Olson, Janet E.

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

ABSTRACT Background Alcohol intake is a modifiable risk factor for breast cancer, yet patterns of alcohol intake in women with breast cancer remain underexplored. This study evaluates demographic and clinical predictors of alcohol intake in patients with breast cancer. Methods Patients at Mayo Clinic Rochester diagnosed with breast cancer (Stage 0–3) between July 2014 to March 2022 were surveyed about their average alcohol intake over the 10 years prior to their diagnosis. Alcohol intake was categorized as < 1, 1–4, 5–14, and ≥ 15 drinks per week. Demographic, behavioral, and clinical data were analyzed using univariate Fisher exact tests and multivariate multinomial logistic regression. Results Of 2030 participants (mean age at diagnosis: 59 years; 99.3% female; 95.9% White), 29% consumed < 1 drink/week, 48% reported 1–4 drinks/week, 20% consumed 5–14 drinks/week, and 3% reported ≥ 15 drinks/week. Older age at diagnosis (≥ 60 years), non‐White race, financial difficulty, and never smoking were associated with less alcohol intake. Patients who reported higher levels of mild–moderate intensity exercise reported more alcohol intake. Tumor stage, tumor receptors, and BRCA mutation status were not associated with alcohol intake. PROMIS‐10 physical health scores correlated with alcohol intake in univariate but not multivariate models. Conclusion Alcohol intake is more common prior to a breast cancer diagnosis for patients who are younger, White, financially secure, exercising, and smoking. These findings may inform alcohol intake‐related breast cancer prevention efforts and highlight patient subgroups who could benefit from targeted counseling at the time of diagnosis.

e12697 Background: Postpartum-associated breast cancer (PABC) has been defined clinically as breast cancer (BC) diagnosed within the first 5 years of the most recent birth. Though generally rare, incidence rates are increasing in conjunction with delayed childbearing and older maternal age at first birth. Currently, there are limited data regarding serial patient-reported outcomes in this patient population compared to non-PABC patients. Methods: Patients with PABC from the Mayo Clinic Breast Disease Registry who completed baseline, 2, and 4-year surveys were matched 1:1 to BC patients whose cancers occurred more than 5 years after their most recent birth (or in the setting of nulliparity) based on age, clinical stage, treatment received, and tumor subtype. Survey results from the Patient Health Questionnaire-2 (PHQ-2), Patient-Reported Outcomes Measurement Information System-10 (PROMIS-10), and Impact of Event Scale-Revised (IES-R) collected at approximately two and four years after diagnosis were compared between PABC and non-PABC patients. Univariable analyses used Wilcoxon rank sum tests, whereas multivariable analyses employed linear regression models adjusting for potential confounding effects. Results: A total of 222 individuals were included (111 with PABC). A higher proportion of individuals in the PABC cohort were married compared to the non-PABC cohort (80% vs. 42%, p < 0.001); otherwise, the groups were well-balanced across multiple categories, including age, gender, race/ethnicity, menopausal status, and germline mutation status. In univariable analyses, the Year 2 composite PHQ-2 score was significantly worse among individuals with non-PABC (p = 0.04), and the non-PABC cohort reported greater difficulty with sleep (p = 0.03) as measured by IES-R at Year 4. Both associations attenuated in a multivariable analysis controlling for marital status. In marital status-adjusted analyses of Year 4 survey results, PABC participants reported greater difficulty in carrying out social activities but were less likely to report emotional distress as evaluated by PROMIS-10 (compared with non-PABC participants). No other variables were significant univariably or multivariably (p > 0.05). Conclusions: In general, quality of life is similar among survivors of PABC compared to those diagnosed with breast cancer outside the postpartum period (or when nulliparous). However, our findings reveal that individuals with PABC are less likely to experience emotional distress 2 and 4 years after the BC diagnosis, which is unexpected, given that postpartum patients typically report higher levels of distress compared to their non-postpartum counterparts. Further investigation into these findings is warranted.

