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Abstract Introduction: TP53 aberrations, including mutations and deletion of 17p (del17p), are important adverse prognostic markers in chronic lymphocytic leukemia (CLL). Prevalence of TP53 aberrations ranges from 7-11% in untreated CLL and increases with disease progression and treatment. Among CLL patients with TP53 aberrations, co-occurrence of TP53 mutations with del(17p) is common. CLL patients with TP53 mutations or del(17p) have significantly worse outcomes when compared to wild-type patients. Previous studies, focusing on CLL patients at time of treatment, are mixed as to whether a single or more than one TP53 aberration impacts outcomes. TP53 is less well studied in monoclonal B-cell lymphocytosis (MBL), an asymptomatic pre-malignant state of CLL. Del(17p) occurs in 3-4% of MBL individuals, and a study of 54 MBL individuals reported a 2% mutation frequency in TP53. Here we estimated prevalence and evaluated the impact of TP53 aberrations in a large cohort MBL or untreated CLL individuals. Methods : Patients with CLL or MBL diagnosed between 2000 and 2019 from the Mayo Clinic CLL Resource with pre-treatment peripheral blood mononuclear cells (PBMC) collected within two years of diagnosis were considered. DNA was extracted from PBMCs with purity >80% or with sorted CD5+/CD19+ clonal cells. The entire coding regions of 59 CLL driver genes were paired end sequenced. Median coverage depth was >1000x per nucleotide, allowing for detection of mutations with variant allelic fraction (VAF) as low as 1%. Somatic mutations were called using MuTect2 in tumor-only mode, and high impact mutations (frameshift, nonsense, and splicing variants) and missense mutations in CLL hot spots were selected. Somatic mutations and FISH del(17p) were used to define TP53 state for each patient: 1) wild-type [no TP53 mutations and normal del(17p)], 2) single-hit [one TP53 mutation or del(17p)], or 3) multi-hit [multiple TP53 mutations or TP53 mutation and del(17p)]. Time to first treatment (TTFT) and overall survival (OS) were analyzed by TP53 state. TTFT and OS were defined as time from sample collection to first treatment or death, respectively, or last follow-up date. Median TTFT and OS was estimated by the Kaplan-Meier method. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals for TTFT and OS associations. The models were adjusted for known adverse prognostic factors including clinical diagnosis (CLL or MBL), age at diagnosis, Rai stage, b2 microglobulin, and IGHV mutation status. Results: Individuals with CLL (N=597) or MBL (N=285) were analyzed for prevalence of TP53 mutations and del(17p). We found 58 CLL patients (9.7%) and 15 MBL individuals (5.3%) had TP53 mutations. The median VAF in CLL was 30.9% (<10% VAF, n=21) and in MBL was 13.5% (<10% VAF, n=7). Del(17p) was present in 37 patients with CLL (6.2%) and 7 individuals with MBL (2.7%). In total, 86 CLL/MBL patients had a TP53 mutation and/or del(17p): 56.8% (48 patients) were single-hit and 44.2% (38 patients) were multi-hit (Fig. 1a). Patients with any TP53 aberration had shorter TTFT than wild-type patients (median 2.3 vs 9.4 years). Among patients with TP53 aberrations, median TTFT was shorter in multi-hit patients (20 events, 1.8 years) compared to single-hit patients (24 events, 3.2 years) (Fig. 1b). In Cox regression, single-hit (HR = 1.7 [1.1-2.6]) and multi-hit (HR = 1.8 [1.1-2.9]) patients had shorter TTFT compared to wild-type patients after adjusting for covariates (Fig. 1c). Multi-hit patients also had shorter OS compared to wild-type patients, while OS in single-hit patients did not significantly differ from wild-type patients (Fig. 1d). Median OS was 5.5 years in multi-hit patients (22 deaths) compared to 15.1 years in wild-type patients (196 deaths) and 14.3 years in single-hit patients (15 deaths). In the OS model adjusted for covariates, multi-hit patients had a significant increased risk (HR = 2.6 [1.6-4.1]), but single-hit patients did not (HR = 1.4 [0.8-2.5]) compared with wild-type patients (Fig. 1e). OS HRs remained stable after censoring at time of treatment. Both TTFT and OS HRs were consistent when mutations with VAF < 10% were excluded. Conclusions: This study suggests single versus multi-hit TP53 aberrations may be important for prognostic outcomes in untreated CLL and MBL patients. Prognostic metrics may need to consider single versus multi-hit TP53 aberrations and include TP53 mutations with low VAF. Figure 1 Figure 1. Disclosures Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: MEI Pharma: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction