Norman, Aaron D.

Abstract BACKGROUND: Multiple Myeloma (MM) is an incurable disease with no known germline high penetrant risk gene. The higher risk of MM among affected relatives suggests a genetic contribution to the etiology. To date, 24 common risk variants with low effect sizes were identified using genome-wide association studies, which account for 17% of heritability. However, a systematic analysis of the known rare alleles in cancer predisposition genes has not been undertaken so far in MM. We collaborated with six other academic centers across the United States to identify and select cases for analysis of germline predisposition of MM. METHODS: We performed whole exome, next-generation sequencing of 2,387 familial or early onset germline MM cases from the myeloma sequencing consortium (MMSEQ). We called 1.5 million variants and performed standard quality control of the data. We also obtained exome data on 1,285 cases from UK Biobank (UKBB) and 344,513 non-cancer controls (total=3,672 cases). We analyzed the ultra-rare, coding variants in 90 clinically relevant or putative candidates for cancer predisposition. We then used the automated variant curator PathoMAN to annotate and assert pathogenicity of each variant. We contrasted our results with assertions of pathogenicity from ClinVar and tested for gene association with MM. RESULTS: Overall, we observed several pathogenic or likely pathogenic variants, both singleton and recurrent founder mutations. In the MMSEQ, 8.7% of MM cases harbored a pathogenic variant in these known/putative cancer predisposition genes. Predominant group of pathogenic variants were observed within CHEK2 (19%), TP53 (8%), and ATM (5%). A case-control analysis revealed strong association with TP53 and weakly with ATM. In the familial/early onset MMSEQ cases, TP53 mutations were enriched 68 times more than in the UKBB controls. Our preliminary results suggest that known genes of cancer susceptibility such as TP53 and ATM may also play a role in myeloma risk. CONCLUSION: In a large study of multi-center MM cases, we identified a significant proportion of individuals who are carriers of known (solid) cancer predisposition genes. This study suggests that these known cancer predisposition genes may be relevant in a subset of MM cases. Citation Format: Michael T. Conry, Nicola Camp, Celine Vachon, Michelle Hildebrandt, Elizabeth E. Brown, Steven M. Lipkin, Judy Garber, Susan L. Slager, Samantha Stokes, Aaron D. Norman, Aalin Izhar, Sita Dandiker, Kylee Maclachlan, Kenneth Offit, Saad Usmani, Vijai Joseph. Pathogenic germline mutations and risk of multiple myeloma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5229.

7577 Background: Prior research has consistently shown that patients with chronic lymphocytic leukemia (CLL) have an ~2-fold increased risk of developing melanoma compared to controls. MBL is a common condition affecting 8-10 million adults over the age of 40 years in the United States and is a precursor to CLL. Little is known about the association between MBL and melanoma. Herein, we evaluated the risk of incident melanoma in a large cohort of individuals screened for MBL. Methods: Participants from the Mayo Clinic Biobank who had no prior history of hematologic malignancy, were 40 years or older, were residents of counties surrounding Mayo Clinic, and who provided blood samples between 7/2009 and 4/2022 were included in the study. Peripheral blood mononuclear cells were screened for MBL using highly sensitive eight-color flow cytometry. Individuals with MBL were classified as CLL-like MBL (CD5+, CD20dim) or atypical MBL (CD5+, CD20+) based on immunophenotypes, and also classified as low-count MBL (LCMBL) or high-count MBL (HCMBL) based on whether the percent clonal B-cell count was < 85% or ≥85%, respectively. Diagnosis of melanoma was ascertained using ICD codes and review of the electronic health records. All individuals were followed from date of sample upon which MBL screening was performed to the earliest of incident melanoma, loss to follow-up, withdrawal from the study, or September 30, 2022. We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI), adjusting for age, sex, and history of melanoma in previous 5 years. Results: A total of 7,334 participants were screened for MBL, of which 1,151 (16%) individuals had MBL. Among those with MBL, 1,107 (96.2%) had CLL-like MBL and 1098 (95.4%) had LC MBL. The median age at entry into the MBL screening cohort was 67 years (range 40-101) and 37% were male; individuals with MBL were older (median age 72 vs 65 years) and male (49% vs 35%). After a median follow-up of 2.9 years (range 0-13.2), 121 of the 7,334 (1.6%) participants developed incident melanoma after the date of MBL screening. The 10-year cumulative incidence of melanoma among individuals with MBL was 7.8% (95% CI 4.5-13.5%) compared to 3.4% (2.7-4.4%) in those who screened negative for MBL. After adjusting for age, sex, and history of prior melanoma, we found a 1.81-fold increased risk of incident melanoma (95% CI 1.19-2.76) among individuals with MBL. The increased risk of melanoma persisted when the analysis was restricted to individuals with LCMBL (HR = 1.84; 95% CI 1.21-2.82). Conclusions: In the largest MBL screening cohort to date, we found that LCMBL, a common condition, was associated with an 84% elevated risk of melanoma, similar to the ~2-fold increased risk observed in patients with CLL. These data, together with our prior findings of a heightened risk of serious infections and lymphoid malignancies, suggest that individuals with LCMBL are at increased risk for adverse health outcomes.