Abstract Background. Genome-wide association studies (GWAS) have identified 35 genetic susceptibility single-nucleotide polymorphisms (SNPs) for multiple myeloma (MM) in individuals of European ancestry (EA) and shown strong genetic correlation between MM and its precursor, monoclonal gammopathy of undetermined significance (MGUS). We evaluate the contribution of the 35 MM variants to MGUS susceptibility overall and by prognostic subgroups. Methods. The study included 20,756 participants (14,486 controls, 1,883 with MGUS, and 2,163 with MM) from the Mayo Clinic. Logistic regression assuming an additive model estimated odds ratios (ORs) and 95% confidence intervals (CIs) for individual SNPs and for the MM-PRS, adjusted for age, sex, study, and principal components. The PRS was a weighted sum of 35 SNPs with effect estimates from the largest MM GWAS and was modeled continuously (per SD) and by quintiles (Q1-Q5). SNPnexus annotated variants that replicated in MGUS (P &lt; 0.05 and OR &gt; 1.01) versus those that did not (P &gt; 0.05 and OR &lt; 1.01). Results. The 35-SNP MM-PRS was strongly associated with MM risk and modestly with MGUS. Compared with the middle quintile (Q3), MM odds rose from OR=0.55 (CI=0.46-0.65, P=2.2e-11) in Q1 to OR = 1.82 (CI=1.59-2.09, P=6.2e-18) in Q5. MGUS showed a similar, attenuated pattern (Q1 OR = 0.74, CI=0.64-0.84, P=6.4e-6 / Q5 OR=1.36, CI=1.21-1.53, P=3.4e-7). Each SD increase in PRS corresponded to OR=1.52 (CI=1.45-1.59, P=1.3e-66) for MM and OR = 1.22 (CI=1.18-1.27, P=1.0e-23) for MGUS. Higher PRS values were linked to larger M-protein ((0.1-1.5 g/dL: OR=1.40, CI=1.18-1.65, P=5.8e-12) vs &lt;0.1 g/dL: OR = 1.19, CI=1.13-1.24, P=5.8e-12)) and abnormal free light chain (FLC) ratio ((OR = 1.33, CI=1.21-1.46, P=1.0e-9) vs normal ratio (OR=1.19, CI=1.14-1.25, P=1.4e-13)). Ten risk loci replicated in MGUS, mapping to genes involved in plasma-cell function, immune regulation, and DNA repair and enriched for Rho GTPase signaling, NF-κB-mediated apoptosis, and RNA polymerase II transcription, implicating early plasma-cell activation and transcriptional control. The 12 non-replicating loci, including PHC3, ATG5, and NFIC, mapped to genes involved in chromatin remodeling, autophagy, and SUMOylation, suggesting roles in stress response and genomic maintenance. Conclusions. The MM-PRS captures shared heritability between MM and MGUS and correlates with MGUS subtype and severity. Replicating variants highlight immune and cell-cycle pathways relevant to MGUS onset, whereas non-replicating loci cluster in DNA-repair and stress-response processes, underscoring their potential role in progression. Citation Format: Alyssa Ione Clay-Gilmour, Angelica Macauda, Cristine Allmer, Danelle Moonen, Aaron D. Norman, Nicholas Boddicker, Janet E. Olson, Elizabeth E. Brown, Vincent S. Rajkumar, Esteban Braggio, David Murray, Susan Slager, Shaji Kunnathu Kumar, Celine Vachon. Implications of multiple myeloma polygenic risk scores (PRS) for MGUS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3603.

Abstract Purpose To evaluate alcohol intake trends and identify demographic, clinical, lifestyle and socioeconomic factors associated with alcohol consumption in late survivorship among breast cancer survivors. Methods Individuals diagnosed with stage 0–3 breast cancer enrolled in the Mayo Clinic Breast Disease registry between 2014 to 2022 reported their average weekly alcohol intake at baseline (time of diagnosis) and at approximately four years post-diagnosis. Alcohol intake was divided into four categories and cross-sectional associations with demographic, clinical, and lifestyle factors were examined using Monte Carlo-based Fisher exact tests and multivariable multinomial logistic regression. Changes in alcohol consumption from baseline to Year 4 were evaluated using Bowker’s test of symmetry and multinomial models. Results Among 719 participants, alcohol intake 4 years post diagnosis closely resembled baseline patterns, with 30.2% of patients reporting no alcohol use and 48.8% of patients consuming 1–4 drinks per week. Younger age and current smoking status were strongly associated with higher intake at Year 4. Exercise and better physical health were associated with higher alcohol intake in univariable models, however not in adjusted models. From time of diagnosis to Year 4, 15.6% of patients decreased their alcohol intake, 10.2% increased alcohol intake, and 74.3% reported no change. Higher levels of mild intensity exercise were associated with an elevation in alcohol intake over time. Conclusion Alcohol consumption remained stable in late survivorship, in contrast to the initial decline in alcohol use during early survivorship seen in this cohort. Younger age and smoking were key associations with higher alcohol intake.