Monoclonal B-cell lymphocytosis (MBL), monoclonal gammopathy of undetermined significance (MGUS), and clonal hematopoiesis (CH) are three common premalignant hematological conditions. MBL is a precursor to chronic lymphocytic leukemia (CLL), MGUS is a precursor to both multiple myeloma (MM) and Waldenström macroglobulinemia (WM), and CH is a possible precursor to myeloid disease. All three conditions are independently associated with aging. Furthermore, there is evidence that all three conditions are associated with increased risk of infection. The relationship among these conditions, the prevalence with which they co-exist, and the association between the number of premalignant conditions and risk of infection is unknown. Methods Study participants from the Mayo Clinic Biobank, a large-scale biorepository of adult patients, provided a peripheral blood sample between 7/14/2009 to 06/18/2015. Individuals were screened for MBL using eight-color flow cytometry capable of detecting clonal B-cells to the 0.005% level. MGUS was screened using a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) assay. CH was screened using a targeted sequencing panel of 42 CH-associated genes with at least 1000x read depth and the ability to detect variant allele fractions down to 1%. All study participants resided in Olmsted County, Minnesota, the county that includes Mayo Clinic. Serious infection, defined as hospitalization due to infection, was abstracted from medical records from the time of sample collection through 12/31/2020 or date of death. The medical record abstractor collecting data was blinded to condition. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between each of the conditions. Cox regression was used to estimate hazard ratios (HR) and 95% CI to assess the association between number of premalignant conditions with risk of infection. All analyses were adjusted for age at sample collection and sex. Results A total of 407 individuals (55% male, median age 68 years) were screened for all three conditions. The prevalence was 19.9% (n=81) for MBL, 14.5% (n=59) for MGUS, and 25.6% (n=104) for CH. When we evaluated the association between each of the conditions, we found no evidence of an association between the prevalence of CH and risk of MBL (OR=0.79, 95% CI: 0.43-1.42), CH and risk of MGUS (OR=1.24, 95% CI: 0.66-2.27), or MGUS and risk of MBL (OR=1.32, 95% CI:0.66-2.52). The prevalence of co-existence of these conditions was assessed by grouping individuals based on their condition or conditions (Figure 1A). We found that 197 (48.4%) study participants had at least one premalignant condition and 10.6% had two or more. Individuals with 2 or more conditions were the oldest (median age 74 years), followed by 1 condition (median 69 years) and 0 conditions (median 67 years, P-trend <0.001). Sex was not significantly different across the groups, with 55%, 58%, and 47% male for 0, 1, and 2 conditions, respectively. Medical record abstraction identified 97 serious infection events in 80 individuals. Medical records were not available on 7 individuals. The most common infections were urinary tract (20 events), pneumonia (14 events), and cellulitis (14 events). Median follow-up time was 10.6 years (range 0.1-11.5 years). Compared to individuals with no condition, MBL (HR=1.75, 95% CI: 1.06-2.88) and MGUS (HR=1.75, 95% CI: 1.04-2.93) were associated with increased risk of serious infection. We found no evidence of an association with CH (HR=1.15, 95% CI: 0.71-1.87). When grouped by the number of conditions, we observed a significant trend (P-trend <0.01, Figure 1B) in risk of serious infections by the number of conditions: individuals with 1 condition had a 35% increased risk of infections (HR=1.35, 95% CI:0.83-2.20) and individuals with 2 or more conditions had a 2.6-fold increased risk (HR=2.58, 95% CI: 1.37-4.84). Discussion At least one premalignant condition was present in nearly 50% of the study population, with CH being the most prevalent. No evidence of a relationship between any of the three conditions was observed. However, we found increased susceptibility to serious infections as the number of conditions increased with individuals with at least two conditions had 2.6-fold increased risk of infections. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; Novartis: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Kay: TG Therapeutics: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Research Funding; Genentech: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees. Shanafelt: Genentech, Pharmacyclics: Research Funding.

