Shanafelt, Tait D

Monoclonal B cell lymphocytosis (MBL) has been shown to be the precursor condition that precedes overt diagnosis of chronic lymphocytic leukemia (CLL). Whereas CLL is classified with greater than or equal to 5 × 109/L B lymphocytes in the peripheral blood, MBL is a clonal expansion of B-cells below this threshold. MBL can be further divided into high- or low-count based on whether the B-cell count is above or below 0.5 × 109/L. Approximately 10% of the population over 40 is estimated to have MBL, increasing to >50% over the age of 90. While low-count MBL is unlikely to progress, 1-2% of high-count (HC) MBL individuals progress to CLL requiring therapy per year. It is debatable if all patients with detectable MBL should be classified as an entity requiring monitoring by a hematologist, especially for low-count MBL. In addition, the diagnosis of leukemia is distressing to patients; therefore, it is important to identify HC MBL patients that are more likely to progress to disease requiring treatment and thus should be monitored more closely. As the majority of MBL cases phenotypically resemble CLL, established prognostic markers including recurrent chromosomal aberrations, beta-2 microglobulin levels, and the mutational status of the Immunoglobulin heavy-chain variable region locus (IGHV) have been shown to predict time to treatment (TTT) and overall survival (OS) in a large retrospective study of MBL1. CLL patients can also be divided into three distinct epigenetic subtypes that reflect progressive DNA methylation changes that occurs during B cell development. These 'epitypes' termed low-programmed (LP), intermediate-programmed (IP), and high-programmed (HP) independently predict clinical outcomes irrespective of disease stage and treatment2. LP-CLL patients follow a generally unfavorable clinical course compared to the more indolent HP-CLL patients, while IP CLL patients display an intermediate outcome. Here we sought to determine if epitype forecasts progression to CLL and eventual clinical outcome for individuals with MBL. We analyzed 66 individuals diagnosed with HC MBL at the Mayo Clinic with a median follow-up of 6.3 years. Developmental epitype was determined using our novel Methylation-iPLEX technique that interrogates 34 CpGs and assigns epitype using a random forest model2. Seventy-seven percent of the MBL cases were assigned to one of the three epitypes: 42.4% HP, 19.7% IP, and 15.2% LP. The residual 23% remained unclassified due to ambiguous (low confidence) epigenetic patterns or insufficient purity (Figure 1A). The overall proportion of HP and IP epitypes in MBL were significantly greater than proportions observed in CLL cohorts (P<0.01). Epitypes remained stable over time as 20/21 cases for which we obtained a high-confidence epitype classification at multiple time points remained unchanged. Epitype significantly predicted MBL individuals progressing to treatment (P=0.001) with LP individuals progressing in a median of 5.6 years (P=0.049 and P=0.0002 versus IP and HP, respectively); median was not reached in HP or IP (Figure 1B). Epitype also predicted overall survival (OS) in MBL (P=0.04), with LP individuals having a significantly shorter OS (median of 11 years versus not reached in IP and HP; P=0.056 and P=0.048 versus IP and HP, respectively). In this study we evaluated a cohort of 66 HC MBL cases and determined that classification using developmental DNA methylation epitypes can be employed in HC MBL to aid in risk stratification. HC MBL patients classified as LP are more likely to progress to requiring treatment and have a significantly reduced OS. The epigenetic classification may help clinicians decide how closely and frequently a HC MBL individual needs to be monitored. Figure 1: (A) Breakdown of the epigenetic subtype assigned to 66 HC MBL samples. (B) Kaplan-Meier analysis of time to treatment and (C) overall survival of MBL patients separated by epitype. 1. Parikh, S. A. et al. Outcomes of a large cohort of individuals with clinically ascertained high-count monoclonal B-cell lymphocytosis. Haematologica103, e237-e240 (2018). 2. Giacopelli, B. et al. Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia. Blood blood.2019000490 (2019). doi:10.1182/blood.2019000490 Disclosures Byrd: Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding. Shanafelt:Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Merck: Research Funding; Polyphenon E International: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Hospira: Research Funding; Glaxo-SmithKline: Research Funding; Abbvie: Research Funding; Cephalon: Research Funding; Celgene: Research Funding. Parikh:Genentech: Honoraria; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding. Kay:Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board.

