Batalini, Felipe

225 Background: HR deficient (HRD) CRC has improved outcomes following exposure to DNA damaging agent (DDA) (irinotecan, IR; oxaliplatin, OX) compared to HRP CRC. Low expression of wild type (WT) BRCA1 mRNA is associated with prolonged OS in ovarian cancer; however, this finding has not been investigated in CRC or outside of BRCA. Here, we examine the effect of low expression of HR genes in HRP CRC on post-DDA survival. Methods: 12,860 CRC samples were analyzed by NGS (592, NextSeq; WES, NovaSeq) and WTS (NovaSeq) at Caris Life Sciences (Phoenix, AZ). Samples were classified by RNA expression percentiles. Real world OS was extracted from insurance claims and calculated using Kaplan-Meier estimates for molecularly defined cohorts from first of OX or IR to last contact. Results: Post-IR survival was prolonged with low expression of ATM, CHEK2 and PALB2 in WT ATM, PALB2, and CHEK2 WT CRC, respectively (bottom vs. top 10%, bottom vs. top 25%; p<0.05). Notably, low PALB2 expression (bottom 10%) showed a 14.5-month post-IR benefit compared to high PALB2 expression (top 10%) in WT PALB2 CRC (p=0.003). Post-OX survival was not significantly prolonged with low expression of CHEK2 in WT CHEK2 CRC (bottom 10% vs top 10%, bottom 25% vs top 25%) but was with low expression of ATM (+9.7 months, p=0.02) and PALB2 (+5.6 months, p=0.03) in WT ATM and PALB2 CRC, respectively (all bottom 25% vs top 25%). Conclusions: Here we report the first findings to suggest a novel subclass of CRC defined as the low expression of mRNA of non-mutated HRD genes that exhibit sensitivity to DDA. Low expression of WT ATM, CHEK2, and PALB2 correlates with prolonged OS following IR, post-OX survival was prolonged with low expression of ATM and PALB2. Further characterization defining sensitivity of low expressing HRP genes to DDA may help guide treatment considerations in HRP CRC. [Table: see text]

Abstract Purpose Accurately predicting the clinical breast cancer subtypes could be extremely helpful for radiologists, pathologists, surgeons, and clinicians and inform future treatment prediction algorithms. Therefore, we evaluate and compare the accuracy of radiomic features extracted from contrast enhanced mammography (CEM) and magnetic resonance imaging (MRI) scans to make predictions to subtypes of breast cancer. Methods This HIPAA-compliant prospective single institution study was approved by the local institutional review board with written informed consent. Women with breast tumors 2 cm or larger underwent dynamic contrast-enhanced MRI and/or CEM for surgical staging. Semi-manual regions of interest were drawn by radiologist using Cancer Imaging Phenomics Toolkit (CaPTk). Radiomic features were obtained using PyRadiomics and MR- and CEM- based classification models were built on a low-dimensional representation of the features obtained via kernel principal component analysis. We subscribed to an ensemble tree-based learning approach called extremely randomized trees (ERT) to predict cancer subtypes captured via immunohistochemistry markers. Results For MRI analysis, 124 women with newly diagnosed breast cancer were included in the analysis comprising 49 HR+HER2-, 37 HR+HER2+, 11 HR-HER2+, and 27 HR-HER2- cases. For CEM analysis, models were built using data from 170 female patients including 74 HR+HER2-, 41 HR+HER2+, 14 HR-HER2+, and 43 HR-HER2-. CEM based model resulted in accuracies of 55%, 72%, 88%, and 71% respectively for HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2- whereas MRI based model alone led to accuracies of 54%, 62%, 89%, and 76% respectively for HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-. Conclusions Radiomic features extracted from CEM and MR were strong predictors of breast cancer subtypes with CEM-based radiomic features performing slightly better, though not statistically significantly better (p = 0.82), than its MRI counterpart.

