Boddicker, Nicholas

Abstract Purpose: Germline pathogenic variants (PV) in ATM increase the risk of pancreatic ductal adenocarcinoma (PDAC), but the underlying tumor biology of PDAC associated with germline PV in ATM has not been adequately explored. Experimental Design: Whole-genome, whole-exome, and RNA sequencing were performed on PDAC tumors from 25 germline ATM PV carriers diagnosed at Mayo Clinic between 2007 and 2017. Somatic and copy-number alterations, mutational signatures, transcriptomic subtypes, and the immune landscape were evaluated. Results: High-quality whole-exome and whole-genome sequencing were obtained from 21 and 15 tumors, respectively. Biallelic inactivation of ATM was observed in 87%, KRAS PV in 90%, CDKN2A homozygous loss in 60%, and TP53 alterations in <10% of these tumors. A predominant clock-like mutational signature was present in all samples. Whole-transcriptome analysis identified that the aberrantly differentiated endocrine exocrine subtype accounted for 18% of PDAC and was consistently associated with >5-year overall survival. In addition, a 28-gene expression–based signature associated with overall survival was identified and further validated in The Cancer Genome Atlas cohort. Immune landscape analysis through CODEX identified enriched CD4 T-helper cell/tumor interactions and reduced B7H3-high cell/tumor interactions in ATM PV carriers compared with noncarriers. Conclusions: The observed absence of TP53 PV and enrichment for CDKN2A alterations in ATM tumors, along with differences in the mutational signatures, transcriptomic subtypes and immune landscape, improve our understanding of the mechanistic pathways involved in PDAC development in germline ATM PV carriers and help identify potential targeted therapeutic strategies.

10582 Background: Breast cancer is the most common cancer in young women, with an increasing incidence over the past two decades. This study aims to evaluate the characteristics of young-onset breast cancers among patients aged ≤50 and compare tumor characteristics by germline mutation carrier status. Methods: Patients with breast cancer diagnosis ≤50 years old and evaluated across the Mayo Clinic enterprise between 2000 and 2024 were identified through the prospective Mayo Clinic Breast Cancer Study and the institutional tumor registry. Demographics, tumor characteristics, and clinical outcomes were obtained and described using summary statistics. Germline pathogenic or likely pathogenic variant (PV) carrier status for 5 established breast cancer predisposition genes (BRCA1, BRCA2, ATM, CHEK2 and PALB2) was available in a subset of unselected patients who consented to participation in sequencing studies at Mayo Clinic. Clinical characteristics were compared between PV carriers in each gene and non-carriers utilizing Chi-square test. All tests were two-sided and p-value less than 0.05 was considered statistically significant. Results: Among 8,462 patients (8435 women, 27 men) with breast cancer diagnosis at age ≤50 in the study, the median age of diagnosis of breast cancer was 44 years (range 18 – 49). At diagnosis, 84% had invasive disease, 43% of the tumors were high-grade, 15.8% had triple-negative breast cancer (TNBC), more than two-thirds (67.5%) presented with stage I or II breast cancer, and 3.7% had bilateral breast cancer. Among the 2,527 patients who consented to germline sequencing, 10.1% were found to be carriers of PVs; these included BRCA1 (3.3%), BRCA2 (2.7%), CHEK2 (2.3%), ATM (1.3%), and PALB2 (0.6%). Compared to non-carriers, a significant enrichment (p<0.05) of invasive breast cancer (92.6% vs. 83.3%) and high grade tumors (61.7% vs. 31.4%) were noted in BRCA1 PV carriers, and of bilateral breast cancer (13.4% vs. 3.8%) and high grade tumors (46.4% vs. 31.4%) in BRCA2 PV carriers. After exclusion of in-situ disease, proportion of TNBC was observed to be significantly higher in BRCA1 (61.3%), BRCA2 (15.5%) and PALB2 (30.7%) PV carriers compared to non-carriers (11.2%), whereas >90% of ATM or CHEK2 PV carriers had ER+ breast cancer and none had TNBC. A significant difference in stage at presentation was not observed by germline PV carrier status. Conclusions: The high frequency (>10%) of PVs in young-onset breast cancer underscores the importance for genetic testing in this population. The observed differences in breast cancer phenotypes based on germline PV carrier status among young-women may have significant implications for clinical outcomes and needs to be further explored.

