Vachon, Celine M.

10544 Background: Incorporation of Polygenic Risk Scores (PRS) can refine traditional breast cancer risk assessment models to provide precise estimates of breast cancer risk. However, the impact of such an integrated model on clinical decision-making related to breast cancer surveillance and preventive strategies is not fully understood. Methods: The GENRE-2 is a prospective single-arm multisite clinical trial (NCT04474834) incorporating PRS into standard breast cancer risk assessment models to determine the impact of PRS on clinical decisions on breast cancer prevention and surveillance. Women at high risk of breast cancer due to NCI-BCRAT 5-year risk of ≥ 3%, or IBIS (Tyrer-Cuzik) 10-year breast cancer risk of ≥5%, biopsy-proven high-risk breast lesion, or a pathogenic variant (PV) in ATM , BRCA1, BRCA2, CHEK2 or PALB2 , were enrolled from five sites in the United States. All women were invited to complete surveys on their breast surveillance and cancer prevention decisions based on pre-PRS standard risk models and post-PRS risk estimation, and further annual surveys are planned for 10 years. Results: Among 902 women enrolled in the study, 605 (median age: 52 years) received PRS results and completed a survey to date. Of those who received PRS results,195 (32.2%) were PV carriers. Among non-carriers, the median 10-year and lifetime pre-PRS IBIS-based risk was 10.0% and 28.7%, respectively. Among PV carriers, the CanRisk-based 10-year and lifetime pre-PRS risk estimates were 6.3% and 25.2% for ATM , 22.3% and 77.6% for BRCA1 , 18.5% and 77.7% for BRCA2 , 7.1% and 25.7% for CHEK2 , and 16.8% and 38.0% for PALB2 PV carriers, respectively. After the incorporation of PRS, the lifetime risk of breast cancer increased by at least 10% in 31% of non-carriers and 7.7% of PV carriers and decreased by at least 10% in 10.7% of non-carriers and 7.7% of PV carriers. The proportion of non-carriers with lifetime risk < 20% or > 40% changed from 17.3% and 22.0%, respectively, in the pre-PRS evaluation to 24.4% and 32.9%, in the post-PRS evaluation. A higher lifetime post-PRS score was associated with intent to take preventive action (surgery or endocrine agents). In non-carriers, the proportion of women with a lifetime risk < 20% with intent to take preventive action was 11%, compared to 36.8% of those with a lifetime risk > 40% (p < 0.001). Similarly, in PV carriers, the proportion of women with lifetime risk < 20% with intent to take preventive action was 20.8% compared to 41.1% of those with lifetime risk > 40% (p = 0.015). Conclusions: The GENRE-2 trial demonstrates that the incorporation of PRS into breast cancer risk assessment models in high-risk women is feasible and leads to clinically meaningful changes in breast cancer risk estimates and decision-making regarding preventive strategies. Evaluation of the implementation of breast cancer risk management strategies in study participants is ongoing and will be reported. Clinical trial information: NCT04474834 .

Radiomic parenchymal phenotypes on mammograms were used to predict breast cancer risk among both Black and White women, notably for false-negative findings and symptomatic interval cancer.

