Ernst, Brenda

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]

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.

Abstract 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.

Abstract Background: Contrast-enhanced mammography (CEM) is an emerging breast imaging technique utilizing iodinated contrast to highlight areas of neovascularity. The role of CEM in patients with breast implants has not yet been characterized. We report our clinical experience of CEM in patients with breast augmentation surgery to better understand the potential diagnostic utility and limitations of CEM in the setting of breast implants. Materials and Methods: A HIPPA compliant, IRB exempt single-institution review of prospective CEM cases who had “breast implants” in their report between 01/2015 and 03/2020. Medical records were reviewed to supplement database information. Results: Forty-six patients were included with a mean age of 52 years (range 33-72). Clinical indications included: high risk research screen 3 (6%), diagnostic evaluation for abnormal imaging 24 (52%), further evaluation of newly diagnosed breast cancer 12 (26%) or assessment of neoadjuvant treatment response 7 (15%). Thirty patients had malignant lesions. Histology was invasive ductal carcinoma (90%), invasive lobular carcinoma (7%), and ductal carcinoma in situ (3%). CEM identified the index cancer and extent of disease in 28/30 (93%) of malignant cases. In two patients (7%), the malignant lesion was not included in the field-of-view due to its location. One of these lesions was a far medial mass within the breast which was detected by ultrasound alone. The other false negative CEM was a palpable axillary mass negative on both mammogram (MG) and MRI but seen by ultrasound. Twenty-three (50%) underwent additional breast MRI of which 20 had an already diagnosed cancer. the findings on CEM were concordant with MR imaging for the index lesion in 19/20 (95%) cases (kappa=0.86; p &lt;0.001). Six additional lesions were found by CEM and confirmed by MRI. Of these lesions, 33% were found to be malignant and changed the surgical procedure. Four were only seen on CEM (no MRI comparison was available) and 75% were found to be malignant. One was only seen on MRI and was benign. One additional lesion was only seen as an asymmetry on MG without CEM or MRI correlate. This was benign on both the biopsy and surgical pathology. Conclusions: CEM appears to be a valuable breast imaging modality for diagnostic evaluations and surgical staging, including patients with breast implants. Due to technical artifacts and positioning limitations for posterior lesions, we recommend performing CEM with implant displaced views. Breast centers that use CEM, should be aware of field of view as a potential limitation when evaluating extent of disease in patients with breast augmentation. Citation Format: Molly Carnahan, Barbara Pockaj, Victor Pizzitola, Marina Giurescu, Roxanne Lorans, William Eversman, Richard Sharpe, Patricia Cronin, Donald Northfelt, Karen Anderson, Brenda Ernst, Bhavika Patel. Experience of contrast-enhanced mammography in patients with breast augmentation surgery [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 PS3-23.

Abstract 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 &gt;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.

Abstract 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.

AbstractBackground and ObjectivesNeoadjuvant endocrine therapy (NET) for ER+ breast cancer can downstage primary tumors. We evaluated NET efficacy in node‐positive patients.MethodsNode‐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.ResultsThirty‐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%.ConclusionsWhile NET is reported to downstage primary tumors, downstaging of the axilla was unsuccessful in the majority of patients.

Abstract Introduction New treatment strategies are improving outcomes for patients with Hodgkin (HL) and non-Hodgkin lymphoma (NHL) but achieving durable responses and cure in the relapsed patient remain a challenge. Both the mTORC1 inhibitor everolimus (RAD001) and the IMiD, lenalidomide (LEN) have efficacy as single agents in patients with relapsed and refractory (R/R) HL and NHL. Individually, LEN and RAD present a low toxicity profile and in combination may offer synergistic therapeutic efficacy by unique mechanisms of action. A phase I/II clinical trial of RAD and LEN was designed to explore the tolerability, toxicity and to determine the maximum tolerated dose (MTD) of this combination for the Phase II study. The results of phase I/II data are reported here. Methods MC0981 was activated on January 10, 2011. In phase I, the study enrolled a total of 25 patients and RAD 5 mg daily + LEN 10 mg/d X 21d in a 28-day cycle was defined as the MTD. The phase II opened on May 14, 2013, and closed on Feb 19, 2014, during which 33 patients were enrolled and were treated until progression of disease. Eligibility required age ≥18, biopsy proven relapsed or refractory NHL or HL, ECOG PS 0- 2, measurable disease, Hb >9g/dl, ANC ≥1200/uL, platelet ≥ 50,000/uL, creatinine ≤1.5xULN and willingness to sign informed consent. Women of child bearing potential had pregnancy testing and all patients followed recommendations for contraception. Follow up data was analyzed as of July 2014. Results A total of 58 patients were enrolled to this study and fifty five are evaluable for analysis (2 never started therapy, 1 deemed ineligible). The median age was 62 years (21-82) and 38 (69.1%) were male. Sixty-five percent had stage IV disease and 42% had 4 or more prior treatments including stem cell transplantation in 49%. Histologies included HL (n=10) and NHL (n=45 with 23 DLBCL, 2 FL-III, 5 LPL, 3 MCL, 2 MF, and 3 other). At least 1 Gr≥3 adverse event was seen in 74.5% of patients. The most common Gr≥3 toxicities were hematologic - neutropenia (30.9%), and thrombocytopenia (21.8%), and anemia (10.9%). Nine of 55 patients (16%) had Gr≥3 infection; 2 with skin infection, 1 with cholecystitis, 1 with lung infection, 1 with pharyngitis 1 with otitis externa, 1 with otitis media, and 1 with pleural infection and 1 with upper respiratory tract infection. Seven patients discontinued treatment due to adverse events. At this time, 44% (25/55) remain progression-free. A documented tumor response, as overall response rate (ORR) was seen in 20% (11/55) with 1CR, 8PR, and 2MR; 17 remain on therapy; and 22 deaths have occurred with a median survival of 15.0 months (95% CI 7.5-NR). Median follow up time was 5.5 (range, 0.7- 41.0) months. The median duration of response (DOR) in those responding is 19.4 months. Conclusions In a heavily pretreated population with baseline compromised bone marrow function, the combination of everolimus and lenalidomide is feasible with a modest ORR and a surprisingly long DOR. Future studies in more defined groups of NHL or HL are necessary to better predict which patients will be long-term responders. This trial is sponsored by Novartis and Celgene Disclosures Off Label Use: mTORC1 inhibitor (Everolimus) and the Immunomodulatory (IMiD) drug Lenalidomide for patients with Heavily Pretreated Relapsed Lymphoma . Mikhael:Onyx: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Novartis: Research Funding. Nowakowski:Celgene, Morphosis: Consultancy. Witzig:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding. Reeder:Millennium, Celgene, Novartis: Research Funding.

Abstract 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 &gt;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%; p&lt;2E-23). PD-L1 positive and TMB high populations were not significantly co-occurrent (OR = 1.02, p = 0.87). Similar percentages of PD-L1 positivity were observed in both TMB low (9.3%) and TMB high (9.5%). However, among patients with very high TMB (&gt;20 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 &gt; 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.

A robust personalized ctDNA test, TARDIS, achieves high accuracy for residual disease after completion of neoadjuvant therapy.