Abstract Introduction: Several prognostic models for overall survival (OS) in chronic lymphocytic leukemia (CLL) have been developed, but none were derived for patients (pts) with relapsed or refractory (R/R) CLL treated in the era of novel agents. We used a comprehensive approach to derive and validate a novel risk model for OS in 2,475 pts with R/R CLL who received therapy in randomized phase 3 trials evaluating ibrutinib (IBR), idelalisib (IDELA), and venetoclax (VEN) vs control arms, or the Mayo Clinic CLL Database (MCCD). Methods: In collaboration with Janssen, Gilead, Pharmacyclics, and Genentech/Roche, the analysis included 2,475 pts from 6 multicenter randomized phase 3 trials or the MCCD. Trials included were: IBR plus bendamustine-rituximab (BR) vs placebo plus BR (HELIOS: NCT01611090), IBR vs ofatumumab (RESONATE: NCT01578707), IDELA plus BR vs placebo plus BR (Study 115: NCT01569295); IDELA plus rituximab vs placebo plus rituximab (Study 116: NCT01539512); IDELA plus ofatumumab vs ofatumumab (Study 119: NCT01659021); VEN plus rituximab vs BR (MURANO: NCT02005471). All pts had R/R CLL and required treatment by iwCLL criteria. The model-building dataset (n=969) included pts from HELIOS and RESONATE, and was randomly assigned to the IBR/chemoimmunotherapy (CIT) training dataset (n=727) and IBR/CIT internal-validation dataset(n=242). Three independent external validation datasets included IDELA/CIT (n=897), VEN/CIT (n=389), and MCCD (n=220). We applied univariate and multivariate analyses (MVA) to 28 candidate clinical/laboratory and genetic prognostic factors to derive the risk model in the training dataset. The primary endpoint was OS. We assessed the need for separate models for targeted agents by interactions with treatment in univariate analyses. We proceeded to develop a single model for all pts with R/R CLL, as only one candidate factor (del(13q), interaction p value <0.1) demonstrated a marginal differential effect. We evaluated cutoffs for dichotomized covariates and for definition of risk groups after the final factors were selected. We fit a Cox regression on the training and internal/external validation datasets using the risk categories as the covariate to test the difference among the groups, and calculated the C-statistic as a measure of discrimination. Results: Of 11 selected factors with a significant univariate effect on OS (p<0.1), 6 were independently prognostic in the MVA of OS (p<0.05): Baseline β2-microglobubulin (B2M), lactate dehydrogenase (LDH), hemoglobin (HGB), IGHV mutational status, number of prior therapies, and time from initiation of last therapy. We excluded number of prior therapies from the model, reasoning that its optimal cutoff might change with advances in CLL therapies. IGHV did not remain significant (p=0.0592) in MVA of 5 remaining prognostic factors. Notably, del(17p) was not independently prognostic for OS. The final risk model consisted of 4 prognostic factors: B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months. Because hazard ratios for each factor were similar (range, 0.55-0.68) with overlapping confidence intervals, 1 point was assigned to each factor. The resulting score separated pts into low (score 0-1), intermediate (score 2-3), and high risk (score 4) groups. Our risk model was prognostic for OS in the IBR/CIT training dataset (C-statistic 0.74 [95% CI 0.60-0.85]; log-rank p<0.0001) and was validated in the IBR/CIT internal validation (C-statistic 0.79 [95% CI 0.56-0.97]; log-rank p<0.0001), as well as in all 3 external validations: IDELA/CIT dataset (CS=0.71, 95% CI 0.59-0.81; log-rank p<0.001); VEN/CIT dataset (CS=0.76, 95% CI 0.66-0.85; log-rank p=0.01); MCCD (CS=0.61, 95% CI 0.56-0.66; log-rank p<0.001). Conclusions: We present the first validated risk model for OS in R/R CLL in the era of targeted therapies. Our model consists of 4 readily available factors (B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months), identifies 3 prognostic groups with significantly different OS, and has been validated for pts treated with all FDA approved targeted therapies: IBR, IDELA, and VEN. This identifies a well-defined cohort of pts with R/R disease with an unmet clinical need who are suitable for prospective trials targeting these pts. An exploratory analysis regarding prediction of MRD is ongoing. Figure. Figure. Disclosures Darif: Jannsen: Employment. Londhe:Jannsen: Employment. Xing:Gilead Sciences, Inc.: Employment. Mun:Genentech: Employment, Equity Ownership. Kay: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; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Shanafelt:Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Abbvie: Research Funding; Celgene: Research Funding. Furman:Loxo Oncology: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy; Verastem: Consultancy; Gilead: Consultancy; Incyte: Consultancy, Other: DSMB; Acerta: Consultancy, Research Funding; Genentech: Consultancy; Janssen: Consultancy; AbbVie: Consultancy. Hillmen:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Alexion Pharmaceuticals, Inc: Consultancy, Honoraria; Novartis: Research Funding; Gilead Sciences, Inc.: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees. Sharman:Acerta: Consultancy, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Research Funding. Seymour:AbbVie: Consultancy, Honoraria, Research Funding; Celgene: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding. Jones:Celgene: Employment, Equity Ownership. Ferrante:Jannsen: Employment. Dreiling:Gilead: Employment. Mobasher:F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC; Genentech Inc: Employment. Stark:Genentech: Employment. Reddy:Actinium Pharmaceuticals: Employment, Equity Ownership; Pharmacyclics: Employment. Howes:Janssen: Employment. James:Pharmacyclics: Employment. Bhargava:Gilead: Employment. Zelenetz:Novartis/Sandoz: Consultancy; Abbvie: Research Funding; Celgene: Consultancy; Amgen: Consultancy; Gilead: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech/Roche: Consultancy, Research Funding.

Abstract The targeted therapy ibrutinib inhibits B cell receptor signaling (BTK inhibitor) and has yielded high response rates and durable remissions in patients with chronic lymphocytic leukemia (CLL). However, it is widely believed that the addition of immune therapies to targeted drugs will be required to activate anti-tumor immunity and work towards curative therapy. Identifying effective combinations of targeted drugs and/or standard chemotherapy with immunotherapy is a priority research area and particularly relevant for CLL, as patients' T cells have been shown to exhibit profound tolerance/exhaustion and notably, no activity was reported in a recent trial of anti-PD-1 immunotherapy for relapsed disease. Ibrutinib has shown beneficial immunomodulatory activity in CLL by inhibiting IL-2-inducible T cell kinase (ITK) as well BTK that is associated with increased effector CD4+and CD8+ T cell numbers and decreased expression of inhibitory checkpoint receptors such as PD-1 on patient T cells. Here we have performed comparative immune bioassays from a randomized phase III trial comparing ibrutinib-based therapy to traditional FCR chemoimmunotherapy to assess the effects of treatments on anti-tumor T cell function. Viable peripheral blood mononuclear cell samples were collected serially (baseline, 6 months and 12 months) from CLL patients on the randomized phase III E1912 trial of ibrutinib and rituximab versus FCR for previously untreated disease to allow longitudinal batched immune analysis. Cytotoxicity assays revealed that highly purified CD3+ T cells from the FCR treated patients at 6 and 12-month time-points did not change their activated killing function against autologous baseline CD19+ CLL tumor B cells (acting as target antigen-presenting cells pulsed with superantigen, sAg) compared to pre-treatment/baseline exhausted T cells (n=22). In contrast, patients treated with ibrutinib-based therapy had a significant increase in activated anti-tumor T cell killing function (P<.01, n=22) at both 6-month (66% increase) and 12-month (89% increase) time-points. Flow cytometric analysis of circulating immune subsets revealed that the percentage of PD-1 and PD-L1 positive cells among CD8+ and CD4+ T cells (particularly effector compartments) were reduced with ibrutinib-based therapy, whereas only a partial reduction was detected following FCR treatment. However, patients' T cells from both treatment arms responded normally to T cell receptor engagement by upregulating these checkpoint molecules. This led us to explore ex vivo treatment of highly purified CD3+ T cells and CD19+ CLL B cells from both treatment arms with anti-PD-L1 or anti-PD-1 immunotherapy prior to cytotoxicity assays. Our functional data revealed that the T cells from both FCR time-points (6 and 12-months) were not sensitive to either anti-PD-L1 (n=14) or anti-PD-1 (n=14) treatment. In contrast, ibrutinib-based treatment sensitized anti-tumor T function (23% increase in killing) following anti-PD-L1 treatment (n=14) at the 6-month time-point only (P<.01) but not with anti-PD-1. To investigate the mechanism underlying these effector function differences, we compared the ability of highly purified CD3+ T cells from each treatment arm (n=45) time-point to form F-actin immunological synapses with baseline autologous CLL tumor B cells. Quantitative confocal image analysis revealed that ibrutinib-based therapy significantly (P<.01) enhanced polarization of F-actin, tyrosine-phosphorylated proteins and granzyme B at immune synapses with tumor cells at both 6 and 12-month time-points, whereas FCR treated patient T cells failed to mobilize these lytic synapse molecules. Importantly, our assays have revealed that T cells from both FCR