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.

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 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.

INTRODUCTION:Non-GFR determinants of filtration markers reduce the accuracy of estimated GFR (eGFR) and genetic factors may explain part of this reduced performance. Here, we identify genetic variants associated with serum levels of creatinine or cystatin C (but not GFR), compute their effect, and investigate candidate genes. METHODS:We used data from the UK Biobank (approximately 470,000 people) and the CKD-EPI creatinine (eGFRcr) and cystatin C (eGFRcys) equations. Using genome-wide association studies (GWAS), we defined strict criteria to classify loci as creatinine-specific or cystatin C-specific, refined with co-localization studies, and identified associated pathways. We computed biomarker and eGFR polygenic scores as the cumulative effect of biomarker-specific loci (genetic bias) and tested their associations to surrogate markers of identified pathways. Findings were validated by independent studies with measured GFR and mapped candidate genes using expression quantitative trait loci (eQTL) resources. RESULTS:We identified 52 creatinine-specific and 48 cystatin C-specific loci. Using eQTLs to identify candidate causal genes, enriched pathways were energy and muscle metabolism for creatinine, and inflammatory response, cancer, cysteine endopeptidase activity, wound healing, and immune modulatory functions for cystatin C. Polygenic scores showed that individual-level genetic bias in eGFRcr and eGFRcys had mean values of 3.8 (standard deviation 0.94, range -1.5 to 7.9) mL/min per 1.73m2 and 0.6 (standard deviation 0.93, range -3.5 to 4.7) mL/min per 1.73m2 , respectively. Genetic bias was different per self-reported race for creatinine and correlated with surrogate markers of selected pathways (muscle mass, for creatinine; body mass index and C-reactive protein, for cystatin C). Lastly, we showed that the difference between polygenic scores derived from GWAS with and without adjustments for the biomarker-specific variants was associated with GFR bias in two independent cohorts (1304 and 939 individuals). CONCLUSIONS:Our study identified loci related to serum creatinine or cystatin C but not to GFR and quantified the populational and individual-level effect of genetic determinants on filtration markers and eGFRs.

Abstract Immune dysfunction has been increasingly implicated in bipolar disorder, but the underlying mechanisms remain unclear. To address this, we profile 833 genome-wide chromatin immunoprecipitation sequencing datasets spanning five histone marks in peripheral blood immune cells from 88 Type I bipolar disorder patients and 92 controls, integrating them with whole-genome sequencing and clinical data. We identify disease-associated cis -regulatory elements and genetically influenced regulatory elements, revealing immune signatures and pathways involving calcium signaling and endoplasmic reticulum transport. By integrating genetic risk variants, differential and genetically influenced regulatory elements, and regulatory element—gene links, we prioritize 39 driver genes, 28 of which are exclusively supported by blood evidence. We further stratify patients into five epigenomic subtypes with distinct clinical features and genetic risk profiles and identify compounds that reverse disease-associated epigenomic signatures. Here, we combine immune epigenomics with genetics and clinical traits to identify driver genes, patient subtypes, and therapeutic candidates, highlighting immune contributions to type I bipolar disorder pathogenesis.

To evaluate alcohol intake trends and identify demographic, clinical, lifestyle, and socioeconomic factors associated with alcohol consumption in late survivorship among breast cancer survivors. Individuals diagnosed with stage 0–3 breast cancer enrolled in the Mayo Clinic Breast Disease registry between 2014 and 2022 reported their average weekly alcohol intake at baseline (time of diagnosis) and at approximately 4 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. Among 719 participants, alcohol intake 4 years post-diagnosis closely resembled baseline patterns, with 30.2

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 < 0.05 and OR > 1.01) versus those that did not (P > 0.05 and OR < 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 <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.

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 (<0.2 g/dL; 0.2-1.5 g/dL; >1.5 g/dL); isotype (IgG, IgA, IgM); free light chain (FLC) ratio (Normal (0.26-1.65), Abnormal (<0.26 or >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 > 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 <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. 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.

