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Abstract Data from germline testing in unselected patients with hepatobiliary cancers are limited. Identification of germline predisposition can have important implications on cancer treatment and family counseling. To determine prevalence of pathogenic germline variants (PGV) in patients with hepatobiliary cancer, we undertook a prospective multi-site study of germline sequencing using a >80-gene next-generation sequencing platform among patients with hepatobiliary cancers receiving care at Mayo Clinic Cancer Centers between April 1, 2018 and March 31, 2020. Patients were not selected on the basis of stage, family cancer history, ethnicity, or age. Family cascade testing was offered at no cost. Of 205 patients, the median age was 65 years, 58.5% were male, 81% were White, and 64.4% had cholangiocarcinoma, 21.5% hepatocellular carcinoma, 7.8% gallbladder cancer, and 4.3% carcinoma of ampulla of Vater. PGV were found in 15.6% (n = 32) of patients, including 23 (71%) in moderate and high penetrance cancer susceptibility genes. A total of 75% of patients with a positive result would not have been detected using guidelines for genetic evaluation. Prevalence of PGV was 15.7% in intrahepatic cholangiocarcinoma, 17% in extrahepatic cholangiocarcinoma, 15.9% in hepatocellular cancer, and 33% in carcinoma of ampulla of Vater. On the basis of these genetic findings, 55% were potentially eligible for approved precision therapy and/or clinical treatment trials. Universal multi-gene panel testing in hepatobiliary cancers was associated with detection of heritable mutations in over 15% of patients most of whom would not have been tested using current guidelines. Germline testing should be considered in all patients with hepatobiliary cancers. Prevention Relevance: Universal multi-gene testing in hepatobiliary cancers was associated with heritable mutations in over 15% of patients, most of whom would not have been tested using current guidelines. 55% were potentially eligible for approved precision therapy and/or clinical treatment trials. Germline testing should be considered in all patients with hepatobiliary cancers.

e19023 Background: Acute GVHD (aGVHD) is a major cause of mortality and morbidity following stem cell transplantation (HCT). In effort to prognostic patients with aGVHD, the Mount Sinai Acute GVHD International Consortium (MAGIC) combined two biomarkers, ST2 and REG3α to generate an algorithm known as the Ann Arbor (AA) biomarker risk. This is now available as a commercial test to help predict risk for severe acute GVHD and non-relapse mortality when done at the onset of symptomatic aGVHD. Our institution began utilizing these lab values and here we report our “real world” experience. The primary aim was to correlate AA risk probabilities with recently defined endpoints including day 28 overall response rate (ORR) and 6 month freedom from treatment failure (6mFFTF) and overall survival (OS). Methods: 58 HCT patients who underwent HCT between October 2018 and November 2019 and had the biomarker assay at the onset of aGVHD were identified from the institutional database and clinical information about disease, transplant and outcomes was obtained from the medical records. Clinical staging of aGVHD was documented per standardized published guidelines. Day 28 ORR was defined as complete response by day 28. 6mFFTF was defined as a patient being alive, without relapse of underlying disease or addition of new systemic therapy for aGVHD, and prior to the development of cGVHD. Results: When comparing low (n = 39), intermediate (n = 11), and high (n = 8) AA risk, there was no difference in age ( p =0.254), primary disease ( p =0.10), DRI ( p =0.994), donor source ( p =0.193), conditioning regimen intent ( p =0.537), GVHD prophylaxis ( p =0.351) ATG use ( p =0.06). Low AA risk was associated with lower grades of aGVHD at onset (grade I = 15%, grade II = 80%, grade III = 5%, grade IV = 0%), whereas high AA risk was associated with higher grades of aGVHD at onset (grade I = 0%, grade II = 50%, grade III = 25%, grade IV = 25%) ( p =0.009). For low, intermediate, and high AA risk the day 28 ORR was 69%, 45% and 29% ( p = 0.083); the 6mFFTF was 82%, 82%, and 25% ( p = 0.0001); 6 month OS was 92%, 100%, and 50% ( p = 0.0006) respectively. Conclusions: Our study shows a high correlation between AA risk and outcomes. High risk AA risk was associated with inferior outcomes This study was limited by the retrospective single institutional experience with relatively small numbers. However, our findings using the commercial assay mirror that seen with the MAGIC studies. Our “real world data” can serve as a foundation and continued validation for institutional implementation of AA risk stratification for aGVHD.