treatment time-points formed "non-polarized" immune synapses with tumor cells, in keeping with cytotoxic dysfunction and insensitivity to additional checkpoint immunotherapy. In contrast, our functional correlative bioassays have revealed that ibrutinib-based therapy can reactivate exhausted cytolytic T cell function and suggest to us, a potential therapeutic window for anti-PD-L1 immunotherapy at the earlier 6-month time-point. We believe this data supports the concept of incorporating functional bioassays to immune-monitoring assays associated to clinical trials that should aid knowledge-led design of future combination immunotherapy. Disclosures Kay: 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; Acerta: Research Funding; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: 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; Celgene: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding. Shanafelt:Pharmacyclics: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding; Jansen: Research Funding. Ramsay:Celgene Corporation: Research Funding; Roche Glycart AG: Research Funding; MedImmune: Research Funding.

Abstract The characteristic clinical heterogeneity observed in chronic lymphocytic leukemia (CLL) reflects its biological diversity and as a consequence, better understanding of the biology of this disease has led to the identification of a number of useful prognostic tools. Advances in massively parallel sequencing technologies have unearthed genetic and epigenetic heterogeneity and reinforced the concept that specific genetic lesions and the development of genomic complexity can modulate the pathology of CLL. In addition, DNA methylation profiling has shown that CLL patients can be grouped into at least three clinically relevant epigenetic subgroups with distinct outcomes. However, despite this explosion in knowledge, defining the prognosis of individual CLL patients remains a significant clinical challenge. Consequently, there is a need to identify prognostic tests that can provide reliable personalized risk assessments. We have recently shown that a subset of CLL patients manifest telomere dysfunction, which drives genomic instability and clonal evolution. We went on to show an association between short, dysfunctional telomeres and 'high-risk' genetic lesions1,2. Importantly, longitudinal analysis confirmed that tumor cell telomere length remained remarkably stable throughout the course of the disease suggesting that the telomere length is fixed at an early point in disease pathogenesis making it a reliable predictor of both clinical progression and overall survival (OS) regardless of when the measurement is made. In this study, we generated telomere length profiles in 224 newly diagnosed, early stage CLL patients seen at the Mayo clinic in Rochester using high-throughput single telomere length analysis (HT-STELA). We then tested the ability of telomere length to predict time to treatment (TTT) and OS and compared its predictive power with DNA methylation profiling and CLL-IPI scores. Patients with a mean telomere length inside the fusogenic range (IFR) had a significantly shorter time to treatment (P<0.0001; HR = 3.2) and OS (P = 0.0027; HR = 2.3) when compared to patients with a mean telomere length outside the fusogenic range (OFR) (Figure 1A and B). When considering epigenetic subgroups, we found a strong association between telomere length and 'epitype'; high programmed (HP) CLL cells had significantly longer telomeres than intermediate programmed (IP), and low programmed (LP) CLL cells (P = 0.0002 and P<0.0001 respectively). Furthermore, bifurcation of the HP and IP groups into telomere length OFR and IFR subsets identified patients with distinctly different TTT (P = 0.0008; HR = 2.74) and OS (P = 0.004; HR = 2.4). 79/81 (97.5%) of the LP group had short telomere length IFR, but when we divided the LP group above and below the mean telomere length of the fusogenic range (≤/>2.17kb), patients with the shortest telomeres had a significantly worse OS (P = 0.034; HR = 2.83). Telomere length was also strongly associated with CLL-IPI score; the CLL-IPI low-risk group (CLL-IPI 1) had the longest telomeres and the CLL-IPI high-risk group (CLL-IPI 4) had the shortest telomeres (P<0.0001). More heterogeneity in telomere length was observed in the CLL-IPI 1 and 2 groups and patients with telomere length IFR in these 'low-risk' groups showed significantly shorter TTT (P<0.0001; HR = 4.24) and overall survival (P<0.0001; HR = 10.1) (Figure 1C and 1D). Finally, multivariate modelling, using Cox proportional hazards with forward selection, revealed that telomere length retained independent prognostic significance when CLL-IPI score was entered in the model for time to treatment (HR = 1.42; P = 0.023) and OS (HR = 1.68; P = 0.008). In conclusion, telomere length analysis provides more accurate prognostic information about the progression and outcome of CLL patients and can augment the prognostic power of the CLL-IPI for early stage CLL. References Lin TT et al. Blood. 