Germ cell tumors (GCTs) pose significant diagnostic challenges because of the limited performance of existing tumor markers. Here, we used phage immunoprecipitation sequencing (PhIP-Seq) to develop a unique immunosignature panel to improve diagnosing and differentiating GCT. Using 427 serum samples (150 GCT, 277 controls), we developed and validated an immunosignature panel (GCT-iSIGN) comprising 24 peptides from 16 unique proteins. This panel achieved 93% sensitivity, 99% specificity, and an area under the curve (AUC) of 0.98, identifying 23/24 biomarker-negative GCT cases. A secondary model (Sem-iSIGN), consisting of 17 peptides from five proteins, differentiated seminoma from nonseminoma with 96% specificity, 65% sensitivity, and AUC of 0.77. RNA sequencing data from The Cancer Genome Atlas confirmed differential overexpression of target antigens in testicular cancer. ELISA validation of ERVK7 and LUZP4 and immunohistochemical detection of ERVK7, MUC4, ZNF91, and LUZP4 in tumor tissues supported target expression. This study highlights PhIP-Seq immunoprofiling to identify serum-based immunosignature panels that can serve as biomarkers for GCTs. This approach addresses the shortcomings of conventional markers and offers a scalable, cost-effective tool for improving cancer diagnosis and management.

Background: Alcohol intake (AI) has consistently been shown to increase the risk of breast cancer (BC), and AI during survivorship may impair prognosis. The American Cancer Society, American Institute for Cancer Research, and National Comprehensive Cancer Network guidelines recommend that female survivors abstain from or limit AI to no more than 1 drink per day. Yet many US cancer survivors self-report regular AI, including some who display excessive drinking behaviors. As AI is potentially modifiable, a better understanding of factors associated with AI in BC survivors may inform public health strategies to reduce risk of recurrence. This study aimed to describe sociodemographic and treatment-related predictors of AI near the time of BC diagnosis, and approximately four years after the same. METHODS: Adult patients newly diagnosed (within 1 year prior) with BC (stage I-III) and seen at Mayo Clinic Rochester were invited to enroll in the Mayo Clinic Breast Disease Registry. Those who consented to participate between 12/4/2014 and 4/16/2018 (N=3252) were asked to complete self-reported questionnaires at baseline and at four years after diagnosis. These questionnaires included questions about weekly AI, education, and other demographic factors. Respondents reported weekly AI as follows: none, 1-4, 5-9, 10-14, 15-19, 20-29, 30-39, or 40+ drinks per week, with one drink defined as 5 ounces of wine, 12 ounces of beer or 1 ounce of liquor. Three patients with recurrences were excluded (N=734). Clinical data were abstracted from medical records by a trained nurse abstractor. Questionnaire data from year 2 were used to understand how posttraumatic symptoms, assessed by the Impact of Event Scale (IES-R), as well as depression, assessed by the PHQ-2, might be associated with later AI. Univariate models were used to assess which factors were associated with higher AI (5+ drinks per week) at year 4. Associations of AI with variables of interest were assessed using Cochran Mantel Haenszel tests for trend. This longitudinal cohort study was approved by the institutional review board. Results: Among 734 participants who reported their weekly AI at both timepoints (mean age 58.5 years, 98.9% female, 97% white), 176 (24%) and 137 (18.7%) reported AI of ≥5 drinks weekly at baseline and year 4, respectively. Higher AI at baseline was strongly associated with higher AI at year 4 (p<0.001). There was a decrease in total AI over time across the cohort (p=0.003). In univariate models, younger age at cancer diagnosis (p<0.001), not having received radiotherapy (p=0.05), and carrying a known deleterious BRCA mutation (p=0.05) were associated with greater AI at year 4. Smoking was associated with greater AI at both baseline and year 4 (p<0.001). More minutes of moderate intensity exercise (described as “not exhausted”, example fast walking) and mild intensity exercise (described as “minimal effort”, example easy walking), higher Godin activity scores, and greater physical health at baseline and year 4 were also associated with increased AI. The IES-R total score at year 2 was strongly positively associated with high AI at year 4 (p<0.001), as were IES-R subscale scores for intrusion (p=0.008), avoidance (p=0.006), and hyperarousal (p<0.001). Higher depression scores at year 2 also were linked to greater AI at year 4 (p=0.04). Financial stability, educational status, having received chemotherapy, having received endocrine therapy, tumor stage and type of surgical treatment pursued were not associated with AI at year 4. Coclusion: While overall AI decreased over time in this cohort of BC survivors, AI at baseline was still associated with AI at 4 years. Young patients and those with deleterious BRCA1/2 mutations, as well as those who reported posttraumatic distress and depressive symptoms at year 2, were more likely to report AI at year 4 after a BC diagnosis. These findings may inform targeted public health interventions to mitigate AI and improve BC outcomes. Citation Format: Sanjna Rajput, Robert A Vierkant, Nicole L. Larson, Daniela L. Stan, Dawn M. Mussallem, Shawna L. Ehlers, Stacy D. D’Andre, Fergus J. Couch, Janet E. Olson, Ciara C. O’Sullivan, Kathryn J. Ruddy. Factors and trends associated with alcohol intake in late survivorship for patients with breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr PS15-08.