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27− cells (p = 9.3 × 10−4). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3−, MCP-2−, and IL20-dependent pathways.

Chronic lymphocytic leukemia (CLL) is the most common leukemia among adults worldwide. Although genome-wide association studies (GWAS) have uncovered the germline genetic component underlying CLL susceptibility, the potential use of GWAS-identified risk variants to predict disease progression and patient survival remains unexplored. Here, we evaluated whether 41 GWAS-identified risk variants for CLL could influence overall survival (OS) and disease progression, defined as time to first treatment (TTFT) in a cohort of 1039 CLL cases ascertained through the CRuCIAL consortium. Although this is the largest study assessing the effect of GWAS-identified susceptibility variants for CLL on OS, we only found a weak association of ten single nucleotide polymorphisms (SNPs) with OS (p < 0.05) that did not remain significant after correction for multiple testing. In line with these results, polygenic risk scores (PRSs) built with these SNPs in the CRuCIAL cohort showed a modest association with OS and a low capacity to predict patient survival, with an area under the receiver operating characteristic curve (AUROC) of 0.57. Similarly, seven SNPs were associated with TTFT (p < 0.05); however, these did not reach the multiple testing significance threshold, and the meta-analysis with previous published data did not confirm any of the associations. As expected, PRSs built with these SNPs showed reduced accuracy in prediction of disease progression (AUROC = 0.62). These results suggest that susceptibility variants for CLL do not impact overall survival and disease progression in CLL patients.

PURPOSE Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown. METHODS We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance. RESULTS On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures ( P LRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer. CONCLUSION AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.

Abstract Low count (LC) MBL is characterized by a circulating population of clonal B-cells and is a precursor state to CLL. Most individuals with LC MBL do not progress to CLL and never come to clinical attention. An active area of research is to identify factors that distinguish those individuals with MBL who progress from those who do not. Currently, 41 single nucleotide polymorphisms (SNPs) are known to be associated with CLL risk, and a portion of these SNPs have also been found to be associated with MBL risk. We hypothesize that these CLL-susceptibility SNPs associated with both MBL and CLL risk are SNPs associated with developing a B-cell clone; whereas the remaining SNPs found not to be associated with MBL risk are associated with progression of the B-cell clone (i.e., progression from MBL to CLL). To test this hypothesis, we evaluated the association of these 41 SNPs with risk of progression to CLL using a case-control study of 1,911 CLL cases and 1,579 individuals with MBL from Mayo Clinic. Individuals with MBL were identified through screening using 8-color flow cytometry assay. Individuals with LC MBL (defined by having a clonal B-cell population with the percent clonal B-cells out of total B-cell count &lt;85%) who had an immunophenotype consistent with CLL were included as controls. CLL cases were obtained through the Mayo Clinic hematology practice. DNA was genotyped from whole blood. We analyzed the 41 CLL susceptibility SNPs with risk of progression to CLL using logistic regression and estimated odds ratio (OR) and 95% confidence interval (CI), adjusting for sex and age. We evaluated the CLL polygenic risk score (CLL-PRS), comprised of a weighted average of the 41 SNPs, with risk of CLL. Out of the 41 established CLL susceptibility SNPs, 15 were associated with CLL progression from MBL to CLL (all P&lt;0.05). Nine of these 15 significant SNPs were not previously found to be associated with risk of MBL. The most significant SNPs were rs9880772 (OR=1.23, CI: 1.11-1.36, P=6.1 × 10−5), rs888096 (OR=1.25, CI: 1.12-1.38, P=3.0 × 10−5), and rs305065 (OR=1.28, CI: 1.14-1.43, P=1.5 × 10−5). One SNP (rs77551289) had a suggestive association (OR=1.21, P=0.069). The remaining 25 SNPs had no evidence of association with progression (ORs ranging between 0.9-1.1 and all P&gt;0.1). The CLL-PRS was also associated with CLL risk (continuous OR = 1.25, CI: 1.15 - 1.35, P = 6.7 × 10−8). In our study accounting for the presence of B-cell clonal population, we identified 15 out of 41 CLL-susceptibility SNPs to be significantly associated with progression from LC MBL to CLL. The remaining 25 non-significant CLL-SNPs were not associated with progression and may instead be associated with development or initiation of the B-cell clone. These findings suggest that the established CLL susceptibility SNPs may play differing role (i.e., development or progression of the clone) in the etiology of CLL. Citation Format: Raphael Mwangi, Geffen Kleinstern, Sara J. Achenbach, Dennis Robinson, Aaron D. Norman, Kari G. Rabe, Janet E. Olson, Neil E. Kay, Rosalie G. Waller, Nicholas J. Boddicker, James R. Cerhan, Esteban Braggio, Sameer A. Parikh, Curtis A. Hanson, Celine M. Vachon, Tait Shanafelt, Susan L. Slager. Genetic variants associated with progression from monoclonal B-cell lymphocytosis (MBL) to chronic lymphocytic leukemia (CLL). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5222.