Introduction: Response assessment at day 100 post Autologous Stem Cell Transplant (ASCT) is associated with long-term relapsed free survival (RFS) and overall survival (OS) in multiple myeloma (MM). The International Myeloma Working Group (IMWG) are the preferred criteria to define best response to treatment and define relapse. In the last years, response assessment has incorporated minimal residual disease (MRD) status -associated with improved RFS and OS (Munshi et al); and PET/CT combined with clinical characteristics -also associated with favorable outcomes (Zamagni et al. NCT01910987; MMY3033). The 2016 IMWG MRD criteria, combined imaging (PET/CT) plus next-generation sequencing (NGS) MRD-negative to define complete response (CR). To our knowledge, there is limited data examining the correlation and prognostic value of MRD and FDG-PET/CT at day 100 post ASCT in MM. IN this study, we aimed to determine the prognostic valued of MRD by NGS combined with PET/CT in RFS and OS status after high dose chemotherapy and ASCT in MM. Methods: Patients who underwent ASCT for MM at Mayo Clinic Arizona and had MRD and PET/CT data were included in the study. Clinical data was obtained via retrospective chart review. Cytogenetic risk (CyR) was classified using the mSMART criteria . Disease and ASCT related characteristics were compared by MRD status. MRD was measured by NGS on bone marrow aspirates using the previosly validated clonoSEQ ® Assay (Adaptive Biotechnologies Corporation, Seattle, USA) tracking the IgH, IgK and IgL rearrangements at a minimum sensitivity level of 10-5. MRD was defined by residual clonal cells per million nucleated cells as: negative= 0, borderline= 1-5, positive >5. PET/CT scans were performed locally at baseline and at day 100. Comparisons were performed using the chi-square test for categorical variables, Wilcoxon rank-sum test for continuos variables, McNemar's test and Cohens's Kappa for agreement measures. Results: A total of 103 patients had matched MRD and PET/CT assessment around day 100 (+/-9 days) and were included in the analysis. Median age at diagnosis was 62 years (range, 54-66 years), 71 patients (68.9%) were men. CyR was standard risk in 49 (47.6%), high-risk in 39 (37.9%) and unknown in 15 (14.6%) patients. Most 75 (72.8%) patients were MRD positive, 16 (15.5%) were MRD negative, and 12 (11.7%) borderline. The median main MRD clone detected was 64 (range 0-91,874). 70 patients (68%) and 33 (32%) had a negative and positive PET/CT respectively. The median follow-up time was 18 months (range, 13-31 months). At the time of data analysis, 10 patients (9.7%) had relapsed and only 4 (3.9%) had died. There was a high-correlation between MRD status and PET/CT, 31 patients (93.9%) with positive PET/CT were also MRD positive (p=0.0027). There were no statistical differences between PET/CT and CyR (p=0.95). We analyzed the correlation using the FREQ procedure (McNemars's test); there was a strong association between positive PET/CT and positive MRD in 31/33 patients (93.9%, high sensitivity), and low association for negative PET/CT the negative/borderline MRD in 26/70 (37.1%, low specificity; p<0.001). The agreement measure between the PET/CT and MRD using negative/borderline combined had a kappa of 0.23 (95% CI 0.11, 0.35) indicating a fair agreement beyond chance (Figure 1). PET/CT-CT was a statistically significant predictor of worse RFS (HR 3.53, 95%CI: 1.02-12.24, p<0.0337) and OS (HR 11.38, 95%CI: 1.18-109.56, p<0.0078) (Figure 2-3, respectively). MRD was not predictive of neither RFS (HR 1.72, 95%CI: 0.36-8.14, p<0.49) or OS (p<0.16). Conclusions: In conclusion, we demonstrate that the combination of MRD by NGS (clonoSEQ ®) and PET/CT at day 100 are complementary and have a high sensitivity (true positive rate) and fair correlation of agreement but low specificity (true negative rate). PET/CT was the best most sensitive technique to prognosticate RFS and OS. We did not find prognostic correlation of MRD with RFS and OS. However, our findings might be confounded by the low risk of relapse and death, a longer follow-up may demonstrate clinically important differences. Our results add evidence that MRD plus PET/CT improve the definition of CR in MM patients post ASCT. Prospective studies are needed to elucidate the optimal timing and role of combined MRD, PET/CT with other prognostic markers of clinical outcomes. Disclosures Larsen: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees. Fonseca:Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merck: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Oncopeptides: Consultancy; GSK: Consultancy; AbbVie: Consultancy; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy.