Up to 30% of women with no evidence of disease after curative intent breast cancer treatment will relapse and succumb to metastatic disease. Liquid biopsy of circulating tumor DNA (ctDNA) has been shown to identify patients with relapse prior to imaging. Tumor-informed ctDNA panels are expensive and require patient tumor tissue for customization. We aimed to assess tumor-agnostic methylated DNA markers (MDMs) to detect recurrent metastatic breast cancer in comparison to cancer-free patients and those with no evidence of disease. We discovered and down-selected candidate MDMs from a series of tissue-based experiments on primary breast cancer tissue from a balance of molecular subtypes compared to matched non-cancer patient breast tissues. We then used Target Enrichment Long-probe Quantitative Amplified Signal assays to quantify 16 MDMs from cfDNA extracted from peripheral blood samples from 60 metastatic breast cancer patients (59 females, 1 male), 60 age-matched females with no prior cancer, and 60 age-matched females without evidence of metastatic disease at least 9 months after curative intent treatment of primary breast cancer. Among the 16 MDMs, ten had single-marker areas under the curve (AUCs) above 0.90, with the highest at 0.96, whereas in the same patients, three protein markers (CA153, CEA, CA125) performed with an AUC of 0.86, 0.84, and 0.75, respectively. The results indicate that a multi-marker methylation panel can detect metastatic breast cancer patients.

Clonal hematopoiesis (CH) of indeterminate potential (CHIP), driven by somatic mutations in leukemia-associated genes, confers increased risk of hematologic malignancies, cardiovascular disease, and all-cause mortality. In blood of healthy individuals, small CH clones can expand over time to reach 2% variant allele frequency (VAF), the current threshold for CHIP. Nevertheless, reliable detection of low-VAF CHIP mutations is challenging, often relying on deep targeted sequencing. Here, we present UNISOM, a streamlined workflow for enhancing CHIP detection from whole-genome and whole-exome sequencing data that are underpowered, especially for low VAFs. UNISOM utilizes a meta-caller for variant detection, in couple with machine learning models which classify variants into CHIP, germline, and artifact. In whole-exome sequencing data, UNISOM recovered nearly 80% of the CHIP mutations identified via deep targeted sequencing in the same cohort. Applied to whole-genome sequencing data from Mayo Clinic Biobank, it recapitulated the patterns previously established in much larger cohorts, including the most frequently mutated CHIP genes and predominant mutation types and signatures, as well as strong associations of CHIP with age and smoking status. Notably, 30% of the identified CHIP mutations had < 5% VAFs, demonstrating its high sensitivity toward small mutant clones. This workflow is applicable to CHIP screening in population genomic studies. The UNISOM pipeline is freely available at https://github.com/shulanmayo/UNISOM and https://ngdc.cncb.ac.cn/biocode/tool/7816.