Abstract INTRODUCTION Sparse data exist regarding I+V in an off-trial setting, particularly in patients (pts) with progression of disease on either I or V as single agent treatment. The 1-year overall survival (OS) rates with V monotherapy following I range from 75%-91% (Eyre et al, BJH 2019; Jones et al, Lancet Oncol 2018); however, longer-term follow-up of these or other patient cohorts treated with V after I has not yet been reported. Effective options in double-refractory pts are lacking when a clinical trial is not feasible. Here, we report our experience with I+V in these patient groups. METHODS After IRB approval, we reviewed the records of pts seen at Mayo Clinic (between 4/2012-1/2021) who received I+V therapy off-trial for CLL progression. Pts treated with I+V for Richter's transformation were excluded. Time to next treatment (TTNT) was measured from I+V treatment start date to the date of next treatment start or last known treatment status with death as a competing risk. OS was measured from I+V start date until date of death or when the patient was last known alive; OS was analyzed using the Kaplan-Meier method and Cox proportional hazards model. RESULTS Thirty-three pts with progressive CLL were treated with I+V (median duration 13.3 months [95% CI: 7.1 months-not estimable (NE)]). The median age was 70 years (range 47-86), 6 (18%) were women, and 20 (65%) had del(17p) or TP53 mutation. The median number of prior lines of therapy was 3 (range 1-15). Additional characteristics at the time of I+V start are shown in Table 1. Median follow-up from start of I+V was 23.8 months. Among 22 pts with prior progression on I only (V-naïve), the median duration of I+V was 14.8 months (95% CI 7.6 months-NE). The median duration on either I or V from the start of combination was 20.3 months (95% CI 8.3 months-NE). The median TTNT was 25.1 months (Figure 1A). Four pts proceeded to cellular therapy (alloSCT [n=3], CAR-T [n=1]) while on I+V. Next therapy (n=9) consisted of Richter transformation treatment (n=2), chemotherapy plus continued I+V (n=1), anti-CD20 plus continued I+V (n=1), duvelisib + I (n=1), TP-0903 + I (n=1), reintroduction of I at disease progression after previously stopping I during I+V therapy (n=1), and reintroduction of I (n=1) or V (n=1) at disease progression after previously stopping I+V. Of 9 pts who did not receive subsequent therapy, 4 pts remain on I+V (median duration 16.4 months), 4 pts continued V after discontinuing I (median duration on V from start of I+V was 21.5 months), and 1 pt discontinued I+V following a second cancer diagnosis and died without receiving additional CLL-directed treatment. Eleven pts received I+V in the double-refractory setting; 9 pts had prior disease progression on sequential I then V and 2 pts had prior disease progression on sequential V then I. The median duration of I+V was 7.5 months (95% CI 4.3 months-NE), and the median duration of either agent from I+V start was 10.8 months (95% CI 7.1 months-NE). The median TTNT was 14.0 months (Figure 1A). Eight pts required additional treatment, consisting of PI3K inhibitor (n=2), anti-CD20 added to I+V (n=1), CAR-T (n=1), anti-CD20 with (n=1) or without (n=1) bendamustine added to continued I, and Richter transformation treatment (n=2). One pt continues I+V (17.4 months ongoing) without further treatment. Two pts died from disease progression without receiving additional treatment. The median OS of all 33 pts was 27.4 months (95% CI 25.9 months-NE; Figure 1B). The median OS of the 22 pts with prior progression on I (V-naïve) was 47.1 months (95% CI 27.7 months-NE), and the median OS of the 11 pts with prior progression on I and V separately was 27.0 months (95% CI 15.5 months-NE). In univariate analyses, prior progression on V was a predictor of shorter OS (HR=3.9; 95% CI 1.4-11.2; p=0.01). CONCLUSIONS Combination I+V therapy in heavily pre-treated CLL pts who have disease progression after