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Background: Hereditary factors play a key role in the risk of developing breast cancers. Identification of a germline predisposition can have important implications for treatment decisions, risk-reducing interventions, cancer screening, and testing for family members. Aim: To determine the prevalence of pathogenic or likely pathogenic germline mutations (P/LP) using a “universal” testing approach and uptake of no-cost cascade family testing in patients with breast cancer. Methods: We undertook a prospective multi-site study of germline genetic alterations among breast cancer patients receiving care at Mayo Clinic cancer centers in Rochester, MN; Eau Claire, WI; Jacksonville, FL and Phoenix, AZ between April 1, 2018 and March 31, 2020. Patients with a new or active breast cancer diagnosis (all stages) irrespective of cancer family history were tested with a >80-gene next generation sequencing panel.Results: Of 390 patients, the median age was 58 years (SD 12.3), 1% were male, 85% were white and 28% had advanced (stage 3-4) disease. P/LP were found in 12.1% (n=47) of patients, including 29 in moderate and high penetrance cancer susceptibility genes. 13 (3.3%) patients had mutations in BRCA1 or 2, while 33 (8.4%) had mutations in BRCAness (ATM, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CHEK2, NBN, PALB2, RAD50, RAD51C, RAD51D, WRN) associated genes. Of the P/LP findings the most frequent aberrations were in BRCA2 (13.5%), BRCA1 (11.5%), CHEK2 (11.5%), MUTYH (11.5%), and WRN (9.6%). Variants of uncertain significance were found in 209 (53.6%) including 26 (6.6%) with concurrent P/LP and VUS. 37 (9.4%) patients had mutations associated with published management recommendations, precision therapies and/or clinical trial eligibility. 10 (2.6%) patients had P/LP that would not have met current screening guidelines, including 4 with moderate or high penetrance mutations. Patients with younger age of diagnosis were less likely than patients with older age of diagnosis to have a P/LP mutation (OR= 0.47, 95%CI: 0.25-0.90 p = 0.020). Only 10 (21%) patients with P/LP had family members undergo familial site- specific testing at no cost.Conclusions: In this prospective multi-center study of unselected breast cancer patients, universal multi-gene panel testing found that 1 in 8 patients harbor P/LP germline variants. Current guidelines were able to identify the majority of patients with P/LP mutations. Familial site specific testing is greatly under-utilized even when cost is not a barrier. Multigene panels impact cancer patient care by identifying precision medicine treatment interventions, and guiding long-term medical management and preventive surveillance. Citation Format: Brenda Ernst, Natalie Ertz-Archambault, Deborah J Rhodes, Donald W Northfelt, Myra Wick, Douglas L Riegert-Johnson, Scott Okuno, Katie Kunze, Michael Golafshar, Cindy M Azevedo, PLS Uson Junior, ED Esplin, Robert Nussbaum, Margaret Klint, Sarah Mantia, Megan Hager, Keith Stewart, Niloy Jewel Samadder. Universal genetic testing in breast cancer patients: A multi-center prospective study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD10-05.

BACKGROUND –: Unrelieved chemotherapy-induced nausea (CIN) is a significant problem for patients with breast cancer (BC). OBJECTIVE -: In a sample of patients with BC who were assessed prior to their second or third cycle of chemotherapy, study purposes were to: evaluate for the occurrence, severity, frequency, and distress associated with CIN; evaluate for differences in demographic and clinical characteristics and gastrointestinal (GI) symptom occurrence rates between patients who did and did not report CIN, and determine which demographic, clinical, and symptom characteristics were associated with the occurrence of CIN. METHODS -: Patients completed demographic, clinical questionnaires and Memorial Symptom Assessment Scale for nausea and common GI symptom assessments. Univariate analyses evaluated for differences in demographic and clinical characteristics and GI symptom occurrence between patients who did and did not report CIN. Multiple logistic regression analysis evaluated for characteristics associated with CIN. RESULTS -: Of the 532 patients with BC, 47.2% reported CIN occurrence. Characteristics associated with CIN group membership were: poorer functional status, receipt of chemotherapy on a 14-day cycle, higher occurrence rates of five GI symptoms (i.e., dry mouth, vomiting, constipation, change in the way food tastes, and lack of appetite (all p