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: With over 80, 000 new cases of non-Hodgkin's lymphoma (NHL) diagnosed annually, modifiable risk factors remain unclear. Circadian disruption, linked to cancers like breast and prostate, affects immune cells (e.g., natural killer cells and T-helper cells) by altering their trafficking and proliferation. Some studies (PMID: 30566672, 27611440) suggest long sleep may increase overall NHL risk, including a Mendelian randomization (MR) study (PMID: 32895918). However, no research has examined the causal relationship between sleep traits, including long sleep, and NHL risk, by subtypes. We hypothesize that sleep traits are causally associated with NHL subtypes in European populations, testing this using MR with data from the International Lymphoma Epidemiology Consortium (InterLymph). Methods: We conducted two-sample MR using genome-wide association studies (GWAS) summary data for sleep traits and NHL subtypes. Only independent, genome-wide significant (p &lt; 5×10-8) Single Nucleotide Polymorphisms (SNPs) were selected as valid instruments, sourced from the UK Biobank. Sleep traits included chronotype (153 SNPs), insomnia (48 SNPs), sleep duration (78 SNPs), excessive daytime sleepiness (37 SNPs), short sleep (27 SNPs), and long sleep (8 SNPs). NHL subtype data were from InterLymph: follicular lymphoma (6, 508 cases / 64, 183 controls), mantle cell lymphoma (1, 169 cases / 61, 603 controls), Waldenstrom macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL: 1, 697 cases / 59, 333 controls), and chronic lymphocytic leukemia (8, 522 cases / 67, 653 controls). The primary analysis used inverse-variance weighted (IVW) random-effects, with MR-Egger for pleiotropy adjustment. Results: Using the IVW method, we did not identify any statistically significant causal association between sleep traits and the risk of NHL subtypes, but did yield several intriguing trends. Long sleep (sleep duration &gt;= 9 h per night) showed a marginally increased NHL risk [Odds ratio (OR) range: 1.51 - 247.9] across each subtype. Short sleep (sleep duration &lt; 7 h per night) showed a similar trend [OR range: 1.25 - 1.81], except for WM/LPL, where we noticed a negative trend. The confidence limit for long sleep was imprecise due to the small number of variants. We did not notice any significant directional horizontal pleiotropy or weak instrument bias. Conclusions: We found no conclusive evidence of a relationship between sleep traits and four NHL subtypes. However, we see suggestive trends of long and short sleep associated with higher risk of some NHL subtypes. These findings align with the previous studies, which showed long sleep was associated with higher risk of NHL overall. Future directions include expanding our analysis to additional NHL subtypes, generating polygenic risk scores, and conducting stratified analyses. Citation Format: Pankhil Shah, Brittany Crawford, Anwar Merchant, Brenda Birmann, Angelica Macauda, Michelle A. Hildebrandt, Aaron Norman, Neil E. Caporaso, Meredith Yeager, Michael Dean, Immaculata De Vivo, Lynn Goldin, Nicola J. Camp, Rosalie Griffin, Delphine Casabonne, Federico Canzian, Pelin Unal, Elad Ziv, Catherine R. Marinac, Alexandra Nieters, Stephen J. Chanock, Mitchell J. Machiela, Michael Conry, Charlie Zhong, Hanla A. Park, Simon Cheah, Jonathan N. Hofmann, Elizabeth E. Brown, Celine Vachon, Susan Slager, Sonja Berndt, Sophia S. Wang, Vijai Joseph, James McKay, Henrik Hjalgrim, Lara Sucheston-Campbell, Karl Smith-Byrne, Alyssa Clay-Gilmour. Association between sleep traits and risk of non-Hodgkin's lymphoma subtypes: a mendelian randomization study in the International Lymphoma Epidemiology (InterLymph) Consortium [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 7415.

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.

Abstract Studies have identified genetic and epidemiologic factors associated with mammographic density (MD) phenotypes. However, MD-associated genetic variants only account for a small proportion of the total estimated heritability. Interrogating interactions between genetic and epidemiologic factors could potentially identify additional MD-associated loci, expand our understanding of the genetic basis of MD phenotypes, and clarify how epidemiologic factors modulate relationships between genetic variants and MD. We conducted six separate genome-wide, gene–environment (GxE) interaction analyses, applying 2 degrees of freedom (df) and 1df interaction tests, for each of three MD phenotypes (percent density, dense area (DA), and nondense area (NDA)). The six epidemiologic factors considered were height, ever parous, parity, ever menopausal hormone therapy, ever breastfeeding, and months of breastfeeding. We included European ancestry participants from multiple studies within the Markers of Density consortium and the Breast Cancer Association Consortium (n = 4895-16 218 depending on specific analyses). We identified 11 loci with genome-wide significant (P &lt; 5 × 10−8) interaction tests including two novel common genetic signals interacting with parity (8p21.2) and ever breastfeeding (19p13.2) for NDA. Our results suggest that epidemiologic risk factors might influence relationships between common genetic variants and MD phenotypes at particular genomic loci.

