Background: The risks for cancers other than breast (BC) or ovarian (OC) cancer in breast cancer gene 1 and 2 (BRCA1/2) mutation carriers were elevated in studies of carrier families. However, case-control studies did not confirm this observation. Objective: To compare the risks for other cancers in BRCA1/2 mutation carriers and non-carriers, all affected with BC and/or OC. Both groups share risk modifiers of BC/OC, which enabled assessment of the role of BRCA1/2 mutations. Methods: 1098 Ashkenazi Jewish women affected with BC and/or OC were ascertained during 1995-2003; molecular testing revealed 229 BRCA1 and 100 BRCA2 carriers and 769 non-carriers. COX proportional hazard models were used to evaluate the risk of other cancers. Analyses were conducted including all other cancers or only those diagnosed after BC/ OC diagnosis. Results: The HRs for any other cancer were 2.6 (95% CI 1.7 to 4.2, p,0.001) and 1.8 (95% CI 0.95 to 3.6, p = 0.07) in BRCA1 and BRCA2 carriers, respectively. The corresponding colon cancer HRs were 3.9 (95% CI 1.3 to 12.1, p = 0.02) and 2.3 (95% CI 0.5 to 11.3, p = 0.3) in BRCA1 and BRCA2 carriers. The HR for lymphoma was 11.9 (95% CI 3.1 to 46.2, p = 0.001) in BRCA2 carriers. Risk estimates for other cancers after the onset of BC/OC were similar. Conclusion: A 2.5-fold increase in any other cancer and a fourfold risk of colon cancer were found among BRCA1 carriers. The corresponding HRs in BRCA2 carriers were nonsignificant, except for the markedly elevated risk of lymphoma. These results suggest a role for BRCA1/2 mutations in colorectal cancer risk in a subgroup of BC/OC-affected carriers.

Objectives ALK inhibitors (ALKi) are the standard-of-care treatment for metastatic ALK-rearranged non-small cell lung cancer (NSCLC) in the first- and second-line setting. We conducted a real-world multi-institutional analysis, aiming to compare the efficacy of third-line ALKi versus chemotherapy in these patients. Methods Consecutive ALK-positive metastatic NSCLC patients treated with at least one ALKi were identified in the working databases of 7 Israeli oncology centers (the full cohort). Demographic and clinical data were collected. Patients receiving any systemic treatment beyond 2 ALKi comprised the third-line cohort, whether a third ALKi (group A) or chemotherapy (group B). Groups A and B were compared in terms of overall survival (OS) and time-to-next-treatment line (TNT). Results At a median follow-up of 41 months (95% confidence interval [CI]: 32-55), 80 (47.1%) have died. Median OS (mOS) in the full cohort (n = 170) was 52 months (95% CI: 32-65). Number of ALKi (hazard ratio [HR] 0.765; 95% CI: 0.61-0.95; P = .024) and age (HR 1.02, 95% CI: 1.01-1.04, P = .009) significantly associated with OS in the full cohort. The third-line cohort included 40 patients, of which 27 were treated with third ALKi (group A) and 13 treated with chemotherapy (group B). mOS from third-line initiation was 27 months in group A (95% CI: 13-NR) and 13 months for group B (95% CI: 3-NR); the difference was not significant (NS; P = .12). Chemotherapy as first line (HR 0.17, 95% CI: 0.05-0.52, P = .002) and a higher number of ALKi (HR 0.38, 95% CI: 0.20-0.86, P = .011) associated significantly with longer OS of the third-line cohort. TNT was 10 months for group A (95% CI: 5-19) and 3 months for group B (95% CI: 0-NR); the difference was NS (P = .079). Conclusion We report mature real-world data of more than 4-year mOS in ALK-positive patients. The number of ALKi given was associated with a better outcome. OS and TNT demonstrated a statistically nonsignificant trend for a better outcome in patients receiving a third-line ALKi.