Background Survivors of ER-expressing operable breast cancer (ER+BC) generally do not receive hormone replacement therapy for menopausal symptoms due to concern about provoking recurrence of disease. Single dose depomedroxyprogesterone acetate (MPA) 400 mg IM has previously been shown (Loprinzi CL, et al. J Clin Oncol 2006;24:1409) to be the most effective non-estrogen therapy available for menopausal hot flashes (HF) but long-term evidence of safety in survivors of ER+BC is lacking. Methods Consecutive patients previously diagnosed with ER+BC who received MPA for HF between January 2007 and December 2012 were retrospectively identified in the breast cancer patient database at Mayo Clinic Arizona. Medical records were audited for breast cancer outcomes in these cases and in contemporaneous control patients with ER+BC who did not receive MPA, matched for age, stage of disease, and year of diagnosis. Statistical comparisons of local-regional recurrence and event-free survival were performed. Results 92 patients who received MPA were identified and matched 1:1 with contemporaneous controls. Median follow-up duration was 5.7 years in cases and 4.5 years in controls. Estimated local-regional recurrence free survival at 10 years was 85% (95% CI, 72-100%) in cases and 95% (95% CI, 86-100%) in controls. Matched pairs hazard ratio was 1.0 (95% CI, 0.06-16.0) for local-regional recurrence free survival. Estimated event-free survival at 10 years was 81% (95% CI, 69-97%) in cases and 76% (95% CI, 64-92%) in controls. Matched pairs hazard ratio was 0.38 (95% CI, 0.10-1.41) for event-free survival. The majority (77%) of case patients experienced satisfactory relief of hot flashes from MPA injection. Conclusion In this retrospective case-control study we were unable to identify a detrimental effect of MPA therapy for HF in survivors of ER+BC. MPA may be acceptable for management of HF in this population. Citation Format: Ertz-Archambault N, Rogoff L, Kosiorek H, Ernst B, Anderson K, Pockaj B, Gray R, Northfelt D. Depomedroxyprogesterone therapy for hot flashes in survivors of ER-expressing breast cancer: Impact on recurrence and survival [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-11-13.

Background and objectives Neoadjuvant endocrine therapy (NET) for ER+ breast cancer can downstage primary tumors. We evaluated NET efficacy in node-positive patients. Methods Node-positive patients undergoing NET for ER+ breast cancer from 2012 to 2019 were reviewed. Primary endpoints included rates of axillary lymphadenectomy (ALND), pathologic complete response (pCR), and final nodal staging. Results Thirty-nine patients were included. Before NET, all were clinically node-positive (cN1 = 36, 94%; cN2 = 2, 5%; cN3 = 1, 3%; Stage II = 23, 59%, Stage III = 16, 41%). After NET, nine (23%) had clinically persistent axillary disease necessitating ALND. The remaining 30 (77%) underwent sentinel lymph node biopsy (SLNB). Of these, 25 (83%) were SLNB+ on frozen section, undergoing immediate ALND. Five patients were negative on frozen section: one had a confirmed axillary pCR, and four had residual nodal disease on permanent pathology. One underwent delayed ALND, and for the remaining three patients, decision was made to forgo ALND. Final overall axillary staging was: N0 (pCR) = 1, 3%, pN1mic = 1, 3%, pN1 = 20, 51%, pN2 = 12, 30%, pN3 = 5, 13%; Stage II = 16, 41%, Stage III = 23, 59%. Conclusions While NET is reported to downstage primary tumors, downstaging of the axilla was unsuccessful in the majority of patients.