I provides durable benefit with a median OS approaching 4 years. In the double-refractory setting, repurposing both drugs as combination I+V therapy can be a useful strategy, despite the short-term disease control, for pts where clinical trial options are limited or not available. Further examination of these approaches in larger cohorts and understanding the operative resistance mechanisms in pts with double-refractory disease are key next studies. Figure 1 Figure 1. Disclosures Ding: Octapharma: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. Chanan-Khan: BeiGene, Jansen, Ascentage: Honoraria; Ascentage, Starton, Cellectar, NonoDev, Alpha2 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Alpha2 Pharmaceuticals: Patents & Royalties: Tabi; Ascentage: Research Funding; Cellectar: Current equity holder in publicly-traded company; Alpha2 Pharmaceuticals, NonoDev, Starton: Current holder of stock options in a privately-held company; BieGene, Jansen, Ascentage: Consultancy. Kenderian: Humanigen, Inc.: Consultancy, Honoraria, Research Funding. Wang: TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; Novartis: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees. Ailawadhi: Pharmacyclics: Consultancy, Research Funding; Xencor: Research Funding; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Sanofi: Consultancy; BMS: Consultancy, Research Funding; GSK: Consultancy, Research Funding; Ascentage: Research Funding; Medimmune: Research Funding; Karyopharm: Consultancy; Amgen: Consultancy, Research Funding; Beigene: Consultancy; AbbVie: Consultancy; Takeda: Consultancy; Genentech: Consultancy. Koehler: AbbVie: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Kay: AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: Combination ibrutinib and venetoclax in patients with relapsed CLL.

Abstract Background: ABO blood group is associated with pancreatic cancer risk. Whether ABO blood group alone or when combined with inherited mutation status of index pancreatic cancer cases (probands) can enhance pancreatic cancer risk estimation in first-degree relatives (FDR) is unclear. We examined FDRs' risk for pancreatic cancer based on probands' ABO blood group and probands' cancer susceptibility gene mutation status. Methods: Data on 23,739 FDRs, identified through 3,268 pancreatic cancer probands, were analyzed. Probands' ABO blood groups were determined serologically or genetically, and 20 cancer susceptibility genes were used to classify probands as “mutation-positive” or “mutation-negative.” SIRs and 95% confidence intervals (CI) were calculated, comparing observed pancreatic cancer cases in the FDRs with the number expected in SEER-21 (reference population). Results: Overall, FDRs had 2-fold risk of pancreatic cancer (SIR = 2.00; 95% CI = 1.79–2.22). Pancreatic cancer risk was higher in FDRs of mutation-positive (SIR = 3.80; 95% CI = 2.81–5.02) than mutation-negative (SIR = 1.79; 95% CI = 1.57–2.04) probands (P < 0.001). The magnitude of risk did not differ by ABO blood group alone (SIRblood-group-O = 1.57; 95% CI = 1.20–2.03, SIRnon-O = 1.83; 95% CI = 1.53–2.17; P = 0.33). Among FDRs of probands with non-O blood group, pancreatic cancer risk was higher in FDRs of mutation-positive (SIR = 3.98; 95% CI = 2.62–5.80) than mutation-negative (SIR = 1.66; 95% CI = 1.35–2.03) probands (P < 0.001), but risk magnitudes were statistically similar when probands had blood group O (SIRmutation-positive = 2.65; 95% CI = 1.09–5.47, SIRmutation-negative = 1.48; 95% CI = 1.06–5.47; P = 0.16). Conclusions: There is a range of pancreatic cancer risk to FDRs according to probands' germline mutation status and ABO blood group, ranging from 1.48 for FDRs of probands with blood group O and mutation-negative to 3.98 for FDRs of probands with non-O blood group and mutation-positive. Impact: Combined ABO blood group and germline mutation status of probands can inform pancreatic cancer risk estimation in FDRs.

