Vierkant, Robert A.

Abstract Rationale Idiopathic Pulmonary Fibrosis (IPF) is characterized by chronic progressive pulmonary fibrosis and high mortality. Genetic markers, summarized into a polygenic risk score (PRS), associate with IPF in well-phenotyped research cohorts. Objectives To evaluate the performance of the PRS using real-world data from routinely captured electronic healthcare records. Methods We conducted an observational study evaluating the association of a PRS for IPF with electronic healthcare record diagnosis of IPF as well as lung transplant-free survival in four independent cohorts; the Mass General Brigham Biobank (MGBB), Mayo Clinic Biobank (MCBB), Mayo Clinic Tapestry Cohort (Tapestry), and U.K. Biobank (UKBB). We used multivariable logistic regression and multivariable Cox proportional hazards models adjusting for age, gender, and principal components of ancestry. The cohorts then underwent fixed and random effects meta-analysis. Measurements and Main Results Of 37,709; 44,195; 43,202; and 447,422 participants from MGBB, MCBB, Tapestry and UKBB respectively, 1,015 (2.7%) 2,879 (6.5%), 1,310 (3.0%), and 2,742 (0.6%) participants had an IPF diagnosis. Meta-analysis demonstrated a high-risk PRS associated with IPF diagnosis, OR 2.88 (95%CI 2.41-3.44) compared to all other individuals. A high-risk PRS also associated with the composite endpoint of mortality or lung transplant among those with an IPF diagnosis, HR 1.23(95%CI 1.11-1.35) compared to all other individuals. Conclusions A PRS can identify those at risk for an IPF diagnosis and mortality in biobank-scale data, which may have implications for clinical decisions. Further work is necessary to evaluate the utility of adding genetics in clinical settings.

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.

8077 Background: Small cell lung cancer (SCLC) is an aggressive malignancy with poor prognosis. This study evaluates national trends in surgical management of early-stage SCLC using the National Cancer Database (NCDB), aiming to identify factors associated with improved outcomes and assess the survival benefit of surgical resection. Methods: Patients diagnosed with clinical stage T1–T3 N0 M0 SCLC between 2004 and 2022 were identified from the NCDB. Exclusions included non-SCLC histologies, advanced or missing staging, non-lobectomy surgeries, and incomplete survival data. Propensity score matching (1:1) was used to balance surgical and non-surgical cohorts based on demographic, clinical, and socioeconomic variables. Kaplan-Meier and Cox regression analyses were used to evaluate overall survival, stratified by T stage. Results: Among 17,762 patients with early-stage SCLC, 3,234 (18.2%) underwent lobectomy with mediastinal lymph node dissection. Surgical rates increased from 5% in 2004, 17% in 2013 to 24% in 2021. Surgery was more common in T1 (26.5%) than T2 (11.4%) or T3 (4.6%) disease. After matching, surgery was associated with improved survival across all T stages, with no significant interaction between T stage and surgical benefit (p=0.43). Older age, male sex, and higher comorbidity scores predicted worse outcomes. Among surgical patients, 2.3% received neoadjuvant therapy and 71.6% received adjuvant treatment. Systemic therapy-both neoadjuvant (HR 0.63) and adjuvant (HR 0.69)-was significantly associated with improved survival. Conclusions: Lobectomy remains underutilized in early-stage SCLC but is linked to significantly improved survival. Albeit small patient's number, neoadjuvant systemic therapy further enhanced survival, supporting broader use of surgery and multimodal treatment in appropriately selected patients Univariable results 1 Multivariable results 2 Characteristic No. deaths Person-months HR (95% CI) p-value HR (95% CI) p-value Charlson score <0.001 <0.001 0 761 77727 1.00 (ref) 1.00 (ref) 1 623 60483 1.06 (0.95,1.18) 1.07 (0.96,1.20) 2 or more 350 27025 1.30 (1.15,1.48) 1.30 (1.13,1.48) Clinical T-stage 0.011 0.014 cT1N0M0 1266 124916 1.00 (ref) 1.00 (ref) cT2N0M0 406 33924 1.18 (1.06,1.32) 1.20 (1.06,1.35) cT3N0M0 62 6393 0.96 (0.75,1.24) 1.00 (0.76,1.31) Residual disease <0.001 <0.001 No residual tumor 1626 158838 1.00 (ref) 1.00 (ref) Residual tumor 92 4699 1.91 (1.55,2.36) 1.91 (1.52,2.40) Neoadjuvant systemic treatment 0.253 0.034 No 1629 154116 1.00 (ref) 1.00 (ref) Yes 30 3495 0.81 (0.56,1.16) 0.63 (0.41,0.97) Adjuvant radiation 0.067 <0.001 No 1209 118925 1.00 (ref) 1.00 (ref) Yes 452 40471 1.11 (0.99,1.23) 1.33 (1.18,1.51) Adjuvant systemic treatment <0.001 <0.001 No 563 44045 1.00 (ref) 1.00 (ref) Yes 1096 113566 0.75 (0.68,0.83) 0.69 (0.62,0.78)