132 Background: Enhancing equitable oncologic care is an increasingly emphasized priority. Our study aims to identify aspects of breast cancer (BC) care in which differences exist based on insurance coverage. Methods: We performed a retrospective, case control study, (from 2014-2020); 39 Hispanic ethnicity uninsured patients (UP) from underserved communities with newly diagnosed BC and 119 insured patients (IP) diagnosed at Mayo Clinic Arizona (MCA). Patients were matched 3:1 for age, stage, year of diagnosis, estrogen receptors and HER-2 status. Demographic information, clinical variables, and zip code level specific socioeconomic information were compared. Continuous variables were compared by Wilcoxon rank-sum test and categorical variables by chi-square test. All patients were treated at MCA. Results: Similar treatment patterns with radiotherapy, chemotherapy and surgery were observed between groups. Primary language was Spanish for 94% of UP and English for 97.5% of IP. The majority of UP were of Hispanic ethnicity (97.4%); IP were 83.2% non-Hispanic White, 9.2% Hispanic, 3.4% African American. Zip code level information reflected more unemployment with a median of 10.6% versus 6.9% p < 0.001, percent of high school or lower (53.0 % v 23.2 %, p < 0.001), and lower income for UP (33733.5 v 64728.0 p values < 0.001).BMI was significantly higher for UP (30.6 V 24.7, p = 0.005), with presence of more co-morbidities; diabetes (28.2% v 5.0%, p < 0.001), hypertension (35.9 % v 20.2%, p = 0.046), dyslipidemia (28.2% v 12.6%, p = 0.023), metabolic syndrome (p 23.7% v 8.5, p = 0.013), and tobacco use (17.9% v 2.5%, p < 0.001). Genetics consultation was performed for 62.2% IP versus 35.9% UP (p = 0.004), lower acceptance of nutrition consultation for UP (29.4% vs 7.4%, p = 0.024). Median time from mammogram to biopsy (25.5 days vs. 14 days, p = 0.056), and interval from diagnosis to treatment (62 days vs. 39 days) (p = 0.001) were less favorable for UP compared to IP. Conclusions: In comparing the status of UP and IP with newly diagnosed BC, we identified greater prevalence of co-morbidities and adverse social determinants of health in the former group. We identified access to genetic counseling, nutrition consultation, and timeliness of diagnostic biopsy and initiation of treatment as disparate features in the care pathway. These observations allowed development of tailored interventions to achieve greater equity in delivery of BC care at Mayo Clinic.

Longitudinal analysis of circulating tumor DNA (ctDNA) has shown promise for monitoring treatment response. However, most current methods lack adequate sensitivity for residual disease detection during or after completion of treatment in patients with nonmetastatic cancer. To address this gap and to improve sensitivity for minute quantities of residual tumor DNA in plasma, we have developed targeted digital sequencing (TARDIS) for multiplexed analysis of patient-specific cancer mutations. In reference samples, by simultaneously analyzing 8 to 16 known mutations, TARDIS achieved 91 and 53% sensitivity at mutant allele fractions (AFs) of 3 in 104 and 3 in 105, respectively, with 96% specificity, using input DNA equivalent to a single tube of blood. We successfully analyzed up to 115 mutations per patient in 80 plasma samples from 33 women with stage I to III breast cancer. Before treatment, TARDIS detected ctDNA in all patients with 0.11% median AF. After completion of neoadjuvant therapy, ctDNA concentrations were lower in patients who achieved pathological complete response (pathCR) compared to patients with residual disease (median AFs, 0.003 and 0.017%, respectively, P = 0.0057, AUC = 0.83). In addition, patients with pathCR showed a larger decrease in ctDNA concentrations during neoadjuvant therapy. These results demonstrate high accuracy for assessment of molecular response and residual disease during neoadjuvant therapy using ctDNA analysis. TARDIS has achieved up to 100-fold improvement beyond the current limit of ctDNA detection using clinically relevant blood volumes, demonstrating that personalized ctDNA tracking could enable individualized clinical management of patients with cancer treated with curative intent.