Abstract Background: Monoclonal B-cell lymphocytosis (MBL), a precursor to chronic lymphocytic leukemia (CLL), is an understudied yet common premalignant condition present in ~8 million adults in the United States. Based on flow cytometry, MBL can be classified into two immunophenotypes: CLL-type (CD5, CD23, and CD20 co-expression) and non-CLL-type (CD5-negative). While the majority of the data to date pertains to CLL-type MBL, the available evidence indicates non-CLL-type MBL is also associated with an increased risk of hematologic malignancies. Clonal hematopoiesis of indeterminate potential (CHIP) is another precursor condition associated with hematologic malignancies. The relationship between non-CLL-type MBL and CHIP and their combined effect remains unknown. Herein, we report findings on these two precursor conditions in the largest screening cohort to date. Methods: Using flow cytometry, we screened for MBL in the Mayo Clinic Biobank participants who were 40 years or older with no prior history of hematologic cancers. Using whole-exome sequencing of whole-blood DNA, CHIP was screened on 291 genes related to myeloid (56 genes) or lymphoid malignancies (235 genes). Incident hematologic malignancies were detected during follow-up using International Classification of Diseases (ICD) codes in the medical record. All diagnoses were manually reviewed for confirmation. Multivariable logistic regression was used to evaluate the association between non-CLL-type MBL and CHIP. Time to incident hematologic malignancy was calculated from date of MBL screening to the earliest date of incident malignancy, withdrawal, death, last medical visit, or study end. Overall survival (OS) was calculated from date of MBL screening to date of death or last known alive. Multivariable Cox regression, adjusted for age, sex and residency, was used to investigate associations between non-CLL-type MBL and CHIP with clinical outcomes; with results reported using hazard ratios (HR) and 95% confidence intervals (CI). Results: In total, 8,802 individuals with MBL screening and CHIP data were analyzed. Non-CLL-type MBL was detected in 249 (2.8%) individuals; 121 (49%) were male, and median age was 78 years (range, 47-95). We identified 757 (8.6%) individuals with CHIP in at least one of the 291 genes tested. The most frequently mutated CHIP genes were DNMT3A, TET2, ASXL1, PPM1D, and TP53. A total of 47 (0.5%) individuals had both non-CLL-type MBL and CHIP; the four genes with the highest number of CHIP variants in these individuals were DNMT3A (n=16), TET2 (n=10), ASXL1 (n=3), and ATM (n=3). An association between non-CLL-type MBL and any CHIP (OR=1.6, 95%CI:1.2-2.3, P=0.006) was observed. When analyzing CHIP in genes related to myeloid malignancies, the association with non-CLL-type MBL was also significant (OR=1.6, 95%CI:1.1-2.3, P=0.012); however, the association was not statistically significant for genes related to lymphoid malignancies (OR=1.6, 95%CI:0.8-3.3, P=0.165). With a median follow-up of 5.4 years, 104 individuals developed incident hematologic malignancies (66 lymphoid and 38 myeloid malignancies). Non-CLL-type MBL (HR=3.5, 95%CI:1.9-6.5, P&lt;0.001) and CHIP (HR=3.2, 95%CI:2.1-5.1, P&lt;0.001) were each associated with increased risk of incident hematologic malignancies. Co-existence of both precursor conditions was associated with a substantially higher risk of incident hematologic malignancies (HR=10.3, 95%CI:4.0-26.2, P&lt;0.001) compared to individuals with neither precursor condition. Among individuals with non-CLL-like MBL, any CHIP was a borderline significant predictor for incident hematologic malignancy (HR=3.6, 95%CI:1.0-12.9, P=0.049). Compared to individuals with no precursor conditions, OS was not significantly different in those with non-CLL-type MBL-only (HR=1.1, 95%CI:0.8-1.5, P=0.40), those with CHIP-only (HR=1.2, 95%CI:0.99-1.4, P=0.06), or those with both CHIP and non-CLL-type MBL (HR=1.3, 95%CI:0.8-2.1, P=0.39). Conclusions: In the largest screening cohort to date evaluating the relationship of CHIP and non-CLL-type MBL, we found that non-CLL-type MBL and CHIP are associated with each other. Individuals with non-CLL-type MBL were more likely to have CHIP variants in DNMT3A, TET2, ASXL1, and ATM. Among individuals with non-CLL-type MBL, the presence of any CHIP was associated with increased risk of developing hematologic malignancy.