2010;116(11):1899-907. Britt-Compton et al. Leukemia. 2012; 26(4):826-30. Disclosures Norris: Cardiff University: Patents & Royalties: Telomere measurement patent. Shanafelt:GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Jansen: Research Funding. Kay:Acerta: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: 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; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees. Fegan:Napp: Honoraria; Gilead Sciences, Inc.: Honoraria; Roche: Honoraria; Abbvie: Honoraria; Janssen: Honoraria. Baird:Cardiff University: Patents & Royalties: Telomere measurement patents. Pepper:Cardiff University: Patents & Royalties: Telomere measurement patents.

Abstract Clonal hematopoiesis of indeterminate potential (CHIP) is defined as somatic mutations in clonal blood cells of individuals without any other hematological abnormalities and have been identified using whole exome sequencing (WES) from pre-specified genes. CHIP is reportedly associated with aging, reduced overall survival, cardiovascular disease, and hematologic disease, mainly myeloid cancers. Additionally, whole genome sequencing and WES studies in CLL cases have identified putative CLL driver genes with recurrent somatic variants or copy number alterations. Here, we investigate the associations of CHIP and mutations in CLL somatic driver genes with risk of CLL and MBL, a precursor to CLL. Using WES, 571 individuals from 132 CLL families were sequenced from two different sites, Mayo Clinic (92 families) and National Cancer Institute (NCI, 40 families), including 251 CLLs, 74 MBLs, and 246 unaffected relatives. DNA was extracted from buccal cells (Mayo Clinic) and peripheral blood (NCI). Allele counts from gVCF files were extracted for specific genes and analyzed. Variants were annotated using the Variant Effect Predictor in Ensembl, genome build GRCh37 (http://useast.ensembl.org/index.html). Highly-sensitive flow cytometry of the blood was used to screen for MBL. CHIP was defined as in Genovese et al., 2014 as the presence of any of the following: A) disruptive mutations in ASXL1, TET2, or PPM1D; B) missense mutation p.617F in JAK2; C) disruptive or missense mutations in DNMT3Alocalized to exons 7 to 23D) any mutations reported at least 7 times in hematological malignancies in the Catalogue of Somatic Mutations in Cancer (COSMIC); and (E) No variant allelic fraction (VAF) threshold. CLL driver genes included disruptive or missense mutations in ATM, BIRC3, MYD88, NOTCH1, SF3B1, TP53, EGR2, POT1, NFKBIE, XPO1, or FBXW7with VAF greater than 0.1. Mutations from COSMIC and CLL driver genes were excluded if the minor allele frequency in 1000 Genomes was greater than 0.5%. Data was analyzed using logistic regression adjusting for age, sex, and site. Odds ratios (OR) and 95% confidence intervals (CI) were estimated. Median age for CLL, MBL, and unaffected was 63, 61.5, and 54, respectively. The unaffected relatives were significantly younger than both the CLL and MBL groups (p<0.0001), with no difference between CLL and MBL (p=0.46). A total of 70 (12%) individuals from 54 different families had CHIP. CHIP was characterized in the majority of samples as mutations in DNMT3A, ASXL1, and TET2with 43, 9 and 8 individuals, respectively. As expected, CHIP was associated with age (p<0.001) but not sex (p=0.87). CHIP was present in 42 (17%) CLLs, 9 (12%) MBLs, and 19 (8%) unaffected relatives. There was a significant association between the presence of CHIP and CLL risk compared to unaffected relatives (OR= 2.19, 95% CI: 1.20 - 4.13, p=0.013) but not with MBL risk (OR=1.34, 95% CI: 0.54 - 3.11, p=0.51). Using the CLL driver genes, we found mutations in 119 (47%) CLL, 20 (27%) MBL, and 70 (29%) unaffected relatives. Mutations in CLL driver genes were associated with CLL risk compared to unaffected relatives (OR = 2.51, 95% CI: 1.64 - 3.87, p<0.0001), but there was no evidence for increased MBL risk (OR = 1.00). These results held when we subset the analysis to the Mayo only data where the DNA was extracted from buccal cells. This study further supports the association between mutations in CHIP related genes and risk of hematologic malignancies, in particular CLL. This is the first report of the prevalence of CHIP in MBLs. Although MBL and CHIP represent clonal population of blood cells, our data suggest the clones are different. Mutations in CLL driver genes are also associated with CLL risk but show little to no evidence with increased MBL risk. Interestingly, our unaffected relatives of CLL cases also had a high frequency of CLL driver mutations. Future studies are needed to understand these acquired mutations (both in CHIP- and CLL driver- related genes) in the unaffected to MBL to CLL continuum. Disclosures Parikh: Abbvie: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AstraZeneca: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Research Funding. Ding:Merck: Research Funding. Cerhan:Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding; Nanostring: Research Funding. Shanafelt:Jansen: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding. Kay:Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; 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; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