Precision cancer therapy has the potential to revolutionize treatment outcome. While genomic analysis has become central to cancer personalized medicine, recent studies have not shown that it drastically improves patient survival as compared to standard drug selection. Additionally, genomic mutations may suggest several treatment protocols without elucidating which approach will yield the best clinical response. Moreover, for many drugs no genetic predictive biomarkers are available. To advance cancer precision diagnostics, we have developed cResponse, a functional drug sensitivity platform to determine individualized patient treatment regimens. Fresh patient cancer samples are taken by biopsy or resection and sectioned into 300 uM slices which when cultured in the cResponse platform demonstrate similar architecture and tissue proliferation to those found in vivo. We show that cResponse is able to preserve human cancer tissue in 3D together with its microenvironment, including endothelial and immune cells, at a high viability (>90%) with continued cell division for 7 days in over twenty types of solids tumors. Importantly, the high viability of the tissue over an extended period of time allows for a rapid genomic profiling to help prioritize drugs to be tested by cResponse, as well as the capacity to evaluate the effects of slow acting drugs such as targeted therapy. To validate the capacity of the cResponse platform to predict patient response to cancer treatment, forty two patients with different cancer types receiving diverse chemotherapeutic and targeted agents were recruited to the study and their tumors were tested using cResponse prior to initiation of treatment. Cancer types included bladder, pancreatic, lung, colorectal, breast and sarcoma. After five days of treatment ex-vivo, the samples were fixed and designated a viability score (ranging from 0 to 100) based on an algorithm composed of a panel of histological and morphological markers. The cResponse score was compared to the clinical response to treatment of 27 patients for which this data is already available. The results demonstrated that cResponse could predict the patient's response with a specificity of 82% (9/11) and a sensitivity of 93.75% (15/16) when compared to the patient's imaging results. In the future, the integration of this platform in directing anti-cancer treatment may lead to better response rate of cancer patients to therapy. Citation Format: Seth Salpeter, Vered Bar, Sara Aharon, Luba Torovsky, Adi Zundelevich, Hamutal Shachar, Hagit Shapira, Nancy Gavert, Ravid Straussman, Shay Golan, Eli Rosenbaum, Talia Golan, Raanan Berger, Zohar Dotan, Dan Leibovici, Shani Breuer, Yakir Rotenberg, Aviad Zick, Ayala Hubert, Hovav Nechushtan, Guy Neev. A clinical trial of cResponse, a functional assay for cancer precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT209.

of ALK-positive non-small cell lung cancer (NCSLC). However, head-tohead comparisons between most available ALK inhibitors are lacking. The objective of this study was to conduct a systematic literature review (SLR) and meta-analyses to estimate the relative efficacy of brigatinib compared to other approved ALK inhibitors or chemotherapy in patients with locally advanced or metastatic ALK inhibitornaïve ALK-positive NSCLC (1 prior chemotherapy regimen was allowed). Methods: An SLR was conducted following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Searches (from inception to August 1, 2019) were performed in MEDLINE, Embase, the Cochrane Library and key conference proceedings (2016)(2017)(2018)(2019) to identify relevant phase II or III randomized controlled trials (RCTs) in ALK inhibitor-naïve ALK-positive NSCLC patients. Bayesian network meta-analyses (NMAs) and Bucher indirect treatment comparisons (ITCs) were performed using fixed and random effects models to assess the comparative efficacy and safety of brigatinib with other ALK inhibitors or chemotherapy as 1L treatment. Results: The SLR identified 8 RCTs assessing alectinib, brigatinib, ceritinib, crizotinib, and chemotherapy in the 1L setting, of which 5 global trials (ALEX, ALTA-1L, ASCEND-4, PROFILE 1007, PROFILE 1014) were included. The base-case, fixed effects results demonstrated that brigatinib significantly reduced the risk of disease progression or death (independent review committee [IRC]-assessed progression-free survival [PFS]) compared with ceritinib (HR, 0.42; 95% confidence interval [CI], 0.26-0.67), crizotinib (HR, 0.49; 95% CI, 0.35-0.68), and chemotherapy (HR, 0.23; 95% CI, 0.16-0.34). No significant differences were observed between brigatinib and alectinib in IRC-assessed (HR, 0.98; 95% CI, 0.61-1.57) or investigator-assessed PFS (HR, 1.01; 95% CI, 0.64-1.58) for overall patients, and in investigator-assessed PFS (HR, 0.63 95% CI, 0.28-1.42) for the subgroup with baseline CNS metastases. There were also no significant differences between brigatinib and all comparators for overall survival. Subgroup analyses of patients who had not received prior chemotherapy yielded similar results (Table 1). Conclusion:Brigatinib significantly prolonged PFS in ALK inhibitornaïve patients with ALK-positive NSCLC compared with ceritinib, crizotinib, and chemotherapy and was at least as effective as alectinib in reducing the risk of progression, suggesting that brigatinib is an effective 1L treatment. The results also suggest strong efficacy of brigatinib in patients with CNS metastases.

Background: Dual inhibition of epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) pathways have demonstrated promising results for treatment of advanced non-small cell lung cancer (NSCLC). We conducted a systematic review and meta-analysis to assess the efficacy and toxicity of combined treatment with EGFR tyrosine kinase inhibitors (TKIs) and VEGF monoclonal antibodies for patients harboring activating EGFR mutations.Methods: The electronic databases PubMed, Cochrane and EMBASE were searched for relevant randomized trials between 2000 and 2019. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Secondary endpoints included objective response rate (ORR), disease control rate (DCR), and grade 3 or higher adverse events (AEs). Pooled hazard ratios (HR) for OS and PFS and odds ratios (OR) for ORR, DCR and toxicity were meta-analyzed using the generic inverse variance and the Mantel-Haenszel methods. Random-effect models were used to compute pooled estimates. Subgroup analyses compared PFS by gender, age, smoking status, type of EGFR mutation, intracranial disease and ECOG performance status.