10510 Background: The impact of germline pathogenic or likely pathogenic variants (PVs) in cancer predisposition genes on overall survival (OS) after breast cancer diagnosis is not well defined. In particular, unbiased OS estimates from population-based studies accounting for clinical subtypes of breast cancer (based on ER, PR, and HER2 status) and for genes other than BRCA1/2 are lacking. Methods: The study included 25,168 prospectively followed women with locoregional invasive breast cancer within the population-based CARRIERS study. Germline sequencing using a custom multigene amplicon-based panel was performed to identify PVs. OS was compared between germline PV carriers in ATM, BRCA1, BRCA2, CHEK2 and PALB2 and non-carriers (negative for germline PVs in 13 known breast cancer predisposition genes) for each clinical subtype of breast cancer from the time of breast cancer diagnosis to death or last follow up in a multivariable Cox proportional hazard regression analysis adjusting for age at diagnosis, race/ethnicity, histology, TNM stage, type of surgery, use of adjuvant radiation, chemotherapy and endocrine agents. Results: Among 25,168 women with breast cancer, germline PVs in one of the five breast cancer predisposition genes were detected in 5.8% of the women [ ATM : 0.8%, BRCA1 : 1.3%, BRCA2: 1.6%, CHEK2 : 1.5%, and PALB2 : 0.6%]. Among women with ER+ breast cancer, compared to non-carriers, a significantly worse OS was noted for BRCA1 (Hazard Ratio (HR): 1.8, 95% Confidence Interval (CI): 1.1 – 3.0, p=0.02) and BRCA2 (HR: 1.8, 95%CI: 1.4 – 2.4, p<0.001), but not for ATM (HR: 1.2, 95%CI: 0.8 – 1.7, p=0.40) or CHEK2 (HR:1.0, 95%CI: 0.8 – 1.3, p=1.0) PV carriers. Worse OS was noted in PALB2 PV carriers with ER+ breast cancer (HR:1.5, 95%CI: 0.9 – 2.2, p=0.09), although it did not reach statistical significance. Similar HR estimates for OS as with ER+ breast cancer were observed in women with ER+/HER2- breast cancer for BRCA1 , BRCA2 and PALB2 PV carriers, but only BRCA2 results were statistically significant. Among women with ER-negative breast cancer, compared to non-carriers, a significant difference in OS was not observed for PV carriers in ATM (HR:0.8, 95%CI: 0.4 – 1.8, p=0.63), BRCA1 (HR:1.2, 95%CI: 0.8 – 1.7, p=0.35), BRCA2 (HR: 0.8, 95%CI: 0.5 – 1.2, p=0.29), CHEK2 (HR: 0.7, 95%CI: 0.3 – 1.4), or PALB2 (HR: 0.9, 95%CI: 0.5 -1.7, p=0.78). Conclusions: The suggestive differences in OS by ER status of the tumor in BRCA1 and BRCA2 PV carriers warrant further investigation of underlying tumor biology and assessment of endocrine sensitivity of breast cancer in germline PV carriers.

Abstract Monoclonal gammopathy of undetermined significance (MGUS) is a precursor to multiple myeloma (MM). Clonal hematopoiesis of indeterminate potential (CHIP) is a precursor to either myeloid or lymphoid malignancy, depending on whether the mutation is in a gene associated with lymphoid (L-CHIP) or myeloid (M-CHIP) outcome. Little is known about the association between CHIP and MGUS and their combined effect on risk of MM. We examined this question within Mayo Clinic Biobank cohort of participants aged 50 years or older with no prior history of hematological malignancies. Using whole blood, individuals were screened for MGUS using a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry assay. M-CHIP and L-CHIP were defined based on mutations in 56 genes associated with myeloid malignancies or mutations in 235 genes associated with lymphoid malignancies, respectively, using whole-exome-sequencing. Incident MM was identified using International Classification of Diseases (ICD) codes and confirmed via medical record review. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals for the association of CHIP and MGUS. Cox proportional hazards regression was used to estimate hazard ratios (HR), with time defined as date between blood sample and the first incident MM, date of death, or 12/31/2023. All models were adjusted for age and sex. Of the 16, 479 individuals (median age 65 years, 45% male) screened, 12.3% were positive for MGUS, 9.8% were positive for M-CHIP, and 1.5% were positive for L-CHIP. There was no evidence of an association between M-CHIP and MGUS (OR=0.97, 95% CI:0.83-1.12) nor L-CHIP and MGUS (OR=1.12, 95% CI:0.78-1.57), including with any MGUS isotype (IgA, IgG, or IgM; P-values&gt;0.22). Next, we investigated the association of these precursors on risk of MM. Median follow-up was 11.7 years (range 0.1-15.1), and 46 individuals developed incident MM. Both MGUS (HR=29.7, 95% CI: 14.1-62.4) and L-CHIP (HR=4.1, 95% CI: 1.3-13.2) were significantly associated with incident MM, but not M-CHIP (HR-1.0, 95% CI: 0.4-2.5). Investigating the combined effect of MGUS and L-CHIP, we found those with MGUS alone had a 27.5-fold (95% CI: 13.0-58.2) increased risk of incident MM compared to those with no precursors. No individuals with L-CHIP only developed MM, but those with both L-CHIP and MGUS had a 129.4-fold (95% CI: 34.4-486.4) increased risk of incident MM. In the largest cohort with screened MGUS and CHIP, we found no evidence of an association between either definition of CHIP with MGUS. However, individuals with both L-CHIP and MGUS were at the highest risk of developing MM. Citation Format: Nicholas J. Boddicker, Cristine Allmer, Danelle H. Moonen, Aaron D. Norman, Angelica Macauda, Alyssa Clay-Gilmour, Janet E. Olson, Mrinal S. Patnaik, Vincent Rajkumar, Esteban Braggio, David L. Murray, Shaji Kumar, Susan L. Slager, Celine M. Vachon. The association between MGUS and CHIP and their impact on multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4917.

Abstract Introduction: Breast cancer genome-wide association studies (GWAS) have identified over 200 susceptibility loci, many replicated in diverse populations. However, cross-ancestry evaluation of breast cancer genetic architecture remains limited. We examined breast cancer genetic architecture using GWAS summary results from European (EUR; cases (ca) = 188,474, controls (co) = 96,201), East Asian (EAS; ca = 20,393, co = 86,329), African American (AA; ca = 9,235, co = 10,184), and US Hispanic/Latina and Latin American (H/L; ca = 2,396, co =7,468) studies. Methods: GWAS results were derived from the Breast Cancer Association Consortium, the African Ancestry Breast Cancer Genetics Consortium (AABCG), Biobank Japan, and a meta-analysis of five studies of H/L women with breast cancer. Linkage disequilibrium (LD) scores were generated for EUR, EAS, and AMR using the 1000 Genomes Project, while AA LD scores were derived from a subset of AABCG controls. Heritability was estimated for each ancestry group using LD score regression. Genetic correlations between populations were assessed via Popcorn. Polygenicity was analyzed using GENESIS; however, due to the limited sample size in the H/L studies, these estimates were restricted to AA, EAS, and EUR. Enrichment of heritability across regulatory elements was evaluated using stratified LD score regression across all populations. Results: The logit-scale heritability and corresponding standard error (SE) were 0.466 (0.066) for EAS, 0.501 (0.050) for EUR, 0.588 (0.360) for H/L, and 0.614 (0.095) for AA. The estimated number of independent susceptibility loci was 4,446 for EAS, 5,235 for EUR, and 8,308 for AA. Using a clumping and thresholding approach, an optimal set of common variants were projected to explain 38.6% (EUR), 39.4% (EAS), and 26.2% (AA) of genetic variance for samples of 100,000 cases and 100,000 controls with AUCs from corresponding estimated polygenic risk scores (PRSs) of 0.621 (EUR), 0.634 (EAS), and 0.611 (AA). Genetic correlations were strongest between EUR and EAS (ρ = 0.79, SE = 0.08) and EUR and H/L (ρ = 0.68, SE = 0.21), and weakest between AA and EAS (ρ = 0.42, SE = 0.14) and AA and H/L (ρ = 0.26, SE = 0.24). Among 73 genomic features, we found significant (P &lt; 0.05/73) enrichment in heritability in EUR for ‘ancient promoter’ regions, transcription factor binding sites, H3K4me3, ‘super-enhancers’, H3K4me1, H3K27ac; in EAS for ‘super-enhancers’; and in AA for H3K27ac. No genomic features were significantly enriched in H/L, likely due to limited power. Conclusion: These findings suggest a shared breast cancer genetic architecture across diverse populations, as well as the potential for a similar level of breast cancer risk stratification by PRS in these populations. Expanding