Abstract Background MBL is a precursor state to CLL, with a prevalence of ~5-8% in the general population and 15-18% in CLL families. To date, 41 single nucleotide polymorphisms (SNPs) have been found to be associated with CLL. We previously showed that a PRS of the weighted average of the number of risk alleles of these SNPs is associated with CLL risk using cases and controls from the International Lymphoma Epidemiology (InterLymph) Consortium. We validated this score in an independent sample of CLL cases and controls from the Genetic Epidemiology of CLL (GEC) Consortium, a cohort of families with ≥2 members with CLL. In the CLL families we also reported an association between the PRS and MBL risk, where 93% of MBLs were low-count MBL. Here we evaluate the PRS in an independent sample ascertained from the Mayo Clinic Biobank. Methods The Mayo Clinic Biobank is a large-scale bio-repository of adult patients assembled to provide a wide array of health-related research studies. Biobank participants (N=2530) were screened for MBL using a highly-sensitive, 8-color (CD38, CD45, Kappa, Lambda, CD19, CD23, CD5 and CD20) flow-cytometry assay on stored cryopreserved peripheral blood mononucleotide cells. Low-count and high-count MBL were defined as those individuals who had <85% and ≥85 clonal B-cells out of total B-cells, respectively. Individuals without MBL ("controls") were frequency matched to MBLs based on age and sex, after excluding non-Caucasian and non-interpretable flow results. Participants were genotyped using the Illumina OmniExpress array. Standard genotyping quality-control metrics were applied. We computed the PRS as previously published and categorized it by quintiles based on values previously used with InterLymph controls. The middle quintile served as the reference category. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CI), adjusting for age at consent, sex, and socioeconomic status. In addition, we compared the median PRS by low-count MBL and high count MBL using the Mann-Whitney U test. Results We identified 276 MBLs overall and 2109 controls; 97% (N=267) of MBLs had low-count MBL and only 3% (N=9) had high-count MBL. We then selected 844 controls frequency matched to the MBL cases on age and sex. Family history of leukemia/lymphoma was 11.3% among MBLs overall and 8.8% among controls. The median PRS was 7.88 and 7.46 (Figure) among MBLs overall and controls, respectively. The continuous PRS had a 1.75-fold increased risk for MBL overall (CI:1.5-2.1, P=2.65x10-12). Compared to the middle quintile, the highest quintile had 2.2-fold increased risk for MBL overall (CI:1.5-3.3, P=1.46x10-4) and the lowest quintile had 0.6-fold decreased risk (CI:0.4-0.96, P=0.03). The median PRS for low-count and high count MBL were 7.86 and 8.04, respectively. The continuous PRS had a 1.75-fold increased risk for low-count MBL (CI:1.5-2.1, P=4.81x10-12) and a 1.89-fold increased risk for high-count MBL (CI:0.8-4.2, P=0.13), however, the effect is not statistically significant between high-count and low-count MBL (P=0.89). Conclusion In this independent sample, we validated our previous findings that the CLL PRS is associated with MBL risk. Although the sample size of high-count MBL was limited (N=9), there is evidence of a weak trend towards a higher PRS compared to low-count MBL and controls Larger sample size of high-count MBL is warranted in order to stratify MBL risk by low-count and high-count MBL. These results may help identify individuals at higher risk of MBL including low-count and high-count MBL, beyond the risk associated with age and family history of CLL. Figure: Polygenic risk score distribution by control and MBL status Figure. Figure. Disclosures Parikh: Janssen: Research Funding; Pharmacyclics: Honoraria, Research Funding; Gilead: Honoraria; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; MorphoSys: Research Funding. Cerhan:Nanostring: Research Funding; Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board. Kay:Janssen: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: 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; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: 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. Shanafelt:Genentech: Research Funding; Pharmacyclics: Research Funding; GlaxoSmithKline: Research Funding; Jansen: Research Funding.