PURPOSE Over 50% of households in the United States have at least one musician—many musicians are also breast cancer survivors. This group has not been well studied, and given the level of fine sensory-motor skill required for musicianship, we hypothesized that musicians experience unique manifestations of breast cancer treatment toxicities. METHODS A nine-item Musical Toxicity Questionnaire (MTQ) was distributed to patients who had consented to participate in the Mayo Clinic Breast Cancer Registry. The MTQ screened participants by asking if they played a musical instrument or sang in the last 10 years: questions populated for those who answered yes. Respondents were asked if they noticed difficulty with their musical endeavor during or after breast cancer treatment, defined as acute musical toxicity (AMT). The questionnaire asked which side effect and cancer-directed therapy most influenced musical ability, what musical attributes were affected, and the timeline of resolution. Multivariable and classification tree analyses assessed relationships between AMT and treatment characteristics. RESULTS Of 1,871 survey respondents, 29% (535/1,871) self-identified as musicians. Over a quarter (27%, 144/535) reported AMT, and for 57% (82/144), AMT had not resolved at the time of survey. Of the treatments each participant received, chemotherapy was most often reported as most negatively impactful (63/89 who received chemotherapy, 71%). Decreased endurance was the most common musical difficulty (64% of those with AMT, 92/144), followed by decreased accuracy, trouble playing/singing quickly, and difficulty using proper technique. Multivariable and classification tree analyses revealed that receipt of chemotherapy was most strongly correlated with AMT. CONCLUSION These results will help oncology care teams counsel musicians, answer questions about impacts on musicality, and provide a timeline for resolution of musical symptoms.

12038 Background: CIPN, primarily associated with sensory neuropathy rather than motor or autonomic dysfunction, is a potentially long-term complication of cancer treatment including taxanes and platinums (T/Ps), and can negatively impact quality of life for breast cancer (BC) survivors. This project aims to quantify the severity of neuropathic symptoms at one and three years after diagnosis in BC survivors, comparing recipients of T/P to non-recipients. Methods: In the Mayo Clinic Breast Registry (MCBDR), a longitudinal cohort, surveys and medical record data from patients with stage 1-3 BC were used to understand the burden of neuropathic symptoms at 1- and 3-years post-diagnosis (denoted as Y1 and Y3). Y1 and Y3 raw scores from The Quality of Life Questionnaire-Chemotherapy-Induced Peripheral Neuropathy 20 (CIPN20) composite (CIPN20-C) and sensory subscale (CIPN-S) were converted to a 0-100 point scale, with lower scores corresponding to worse symptoms. Patients with BC recurrence prior to Y3 or incomplete surveys were excluded. We used two sample t-tests and multivariable linear regression modeling to compare recipients of T/P to non-recipients of T/P (with threshold for statistical significance p <0.05). Results: 786 patients were included, 112 of whom (14.2%) received T/P. T/P recipients were younger (p<0.001), more likely to have Stage II/III disease (p<0.001), and less likely to have received endocrine therapy (p<0.001). Univariate analyses revealed worse CIPN20-C score at Y1 (p=0.02) and worse CIPN20-S scores (p=0.004) at Y1 and Y3 in T/P recipients compared to non-recipients (Table). However, differences between the groups were no longer statistically significant after adjustment for age, stage and endocrine therapy. Conclusions: In this cohort, neuropathic symptom severity at Y1 and Y3 after a breast cancer diagnosis did not differ between recipients of taxane and/or platinum agents and nonrecipients after adjustment for age, stage, and endocrine therapy. These data may reassure patients and clinicians who are concerned about CIPN and considering use of these chemotherapies in this setting. Patient demographics and CIPN20 results. Clinical characteristic T/P recipients Non-recipients of T/P Age at diagnosis, mean (SD) 55.3 (11.6)* 59.8 (11.9) White race, N (%) 108 (96.4%) 660 (97.9%) Clinical stage II/III, N (%) 76 (68.5%)* 250 (37.5%) Endocrine therapy, N (%) 73 (65.2%)* 636 (94.4%) Diabetes mellitus, N (%) 9 (8.9%) 52 (8.6%) Y1 CIPN20-C score, mean (SD) 89.6 (10.9)* 92.0 (9.7) Y3 CIPN-C score, mean (SD) 89.4 (11.4) 91.1 (9.7) Y1 CIPN20- S score, mean (SD) 87.3 (15.1)* 91.3 (13.0) Y3 CIPN20-S score, mean (SD) 88.2 (14.1)* 91.1 (11.7) *Statistically significant (p <0.05) on univariate analysis.

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.

Frequencies of all reported germline CHEK2 variant carriers and carriers of variants concordantly categorized by functional our kinase assays in breast cancer patients and controls in 12 analyzed population datasets.