AbstractMonoclonal B‐cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL) are clonal B‐cell disorders associated with an increased risk of infections and impaired vaccination responses. We investigated the immunogenicity of recombinant zoster vaccine (RZV) in these patients. Individuals with MBL/untreated CLL and Bruton tyrosine kinase inhibitor (BTKi)‐treated CLL patients were given two doses of RZV separated by 2 months. Responses assessed at 3 and 12 months from the first dose of RZV by an anti‐glycoprotein E ELISA antibody assay and by dual‐color Interferon‐γ and Interleukin‐2FLUOROSPOT assays were compared to historic controls matched by age and sex. About 62 patients (37 MBL/untreated CLL and 25 BTKi‐treated CLL) were enrolled with a median age of 68 years at vaccination. An antibody response at 3 months was seen in 45% of participants, which was significantly lower compared to historic controls (63%, p = .03). The antibody response did not significantly differ between MBL/untreated CLL and BTKi‐treated CLL (51% vs. 36%, respectively, p = .23). The CD4+ T‐cell response to vaccination was significantly lower in study participants compared to controls (54% vs. 96%, p < .001), mainly due to lower responses among BTKi‐treated patients compared to untreated MBL/CLL (32% vs. 73%, p = .008). Overall, only 29% of participants achieved combined antibody and cellular responses to RZV. Among participants with response assessment at 12 months (n = 47), 24% had antibody titers below the response threshold. Hypogammaglobulinemia and BTKi therapy were associated with reduced T‐cell responses in a univariate analysis. Strategies to improve vaccine response to RZV among MBL/CLL patients are needed.

Abstract Introduction: Identifying families with an underlying inherited cancer predisposition is a major goal of cancer prevention efforts. Mendelian risk models have been developed to better predict the risk associated with a pathogenic variant of developing breast/ovarian cancer (with BRCAPRO), and the risk of developing pancreatic cancer (PANCPRO). Given that pathogenic variants involving BRCA2 and BRCA1 predispose to all three of these cancers, we developed a joint risk model to capture shared susceptibility. Methods: We expanded the existing framework for PANCPRO and BRCAPRO to model underlying risk of pancreatic, breast, and ovarian cancer. We then validated this model on three datasets each reflecting the target populations for these models, including patients referred to a high-risk genetics clinic, patients with multiple family members with pancreatic cancer who underwent genetic testing for BRCA1/2, as well as a prospective registry of pancreatic cancer families. The new model is designated BRCAPANCPRO. Results: BRCAPANCPRO yielded good discrimination for differentiating BRCA1 and BRCA2 carriers from non-carriers (AUC = 0.84, 95% CI: 0.78, 0.87) and was reasonably well-calibrated for predicting future risk of pancreatic cancer (observed-to-expected (O/E) ratio = 0.82 [0.69, 0.94]). In these families, BRCAPANCPRO outperformed both the prior BRCAPRO and PANCPRO models. Discussion: The BRCAPANCPRO model improves the identification of families with a pathogenic variant in BRCA2 or BRCA1, particularly for families where there is the co-occurrence of pancreatic cancer in addition to breast and/or ovarian cancer. The model also improves the prediction of pancreatic cancer among families with a pancreatic cancer family history, with or without breast and/or ovarian cancer. Citation Format: Amanda L. Blackford, Erica J. Childs, Nancy Porter, Gloria Petersen, Kari Rabe, Steven Gallinger, Ayelet Borgida, Sapna Syngal, Ann Schwartz, Michele Cote, Ralph Hruban, Michael Goggins, Alison P. Klein, Giovanni Parmigiani. A risk prediction tool for individuals with a family history of breast, ovarian, or pancreatic cancer: BRCAPANCPRO [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 885.