Abstract Background Mosaic chromosomal alterations (mCAs) are large-scale somatic gains, losses, or copy-neutral loss of heterozygosity (CNLOH) detectable by genotyping of peripheral blood DNA. They represent a form of clonal hematopoiesis and are observed in 0.5-5% of cancer-free individuals. The presence of any autosomal mCA has been associated with &gt;3-fold risk of hematological malignancies. In particular, mCAs occurring in regions related to lymphoid malignancies have an 11-fold increased risk of lymphoid malignancies and a 68.6-fold risk for chronic lymphocytic leukemia (CLL). Monoclonal B-cell lymphocytosis (MBL), the precursor state to CLL, is defined by &lt;5×10⁹/L clonal B cells in otherwise healthy individuals and is classified as low-count (&lt;0.5x109/L) or high-count (0.5-5x10⁹/L) based on clonal B-cell count. MBL is also associated with increased risk of lymphoid malignancy (beyond CLL), with 4.3-fold and 74-fold risk in individuals with low- and high-count MBL, respectively. We previously reported a significant enrichment of autosomal mCAs in MBL, demonstrating a 1.7-fold association in those with low-count MBL and a 50.5-fold association in those with high-count MBL. Whether mCAs independently predict lymphoid malignancy risk after accounting for MBL status is unknown. Here, we evaluated the impact of mCAs on risk of incident lymphoid malignancies in individuals with MBL and in individuals screened negative for MBL. Methods CLL-type MBL (CD5 positive) was identified using flow cytometry assay on peripheral blood. Participants were age ≥40, had no prior hematologic malignancy, and were enrolled through the Mayo Clinic Biobank or the Division of Hematology at Mayo Clinic, Rochester. Participants were followed for incident lymphoid malignancy, including CLL, with diagnoses confirmed by medical record review. mCAs with cell fraction &gt;1% were detected from array-based genotyping of whole blood DNA. Cox proportional hazards models, adjusted for age and sex, estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of developing an incident lymphoid malignancy in individuals with autosomal mCA versus those without an autosomal mCA. Results In 4,331 participants with available MBL and mCA status, the median age was 67 years, and 45% were male. Flow cytometry identified 3,231 individuals who screened negative for MBL, 754 individuals with low-count MBL, and 346 individuals with high-count MBL. Autosomal mCAs were present in 6.5% of individuals without MBL, 7.6% with low-count MBL, and 71.1% with high-count MBL. Over a median follow-up of 6.9 years, 237 individuals developed an incident lymphoid malignancy. The most common types were CLL, multiple myeloma, and diffuse large B-cell lymphoma. Ignoring MBL status, the presence of an autosomal mCA was associated with increased risk of lymphoid malignancy (HR = 2.65; 95% CI: 1.45–4.86; P = 0.002), replicating previous results. However, after excluding individuals with MBL, this association attenuated; those with mCA alone did not have a significantly elevated risk (HR = 1.60; 95% CI: 0.57-4.52; P = 0.38) compared to individuals without MBL or mCA. We next examined the effect of mCAs among individuals with MBL. In those with low-count MBL, the most frequent mCA events were 13q loss (2.1%), 12 gain (1.9%), and 4q CNLOH (1.2%), and individuals with an mCA had a borderline significant risk of developing a lymphoid malignancy (HR = 2.78; 95% CI: 1.01–7.67; P = 0.049) compared to those without an mCA. Similarly, in those with high-count MBL, the most frequent mCA events were 13q loss/CNLOH (31.2%), 12 gain (13.0%), and 11q loss (4.9%), and the presence of an mCA conferred an increased risk compared to those without mCA (HR = 1.51; 95% CI: 1.09-2.08; P = 0.012). Conclusions Autosomal mCAs were more frequent in individuals with high-count MBL compared to those with low-count or no MBL. mCAs showed limited predictive value for lymphoid malignancy among individuals without MBL. In contrast, in individuals with low-count MBL, autosomal mCAs emerged as a potential biomarker for identifying those at risk of developing a lymphoid malignancy. In high-count MBL, mCAs were also a biomarker, but were driven by known chromosomal abnormalities identified through clinical testing. These findings suggest that the utility of mCAs as a predictive marker for lymphoid malignancy is contingent on the presence of MBL and may inform risk stratification and surveillance strategies in this population.