Background: Latinas with mammographic dense breasts are at increased risk of breast cancer. This randomized controlled trial tests the effectiveness of three breast density (BD) educational approaches on adherence to subsequent mammography screening among Latinas receiving care at a Federally Qualified Health Center (FQHC). Measure(s): Adherence was ascertained using electronic health record and survey responses. Kaplan–Meier estimates of the time to subsequent mammogram were used to obtain adherence rates at 1- and 2-years post baseline mammogram. Cox modeling assessed whether adherence differed by patient characteristics or group assignment. Results: This analysis was limited to Latinas enrolled between October 27, 2016, and December 21, 2018 ( n = 946; 66.1% <50 years of age, 53.5% with dense breasts). Adherence rates at 1 year was 24.8% increasing to 51.7% by year 2. Latinas randomized to the Promotora + brochure + letter arm (hazard ratio [HR]: 1.09 [95% confidence interval [95% CI] 0.87 to 1.36]) or brochure + letter (HR: 1.03 [95% CI 0.82 to 1.29]) arm were not more likely to be adherent to subsequent mammography compared to the letter only arm ( p = 0.76) . Adjusting for age and study group, having more prior mammograms, being “extremely likely” to get an annual mammogram, and having more confidence to get an annual mammogram at baseline were significant drivers of subsequent adherence. Conclusion: Informational interventions targeting BD education alone are unlikely to significantly improve adherence to subsequent mammography among Latinas receiving care in FQHCs.

Importance Obesity is a risk factor associated with multiple myeloma (MM) and its precursor, monoclonal gammopathy of unknown significance (MGUS). However, it is unclear how cumulative exposure to obesity affects the risk of MGUS progression to MM. Objective To determine the association of cumulative exposure to excess body mass index (EBMI), defined as BMI (calculated as weight in kilograms divided by height in meters squared) greater than 25, with risk of MGUS progression to MM. Design, Setting, and Participants This cohort study included patients with MGUS, including immunoglobin G, immunoglobin A, or light chain MGUS, from the nationwide US Veterans Health Administration database from October 1, 1999, to December 31, 2021. A published natural language processing–assisted model was used to confirm diagnoses of MGUS and progression to MM. Data were analyzed from February 12 to November 4, 2024. Exposures Cumulative EBMI was calculated by area under the curve of measured BMI subtracting the reference BMI at 25 during the first 3 years after MGUS diagnosis. Main Outcomes and Measures The main outcome was progression from MGUS to MM. Multivariable Fine-Gray time-to-competing-event analyses, with death as the competing event, were used to determine associations. Results The cohort included 22 429 patients with MGUS (median [IQR] age, 70.5 [63.5-77.9] years; 21 613 [96.4%] male), with 8329 Black patients (37.1%) and 14 100 White patients (62.9%). There were 4862 patients (21.7%) with reference range BMI (18.5 to &amp;lt;25), 7619 patients (34.0%) with BMI 25 to less than 30, and 8513 patients (38.0%) with BMI 30 or greater at the time of MGUS diagnosis. Compared with reference range BMI at MGUS diagnosis, patients with BMI 25 to less than 30 (adjusted hazard ratio [aHR], 1.17; 95% CI, 1.03-1.34) or 30 or greater (aHR, 1.27; 95% CI, 1.09-1.47) at MGUS diagnosis had higher risk of progression to MM. In patients with reference range BMI at MGUS diagnosis, each 1-unit increase of EBMI per year was associated with a 21% increase in progression risk (aHR, 1.21; 95% CI, 1.04-1.40). However, for patients with BMI 25 or greater at MGUS diagnosis, the incremental risk associated with cumulative EBMI exposure was not statistically significant. Conclusions and Relevance This cohort study found that, for patients with BMI 18.5 to less than 25 at the time of MGUS diagnosis, cumulative exposure to BMI 25 or greater was associated with an increased risk of progression. These findings suggest that for these patients, maintaining a healthy and stable weight following MGUS diagnosis may prevent progression to MM.