Abstract Background: Smoking, a known risk factor for numerous cancers, negatively impacts long-term survival in breast cancer (BC) survivors (Parada H Jr et al., 2017; Pierce et al., 2019). This study aims to characterize baseline smoking behaviors among breast cancer patients who self-reported smoking during an initial survey. Objectives: To assess attributes of patients self-reporting as current smokers near BC diagnosis, examining demographics, habits, quality of life, cancer treatments, comorbidities, and finances. Methods: Patients with newly diagnosed BC seen at Mayo Clinic Rochester between 2014-2024 were invited to enroll in the Mayo Clinic Breast Disease Registry. Consenting participants who completed self-reported questionnaires at baseline were included in this study. Smoking status and related variables at the time of survey completion were assessed via a baseline questionnaire, classifying participants as current, former, or never smokers. Of 3,959 participants completing baseline surveys, 3,729 were analyzed after excluding 103 with missing smoking data and 127 with their baseline survey returned &gt;1-year post-diagnosis. Categorical variables were summarized with frequencies and percents, continuous variables with distributional statistics. Univariable associations with current smoking were assessed via two-sample t-tests (continuous) and chi-square or Fisher exact tests (categorical). Significant variables (p&lt;0.05) were included in a multivariable logistic regression model. Results: Among 3,729 BC patients (mean age 58.3 years, SD 12.9), 99.1% were female, 97.1% White, and 98.7% non-Hispanic. Only 2.7% reported financial difficulty, 56.4% had a bachelor's degree or higher, 81.7% were married or equivalent, and 21.7% consumed ≥5 alcoholic drinks/week. Tumor stage distribution was as follows: Stage 0 (13.9%), Stage 1 (43.9%), Stage 2 (28.9%), Stage 3 (8.9%), and Stage 4 (4.5%); 33.8% received chemotherapy, 56.5% radiotherapy, 63.6% endocrine therapy, and 42.2% underwent mastectomy. Current smokers (2.6%, n = 95) had a median diagnosis age of 59.1 (IQR 31.8-87.1),with 32.6% consuming ≥5 drinks/week (vs. 21.5% in non-smokers, univariable p = 0.012), 69.5% with less than a Bachelor’s degree (vs. 42.9%, p&lt;0.001), 9.6% facing financial difficulty (vs. 2.5%, p&lt;0.001), and 10.5% diagnosed within 270-365 days after survey return (vs. 4.2%, p = 0.022). Tumor stage showed 47% with Stage 1 (vs. 43.7%, p = 0.245); 33.7% received chemotherapy, 60.0% radiotherapy, and 58.9% endocrine therapy. Current smokers had a mean smoking initiation age of 19.9 (SD 6.2), smoked 12.5 cigarettes/day (SD 7.9) for 32.8 years (SD 14.1), with mean 22.3 pack-years (SD 17.2).Univariable associations of demographic and clinical characteristics with current smoking showed Compared to never or former smokers, current smokers at the time of survey took a longer time to return their baseline survey (p = 0.022), were more likely to consume five or more alcoholic drinks per week (p = 0.012), were more likely to have difficulty paying their bills (p&lt;0.001) and were less likely to obtain a Bachelor's degree or higher (p&lt;0.001). These associations remained significant after multivariable adjustment. Conclusion: Current smoking (2.6%) soon after a BC diagnosis was independently associated with delayed survey return, higher alcohol use, financial difficulty, and lower education. Assessing smoking status and referring patients to smoking cessation programs are critical for addressing these risk factors and improving health outcomes. These findings highlight distinct socioeconomic and behavioral profiles among current smokers, suggesting potential targets for tailored interventions. Citation Format: S. Hirani, R. A. Vierkant, N. L. Larson, S. D. D’Andre, F. J. Couch, J. E. Olson, K. J. Ruddy. Identifying Smoking-Related Factors in Breast Cancer Patients: Mayo Clinic Registry Insight [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-04-18.

Abstract Benign breast disease (BBD) confers elevated risk for breast cancer, yet current tools lack precision in identifying lesions likely to progress. Immune mechanisms may influence progression, but the spatial and molecular features of immune responses in BBD versus invasive cancer remain poorly characterized. We applied Digital Spatial Proteomics (DSP) to evaluate immune-related protein expression across 1,540 regions of interest (ROIs) from breast tumors (n=58, Carolina Breast Cancer Study [CBCS]), a UNC BBD cohort (n=20), and a Mayo BBD cohort (n=177). Using Consensus Clustering in CBCS and UNC BBD, we identified two stable immune phenotypes: “High Immune,” enriched in tumors and high-risk benign lesions, and “Quiet Immune,” predominant in low-risk BBD. ROIs were classified by immune marker expression, and patients were labeled as “High” if ≥50% of their ROIs were High Immune. In CBCS, High Immune profiles were associated with ER-negative status (OR=2.92 [0.99-8.65] participant-level; OR=3.28 [1.34-8.04] ROI-level). In BBD, High Immune profiles trended toward higher odds of high-risk lesions (OR=1.00 [0.15-6.70] participant-level; OR=1.68 [0.57-4.97] ROI-level), though this pattern was not replicated in the Mayo cohort. BBD samples exhibited substantial spatial heterogeneity in immune expression (40% within-patient ROI agreement vs. 74% in tumors), potentially limiting biomarker reliability. Nonetheless, four immune proteins (CD44, CD80, CD14, CD66b) were significantly associated with future cancer development in the Mayo cohort, though these findings require validation due to within-person variability. Our findings highlight the challenges posed by spatial heterogeneity in assessing immune biomarkers in BBD and suggest that immune activation may emerge later in disease progression. These results raise important questions about the timing and consistency of immune responses in the natural history of breast cancer. Citation Format: A. Zhang, A. Cozzo, L. Olsson, E. Kirk, X. Gao, S. Nyante, B. Calhoun, R. Vierkant, M. Sherman, M. Troester. Immune Heterogeneity in Breast Cancer Natural History: Benign Breast Disease to Breast Cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-05-23.

