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OBJECTIVE The MHC region harbors the strongest loci for latent autoimmune diabetes in adults (LADA); however, the strength of association is likely attenuated compared with that for childhood-onset type 1 diabetes. In this study, we recapitulate independent effects in the MHC class I region in a population with type 1 diabetes and then determine whether such conditioning in LADA yields potential genetic discriminators between the two subtypes within this region. RESEARCH DESIGN AND METHODS Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects). RESULTS The strongest associations in the MHC class II region (rs3957146, β [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (β [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, β [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA. CONCLUSIONS In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.

Abstract The IGHV4-34 gene is very frequent (~10%) in the B cell receptor immunoglobulin (BcR IG) gene repertoire of chronic lymphocytic leukemia (CLL). Over 30% of IGHV4-34 CLL cases can be assigned to different subsets with stereotyped BcR IG. The largest is subset #4 which represents ~1% of all CLL and ~10% of IGHV4-34 CLL and is considered a prototype for indolent disease. The BcR IG of a great majority (~85%) of IGHV4-34 CLL cases carry a significant load of somatic hypermutation (SHM), often with distinctive SHM patterns. This holds especially true for stereotyped subsets and is suggestive of particular modes of interactions with the selecting antigen(s). In detail, subsets #4 and #16, both involving IgG-switched cases (IgG-CLL), exhibit the greatest sequence similarity in SHM profiles, whereas they differ in this respect from IgM/D subsets #29 and #201. Prompted by these observations, here we explored the extent that these subset-biased SHM profiles in different IGHV4-34 stereotyped subsets were reflected in distinct demographics, clinical presentation, genomic aberrations and outcomes. Within a multi-institutional series of 20,331 CLL patients, 1790 (8.8%) expressed IGHV4-34 BcR IG. Following established bioinformatics approaches for the identification of BcR IG stereotypy, 573/1790 IGHV4-34 CLL cases (32%) were assigned to stereotyped subsets; of these, 340 cases (19% of all IGHV4-34 CLL and 60% of stereotyped IGHV4-34 cases) belonged to subsets #4, #16, #29 and #201, all concerning IGHV-mutated CLL (M-CLL). Clinicobiological information was available for 275/340 patients: #4, n=150; #16, n=44; #29, n=39; and #201, n=42. Comparisons between subsets revealed no differences in gender and age distribution. Interestingly, however, 36-43% of each subset cases were young for CLL (defined as patients aged ≤55 years), which is higher compared to general CLL cohorts, where young patients generally account for ~25% of cases. In contrast, significant differences were identified between subsets regarding: (i) disease stage at diagnosis, with >90% of IgG subsets #4 and #16 diagnosed at Binet stage A versus 83% in subset #201 and 74% in subset #29 (p=0.029); (ii) CD38 expression, ranging from 1% in subset #4 to 10% in subset #201 (p=0.013); (iii) the distribution of del(13q), peaking at a remarkable 92% in subset #29 versus only 37% in subset #16 (p<0.0001). Regarding other genomic aberrations, they were either absent (NOTCH1 mutations) or rare (SF3B1 mutations, trisomy 12, del(11q), TP53 aberrations due to either del(17p) and/or TP53 mutations). The sole exception concerned a high frequency (14%) of TP53 aberrations in subset #29 (p<0.05 compared with the other subsets), which is notable for M-CLL cases in general. Time to first treatment (TTFT) could be analyzed in 228 cases. IgG subsets #4 and #16 had significantly (p=0.036) longer TTFT (median TTFT: not yet reached) compared to the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). In conclusion, we have identified distinct clinicobiological profiles for different stereotyped IGHV4-34 M-CLL subsets, highlighting subsets #4 and #16 as particularly indolent, which is important for both medical and social reasons, especially considering that a significant proportion of patients in these subsets are diagnosed at younger ages. Our findings support the notion that BcR IG stereotypy refines prognostication in CLL, superseding the crude immunogenetic distinction based on SHM load only. Additionally, the observed heterogeneity suggests that not all M-CLL are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Disclosures Tausch: Gilead: Other: Travel support. Shanafelt:Glaxo-Smith_Kline: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Polyphenon E Int'l: Research Funding; Hospira: Research Funding; Janssen: Research Funding; Pharmactckucs: Research Funding; Cephalon: Research Funding. Niemann:Gilead: Consultancy; Janssen: Consultancy; Roche: Consultancy; Novartis: Other: Travel grant. Langerak:InVivoScribe: Patents & Royalties: Licensing of IP and Patent on BIOMED-2-based methods for