Survivors of estrogen receptor–expressing breast cancer generally do not receive estrogen-based therapy for menopausal symptoms due to concern for provoking recurrence of disease. Single-dose depomedroxyprogesterone acetate has been shown to be among the most effective non-estrogen strategies for treatment of menopausal hot flashes, but long-term evidence for safety in survivors is lacking. We conducted an institutional review board approved, retrospective, case-control cohort study at a tertiary, academic referral center. Patients with estrogen receptor-expressing early-stage operable breast cancer who received depomedroxyprogesterone acetate for hot flashes between January 2005 and December 2012 were identified. We confirmed 75 patients who met strict inclusion criteria who were matched 1:1 with controls for age, stage of disease, HER2 status, and year of diagnosis. Overall survival, loco-regional recurrence-free survival, and progression-free survival assessments for cases were compared with controls. Median follow-up duration was 68.4 months in cases and 57.6 months in controls. Estimated local-regional recurrence-free survival at 10 years was 97% (95% CI, 92–100%) in cases and 98% (95% CI, 95–100%) in controls. Estimated progression-free survival at 10 years was 89% (95% CI, 80–100%) in cases and 83% (95% CI, 73–95) in controls. The majority (75%) of case patients experienced satisfactory relief of hot flashes from depomedroxyprogesterone injection. In this retrospective case-control study, we were unable to identify a detrimental effect of depomedroxyprogesterone acetate therapy for hot flashes in survivors of estrogen receptor–expressing breast cancer. Depomedroxyprogesterone acetate may be acceptable for management of hot flashes in this population.

e18518 Background: Initiatives enhancing equitable oncologic care are an increasingly emphasized priority. Our study aims to identify aspects of breast cancer (BC) care in which differences exist based on insurance coverage status. Methods: We performed a retrospective, case control study consisting of 39 Hispanic ethnicity uninsured patients (UP) with newly diagnosed BC at federally qualified health centers and 119 insured patients (IP) diagnosed at Mayo Clinic Arizona (MCA). Patients were matched 3:1 for age, stage, year of diagnosis, ER and HER2 status. Demographic information, clinical variables, and zip code level specific socioeconomic information were compared. Continuous variables were compared by Wilcoxon rank-sum test and categorical variables by chi-square test. All patients ultimately received their cancer treatment at MCA. Results: Similar treatment patterns with chemotherapy, surgery, and radiation treatment were observed between groups. Primary language was Spanish for 94% of UP and English for 97.5% of IP. The majority of UP were of Hispanic ethnicity (97.4%); IP were 83.2% non-Hispanic White, 9.2% Hispanic, 3.4% African American. Zip code level information reflected more unemployment with a median of 10.6% versus 6.9% p ˂ 0.001, percent of high school or lower (53.0 % v 23.2 %, p ˂ 0.001), and lower income for UP (33733.5 v 64728.0 p values ˂ 0.001). UP BMI was significantly higher (30.6 V 24.7, p=0.005), with presence of more co-morbidities; diabetes (28.2% v 5.0%, p ˂ 0.001), hypertension (35.9 % v 20.2%, p= 0.046), dyslipidemia (28.2% v 12.6%, p = 0.023), metabolic syndrome (p 23.7% v 8.5, p= 0.013), and tobacco use (17.9% v 2.5%, p ˂ 0.001). IP had higher alcohol use (52.9% v 5.3%, p ˂ 0.001). Genetics consultation was performed for 62.2% IP versus 35.9% UP (p=0.004), lower acceptance of oncology nutrition consultation for UP (29.4% vs 7.4%, p= 0.024) Median time from abnormal mammogram to biopsy (25.5 days vs. 14 days, p=0.056), and interval from diagnosis to treatment (62 days vs. 39 days) (p=0.001) were less favorable for UP compared to IP. Conclusions: In comparing the status of UP (primarily Hispanic, Spanish-speaking) and IP (primarily non-Hispanic White, English-speaking) with newly diagnosed BC we identified greater prevalence of co-morbidities and adverse social determinants of health in the former group. We identified access to genetic counseling services, access to oncology nutrition consultation, and timeliness of diagnostic biopsy and initiation of treatment as disparate features in the care pathway. These observations can allow development of tailored interventions to achieve greater equity in delivery of BC care.