Abstract Clinical practice guidelines recommend that individuals with HC MBL are evaluated annually for evidence of progression as it has been shown that they progress to develop CLL requiring therapy at a rate of 1-5%/year. Next-generation sequencing identified 59 genes recurrently mutated in CLL, and we previously showed that the tumor mutational load (TML), i.e., the total number of these genes mutated, is associated with a shorter time to first treatment (TTT) among 112 HC MBLs independent of the CLL international prognostic index (CLL-IPI), an established prognostic score. Herein, we continue to support our finding in additional HC MBLs and report the pooled results across the two cohorts. From the Mayo Clinic CLL Resource, we sequenced a total 167 HC MBL (112 from the initial round and 55 from additional sequencing). We extracted DNA from CD5+/CD19+ B-cells and sequenced the coding regions of 59 driver genes. Somatic mutations were called using MuTect2 in tumor-only mode. Germline variants were eliminated based on minor allele frequencies &gt;0.01% and by those identified in public databases, unless present in known CLL mutation hotspots. After filtering, we computed the TML based on the number of genes with high impact (nonsense, frameshift and splicing) and hotspot mutations. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI), adjusted for sex and CLL-IPI. Stratified analyses were conducted by low/intermediate risk and high/very high CLL-IPI. Of the 167 HC MBL, low risk CLL-IPI comprised 60%, intermediate risk 28%, high risk 12%; and none were very-high risk. The most commonly mutated genes were SF3B1 (11%), NOTCH1 (9%), TP53 (7%), BIRC3 (7%), and MYD88 (6%); and 52 (31%) individuals had mutations in at least one gene. The median follow-up was 4.4 years, and 26 of the 167 individuals progressed to CLL requiring therapy. HC MBL with ≥2 mutated genes had a 28% 5-year risk of needing therapy compared to 6% among those with no mutated genes. Similar to our initial finding (HR=1.53, CI:1.12-2.07; P=0.007), we found a shorter TTT in the additional HC MBLs (HR=4.63, CI:1.57-13.7, P=0.006), and in the pooled cohort (HR=1.72; CI:1.29-2.28, P=0.0002). When we stratified by CLL-IPI risk, TML remained associated with TTT among individuals with low/intermediate CLL-IPI risk in the additional HC MBLs (HR=3.52, CI:1.11-11.2, P=0.03) and in the pooled cohort (HR=2.25, CI:1.34-3.77, P=0.002). A non-significant 2.8 fold association was observed with high risk CLL-IPI in the pooled cohort. In conclusion, the TML along with the CLL-IPI provide clinicians with a more accurate prognostic information regarding disease progression requiring therapy, especially for those MBLs with low to intermediate risk based on CLL-IPI. If validated, these findings may modify current practice guidelines for individuals with HC MBL. Citation Format: Geffen Kleinstern, Cecilia Bonolo de Campos, Nicholas J. Boddicker, Daniel R. O'Brien, Shulan Tian, Chantel Barney, Kari G. Rabe, Cristine Allmer, Laura Bruins, Aaron D. Norman, Timothy G. Call, Sameer A. Parikh, Jose F. Leis, Wei Ding, Huihuang Yan, James R. Cerhan, Neil E. Kay, Celine Vachon, Esteban Braggio, Susan L. Slager. Tumor mutational load derived from recurrently mutated genes in chronic lymphocytic leukemia (CLL) predicts time-to-first treatment in high-count monoclonal B-cell lymphocytosis (HC MBL) [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 884.

Abstract Chronic lymphocytic leukemia (CLL) is a neoplastic disease of mature B-cells with a highly heterogeneous clinical course. While European ancestry (EA) populations present an increased incidence of CLL, African ancestry (AA) populations have a younger median age of onset, higher frequency of adverse prognostic factors, and inferior clinical outcomes. Despite the considerable effort to characterize the genetic landscape of CLL, AA are overwhelmingly underrepresented. Our hypothesis is that the clinical differences observed between AA and EA populations are, in part, explained by underlying genetic features. To address this imbalance, we identified 90 AA patients diagnosed with CLL, 64% of which were untreated at sample collection. RNA and DNA were extracted from CD5+/CD19+ clonal B-cells. We performed mRNA-seq and targeted sequencing in 59 recurrently mutated