS Eligible patients had MBC with measurable disease and germline mutations in non- BRCA1/ 2 HR-related genes (cohort 1) or somatic mutations in these genes or BRCA1/ 2 (cohort 2). Prior PARPi, platinum-refractory disease, or progression on more than two chemotherapy regimens (metastatic setting) was not allowed. Patients received olaparib 300 mg orally twice a day until progression. A single-arm, two-stage design was used. The primary endpoint was objective response rate (ORR); the null hypothesis (≤ 5% ORR) would be rejected within each cohort if there were four or more responses in 27 patients. Secondary endpoints included clinical benefit rate and progression-free survival (PFS). RESULTS Fifty-four patients enrolled. Seventy-six percent had estrogen receptor–positive HER2-negative disease. Eighty-seven percent had mutations in PALB2, s BRCA1/ 2, ATM, or CHEK2. In cohort 1, ORR was 33% (90% CI, 19% to 51%) and in cohort 2, 31% (90% CI, 15% to 49%). Confirmed responses were seen only with g PALB2 (ORR, 82%) and s BRCA1/ 2 (ORR, 50%) mutations. Median PFS was 13.3 months (90% CI, 12 months to not available/computable [NA]) for g PALB2 and 6.3 months (90% CI, 4.4 months to NA) for s BRCA1/ 2 mutation carriers. No responses were observed with ATM or CHEK2 mutations alone. CONCLUSION PARP inhibition is an effective treatment for patients with MBC and g PALB2 or s BRCA1/ 2 mutations, significantly expanding the population of patients with breast cancer likely to benefit from PARPi beyond g BRCA1/ 2 mutation carriers. These results emphasize the value of molecular characterization for treatment decisions in MBC.

During the coronavirus disease 2019 (COVID-19) outbreak in China, fear about COVID-19, together with worry about progression of cancer, caused strong emotional stress in patients with cancer. We evaluated patientreported outcome in 658 patients with breast cancer (BC) and survivors recruited from multiple BC centers in Hubei Province using 4 standardized assessment scales. Multivariable logistic regression analysis was used to identify potential affecting factors on mental health outcomes. High rates of anxiety, depression, distress, and insomnia were observed in patients with BC during the COVID-19 outbreak. Based on our results, living in Wuhan, poor general condition by self-identification, shorter duration after BC diagnosis, aggressive BC molecular subtypes, metastatic BC clinical stage, treatment discontinuation, central venous catheter flushing delay, or close contact with patients with COVID-19 are associated risk factors for poorer psychological status. Special attention should be paid to the psychological status of patients with BC, especially those with poor general condition, treatment discontinuation, aggressive molecular subtypes, and metastatic BC. Introduction: We aimed to analyze the psychological status in patients with breast cancer (BC) in the epicenter of the coronavirus disease 2019 (COVID-19) pandemic. Patients and Methods: A total of 658 individuals were recruited from multiple BC centers in Hubei Province. Online questionnaires were conducted, and these included demographic information, clinical features, and 4 patient-reported outcome scales (Generalized Anxiety Disorder Questionnaire [GAD-7], Patient Health Questionnaire [PHQ-9], Insomnia Severity Index [ISI], and Impact of Events Scale-Revised [IES-R]). Multivariable logistic regression analysis was designed to identify potential factors on mental health outcomes. Results: Questionnaires were collected from February 16, 2020 to February 19, 2020, the peak time point of the COVID-19 outbreak in China. Of patients with BC, 46.2% had to modify planned necessary anti-cancer treatment during the outbreak. Severe anxiety and severe depression were reported by 8.9% and 9.3% of patients, respectively.

While identifying genomic alterations in tumor tissue is the current gold-standard technique for molecular profiling, circulating tumor DNA (ctDNA) represents a noninvasive method of assessing genomic alterations using peripheral blood. The concordance of genomic alterations between two commercially available ctDNA and tissue biopsies was compared in 45 patients with breast cancer using paired next-generation sequencing tissue and ctDNA biopsies. Across all genes, concordance between the two platforms was 91.0% to 94.2%. When only considering genomic alterations in either assay (e.g., excluding wild type/wild type genes), concordance was 10.8% to 15.1% with full plus partial concordance of 13.8% to 19.3%. Concordant mutations were associated with significantly higher variant allele frequency. Over half of mutations detected in either technique were not detected using the other biopsy technique. Including variants of unknown significance, the average number of alterations per patient was significantly higher for tissue (4.56) compared with ctDNA (2.16). When eliminating alterations not detectable in the ctDNA assay, mean number of alterations for tissue and ctDNA was similar (2.67 for tissue, 2.16 for ctDNA). Across five representative genes (TP53, PIK3CA, ERBB2, BRCA1, and BRCA2), sensitivity and specificity were 35.7% and 95.0%, respectively. Concordance when genomic alterations was detected in either tissue or ctDNA was low with each technique detecting a significant amount of nonoverlapping mutations. Potential explanations for the lack of concordance include tumor heterogeneity, different sequencing techniques, spatial and temporal factors, and potential germline DNA contamination. The study indicates that both tissue and blood-based NGS may be necessary to describe the complex biology of breast cancer.

The low response rate of immune checkpoint blockade in breast cancer has highlighted the need for predictive biomarkers to identify responders. While a number of clinical trials are ongoing, testing all possible combinations is not feasible. In this study, a quantitative systems pharmacology model is built to integrate immune–cancer cell interactions in patients with breast cancer, including central, peripheral, tumour-draining lymph node (TDLN) and tumour compartments. The model can describe the immune suppression and evasion in both TDLN and the tumour microenvironment due to checkpoint expression, and mimic the tumour response to checkpoint blockade therapy. We investigate the relationship between the tumour response to checkpoint blockade therapy and composite tumour burden, PD-L1 expression and antigen intensity, including their individual and combined effects on the immune system, using model-based simulations. The proposed model demonstrates the potential to make predictions of tumour response of individual patients given sufficient clinical measurements, and provides a platform that can be further adapted to other types of immunotherapy and their combination with molecular-targeted therapies. The patient predictions demonstrate how this systems pharmacology model can be used to individualize immunotherapy treatments. When appropriately validated, these approaches may contribute to optimization of breast cancer treatment.