10541 Background: Biomechanical tissue properties may vary in the breasts of patients at elevated risk for breast cancer. We aim to quantify in vivo biomechanical tissue properties in various breast densities and in both normal risk and high risk women using Magnetic Resonance Imaging (MRI)/MRE and examine the association of biomechanical properties of the breast with cancer risk. Methods: In this IRB–approved prospective single-institution study, we recruited two groups of women differing by breast cancer risk to undergo a 3.0 T dynamic contrast enhanced MRI/MRE of the breast. Low-average risk women were defined as having no personal or significant family history of breast cancer, no prior high risk breast biopsies and a negative mammography within 12 months. High-risk breast cancer patients were recruited from those patients who underwent standard of care breast MR. Within each breast density group (non-dense versus dense), two-sample t-tests were used to compare breast stiffness, elasticity, and viscosity across risk groups (low-average vs high). Results: There were 50 low-average risk and 86 high-risk patients recruited to the study. The risk groups were similar on age (mean age = 55.6 and 53.6 years), density (68% vs. 64% dense breasts) and menopausal status (66.0% vs. 69.8%). Among patients with dense breasts, mean stiffness, elasticity, and viscosity were significantly higher in high risk patients ( N = 55) compared to low-average risk patients ( N = 34; all p < 0.001). In the multivariate logistic regression model, breast stiffness remained a significant predictor of risk status (OR=4.26, 95% CI [1.96, 9.25]) even after controlling for breast density, MRI BPE, age, and menopausal status. Similar results were seen for breast elasticity (OR=4.88, 95% CI [2.08, 11.43]) and viscosity (OR=11.49, 95% CI [1.15, 114.89]). Conclusions: Structurally-based, quantitative biomarker of tissue stiffness obtained from global 3D breast MRE is associated with differences in breast cancer risk in dense breasts. As such, tissue stiffness could provide a novel prognostic marker to help identify the subset of high-risk women with dense breasts who would benefit from increased surveillance.[Table: see text]

Background: DNIV accounts for 6%–10% of newly diagnosed breast cancer cases. Despite widespread mammography screening, its incidence is increasing in the United States and survival of this disease has only modestly improved since the late 1970s. As patient data accumulates in EHR, it’s promising to generate practice-based evidence through utilization of observational data sources. However, assembly of a DNIV cohort based on EHR data is challenging, as key pathologic and staging information are stored in unstructured clinical narratives and not available as structured data. In this study, we developed a rule-based algorithm to phenotype DNIV using natural language processing (NLP) techniques, and implemented the algorithm on our institutional EHR to extract potential DNIV cases. Methods and Results: We defined DNIV as those with either (1) M1 disease identified at time of initial presentation or M1 disease identified within 4 months after definitive surgery. We first developed a reference case list of DNIV verified by physician chart review of the EHR. We next refined the algorithm on a training dataset containing 51 positive and 38 negative reference cases. Next we tested the performance on the testing data containing 23 positive and 55 negative cases. The phenotyping algorithm identified key data elements using NLP, i.e., stage IV breast cancer, definitive surgery, stage 0-III, recurrent breast cancer and associated dates. To identify DNIV cases, phenotyping algorithm integrated temporal relations among the key data elements. The following steps were conducted in the following sequential order: (1) Identification of patients with breast cancer diagnosis using ICD-9 and ICD-10 codes. (2) Patients are positive cases if there are explicit mentions that delineate DNIV from recurrent metastatic breast cancer, such as “de novo stage IV” or “primary intact” detected by NLP at time of diagnosis. (3) Otherwise, patients with definitive surgery are selected if stage IV was within 5 years before definitive surgery or within 4 months after definitive surgery, along with patients with stage IV but without definitive surgery. (4) We further excluded patients with stage 0-III detected within 5 years after stage IV. (5) We further excluded patients with recurrent breast cancer detected before or at time of detection of stage IV. The remaining patients were left as positive cases. Precision of the algorithm was 70%, recall was 87% and F1, the weighted average of precision and recall, was 77%. We implemented our algorithm to interrogate 10 million clinical documents in a cohort of 56,548 patients with breast cancer diagnosis codes who presented to our institution between 2004 and 2018 and had research authorization. We identified 1918 potential DNIV cases. Conclusion: Our future focus is on algorithm refinement. An algorithm-generated cohort could serve as a data source for further study on outcomes related to DNIV and ideally as automated data abstractor and staging process. Citation Format: Liwei Wang, Karthik Giridhar, Kimberly Corbin, Brenda Ernst, Sadia Choudhery, Emmanuel Gabriel, Feichen Shen, Hongfang Liu, James Jakub. Identifying de novo stage IV breast cancer (DNIV) cases in Electronic Health Records (EHR) using natural language processing [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-050.