GWAS in underrepresented populations is essential to improve genetic risk predictions and foster equitable cancer prevention. Citation Format: James L. Li, Maria Zanti, Jacob Williams, Om Jahagirdar, Guochong Jia, Qiang Hu, Jean-Tristan Brandenburg, Li Yan, Weang-Kee Ho, Jingmei Li, José P. Miranda, Devika Godbole, Julie-Alexia Dias, Leila Dorling, Wenlong C. Chen, Nicholas Boddicker, Ying Wang, Alicia Martin, Martin J. Zhang, Yan Zhang, Joe Dennis, Esther M. John, Gabriela Torres-Mejia, Larry Kushi, Jeffrey Weitzel, Susan L. Neuhausen, Luis Carvajal-Carmona, Christopher Haiman, Elad Ziv, Laura Fejerman, Wei Zheng, Dezheng Huo, Douglas Easton, Nilanjan Chatterjee, Peter Kraft, Montserrat Garcia-Closas, Wendy Wong, Kyriaki Michailidou, Qianqian Zhu, Diptavo Dutta, Thomas U. Ahearn, Haoyu Zhang. Genetic architecture of breast cancer across diverse populations: Assessing heritability, genetic correlation, and polygenicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2282.

Genome-wide association studies (GWAS) of multiple myeloma (MM) in individuals of genetic European ancestry (EA) have identified 35 susceptibility loci. Co-heritability analyses have revealed a strong genetic correlation between MM and its precursor condition, monoclonal gammopathy of undetermined significance (MGUS). Previous research validated the association between a polygenic risk score (PRS) based on 23 MM risk loci and the risk of MGUS. Went and colleagues recently reported 12 new MM risk loci. We constructed a MM-PRS using all 35 MM risk variants and assessed its association with MGUS. Additionally, among individuals with MGUS, we assessed associations of MM-PRS with established prognostic factors [M-protein (&lt;0.2 g/dL; 0.2-1.5 g/dL; &gt;1.5 g/dL); isotype (IgG, IgA, IgM); free light chain (FLC) ratio (Normal (0.26-1.65), Abnormal (&lt;0.26 or &gt;1.65))]. Our study population included 1,723 individuals with MGUS seen at Mayo Clinic, Rochester, MN and 14,175 controls from the Mayo Clinic Biobank who lived in the 27-county region around Rochester, MN, and screened negative for MGUS using MALDI-TOF MS. The majority of MGUS patients and controls were of EA. We used logistic or multinomial regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs). All models were adjusted for age, sex, and the first three principal components. The MM-PRS was significantly associated with MGUS when assessed continuously (OR, 1.28 per standard deviation (SD); 95% CI, 1.22-1.35). When comparing to the middle quintile of the MM-PRS distribution, individuals in the highest quintile had 1.41-fold increased risk of MGUS (95% CI, 1.21-1.64), and individuals in the lowest quintile had 0.68 decreased risk of MGUS (95% CI, 0.57-0.81). Of the 35 SNPs evaluated, 27 demonstrated consistent directions of effect for risk of MGUS with published risk estimates for MM. The effect of MM-PRS differed by isotype (P = 2.2 x 105), with higher MM-PRS associated with IgA MGUS (OR, 1.40 per SD; 95% CI, 1.08-1.81) and a lower MM-PRS associated with IgM (OR, 0.66 per SD; 95% CI, 0.52-0.84) compared to IgG MGUS. The MM-PRS was higher in MGUS patients with M-protein &gt; 1.5 g/dL compared to M-protein of size 0.2-1.5 g/dL, although not statistically significant (OR, 1.41 per SD; 95% CI, 0.95-2.08); there were no differences in the MM-PRS between MGUS patients with M-protein size &lt;0.2 g/dL compared to 0.2-1.5 g/dL (OR, 1.01 per SD;95% CI, 0.81-1.26). There were also no differences in MM-PRS by FLC ratio, (OR, 0.95 per SD; 95% CI, 0.852-1.10 for abnormal vs. normal). Our findings of an association of the MM-PRS with risk of MGUS provides further evidence for shared heritability between MGUS and MM. Future studies are needed to examine whether the expanded MM-PRS adds to existing models for MGUS progression. Citation Format: Angelica Macauda, Alyssa Clay-Gilmour, Cristine Allmer, Danelle Moonen, Aaron D. Normann, Nicholas J. Boddicker, Joselle M. Cook, Linda Baughn, Elizabeth E. Brown, Vincent S. Rajkumar, Esteban Braggio, David L. Murray, Susan L. Slager, Shaji Kumar, Celine M. Vachon. Implications of multiple myeloma polygenic risk scores (PRS) for MGUS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2274.