PCR-based Clonality Diagnostics.; DAKO: Patents & Royalties: Licensing of IP and Patent on Split-Signal FISH. Royalties for Dept. of Immunology, Erasmus MC, Rotterdam, NL; Roche: Other: Lab services in the field of MRD diagnostics provided by Dept of Immunology, Erasmus MC (Rotterdam). Hallek:Celgene: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; AbbVie: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Roche: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Boehringher Ingelheim: Honoraria, Other: Speakers Bureau and/or Advisory Boards; Pharmacyclics: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Mundipharma: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Janssen: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Gilead: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding. Ghia:Janssen Pharmaceuticals: Research Funding.

Purpose: Multiple myeloma (MM) is a plasma cell (PC) malignancy with an increasing incidence in the US. Epidemiological studies demonstrate a 2-3 fold higher incidence of the pre-malignant monoclonal gammopathy of undetermined significance (MGUS) and MM with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). With equal access to care, AAs have better overall survival compared to EAs (Waxman, Blood, 2010). This disparity may be explained by ancestral-associated genetic predisposition of AAs to development of monoclonal gammopathies and to specific acquired, cytogenetically-defined subtypes. Using calculated genetic ancestry data, we have previously identified a higher prevalence of IgH translocations t(11;14), t(14;16) and t(14;20) in individuals with >80% African ancestry (Baughn, BCJ, 2018). Since SNP rs9344 encoding the CCND1 870G>A polymorphism has been reported in association with increased risk of t(11;14) (Weinhold, Nature Genetics, 2013), we investigated whether rs9344 correlates with African ancestry and with t(11;14) in our cohort of patients with plasma cell dyscrasias. Methods: We studied 898 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from bone marrow samples was genotyped on the Precision Medicine Research Array and biogeographical ancestry was assessed using the Geographic Population Structure Origins tool (Elhaik, Nat Commun, 2014). Plasma cell proliferative disorder FISH of immunoglobulin (cIg)-stained positive plasma cells was performed as described (Baughn, BCJ, 2018). Individuals were divided into three ancestral groups: 1. EAs (<0.1% African ancestry and <30% Asian ancestry); 2. AAs (> 80% African ancestry); and 3. Other. Chi-squared test was used to determine the overall comparison between the 3 ancestral groups and also between ancestral groups 1 vs 2, and 2 vs 3 using pairwise comparison. All tests were two-sided with alpha level set at 0.05 for overall statistical significance. Pairwise comparison was considered statistically significant when p<0.025 based on Bonferroni method for multiple comparisons. Results: We identify increased risk of development of either a t(11;14), t(14;16) or t(14;20) in AAs (48.8%) compared to EAs (33.6%) (p-value=0.0051). To explore the genetic basis of increased t(11;14) specifically (37.4% AAs vs. 27.3% p-value=0.049), we evaluated the frequency of the G risk allele of rs9344 in relation to African ancestry. The frequency of the G risk allele was higher in AAs (0.81) compared to EAs (0.59) (p-value <0.0001) and also higher in t(11;14) cases (0.73) compared to non-t(11;14) controls (0.58) (p-value <0.0001). A multivariate model identified only rs9344 as significantly associated with t(11;14) after adjusting for age, gender and race group suggesting that it plays a role in the development of t(11;14) (p-value <0.001 for GG, p-value=0.005 for AG). To test if these results are replicable, we studied the MMRF CoMMpass cohort. This cohort includes individuals with newly diagnosed MM along with self-report race information and translocation data from long insert whole genome sequencing. Although t(11;14) was not enriched in self-reported Black individuals from this cohort (17.5% Black vs. 20.4% White, p-value=0.47), there was association between the rs9344 and self-reported Black race (p-value <0.0001) and with the presence of t(11;14) when the t(11;14) was analyzed by long insert whole genome sequencing (p-value=0.0001). Conclusions: To our knowledge, this study includes the largest group of African individuals with an abnormal plasma cell clone along with uniformly collected FISH, genotyping and ancestry data. We have identified in this diverse population the association of the CCND1 870G>A polymorphism (rs9344) with African ancestry and with t(11;14) suggesting that it plays a role in the development of t(11;14) plasma cell dyscrasias. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; NanoString: Research Funding. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Dispenzieri:Alnylam: Research Funding; Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Kumar:Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Research Funding.