Background: Accurate circulating biomarkers for detecting residual disease can help guide therapy decisions, particularly in early-stage cancer patients. However, currently available methods lack the sensitivity required to confidently assess the presence of residual disease in patients with low tumor burden. To address this need, we have developed TARDIS (Targeted Digital Sequencing), a personalized, multiplexed amplicon sequencing method capable of tracking as many as 100 or more mutations simultaneously. Methods: We obtained tumor biopsies and longitudinal plasma samples from patients with early-stage breast cancer, glioblastoma, and pancreatic cancer. Each tumor biopsy was analyzed whole-exome sequencing. Founder mutations were selected, accounting for copy number alterations (analyzed using sequenza) and a consensus allele fraction approach that combined pyclone and custom in-house methods. Patient-specific TARDIS primers were designed to detect these mutations in plasma cfDNA. Error suppression in TARDIS was achieved using a combination of unique molecular identifiers and fragment sizes to group sequencing reads into read families. Results: In 33 patients with early-stage breast cancer treated with neoadjuvant therapy, we targeted between 3 and 116 (mean 30) mutations per patient and analyzed between 1 and 4 longitudinal plasma samples using TARDIS. Prior to treatment, we detected ctDNA in 100% patients with Stage I-III breast cancer (n=32, 95% CI= 89%-100%). We detected tumor-specific mutations in 100% of baseline breast cancer plasma samples. After completion of neoadjuvant therapy and before surgery, ctDNA levels were significantly lower in patients with pathologic complete response (pathCR, no evidence of disease at surgery) compared to patients with residual disease (median tumor fractions 0.003% and 0.017%, respectively, p=0.0058, AUC=0.83). Conclusions: TARDIS enables highly sensitive detection of ctDNA in patients with nonmetastatic cancers. Analysis of longitudinal plasma samples using TARDIS holds promise for personalizing the extent of treatment in patients with curable disease. Multiple clinical validation studies across cancer types are ongoing to define quantitative thresholds for changes in ctDNA levels that could improve clinical decision making. Citation Format: Bradon R. McDonald, Tania Contente-Cuomo, Stephen-John Sammut, Michelle D. Stephens, Ahuva Odenheimer-Bergman, Brenda Ernst, Nieves Perdigones, Suet-Feung Chin, Maria Farooq, Rosa Mejia, Patricia A. Cronin, Karen S. Anderson, Heidi E. Kosiorek, Donald W. Northfelt, Ann E. McCullough, Bhavika K. Patel, Jeffrey N. Weitzel, Thomas P. Slavin, Carlos Caldas, Barbara A. Pockaj, Muhammed Murtaza. Personalized monitoring of treatment response using Targeted Digital Sequencing of circulating tumor DNA [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr A51.

Accurate detection of minimal residual disease (MRD) can guide individualized management of early stage cancer patients, but current diagnostic approaches lack adequate sensitivity. Circulating tumor DNA (ctDNA) analysis has shown promise for recurrence monitoring but MRD detection immediately after neoadjuvant therapy or surgical resection has remained challenging. We have developed TARgeted DIgital Sequencing (TARDIS) to simultaneously analyze multiple patient-specific cancer mutations in plasma and improve sensitivity for minute quantities of residual tumor DNA. In 77 reference samples at 0.03%-1% mutant allele fraction (AF), we observed 93.5% sensitivity. Using TARDIS, we analyzed ctDNA in 34 samples from 13 patients with stage II/III breast cancer treated with neoadjuvant therapy. Prior to treatment, we detected ctDNA in 12/12 patients at 0.002%-1.04% AF (0.040% median). After completion of neoadjuvant therapy, we detected ctDNA in 7/8 patients with residual disease observed at surgery and in 1/5 patients with pathological complete response (odds ratio, 18.5, Fisher’s exact p=0.032). These results demonstrate high accuracy for a personalized blood test to detect residual disease after neoadjuvant therapy. With additional clinical validation, TARDIS could identify patients with molecular complete response after neoadjuvant therapy who may be candidates for nonoperative management.One Sentence SummaryA personalized ctDNA test achieves high accuracy for residual disease.