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 The incidence of early onset breast cancers (BCs) has increased, paralleling rising trends in delayed childbearing. We hypothesize that a distinct postpartum BC (PPBC) subtype, identifiable by time since last birth (TSLB) and biomarker expression, contributes to this trend. Methods We applied GeoMx Digital Spatial Profiling (DSP) to measure associations between TSLB and 71 proteins in 640 BCs from women aged ≤40 years included in the Young Women’s Breast Cancer Study. We analyzed data using univariable linear regression and multivariable sliced inverse regression to account for higher order interactions among biomarkers. Results In keratin-rich segments, progesterone receptor (PR) (P = 1.00 × 10−4) and PTEN (P = 1.00 × 10−3) were associated with longer TSLB; multivariable analyses revealed positive associations for GZMB (P = 4.00 × 10−4), SMA (P = 1.00 × 10−4), and NF-1 (P = 1.00 × 10−3). In keratin-poor segments, univariable significant positive associations were found for PR (P = 2.00 × 10−4) and PTEN (P = 1.00 × 10−3), whereas CD20 (P = 3.00 × 10−4) and CTLA4 (P = 4.00 × 10−5) were negatively associated; multivariable significant associations were found for fibronectin (P = 3.00 × 10−5) and pan-Akt (P = 1.00 × 10−3). Associations persisted after adjustment for multiple comparisons and BC molecular subtypes. Associations including for PR, PTEN, and CD20 were strongest among women with the shortest TSLB. OPAL multiplex immunofluorescence assays for PR, PTEN, CD20, SMA, and CTLA4 replicated several DSP findings, particularly when stratified by subtype and with compartment matching. In TCGA, RNA species linked to proteins associated with TSLB correlated strongly with a T-cell exhaustion signature previously linked to poor prognosis among premenopausal women. Conclusion These data support PPBC as a biologically coherent phenotype defined by TSLB and biomarker profile, with potential implications for prevention and therapy.

Background: There is no consensus scoring system for staging and prognosis in hepatocellular carcinoma (HCC), which is the fourth leading cause of cancer-related mortality worldwide. Commonly used systems include the albumin–bilirubin (ALBI) score, the Barcelona staging classification (Barcelona Clinic Liver Cancer, BCLC), the Model for End-Stage Liver Disease (MELD), and the model to estimate survival in ambulatory HCC patients (MESIAH). Liver secretion of pseudocholinesterase (PCHE) has been linked to liver function but is poorly studied in the natural history of HCC. We evaluated whether serum PCHE level predicts HCC mortality and whether it enhances existing scoring systems. Methods: We conducted a retrospective cohort study of individuals diagnosed with HCC. We collected variables including PCHE level, clinical data used in scoring systems, and time to mortality or liver transplant. We then analyzed the association between these variables and survival using Kaplan–Meier curves, Cox proportional hazards regression models, receiver operating characteristic (ROC) curves, and area under the curve (AUC) calculations. Results: We identified 420 individuals with HCC who were tested for PCHE levels, with a follow-up time of more than 20 years. There was a strong inverse relationship between PCHE level and overall survival, with the lowest quartile having high mortality and poor outcomes. Low PCHE level was associated with hepatitis C virus (HCV) infection, vascular invasion, poor liver function, and a high likelihood of liver transplant. In contrast, the highest quartile was associated with metabolic dysfunction–associated steatotic liver disease (MASLD) as the underlying cause. Compared with validated scoring systems, ALBI, BCLC, MELD 3.0, and MESIAH, the PCHE level was an independent predictor of mortality. PCHE levels could predict 3-month survival as well as or better than the other scoring systems, with an AUC of 0.74. PCHE level could also predict mortality related to hepatectomy. The addition of PCHE level to MESIAH and ALBI scoring systems could further improve the ability to predict overall mortality in HCC. Conclusions: PCHE is a reliable stand-alone biomarker of HCC prognosis. It is an independent predictor of mortality and can improve the accuracy of existing scoring systems. Improved risk stratification could improve outcomes by informing treatment decisions regarding hepatectomy or other interventions.