Abstract Pathogenic sequence variants (PSV) in BRCA1 or BRCA2 (BRCA1/2) are associated with increased risk and severity of prostate cancer. We evaluated whether PSVs in BRCA1/2 were associated with risk of overall prostate cancer or high grade (Gleason 8+) prostate cancer using an international sample of 65 BRCA1 and 171 BRCA2 male PSV carriers with prostate cancer, and 3,388 BRCA1 and 2,880 BRCA2 male PSV carriers without prostate cancer. PSVs in the 3′ region of BRCA2 (c.7914+) were significantly associated with elevated risk of prostate cancer compared with reference bin c.1001-c.7913 [HR = 1.78; 95% confidence interval (CI), 1.25–2.52; P = 0.001], as well as elevated risk of Gleason 8+ prostate cancer (HR = 3.11; 95% CI, 1.63–5.95; P = 0.001). c.756-c.1000 was also associated with elevated prostate cancer risk (HR = 2.83; 95% CI, 1.71–4.68; P = 0.00004) and elevated risk of Gleason 8+ prostate cancer (HR = 4.95; 95% CI, 2.12–11.54; P = 0.0002). No genotype–phenotype associations were detected for PSVs in BRCA1. These results demonstrate that specific BRCA2 PSVs may be associated with elevated risk of developing aggressive prostate cancer. Significance: Aggressive prostate cancer risk in BRCA2 mutation carriers may vary according to the specific BRCA2 mutation inherited by the at-risk individual.

Abstract Monoclonal gammopathies, including multiple myeloma (MM), represent a group of plasma cell (PC) disorders that comprise of mostly incurable hematopoietic malignancies with an increasing incidence in the US. Previous epidemiological studies demonstrated a 2-3 fold higher incidence of monoclonal gammopathy of undetermined significance (MGUS) and a similarly higher incidence of MM along with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). This suggests a possible ancestral-associated genetic predisposition of AAs to the development of monoclonal gammopathies (Landgren, Blood, 2006). When access to care is equal, AAs have a better overall survival compared to EAs suggesting that AAs may have a genetic predisposition that renders them better responders to treatment or have more favorable cytogenetic subtypes of MM (Waxman, Blood, 2010). Previous efforts to understand this disparity have relied on self-reported race rather than genetic ancestry. We hypothesize that quantifying genetic ancestry is necessary to fully understand the genetic mechanisms of racial disparities of monoclonal gammopathies. We describe our study of 881 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from the bone marrow samples was genotyped on the Precision Medicine Research Array. Biogeographical ancestry was assessed using the Geographic Population Structure Origins tool, which provides the ancestral breakdown of 36 admixture components for each individual representing different geographic regions and outputs admixture proportions corresponding to those ancestries (Elhaik, Nat Commun, 2014). We evaluated whether an increase in the percentage of African Ancestry altered the odds of any primary cytogenetic abnormality. We demonstrated that a 10% increase in the percentage of African ancestry was associated with a 6% increase in the odds of detecting either an t(11;14), t(14;16) or t(14;20) (odds ratio = 1.06, 95% CI: 1.02 - 1.11; p-value = 0.05). Although we observed an increase in the odds of each of the individual translocations with 10% increase in African ancestry, l t(11;14) (OR=1.03) t(14;16) (OR=1.11) and