Background: Immune checkpoint inhibitors (ICPIs) have led to dramatic improvement in outcome of several cancers. Program death ligand1 (PD-L1) staining and tumor mutational burden (TMB) have emerged as independent predictive biomarkers of ICPIs in lung cancer. Here we examine the landscape of TMB and PD-L1 expression in breast cancer and present a case of patient with high TMB and PD-L1 negative breast cancer with exceptional response to ICPIs. Methods: Hybrid-capture based comprehensive genomic profiling of 395 cancer related genes using the FoundationOne assay was performed on 14,867 breast carcinomas sequenced in the course of routine clinical care. Ventana (SP-263) PD-L1 status (n=1425) and hormone receptor status was available for a subset of patients. Subgroup analyses were performed based on histological type [invasive lobular carcinoma (ILC, n=740)], molecular subtypes [ER-positive (ER+; n= 1371), HER2-amplified (HER2+; n=1522), and TNBC (n=917)], patient age (≤45, 46-60, ≥61), and local vs. metastatic disease (n=5241 and 6710). Results: Consistent with previous reports, the rates of positive PD-L1 staining are highest in TNBC (14%) and lowest in HER2+, ILC, and ER+ disease (6.0%, 5.1%, 2.3%). Interestingly, the rate of PD-L1 positivity, defined as ≥1% tumor staining, was significantly lower in metastatic disease vs. local disease (6.3% vs. 11.1%; p = 0.005). The frequency of high TMB, defined as >10 mutations/mb, was greatest in ILC and HER2+ disease (13.6% and 9.9%) and lowest in TNBC and ER+ disease (7.0% and 6.9%). Rates of high TMB were associated with increased patient age (3.7%, 9.3%, and 12.8% frequency in patients ≤45, 46-60, and ≥61) and were significantly higher in metastatic vs. local disease (11.1% vs 5.3%; p20 mut/mb), there was a significant association between TMB and PD-L1 positivity (OR = 2.6, p = 0.023). Nevertheless, even with high cutoff, 79% of the TMB high samples were PD-L1 negative. We also report on a stage IIIb (T4, N2, M0) ER+ HER2- breast cancer patient with high TMB (40muts/mb) and negative PD-L1 IHC who previously progressed on aromatase inhibitor with CDK4/6 inhibitor and chemotherapy but achieved durable complete response of > 1 year with nivolumab in combination with capecitabine. Conclusions: Predictive biomarkers for ICPIs are critical to identify a subset of breast cancer patients who may respond to immunotherapy. TMB high and PD-L1 positivity do not significantly co-occur and the majority of TMB high cases were PD-L1 negative. Nevertheless, this group of patients may still benefit with ICPIs. Further studies are needed to evaluate this subset of patients. Citation Format: Ethan Sokol, Lee Albacker, Aixa Soyano, Ricardo Parrondo, Brenda Ernst, Emmanuel Gabriel, Garrett Frampton, Jeffrey Ross, Siraj Ali, Jon Chung, Saranya Chumsri. Incidence of high tumor mutation burden (TMB) and PD-L1 positivity in breast cancers and potential response to immune checkpoint inhibitors (ICPIs) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4894.