Introduction: Clonal hematopoiesis (CH) is a common age-related premalignant condition defined by the presence of an acquired somatic mutation in a gene frequently mutated in myeloid malignancies characterized by a variant allele frequency (VAF) of ≥2%, without fulfillment of other diagnostic criteria for myeloid neoplasm. Incidence of CH increases with age and found in 10%-30% of people &gt; 70 years of age. CH-related mutations confer an increased risk of myeloid neoplasms, cardiovascular diseases, and are linked to inferior survival in solid tumor patients treated with chemo/radiation therapy. Such mutations can act as a driver/amplifier of inflammation, especially through myeloid cells. To distinguish true disease drivers from background genetic events related to aging or environmental factors, we need a deeper understanding of the impact of CH in different tissue microenvironments and under therapeutic pressure for better risk stratification of CH carrier patients. Recent reports suggested high prevalence of CH-related mutations in lymphoma. Current analyses aimed to investigate: i) the prevalence of CH-related mutations in two real-world lymphoma cohorts from Molecular Epidemiology Resource (MER) MER-FL and MER-DLBCL, ii) CH-related mutational landscape in DLBCL and FL, iii) the impact of CH-related mutations on clinical outcomes. Methods: Whole exome sequencing (WES) derived from blood/PBMC from lymphoma patients with paired tumor samples was analyzed to identify CH-related myeloid drivers in 42 previously reported genes. We used Sention-Tnhaplotype2 somatic pipeline with a custom panel of normals from whole blood samples. To avoid tumor contamination, we filtered variants for which VAF in the tumor was higher than that in the germline sample. Other filtering criteria included HIGH/MODERATE impact; read count &gt; 1 in both forward and reverse reads; gnomAD_AF &lt; 0.01. We used the R “survival” package Cox regression implementation for outcome and other statistical analysis. Results: Genomic and clinical data of 507 patients from MER-FL and 383 patients from MER-DLBCL cohorts, with median age of 60 and 64 respectively, were available for analysis. CH-related mutations were present in 17.16% (87/507) in FL and 18.28% (70/383) in DLBCL cohorts with a VAF cut off &gt;2%. The most common CH-related mutations were DNMT3A (5%), CREBBP (2%), TET2 (1%), ASXL1 (1%) and PPM1D (1%) in MER-FL while DNMT3A (5%), TET2 (3%), TP53 (3%), ASXL1 (2%) and PPM1D (1%) in MER-DLBCL cohort. Both the prevalence of CH-related mutations and their average VAF increased with age, consistent with literature. Finally, cox regression analysis suggested that CH-related mutations were associated with significantly inferior overall survival (OS) in both FL and DLBCL cohorts (HR 1.6 p=0.028 and HR 2.3 p=&lt;0.001 respectively); however only in DLBCL this association was significant after age correction (HR 1.8 p=0.008). When separated by individual gene mutations, genes of interest with inferior OS included TP53 (n=4, HR 3.1, p=0.057) in FL and PPM1D (n=3 HR 2.6 p=0.1), TP53 (n=8 HR 2.1 p=0.1) and DNMT3A (n=14, HR=2.0, p=0.048) in DLBCL; however, these estimates did not quite reach statistical significance. Conclusions: Taken together, our exploratory analysis indicates that CH-related mutations associate with worse OS in lymphoma patients, supporting the rationale for evaluation of CH for the risk assessment in lymphoma. Furthermore, DLBCL displays of larger size effect, which may be related to different treatment regimes. Additional studies will be needed to elucidate the interaction between high dose chemotherapy regimes and CH-associated adverse events.