t(14;20) (OR=1.10), these three abnormalities were combined to achieve greater statistical power. The differences in cytogenetic abnormalities were most striking among individuals with ≥80.0% African (n=120) compared to individuals with <0.1% African ancestry (n=235). Using these cutoff values comparing the ≥80.0% and <0.1% African ancestry cohorts, there was a higher prevalence of t(11;14), t(14;16) and t(14;20) (51% vs. 33%, respectively, p-value=0.008) and a lower prevalence of trisomies (with or without IgH translocations) (48.3% vs. 61.3%, respectively, p-value=0.066). In addition, the ≥80% African ancestry cohort also displayed a slightly lower prevalence of monosomy 13/13q deletion compared to the cohort with <0.1% African ancestry (34.2% vs. 38.7%, respectively, p-value=0.021). Further, we observed a significantly higher prevalence in the proportion of females with monoclonal gammopathies among the ≥80% African ancestry cohort compared to the cohort with <0.1% African ancestry (56.7% vs. 42.1%, respectively, p-value=0.028). We complement our past studies that relied on self-reported race and characterized patients' demographic and uniformly collected cytogenetic data in relation to genetically defined African ancestry. We demonstrate the prevalence of having one of three specific subtypes (i.e., t(11;14), t(14;16), or t(14;20)) was significantly higher in those with highest (≥80%) compared to lowest (<0.1%) African ancestry demonstrating African ancestry is associated with a subtype distribution of MM that differs from non-African individuals. These differences were only revealed after analysis of individuals with the highest and lowest percentage of African ancestry. Since 38.3% of the individuals with ≥80% African ancestry have the favorable t(11;14) translocation (in comparison to 26.8% of <0.1% African individuals), this finding may explain improved survival with equal access to care. Understanding the genetic mechanisms of this disparity is a fundamental step to understanding differences in incidence and outcomes of patients with monoclonal gammopathies. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding; Celgene: Research Funding. Stewart:Amgen Inc., BMS, Celgene, Takeda, Roche, Seattle Genetics, Janssen, Ono: Consultancy; Amgen Inc., Celgene, Roche, Seattle Genetics: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Kumar:Novartis: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: 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; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: 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, Research Funding; Oncopeptides: 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; Roche: Research Funding.

Abstract Background: Peripheral T-Cell lymphomas (PTCLs) constitute approximately 10% of lymphoid malignancies and consist of several distinct entities based on pathologic and clinical characteristics. With the exception of a few subtypes (e.g., ALK-positive anaplastic large cell lymphoma (ALCL) and some primary cutaneous or leukemic forms of PTCL), a majority of PTCLs are aggressive as characterized by poor treatment response, rapid disease progression and poor overall survival. We have shown that landmark timepoints of event-free survival after diagnosis can stratify subsequent overall survival (OS) in diffuse large B-cell and follicular lymphoma. Here we evaluate this approach in newly diagnosed aggressive PTCLs