Abstract Mammographic breast density (MBD) has been shown to be a strong, independent risk factor for breast cancer (BC) irrespective of race/ethnicity. Given the risk association of MBD and its potential to mask tumors on a mammogram, state and federal laws have mandated that women receive information regarding their personal MBD in their mammography reports. However, concerns have been raised regarding the impact of MBD notification on patient anxiety, especially written information for women who experience health disparities such as racial/ethnic minorities, lower health literacy, limited English proficiency and lower socioeconomic status. We performed a randomized controlled clinical trial to examine the impact of three different written and interpersonal approaches to MBD notification on patient anxiety, BC worry, and self-perceived BC risk, among Latinas receiving routine mammography screening at a federally qualified medical center (FQHC). We hypothesized that interpersonal education would reduce anxiety and worry, relative to the written notifications alone. The study was performed at the Baseline Clinic of Mountain Park Health Center, a FQHC in Phoenix, AZ. Women between ages 40 and 74 years presenting for screening mammogram were eligible. After providing signed informed consent, participants were randomized equally to usual care (UC- mailed notification letter); enhanced care (notification letter and MBD educational brochure designed for this study): interpersonal care (notification letter, brochure, promotora education via telephone). A stratified block randomization procedure was used with age &gt; 50 years (yes vs no), ethnicity (Hispanic vs non-Hispanic), and language preference (Spanish vs. English) as strata. Study participants completed surveys at the time of enrollment/pre-intervention (T0), at two weeks to six months after intervention was delivered (T1), and about one year after randomization (T2). Anxiety state was measured using the state anxiety subscale of the State-Trait Anxiety Inventory scale (STAI-S) (range from 20-80). BC worry was probed using the question: “How frequently do you worry about getting breast cancer someday”. The self-perceived lifetime risk of BC was rated between 0% (no chance of BC) to 100% (definitely will get BC). The proportion of participants with an increase or persistence of higher level for each outcome between time points was compared between the three study groups. The study was approved by the Mayo Clinic Institutional Review Board. 1332 Latina women were enrolled and randomized between October 2016 and October 2019. All completed the baseline (T0) survey, 928 completed T1, 632 completed T2, and 516 completed both T1 and T2 surveys. At study entry, majority of the participants were young (64.1% between age 40-49 years), had no family history of breast cancer (81.0%), had less than high school education (68.8%), and were married or partnered (67.8%). At T0, the mean (SD) anxiety STAI score was 32.5 (11.1); 51.8% with moderate or severe anxiety (score &gt; 30). With regard to BC worry, 41.3% reported worrying “sometimes”, “often”, or “almost all the time”. Further, 25.4% reported a self-perceived lifetime risk of developing BC of &gt;10% while only 6.6% had a Gail model estimated lifetime risk score of &gt;10%. There was no significant difference in changes in anxiety, BC worry or self-perceived risk from T0 to either T1 or T2 surveys between the intervention groups. In summary, this study found high levels of baseline anxiety and BC worry (despite the majority being 40-49 years old and having no family history of BC) which persisted regardless of how notification and education were delivered. Future work is needed to improve the understanding of factors that could lower anxiety and BC worry and improve risk perception in this population. Citation Format: Karthik Ghosh, Sarah Jenkins, Jennifer Ridgeway, Jessica D. Austin, Bijan Borah, Bhavika K. Patel, Deborah Rhodes, Aaron Norman, Edna P. Ramos, Matt Jewett, Crystal Gonzalez, Valentina Hernandez, Davinder Singh, Vera Suman, Celine Vachon. Breast Density Notification: Impact on anxiety, breast cancer worry, and self-perceived risk among Latinas at a federally qualified medical center. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-05-38.