Background: Circulating tumor DNA (ctDNA) analysis holds potential for minimal residual disease (MRD) detection in early stage breast cancer. However, sensitivity for MRD is limited due to low ctDNA levels in early stage patients and limited blood volumes. Loss of input DNA during library preparation, limited multiplexing or low sensitivity of current molecular methods further limit accuracy. To address this gap, we have developed TARgeted DIgital Sequencing (TARDIS), a novel method for simultaneous analysis of multiple patient-specific mutations in plasma DNA. Methods: Using tumor exome sequencing, we identify and prioritize somatic founder mutations, design nested primers and evaluate them for multiplex performance. Using 5-10 ng input plasma DNA, we perform 1) targeted linear pre-amplification to improve downstream molecular conversion, 2) single-stranded adapter ligation to incorporate unique molecular identifiers (UMIs) and 3) targeted PCR to prepare sequencing-ready libraries. The resulting sequencing reads have fixed target-specific ends and variable ligation ends. We utilize fragment size and UMIs to group sequencing reads into read families. To ensure specificity, we require targeted mutations are supported by 2 or more read families. Results: To assess analytical performance, we targeted 8 mutations in cell-free DNA reference samples with 0.25%-2% mutation allele fractions (AFs). Precision across 7-16 replicates at each AF level agreed with expectations of Poisson distribution, demonstrating effective analysis of ˜70% of input DNA. At 2%, 1%, 0.5% and 0.25% AFs, variant-level sensitivity was 96.4%, 96.4%, 91.1% and 65.8%, approaching the theoretical limit given input DNA. At 0.25% AF, 3-7 mutations were detected per sample, achieving 100% sample-level sensitivity. In 16 wild-type replicates, no targeted mutations were called (100% specificity). Averaging multiple mutations improved precision in sample-level AF estimates. Mean AFs from 8 mutations for the 2% sample were 2.34%-2.80% (5.8% CV). In 6 patients with breast cancer treated with neoadjuvant therapy (NAT), we analyzed 8-18 patient-specific mutations (mean 11.8). Before treatment, ctDNA was detected in 5/6 patients at mean AFs of 0.02%-1.19% (mean 0.40%), supported by 2-10 mutations (mean 5.6). Of these 5 patients, 4 had residual disease after NAT and ctDNA was detected pre-operatively or during NAT in 3/4 patients. 1 patient achieved pathological Complete Response and ctDNA was undetectable after NAT. Conclusions: Preliminary results suggest TARDIS enables accurate MRD detection after neoadjuvant therapy in patients with early stage breast cancer. On-going work is expanding this analysis to include additional patients and investigate the clinical validity of peri-operative ctDNA monitoring. Summary of clinical resultsPatientPre-NAT Stage (TNM)SubtypeNo. of Mutations TargetedBaseline ctDNA (AF%, No. of Mutations)ctDNA after or during NAT (AF%, No. of Mutations)Residual Tumor (TNM)1T3 N1ER+ PR+ HER2-8+ (0.02%, 2)-T2 N12T3 N0TNBC12+ (0.29%, 6)+ (0.01%, 1)T1a N03T2 N1TNBC18+ (1.19%, 10)+ (0.01%, 1)T1mi N04T3 N1TNBC10+ (0.02%, 3)+ (0.05%, 3)T3 N15T2 N0TNBC9+ (0.46%, 7)-pathCR6T1c N1TNBC14--pathCR Citation Format: McDonald BR, Contente-Cuomo T, Sammut S-J, Ernst B, Odenheimer-Bergman A, Perdigones N, Chin S-F, Farooq M, Cronin PA, Anderson KS, Kosiorek H, Northfelt D, McCullough A, Patel B, Caldas C, Pockaj B, Murtaza M. Multiplexed targeted digital sequencing of circulating tumor DNA to detect minimal residual disease in early and locally advanced breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-01-21.

e22116Background: Survivors of ER-expressing operable breast cancer (ER+BC) generally do not receive hormone replacement therapy for menopausal symptoms due to concern about provoking recurrence of...

Decades of research are now leading to therapeutics that target the molecular mechanisms of the cancer-specific immune response. These therapeutics include tumor antigen vaccines, dendritic cell activators, adjuvants that activate innate immunity, adoptive cellular therapy, and checkpoint blockade. The advances in targeted immunotherapy have led to clinical advances in the treatment of solid tumors such as melanoma, prostate cancer, lung cancer, and hematologic malignancies. Preclinical and translational studies suggest that patients with breast cancer may also benefit from augmenting effective immune responses. These results have led to early-phase clinical trials of tumor antigen vaccines, adjuvants, and combinations of checkpoint inhibitor blockade to boost breast cancer-specific immunity in patients. This review focuses on the current and emerging development of cancer immunotherapy for breast cancer.