treated with anthracyline-based or related chemotherapy. Methods. Newly diagnosed PTCL patients were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER) from 2002-2012. Clinical data were abstracted from medical records using a standard protocol. For this analysis, we included patients receiving anthracycline-based or other multiagent chemotherapy for the following PTCL subtypes: ALK-negative ALCL (N=24); angioimmunoblastic T-cell lymphoma (AITL, N=34); PTCL, not otherwise specified (NOS; N=60); enteropathy-associated T-cell lymphoma (EATL, N=8); extranodal NK/T-cell lymphoma, nasal type (ENKTL, N=11); and hepatosplenic T-cell lymphoma (HSTCL, N=1). Patients were prospectively followed, and event-free survival (EFS) was defined as time from diagnosis to progression, re-treatment, or death due to any cause. Landmark EFS timepoints were assessed at 12 (EFS12) and 24 (EFS24) months after the date of diagnosis. Subsequent OS was defined as time from a specific endpoint (diagnosis, event or EFS landmark). Replication was performed in a population-based cohort of T-cell lymphomas diagnosed from 2000-2009 from the Swedish Lymphoma Registry. Results. 138 eligible patients were enrolled in the MER from 2002-2012, the median age at diagnosis was 58 years (range, 19-88), 66% were male, 73% had Stage III-IV disease, and 33% had IPI 0-1. At a median follow-up of 47 months (range 11-120), 87 patients (63%) had an event and 70 patients (51%) had died. From diagnosis, only 60 patients were event-free at 12 months (EFS12 45%). Patients who failed to achieve EFS12 had a poor subsequent OS from event (median OS = 6.8 months, 95% CI: 5.3-14.0, figure 1). In contrast, patients who achieved EFS12 had a favorable subsequent OS (median unreached, figure 2). Of the 427 eligible patients in the Swedish registry, the median age at diagnosis was 66 years (range, 18-88), 63% were male, 68% had Stage III-IV disease, and 25% had IPI 0-1. PTCL subtypes were: ALK-negative ALCL (N=89); AITL (N=80); PTCL, NOS (N=183); EATL (N=44); ENKTL (N=24); and HSTCL (N=7). At a median follow-up of 86 months (range 40-158), 333 patients (79%) had an event and 316 patients (74%) had died. From diagnosis, 183 patients were event-free at 12 months (EFS12 44%). Similar to the MER cohort, Swedish patients failing EFS12 had poor subsequent survival (median OS = 3.7 months, 95% CI: 2.9-5.3, figure 1). Swedish patients achieving EFS12 had a favorable subsequent OS (median OS = 89 months, figure 2). Similar results were obtained when conducting landmark analysis at 24 months after diagnosis (EFS24). Conclusion. Relapse and re-treatment events within the first 12 months of diagnosis are associated with very poor OS in PTCL treated with anthracyclines or related chemotherapy, while patients achieving EFS12 have encouraging subsequent OS. Stratifying patients into prognostically distinct subsets using EFS12 may help focus biologic and biomarker studies. EFS12 has potential as an early endpoint for studies of newly diagnosed PTCL. Further investigation of determinants related to post-EFS12 survival is needed. Disclosures Maurer: Kite Pharma: Research Funding. Cerhan:Kite Pharma: Research Funding. Ansell:Bristol-Myers Squibb: Research Funding; Celldex: Research Funding. Link:Genentech: Consultancy, Research Funding; Kite Pharma: Research Funding. Thompson:Kite Pharma: Research Funding. Relander:Respiratorius: Patents & Royalties: valproate for DLBCL.