Abstract Breast parenchymal patterns on radiologic images are associated with breast cancer risk. Radiomic features have been proposed as quantitative measures of parenchymal patterns. We defined intrinsic imaging phenotypes of breast parenchymal patterns based on radiomic features extracted from full field digital mammography (FFDM) in breast screening populations and assessed whether these phenotypes are associated with breast cancer risk and masking. We selected 30,000 women with 4-view FFDM exams from Hologic machines from three institutions (Hospital of the University of Pennsylvania, Mayo Clinic, and San Francisco Mammography Registry), randomly split into a training (20,000 women) and test set (10,000 women). In total, 390 radiomic features were automatically extracted from each image using a validated software pipeline, standardized, and adjusted for site differences using ComBat. We used two methods, hierarchical clustering and Principal Components (PCs) analysis, to classify significant variation among the features in the training set and replicate among the test set. Next, we applied the replicated clusters and PCs to an independent nested case-control set [1082 invasive breast cancer (BC) cases (of which 151 were Black and 893 White women, 38 other race) matched to 2837 controls (411 Black and 2345 White women, 81 other race) on age, race, timing of images, and site]. We examined associations of the clusters and PCs with invasive breast cancer risk, as well as masking [defined as a false-negative (FN) screen (124 cases and 319 matched controls) and additionally the subset with symptomatic interval cancer (IC) within 12 months of negative screen (88 cases and 223 matched controls)] using conditional logistic regression. We evaluated their association with breast cancer alone, and with adjustment for age, body mass index (BMI) and breast density assessed by Breast Imaging Reporting and Data System (BI-RADS) using likelihood ratio tests. We estimated discrimination using area under the curve (AUC) and compared AUCs for models that included the radiomic clusters and PCs with the model that included only age, BMI and density. We also stratified analyses by race (Black/White). From hierarchical clustering, we defined six statistically significant phenotype clusters (each of at least 1000 women) in the training set which were replicated in the test set. For PC Analysis, we identified six PCs in the training set, explaining 85% of the variation in texture features and reproduced these in the test set. The six radiomic phenotype clusters (P&lt; 0.001) and six PCs (P&lt; 0.001) were both associated with invasive BC, including after adjusting for age, BMI, and density (cluster P=0.004; PCs P&lt; 0.001). Improvements in discrimination of invasive BC with inclusion of PCs or clusters were more pronounced among Black women (Table). Further, the PCs (P&lt; 0.001) and clusters (P&lt; 0.001) were significantly associated with FN overall and for symptomatic IC (PCs P&lt; 0.001; clusters P=0.001), but only PCs remained significant after adjusting for age, BMI and density (PCs P=0.004 for FN; PCs P=0.007 for symptomatic IC). Discrimination of masking also improved with inclusion of both clusters and PCs (Table). We identified reproducible radiomic phenotypes that are associated with invasive BC risk, above and beyond breast density with the strongest associations for invasive BC among Black women and symptomatic interval cancers. Citation Format: Stacey Winham, Anne Marie McCarthy, Aimilia Gastounioti, Christopher Scott, Aaron Norman, Walter C. Mankowski, Lauren Pantalone, Matthew Jensen, Eric A. Cohen, Hannah Horng, Kathleen Brandt, Emily F. Conant, Karla Kerlikowske, Despina Kontos, Celine Vachon. Radiomic phenotypes of breast texture and association with breast cancer risk and masking [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS4-06.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

AbstractPleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome‐wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P < 5 × 10−8) with their respective trait. The selected SNPs were analyzed in 2434 MM cases and 3446 controls from the International Lymphoma Epidemiology Consortium (InterLymph). The 10 SNPs showing the strongest associations with MM risk in InterLymph were selected for replication in an independent set of 1955 MM cases and 1549 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and 418 MM cases and 147 282 controls from the FinnGen project. The combined analysis of the three studies identified an association between DNAJB4‐rs34517439‐A and an increased risk of developing MM (OR = 1.22, 95%CI 1.13‐1.32, P = 4.81 × 10−7). rs34517439‐A is associated with a modified expression of the FUBP1 gene, which encodes a multifunctional DNA and RNA‐binding protein that it was observed to influence the regulation of various genes involved in cell cycle regulation, among which various oncogenes and oncosuppressors. In conclusion, with a pleiotropic scan approach we identified DNAJB4‐rs34517439 as a potentially novel MM risk locus.