Abstract BACKGROUND: Chronic lymphocytic leukemia (CLL) is one of the most common lymphoid malignancies, accounting for ~11% of all hematologic neoplasms. Over the last 15 years, a series of phase 3 trials have established that chemoimmunotherapy (CIT) with fludarabine, cyclophosphamide, and rituximab (FCR) improves both progression free survival (PFS) and overall survival (OS) compared with chemotherapy alone. FCR is the gold standard for young fit patients with treatment naïve CLL. In parallel with the advances in CIT, a profound increase in the understanding of CLL B-cell biology led to new therapeutic approaches.1 Among these, ibrutinib (an irreversible inhibitor of Bruton's Tyrosine Kinase [BTK]) has had the largest impact on clinical practice to date. Initial trials of ibrutinib demonstrated robust and durable efficacy in patients with relapsed/refractory disease. Subsequent phase 3 trials showed improved PFS and OS with ibrutinib relative to chlorambucil in previously untreated, older CLL patients. Despite these advances, the efficacy of ibrutinib as a first-line treatment for younger CLL patients (i.e. <70) relative to the most efficacious CIT regimens, such as FCR, is unknown. METHODS: Eligible patients were treatment-naive individuals with CLL who were age <70 and required therapy. Patients with deletion 17p- were excluded from participating given the poor response of these patients to FCR therapy. Participants were randomly assigned in a 2:1 ratio to receive ibrutinib (420 mg/day until disease progression) and rituximab (50 mg/m2 on day 1 of cycle 2; 325 mg/m2 on day 2 of cycle 2; 500 mg/m2 on day 1 of cycles 3-7) or six courses of intravenous fludarabine (25 mg/m2 ) and cyclophosphamide (250 mg/m2) days 1-3 with rituximab (50 mg/m2 on day 1 of cycle 1; 325 mg/m2 on day 2 of cycle 1; 500 mg/m2 on day 1 of cycles 2-6) every 28-days. The planned accrual was 519 patients. Hematologic toxicity was graded according to the 2008 IWCLL Working Group scale. All other adverse events were graded according to the NCI Common Toxicity Criteria (version 4). The primary endpoint was PFS with a secondary endpoint of overall survival (OS). Analysis was by intention to treat. The first planed interim analysis for PFS was scheduled to occur 24-27 months after full accrual with the first interim analysis for OS scheduled to occur if the boundary for PFS was crossed. The primary analysis was a stratified logrank test applied to all patients as randomized. Treatment effect p-values are one-sided. The study was approved by the Central Institutional Review Board for the National Cancer Institute, conducted in accordance with the principles of the Declaration of Helsinki, and registered with ClinicalTrials.gov (NCT02048813). RESULTS: A total of 529 patients were accrued between January 31, 2014 and June 9, 2016. 354 patients were assigned to ibrutinib and rituximab (IR) and 175 to FCR. Nineteen patients did not start protocol therapy. The first interim analysis was performed September 2018. With median follow-up of 33.4 months, we observed 77 PFS events and 14 deaths. The hazard ratio (HR) for PFS favored IR over FCR (HR=0.352; 95% CI 0.223-0.558; p<0.0001) which crossed the pre specified boundary. The HR for OS also favored the IR arm (HR=0.168, 95% CI 0.053-0.538; p=0.0003, pre-specified boundary for superiority p=0.0005). Kaplan-Meier estimates for PFS and OS are shown in Figure 1A and 1B. In subgroup analysis for PFS, IR was superior to FCR independent of age, sex, performance status, disease stage or the presence/absence of del11q23. With current follow-up, IR was also superior to FCR for IGHV unmutated patients (HR=0.262; 95% CI 0.137-0.498; p<0.0001) but not IGHV mutated patients (HR=0.435; 95% CI 0.140-0.1350; p=0.07). Grade 3 and 4 treatment-related adverse events were observed in 58% of IR and 