Abstract Background: Peripheral T-cell lymphomas (PTCLs) comprise a group of non-Hodgkin lymphomas (NHLs) of mature T-cell origin with generally aggressive clinical behavior. Most systemic PTCLs are treated with anthracycline-based combination chemotherapy; however, outcomes remain relatively poor for most subtypes except ALK-positive anaplastic large cell lymphoma (ALCL). We have used landmark analyses based on event-free survival (EFS) to identify clinically useful endpoints in B-cell NHLs, with EFS at 24 (EFS24) months identified to stratify overall survival (OS) in aggressive B-cell NHL. Here we examined the ability of EFS24 to predict subsequent OS in a large, multinational PTCL cohort. Methods: A cohort of newly diagnosed PTCL patients treated with curative intent combination chemotherapy regimens was assembled from the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER), Swedish Lymphoma Registry (SWE), and British Columbia Cancer Agency (BCCA). Subtypes included ALK-negative ALCL, angioimmunoblastic T-cell lymphoma (AITL), PTCL, not otherwise specified (NOS), enteropathy-associated T-cell lymphoma (EATL), extranodal NK/T-cell lymphoma, nasal type (ENKTL), and hepatosplenic T-cell lymphoma (HSTCL). Patients were followed based on local institution guidelines, and EFS was defined as time from the date of pathologic diagnosis to progression, re-treatment, or death due to any cause. EFS24 was defined as being alive and event-free 24 months from diagnosis. Subsequent OS was defined as time from achieving EFS24 (24 months from diagnosis) or time from progression in patients failing to achieve EFS24 (progression within 24 months of diagnosis). OS was compared to the age-, sex-, and country-matched general population using United States, Sweden, and British Columbia rate tables via standardized mortality ratios (SMR) and expected survival. Results: 775 patients diagnosed from 2000-2012 were included in the combined analysis with diagnosis by the WHO classification at the respective institutions (MER=138, SWE=422, BCCA=215). Median age at diagnosis was 64 years (range 18-89) and 63% were male. Patient characteristics are summarized in the table. 736 (95%) received anthracyline-based therapy at diagnosis. At a median follow-up of 77 months (range 1-185), 516 patients (67%) had died. The percentage of patients achieving EFS24 was similar across the 3 cohorts (MER=39%, SWE=35%, BCCA= 36%, combined=36%). Median survival after progression within the first 24 months was only 4.9 months (95% CI: 3.8-5.9), with a 5-year OS of 11% and SMR of 46.4 (95% CI: 41.8-51.3). In contrast, median survival after achieving EFS24 was not reached, with a 5-year OS of 78% (95% CI: 73%-84%). This was inferior to the expected survival of 92% in the age-, sex-, and country matched population (SMR=3.16; 95% CI: 2.48-3.98). In EFS24 subgroup analyses, more favorable outcomes were observed in younger patients (age <=60 years, N=137, 5-year survival of 91% vs. 98% expected) and in patients receiving autologous stem cell transplant in first remission (N=72, 5-year survival of 88% vs. 96% expected). Patients achieving EFS24 who were not transplanted in first remission (N=189) had a 5-year survival of 74% vs. 90% expected. Conclusions: Assessment of EFS24 stratifies subsequent outcome in PTCL. Patients with early relapse from PTCL have extremely poor outcomes. However, over one-third of patients with PTCL remain in remission two years from diagnosis after initial chemotherapy and have encouraging OS rates, although survival remains significantly worse than the matched general population. Subset analysis suggests that younger patients and patients who receive autologous stem-cell transplant in first CR have 5-year survival rates that approach 90%, though still below the expected survival of the background population. The marked differences in OS after failing or achieving EFS24 in PTCL patients suggest that this endpoint may be useful for patient counseling, as a clinical trial endpoint, and as an endpoint to assess novel biomarkers for risk stratification. Table Table. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures Maurer: Celgene: Research Funding; Kite Pharma: Research Funding. Jerkeman:Mundipharma: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Gilead: Research Funding; Celgene: Research Funding. Connors:Seattle Genetics: Research Funding; Millennium Takeda: Research Funding; NanoString Technologies: Research Funding; F Hoffmann-La Roche: Research Funding; Bristol Myers Squib: Research Funding. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding.