Abstract Description The two key determinants of successful vaccines are the ability to induce a protective immune response and a long-lived immune memory. The mechanism determining durability and its contribution to the lower vaccine efficacy in older adults is elusive. We use varicella zoster virus (VZV) vaccination as a model that relies on cellular, not humoral immunity. We compared long-lived antigen-specific memory T cells in adults who were vaccinated at young (&lt;20 years) or older age (&gt;50 years) with a life-attenuated vaccine that confers sustained protection only in young age, or who received an adjuvanted subunit vaccine that is protective at older age. We stimulated PBMCs of vaccine recipients years after vaccination and collected VZV-reactive T cells for spectral flow cytometry and single-cell sequencing. While CD4 T cells were resilient to aging, VZV-specific CD8 T cells lost diversity and lacked stem-like features while gaining end-differentiated, NK-like signatures. These age-associated changes in CD8 T cells were not reversed with the effective subunit vaccine. Instead, this vaccine induced pro-inflammatory VZV-specific TH17 cells. TH17 cells in the less efficient vaccine response, albeit present, were skewed towards a FOXP3+ regulatory phenotype and deficient in TH1 polyfunctionality – a phenotypic shift that is in part controlled by lipid metabolic pathways. Our study uncovers traits of T cell dysfunction with age and informs vaccination efforts tailored towards healthy aging. Funding Sources NIH U19AI057266, R01AG045779, R01AI108891, R01AI129191, T32AG049672, Glenn Foundation for Medical Research Postdoctoral Fellowship, Robert and Arlene Kogod Center on Aging Career Development Award. Topic Categories Lymphocyte Differentiation and Peripheral Maintenance (LYM)

Treatment-induced ovarian function loss is a significant concern for many young patients with breast cancer. Accurately predicting this risk is crucial for counselling young patients and informing their fertility-related decision-making. However, current risk prediction models for treatment-related ovarian function loss have limitations. To provide a broader representation of patient cohorts and improve feature selection, we combined retrospective data from six datasets within the FoRECAsT (Infertility after Cancer Predictor) databank, including 2679 pre-menopausal women diagnosed with breast cancer. This combined dataset presented notable missingness, prompting us to employ cross imputation using the k-nearest neighbours (KNN) machine learning (ML) algorithm. Employing Lasso regression, we developed an ML model to forecast the risk of treatment-related amenorrhea as a surrogate marker of ovarian function loss at 12 months after starting chemotherapy. Our model identified 20 variables significantly associated with risk of developing amenorrhea. Internal validation resulted in an area under the receiver operating characteristic curve (AUC) of 0.820 (95% CI: 0.817–0.823), while external validation with another dataset demonstrated an AUC of 0.743 (95% CI: 0.666–0.818). A cutoff of 0.20 was chosen to achieve higher sensitivity in validation, as false negatives—patients incorrectly classified as likely to regain menses—could miss timely opportunities for fertility preservation if desired. At this threshold, internal validation yielded sensitivity and precision rates of 91.3% and 61.7%, respectively, while external validation showed 92.9% and 60.0%. Leveraging ML methodologies, we not only devised a model for personalised risk prediction of amenorrhea, demonstrating substantial enhancements over existing models but also showcased a robust framework for maximally harnessing available data sources.

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.