72% of FCR treated patients (p=0.0042). Specifically, FCR was more frequently associated with grade 3 and 4 neutropenia (FCR: 69 [44%] of 158 vs. IR: 80 [23%] of 352; p<0·0001) and infectious complications (FCR: 28/158 [17.7%] vs. IR: 25/352 [7.1%]; p<0.0001). CONCLUSIONS: The combination of ibrutinib and rituximab provides superior PFS and OS relative to FCR for patients with previously untreated CLL age <70. These findings have immediate practice changing implications and establish ibrutinib-based therapy as the most efficacious first-line therapy for patients with CLL. Disclosures Shanafelt: Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; Celgene: Research Funding; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Abbvie: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding. Kay:Janssen: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Gilead: 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; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees. O'Brien:Amgen: Consultancy; Astellas: Consultancy; Celgene: Consultancy; GlaxoSmithKline: Consultancy; Janssen: Consultancy; Aptose Biosciences Inc.: Consultancy; Vaniam Group LLC: Consultancy; Abbvie: Consultancy; Alexion: Consultancy; Kite Pharma: Research Funding; Regeneron: Research Funding; Acerta: Research Funding; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding. Barrientos:Pharmacyclics/AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees; astra Zeneca: Membership on an entity's Board of Directors or advisory committees. Erba:Seattle Genetics: Consultancy, Research Funding; Pfizer: Consultancy, Other: grant; Novartis: Consultancy, Speakers Bureau; Pfizer: Consultancy, Other: grant; Pfizer: Consultancy, Other: grant; Incyte: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Astellas: Research Funding; Janssen: Research Funding; Janssen: Research Funding; Amgen: Research Funding; Amgen: Research Funding; Novartis: Consultancy, Speakers Bureau; Astellas: Research Funding; Incyte: Consultancy, Speakers Bureau; Astellas: Research Funding; Pfizer: Consultancy, Other: grant; Novartis: Consultancy, Speakers Bureau; Juno: Research Funding; Juno: Research Funding; Novartis: Consultancy, Speakers Bureau; MacroGenics: Consultancy; MacroGenics: Consultancy; Amgen: Research Funding; Takeda/Millenium: Research Funding; Amgen: Research Funding; Takeda/Millenium: Research Funding; Seattle Genetics: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Immunogen: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Celgene: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding; MacroGenics: Consultancy; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Daiichi Sankyo: Consultancy, Research Funding; Juno: Research Funding; Juno: Research Funding; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Celgene: Consultancy, Speakers Bureau; Daiichi Sankyo: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Daiichi Sankyo: Consultancy, Research Funding. Stone:Juno: Consultancy; Macrogenics: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Research Funding; FujiFilm: Consultancy; Sumitomo: Consultancy; Ono/Theradex: Consultancy; Otzuka/Astex: Consultancy; Pfizer: Consultancy; Roche: Consultancy; AbbVie: Consultancy, Research Funding; Actinium: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Argenx: Membership on an entity's Board of Directors or advisory committees; Arog: Consultancy, Research Funding; Astellas: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy; Celator / Jazz: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cornerstone: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Tallman:ADC Therapeutics: Research Funding; Daiichi-Sankyo: Other: Advisory board; BioSight: Other: Advisory board; AbbVie: Research Funding; Cellerant: Research Funding; AROG: Research Funding; Orsenix: Other: Advisory board.