Background: Monoclonal B-cell lymphocytosis (MBL) is a common premalignant condition that can be classified into chronic lymphocytic leukemia (CLL)-type (CD5, CD23, and CD20 co-expression), and non-CLL-type (CD5-negative) based on flow cytometry immunophenotypes. CLL-type MBL is relatively well characterized with increased risk of hematologic (especially lymphoid) malignancies, serious infections, and decreased response to vaccinations. However, the prevalence, genetic predispositions, and clinical consequences of non-CLL-type MBL remain to be fully elucidated. Herein, we report findings in non-CLL-type MBL in a large screening cohort. Methods: We screened 10,330 individuals (40 years or older with no prior history of hematologic cancers) for MBL with highly sensitive flow cytometry, in the Mayo Clinic Biobank, with patients recruited from primary care-based clinics. Individuals were genotyped by Regeneron Genetics. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Among those individuals residing in the 27 counties surrounding Rochester, Minnesota, we identified incident hematologic malignancies and melanomas using ICD codes and the Rochester Epidemiology Project, a population based medical records linkage system. All diagnoses were manually reviewed for confirmation. Cox regression was used to calculate hazard ratios (HR) and 95% CIs, adjusted for age and sex. Results: We identified 1,736 individuals with MBL and 8,341 individuals without MBL. Among those with MBL, 246 (14.2%) had non-CLL-type MBL as the major clone. The median age of non-CLL-type MBL was 77 years (range, 47-95). The prevalence of non-CLL-type MBL significantly increased with age, with 0.5% prevalence among those between 40 to 59 years of age, 2.3% prevalence among those between 60 and 79 years, and 7.8% prevalence in those 80 years of age or older. The prevalence of non-CLL-type MBL was significantly higher (P &lt; .001) among males (3.1%) than females (2.0%). Using the genome-wide complex trait analysis tool, the heritability of non-CLL-type MBL was estimated to be ~26%, suggesting inherited genetics plays a role in etiology. To identify common inherited variants, we first evaluated the known CLL susceptibility variants, many of which also associated with CLL-type MBL. Among the 42 variants, none were statistically associated (all P &gt; .05) with non-CLL-type MBL. We next conducted a genome-wide association study to identify novel variants, and the most significant variant resided in 10q26.3 (minor allele frequency [MAF]control = 0.7%, MAFMBL = 3.5%, OR = 6.4, 95% CI 3.6-11.3, P = 5.7 * 10-8). Among the 6,478 individuals (192 with non-CLL-type MBL and 6,286 without MBL) followed for incident hematologic malignancies, 36 developed lymphoid and 23 developed myeloid malignancies after a median of 4.2 years of follow up. Similar to CLL-type MBL, non-CLL-type MBL was associated with a 5.2-fold risk for lymphoid malignancies (95% CI 2.0-13.0, P &lt; .001). Elevated but not significant risks were observed for myeloid malignancies (HR = 2.3, 95% CI 0.5-10.3, P = 0.27). The lymphoid malignancies developed by individuals with non-CLL-type MBL included diffuse large B-cell lymphoma, multiple myeloma, marginal zone lymphoma, and other low-grade lymphomas. We recently reported that individuals with CLL-type MBL are at higher risk for developing melanoma (HR = 1.9, 95% CI 1.3-2.8). Interestingly, non-CLL-type MBL had no evidence of an association with melanoma risk (HR = 0.4, 95% CI 0.1-1.8). We did not observe a significant difference in overall survival between individuals with non-CLL-type MBL vs those without MBL. Conclusions: In the largest screening cohort to date, we evaluated the etiology and clinical outcomes of non-CLL-type MBL, an understudied yet common condition that occurs in ~4 million adults in the United States. Non-CLL-type MBL is more common in men and older individuals, and evidence supports that inherited genetics plays an etiological role with 10q26.3 locus identified as a novel susceptibility locus. Individuals with non-CLL-type MBL had significantly increased risk of lymphoid malignancies, similar to CLL-type MBL, but, distinct from CLL-type MBL, no evidence of an increased risk of melanoma. Our study provides insights into the prevalence, genetic predispositions and clinical consequences of non-CLL-type MBL and how it differs from the classic CLL-type MBL.