Abstract In chronic lymphocytic leukemia (CLL), the molecular features of the clonotypic B-cell receptor immunoglobulins (BcR IG) are set from the birth of the clone and in contrast to genetic aberrations, remain stable overtime, rendering the BcR IG a reference biomarker that is usually not significantly affected by clonal evolution. Approximately 30% of CLL cases carry quasi-identical BcR IGs and can be assigned to distinct stereotyped subsets. While preliminary evidence alludes to BcR IG stereotypy being relevant from a clinical viewpoint, this aspect has never been explored systematically or in a cohort of adequate size to enable meaningful conclusions. In order to assess the clinical implications of BcR IG stereotypy, we evaluated clinicobiological data from 8593 CLL patients, particularly focusing on 14 major stereotyped subsets of cases with unmutated (U-CLL) or mutated IGHV genes (M-CLL). The largest subset was #2 (n=254, 3%), within which 156 and 98 cases were M-CLL and U-CLL, respectively, followed by U-CLL subsets #1 (n=173, 2%) and #7 (n=123, 1.4%). Amongst M-CLL, the largest subsets were #4 (n=94, 1.1%) and #148 (n=92, 1%). Stereotyped subsets, even of the same mutational category i.e. U-CLL or M-CLL, exhibited significant clinicobiological differences regarding: age at diagnosis (median age ranging from 53-68 years, p<0.001); gender distribution (male/female ratios ranging from 0.85-4.4, p<0.001); the frequency of advanced stage disease (Binet C) at diagnosis (ranging from 9-21%, p<0.001); CD38 positivity (median percentage of positive cells ranging from 2-73%, p<0.05). Moving to cytogenetic findings, we detected subset-biased spectra of FISH-detected aberrations which can be summarized as follows: (i) isolated del(13q) varied from 10% in subset #8 (U-CLL), to 29% in subsets #59 (U-CLL) and #16 (M-CLL), and >75% in M-CLL subsets #77 and #148 (p<0.001); (ii) trisomy 12 was absent in subsets #31 (U-CLL) and #77 (M-CLL), in 20% of subset #201 (M-CLL) and, 60% in subset #8 (U-CLL) (p<0.001); (iii) del(11q) ranged from 69% in subset #31 (U-CLL) to 12% in subset #8 (U-CLL) and 0% in M-CLL subsets #16 and #201 (p<0.001); (iv) del(17p): absent from all M-CLL subsets except #148 (7.5%); absent from U-CLL subsets #5 and #59, and present in 19% and 17% of stereotyped subset #8 and #6 cases, respectively (p<0.05). We considered subset #2 separately since it included both M-CLL and U-CLL and identified a distinctive clinicobiological profile characterized by a constellation of features, including high incidence of Binet stage C disease (21%), CD38 positivity (41%) and certain cytogenetic abnormalities i.e. del(13q) (56%) and del(11q) (23%) and, in contrast, low frequency of del(17p) (4.5%). Notably, no differences were found between U-CLL versus M-CLL subset #2 cases regarding the incidence of these parameters. Survival analysis for time-to-first-treatment (TTFT) revealed that each stereotyped subset exhibited a distinct clinical course, different from that of other subsets even with similar IGHV gene mutational status and/or expressing the same IGHV gene. Interestingly, subsets #1 and #2 demonstrated a similar TTFT to that of del(17p) positive cases, while within subset #2 the clinical outcome was independent of IGHV mutational status. By integrating BcR IG stereotypy into the Döhner cytogenetic prognostication model, we found that subsets #1, #2 and #4, collectively accounting for ~7% of our series, and representing both U-CLL and M-CLL, constituted distinct clinical entities, with the latter exhibiting a particularly indolent disease even when compared to isolated del(13q) cases or cases with no cytogenetic aberrations. Finally, in multivariate analysis for TTFT, assignment to subset #2 emerged as a new independent unfavorable factor (p=0.002); furthermore, when restricting the analysis to Binet A cases, subset #2 exhibited the second highest hazard ratio after U-CLL. In conclusion, the molecular classification of CLL based on BcR IG stereotypy refines prognostication beyond IG mutational status and improves the Döhner hierarchical model. Hence, we suggest that a compartmentalized approach focusing on and comparing different subsets sheds light on CLL clinical behavior and biology and that BcR IG stereotypy represents a companion molecular diagnostic for personalized medicine in CLL. Disclosures Montillo: Janssen: Honoraria.