Poly-adenosine diphosphate ribose polymerase (PARP) inhibitors (PARPi) are approved for BRCA1/2 carriers with HER2-negative breast cancer in the adjuvant setting with a high risk of recurrence as well as the metastatic setting. However, the indications for PARPi are broader for patients with other cancer types (e.g., prostate and ovarian cancer), involving additional biomarkers (e.g., ATM, PALB2, and CHEK) and genomic instability scores. Herein, we summarize the data on PARPi and breast cancer and discuss their use beyond BRCA carriers.

e17615 Background: Germline BRCA1/2 mutations are associated with response to Poly(ADP-ribose) polymerase inhibitors (PARPi). In addition to BRCA1/2 mutations, there are other Homologous Recombinations Deficiency (HRD) biomarker candidates already available in clinical practice including genome-wide loss-of-heterozygosity (gLOH) and myChoice score. Inconsistencies in biomarkers used in clinical trials with PARPi are a challenge to clinical interpretation. This study aims to compare clinically available HRD biomarkers in terms of benefits from PARPi. Methods: We performed database search for phase II or III randomized clinical trials comparing PARPi versus chemotherapy, and meta-analysis using generic inverse variance and a random-effects model. Patients were classified into three categories according to their HRD status: 1) BRCAmut (patients with BRCA1/2 mutation of germline or somatic origin), 2) non-BRCA HRD (patients BRCA wild-type (wt) with a different HRD biomarker - gLOH or myChoice); and 3) homologous recombination proficiency (HRP) (BRCAwt and without HRD biomarkers). From those that were BRCAwt, we compared myChoice+ with gLOH-high. Results: Eight studies (n = 4372 patients) with PARPi as first-line and recurrence settings were included. BRCAmut had PFS HR 0.29 (95%CI, 0.24-0.35), BRCAwt & HRD 0.43 (95%CI, 0.34-0.53) and HRP 0.74 (95%CI, 0.62-0.89). In a secondary analysis by HRD stratification method, patients with BRCAwt & myChoice > = 42 had PFS HR 0.43 (95%CI, 0.34-0.56), similar to patients with BRCAwt & gLOH-high with PFS HR 0.42 (95%CI, 0.28-0.62). Conclusions: Patients with BRCA mutations benefited the most from PARPi. From patients with BRCA1/2 wild-type, a similar benefit was found in patients with gLOH-high and those myChoice+, which was superior to HRP patients. The clinical development of further HRD biomarkers (i.e. Sig3, HRDetect) may help identify more patients who benefit from PARPi.

A woman in her 50s previously treated for early-stage breast cancer, parotid mucoepidermoid carcinoma and Caroli’s disease was diagnosed with stage IV pancreatic ductal adenocarcinoma (PDAC) metastatic to the liver and was found to harbour a BRCA1 germline mutation. She had palliative chemotherapy, initially with 5-fluorouracil, leucovorin, irinotecan and oxaliplatin, and then FOLFIRI and capecitabine, achieving a sustained near-complete response for at least 86 months. Chemotherapy was eventually discontinued when she was diagnosed with a tongue squamous cell carcinoma. Despite withholding systemic therapy, she has maintained a durable response. This is the first report in the English literature showing a sustained duration of response in a patient with PDAC and BRCA1 germline mutation.

Approximately 5% to 10% of women diagnosed with breast cancer will have a pathogenic variant (PV) in a hereditary cancer susceptibility gene, and this has significant implications for the management of these patients and their relatives. Despite the benefits of genetic testing, many eligible patients with breast cancer never undergo testing because of various barriers, including complicated testing criteria such as those from the National Comprehensive Cancer Network (NCCN). In 2019, the American Society of Breast Surgeons (ASBrS) proposed germline genetic testing for all patients with breast cancer to increase the identification of PV carriers. In 2020, a Mayo Clinic study highlighted the limitations of these 2 genetic testing guidelines (NCCN and ASBrS) and proposed a hybrid approach of testing all women diagnosed with breast cancer by the age of 65 years and using NCCN criteria for older patients. This commentary presents an updated analysis of the Mayo Clinic data and discusses the rationale for using the age of 60 years rather than 65 years as the cutoff for this hybrid approach. Using an age at diagnosis of ≤60 or ≤65 years for the universal testing of patients with breast cancer detected more PVs (11.9% [16 of 134] and 15.7% [21 of 134], respectively) in comparison with using the NCCN criteria. Lowering the age for universal testing from 65 to 60 years maintained the sensitivity of detecting a PV at >90% while sparing testing for an additional 10% of women. Compared with the testing of all patients, the hybrid approach would allow 31% of all women with breast cancer to forgo testing and result in fewer variants of uncertain significance identified and, therefore, would decrease the chance of harm from misinterpretation of these variants.