Objective: To evaluate the incidence of and characterize the presentation of neuropsychiatric symptoms and/or Parkinsonism as a presentation of central nervous system lymphoma (CNSL) in either its primary CNSL form or when it spreads to the brain in systemic diffuse large B-cell lymphoma (secondary CNSL). Patients and Methods: With Institutional Review Board approval we identified patients who had been treated at Mayo Clinic from 1998 to 2018 and were recorded to have a combination of ICD 9/10 codes for CNSL and various psychiatric diagnoses. Results: A total of 20 of the 232 patients (9%) were noted to have neuropsychiatric symptoms preceding diagnosis. The average age at diagnosis was 62, with even split for sex. The majority (85%) of patients had primary CNSL. The average duration of symptoms before the diagnosis was 4.8 months. Confusion (80%), depression (40%), apathy (30%), anxiety (30%), and agitation (30%) were the most common symptoms identified. The majority (65%) of patients had subcortical lesions followed by the frontal lobe (50%). Parkinsonism was identified in 5 of the 20 patients with 4 demonstrating resolution of symptoms with treatment of the lymphoma. Conclusions: Neuropsychiatric symptoms are a rare but notable symptom before the presentation of CNSL. There is an increasing awareness of neurological illness presenting as pure psychiatric disturbance, prompting the need to exclude organic and treatable diseases, particularly in elderly patients. Acknowledgment and diagnosis are important for an appropriate management as there is a significant impact on patient and caregiver quality of life.

Abstract Background: Unlike with solid organ cancers, little data is available on how diabetes mellitus (DM) and hematologic malignancies interact to affect survival and glycemic control. We examined the impact of DM on survival in patients with leukemia and the effect of leukemia on glycemic control. Materials and Methods: Patients with leukemia with and without DM were matched 1:1 (2007–2017), 70 matched pairs (total N=140 pts) were included in the analysis. We compared characteristics between cases and controls and assessed survival with the Kaplan-Meier method and Cox proportional hazards model. Mixed models compared hemoglobin A1c (HbA1c) and glucose levels over time. Results: The median age of patients at diagnosis was 56 (18–94); 60% were male and 89% had acute leukemia. Among those with DM, HbA1c was only recorded in 25 of 70 patients during the year following cancer diagnosis and was 6.8%. There was no change in HbA1c values over time in these DM patients. Mean glucose was significantly different between DM and non-DM patients (p<0.001). Time (days since leukemia diagnosis) was significant (p<0.001) and there was a significant interaction effect (p=0.01). Glucose values increased in the DM patients during the year following diagnosis, while remaining stable in those without DM. Median follow-up time was 23.2 months. Three-year survival was estimated at 46% for DM patients versus 45% in non-DM pts by Kaplan Meier method (p=0.79). Hazard ratio (stratification for matched pairs) was 1.05 (95% CI: 0.57 - 1.94; p=0.88). Three-year relapse-free survival was estimated at 34% for DM patients versus 43% for non-DM patients (p=0.58). Hazard ratio (stratification for matched pairs) = 1.10 (95% CI: 0.61–1.98; p=0.76). Conclusions: DM did not adversely impact survival in patients with leukemia. Leukemia and its treatment did not affect glycemic control. This should be reassuring to hematologists and endocrinologists who treat patients with leukemia and diabetes.