Abstract Background Benign breast disease (BBD) increases breast cancer (BC) risk progressively for women diagnosed with nonproliferative change, proliferative disease without atypia (PDWA), and atypical hyperplasia (AH). Leveraging data from 18 704 women in the Mayo BBD Cohort (1967-2013), we evaluated temporal trends in BBD diagnoses and how they have influenced associated BC risk over 4 decades. Methods BC risk trends associated with BBD were evaluated using standardized incidence ratios (SIRs) and age–period–cohort modeling across 4 eras—premammogram (1967-1981), precore needle biopsy (CNB) (1982-1992), transition to CNB (1993-2001), and CNB era (2002-2013). Results With a median follow-up of 15.8 years, 9.9% of women were diagnosed with BC (invasive and/or DCIS). From the premammogram era to the CNB era, we observed a significant increase in BC risk, rising from an SIR of 1.61 to 1.99. The proportion of proliferative BBD diagnoses (PDWA or AH) increased markedly over time (28.1%-49.7%), as did the proportion of DCIS events (11%-28%; χ2 P &lt; .001). Within specific BBD categories, the risk of invasive BC increased modestly. Conclusions Absolute risk of BC within BBD categories remained stable, but the relative risk of BC after BBD increased over time due to notable increases in higher risk BBD lesions, specifically PDWA and AH. These findings illustrate how evolving screening practices have changed the risk profile of BBD and should inform management strategies for patients with BBD in modern clinical settings.

Abstract Introduction Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. Robust evaluation of the value of adding mammographic density to models with comprehensive information on questionnaire-based risk factors and polygenic risk score is needed to determine its effectiveness in improving risk stratification of such models. Methods We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building and validation to incorporate density to a previously validated literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS). The model was evaluated for calibration and discrimination in three prospective cohorts of European-ancestry women (1,468 cases, 19,104 controls): US-based Nurses’ Health Study (NHS I and II) and Mayo Mammography Health Study (MMHS); and Sweden-based Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Analyses were done separately for women younger (NHS II, KARMA) and older than 50 years (NHS I, MMHS, KARMA). Improvements in terms of risk stratification and reclassification proportions were assessed among European-ancestry women aged 50–70 years in US and Sweden. Results For women younger and older than 50 years, the model with questionnaire-based risk factors, PRS and density was generally well calibrated across risk with some evidence of miscalibration at the extremes of the risk distribution. Incorporation of density led to modest improvements risk discrimination beyond the model with questionnaire-based risk factors and PRS: the area under the curve (AUC) among younger women was 67.0% (95% CI: 63.5–70.6%) vs. 65.6% (95% CI: 61.9–69.3%) for models with and without density; and 66.1% (95% CI 64.4–67.8%) vs. 65.5% (95% CI: 63.8–67.2%) among older women. The model with density identified 18.4% of US women 50–70 years old ≥ 3% 5-year predicted risk (threshold used for recommending risk-reducing medication in the US), with 42.4% of future cases expected to occur in this group. At this threshold, 7.9% of US women were reclassified by adding density to the model, resulting in the identification of 2.8% of additional future cases. The model with density identified 10.3% of Swedish women ≥ 3% 5-year predicted risk, with 29.4% of future cases expected to occur in this group. At this threshold, 5.3% of women were reclassified with the addition of density, leading to the identification of an additional 4.4% of future cases. Conclusion Integrating density with questionnaire-based risk factors and PRS could potentially identify more women of European-ancestry with elevated risk of breast cancer in the United States and Sweden. Further investigations of the integrated model in non-European ancestry populations are needed prior to considering clinical applications.