Background: Immune dysfunction is a hallmark of chronic lymphocytic leukemia (CLL), and several studies suggest that hypogammaglobulinemia at the time of CLL diagnosis may predict shorter time to first therapy (TTFT; Parikh et al, 2015). However, it is unclear if hypogammaglobulinemia can predict TTFT independent of the CLL-International Prognostic Index (CLL-IPI) and the tumor mutational load (TML). We sought to determine if serum immunoglobulin (Ig) levels at diagnosis can independently predict outcomes in patients with CLL and its precursor, high-count monoclonal B-cell lymphocytosis (MBL). Methods: We used the Mayo Clinic CLL Database to identify newly diagnosed CLL/MBL consented within 2 years of diagnosis. Next generation sequencing (NGS) was performed using a 59 gene panel (SureSelect) to detect mutated CLL genes. Serum Ig levels were quantitated by radial immunodiffusion (Immunoplates). Serum Ig levels below the lower limit of normal were defined as hypogammaglobulinemia. We used Chi-squared or Fisher's exact tests to compare discrete variables and the Kruskal Wallis test for continuous variables. TTFT was calculated from date of diagnosis to date of first treatment or date last known to be untreated. We used Cox regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for TTFT and overall survival (OS) associations. Results: We identified 895 newly diagnosed patients (588 CLL and 307 MBL) who had undergone NGS for recurrent somatic mutations and had serum Ig levels available at the time of diagnosis. The median absolute B-cell count was 6.7 x109/L; 613 (69%) were male, 375 (42%) had unmutated IGHV genes, and 81 (9%) had TP53 disruption. Based on CLL-IPI, 412 (46%) patients had low risk, 285 (32%) had intermediate risk, and 198 (22%) had high/very high risk. The most commonly mutated genes were NOTCH1 (14%), SF3B1 (11%), TP53 (10%), NFKBIE (8%), ATM (6%), and BIRC3 (6%). Based on the number of genes with high impact or hotspot mutations, we classified 40%, 29%, and 31% patients with TML scores of 0, 1, or 2+, respectively. At CLL/MBL diagnosis, the median serum IgG, IgA, and IgM was 891 mg/dL (111-2620), 121 mg/dL (1-1150), and 44 mg/dL (5-1320), respectively; 284 (32%) patients had low serum IgG, 128 (17%) had low serum IgA, and 322 (42%) had low serum IgM. Low serum IgA was associated with mutations in NOTCH1, SF3B1, ATM, BIRC3 and NFKBIE, low IgM was associated with SF3B1 and BIRC3 mutations (all comparisons, P &lt; .05), and low IgG was associated with BIRC3 mutation (P = .05). The median follow-up for the cohort was 8.4 years. A total of 359 patients progressed requiring therapy (299 CLL and 60 MBL), and 265 patients died (177 CLL and 88 MBL). The TTFT was significantly shorter for patients with low serum IgG compared to normal serum IgG at diagnosis (median 4.4 vs 10.8 years) and similar findings were observed in individuals with low serum IgA (1.7 vs 10.8 years) and those with low serum IgM (4.6 vs 11.1 years). On univariable analysis, the following were associated with a shorter TTFT: low serum IgG (HR: 1.8, 95% CI 1.4-2.2), low serum IgA (HR: 3.5, 95% CI 2.7-4.4), low serum IgM (HR: 1.9, 95% CI 1.5-2.3), TML score of 1 (HR: 1.7, 95% CI 1.3-2.2), TML of 2+ (HR: 4.4, 95% CI 3.4-5.7), CLL-IPI intermediate risk (HR: 3.7, 95% CI 2.8-4.8), and CLL-IPI high/very high risk (HR: 7.6, 95% CI 5.8-10.1) (all comparisons, P &lt; .0001). In multivariable analyses after adjusting for CLL-IPI and TML, low serum levels of IgG (HR: 1.8, 95% CI: 1.5-2.3), IgA (HR: 2.4, 95% CI: 1.8-3.0), and IgM (HR: 1.8, 95% CI: 1.5-2.3) were independently associated with a shorter TTFT (all comparisons, P &lt; .0001). No significant differences in OS were detected between patients with low and normal serum IgG, IgM, and IgA on univariate analysis. Similar results for TTFT and OS were observed after adding clonal B-cell count to the Cox model. Conclusions: Our study shows that low serum Ig levels at the time of initial diagnosis is predictive of TTFT independently of the CLL-IPI and TML, which can further risk stratify individuals with newly diagnosed CLL/MBL. Additionally, low serum IgA, IgM, and IgG levels at diagnosis are significantly associated with specific somatic mutations in individuals with newly diagnosed CLL/MBL.