somatic CLL driver genes. Differentially expressed genes were identified using edgeR. Data was compared to our previously analyzed EA CLL cohort (N=445). The median age at diagnosis was 59 years for AA and 66 for EA and 74% of AA and 50% of EA had unmutated IGHV (u-IGHV) status. When evaluating the entire AA and EA cohorts, there was a significant increased frequency of mutations in TP53, SF3B1, and NFKBIE, identified in 29%, 24%, and 20% of AA CLLs, compared to 5%, 9%, and 9%, respectively, in EA CLLs (p&lt;0.01). When exclusively evaluating the untreated and u-IGHV cases, AA CLLs showed greater proportion of TP53 (30% vs 12%; p=0.0145), NFKBIE (30% vs 15%; p=0.0492), BIRC3 (21% vs 10%; p=0.0697), and KRAS (15% vs 7%; p=0.1683). Furthermore, there was an increase in mutations targeting relevant molecular pathways, such as NF-κB (42% vs 15%) and MAPK (18% vs 8%). Upregulation MAPK pathway was also confirmed by mRNA-seq analysis in the AA u-IGHV CLLs. Because of the high prevalence of TP53 mutations in the AA cohort, we further evaluated differential gene expression in the DNA Damage/Telomere Stress-Induced Senescence pathway. AA CLLs presented a significant downregulation of multiple genes associated with genome stability and cellular DNA damage response - DDR (including TP53 and ATM), double strand break repair (H2AFX and RAD50), telomere maintenance (POT1 and ACD), and cell cycle regulation (RB1, CCNA1, and CCNE2) (FDR&lt;0.05). DDR is responsible for DNA repair or induction of apoptosis, with its deficiency resulting in the accumulation of chromosomal aberrations, negatively impacting clinical outcome in CLL. Disparities in cancer are influenced by numerous factors that affect disease risk, screening and diagnosis, access to treatment, and survival. We identified an increased number of genomic alterations in the AA CLL cohort, primarily inducing activation of NF-κB and MAPK pathways and DDR impairment, with the increased frequency of mutations, notably in TP53 and BIRC3, expected to negatively impact prognosis. Citation Format: Cecilia Bonolo de Campos, Daniel R. O'Brien, Chantal E. McCabe, Huihuang Yan, Geffen Kleinstern, Zhiquan Wang, Laura A. Bruins, Cristine Allmer, Nicholas J. Boddicker, Charla R. Secreto, Aaron D. Norman, Shulan Tian, Kari G. Rabe, Timothy G. Call, Sameer A. Parikh, Jose F. Leis, Wei Ding, Richard Furman, J Brice Weinberg, James R. Cerhan, Celine M. Vachon, Neil E. Kay, Susan L. Slager, Esteban Braggio. Characterization of underlying genomic features among African ancestry populations diagnosed with chronic lymphocytic leukemia [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 2209.

Abstract The utility of the chronic lymphocytic leukemia-international prognostic index (CLL-IPI) in predicting outcomes of individuals with Rai 0 stage CLL and monoclonal B-cell lymphocytosis (MBL) is unclear. We identified 969 individuals (415 MBL and 554 Rai 0 CLL; median age, 64 years; 65% men) seen at Mayo Clinic between 1 January 2001 and 1 October 2018, and ascertained time to first therapy (TTFT) and overall survival (OS). After a median follow up of 7 years, the risk of disease progression needing therapy was 2.9%/y for MBL (median, not reached) and 5%/y for Rai 0 CLL (median, 10.4 years). Among patients with low, intermediate, and high/very high-risk CLL-IPI risk groups, the estimated 5-year risk of TTFT was 13.5%, 30%, and 58%, respectively, P&lt; .0001 (c-statistic = 0.69); and the estimated 5-year OS was 96.3%, 91.5%, and 76%, respectively, P&lt; .0001 (c-statistic = 0.65). In a multivariable analysis of absolute B-cell count with individual factors of the CLL-IPI, the absolute B-cell count was associated with shorter TTFT (hazard ratio [HR] for each 10 × 109/L increase: 1.31; P&lt; .0001) and shorter OS (HR: 1.1; P = .02). The OS of the entire cohort was similar to that of the age- and sex-matched general population of Minnesota (P = .17), although Rai 0 CLL patients with high and very high-risk CLL-IPI score had significantly shorter OS (P= .01 and P= .0001, respectively). The results of this study demonstrate the ability of CLL-IPI to predict time from diagnosis to first treatment (an end point not affected by therapy) in a large cohort of patients whose only manifestation of disease is a circulating clonal lymphocyte population.