Citations

Introduction Women residing in rural areas or belonging to lower socioeconomic status (SES) strata experience disproportionately low rates of breast cancer screening, contributing to delayed diagnoses and poorer prognoses. In addition, their participation in clinical trials remains markedly limited, reducing opportunities to access preventive and screening interventions. Promoting research preparedness among women before disease onset may empower them to make informed decisions regarding their health and willingness to participate in clinical research with fewer emotional and logistical barriers. Methods and analysis This project applies a community-based participatory research approach to develop and refine the WeCARE (Women’s Engagement for Cancer Awareness, Resources and Education) intervention for women aged 50–74 years who have either never undergone breast cancer screening or have not received screening in the past 5 years and who reside in rural areas or belong to low SES groups. The intervention consists of two components. Component 1 is a single-day, in-person community forum that includes (a) an educational seminar led by an oncologist to address breast cancer risk and screening guidelines, (b) survivor storytelling to enhance emotional engagement and cultural resonance and (c) facilitated navigation to breast cancer screening and future research participation. Component 2 involves structured post-forum follow-up through multiple touchpoints (phone calls and mailed boosters) to reinforce knowledge, address barriers and support screening completion and research enrolment. Quantitative data (eg, screening completion, satisfaction and follow-up engagement) will be summarised using descriptive statistics to assess feasibility and reach on 50 participants. Qualitative feedback from participants will undergo thematic analysis to identify barriers, facilitators and perceived cultural relevance. Integrated mixed-method interpretation will inform iterative refinement of the WeCARE intervention and guide design of subsequent larger trials. Ethics and dissemination Approved by the Mayo Clinic Institutional Review Board (IRB #25–008934). All participants will provide informed consent. Procedures ensure confidentiality, cultural sensitivity and participant safety. Data will be stored in REDCap and disseminated through publications, conferences, local town halls and community reports.

8057 Background: The NCI Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trials (ALCHEMIST) study tested resected stage II-IIIB(N2) NSCLC for targetable EGFR and ALK alterations and PD-L1 expression to screen patients for biomarker-driven adjuvant therapy trials (NCT02194738). Local lab results were requested when available for comparison to central lab results. Methods: We identified patients with both central and local PD-L1 results in the ALCHEMIST adjuvant immunotherapy study screening population. Discrepancies in tumor proportion score (TPS) between central and local PD-L1 were defined using prespecified cut-points (granular: <1%, 1-<5%, 5-<10%, 10-<20%, 20-<30%, 30-<40%, 40-<50%, 50-60%, 60-<70%, 70-<80%, 80-<90%, 90-<100%; clinical: <1%, 1-<50%, 50-100%). Large discrepancies were defined as ≥ 50 percentage point differences; for these cases, local PD-L1 and hematoxylin & eosin-stained slides were requested. These and all central slides were digitally scanned at 40X. Three expert pathologists reviewed the scanned slides in a blinded fashion. Differences between patient or tumor characteristics were assessed by Chi-square and Wilcoxon rank sum tests. Percent agreement was computed within and between the reviewers. Results: Central and local PD-L1 results were available for 497 patients. 177 cases (36%) had discrepancies that placed patients in different clinical TPS categories (<1%, 1-<50%, 50-100%). Among these, 43 cases had large TPS discrepancies; 14 had available local testing slides. 46 of the 320 cases without discrepancy were randomly selected as controls. No patient or tumor characteristics were associated with discrepancy, including tumor location, histology, grade or cancer stage (p > 0.05). Pairwise comparisons of TPS according to three pathologists re-reading the same scanned PD-L1 slides showed similar levels of disagreement in clinical TPS category whether there was initial discrepancy between central and local results (24%, 34%, and 23%; mean 27%) or not (33%, 30%, and 20%; mean 28%). Among the 14 cases with large initial discrepancies and local slides available, there was agreement in clinical TPS category when the anonymized central and local scanned slides were re-read by the pathologists in 54%, 38%, and 43% of cases, despite 100% non-agreement in initial reads. There were higher rates of agreement when the tested slides both originated from the same (100%) versus different (35%) blocks, when the same (48%) versus different (40%) PD-L1 antibodies were used, and when the cases were of non-squamous (52%) versus squamous (14%) cell carcinoma. Conclusions: There are substantial differences in PD-L1 TPS read by pathologists that can result in placement of patients in different categories commonly used for clinical management. These differences have clear implications in clinical trials and routine patient care.

566 Background: Endocrine therapy (ET) resistance (ETR) remains a primary challenge in ER+ breast cancer. Analyzing pretreatment tumor transcriptomes across trials with early response endpoints can reveal shared and specific ETR signatures. This study utilizes baseline RNA data from the Phase III ALTERNATE trial (Alliance A011106, NCT01953588; Anastrozole [A], Fulvestrant [F], or AF) and the ACOSOG Z1031B trial (NCT00824941) to identify predictors of early Ki67 response in postmenopausal ER+/HER2– patients. Methods: ETR was defined as week-4 on-treatment Ki67 >10%. Baseline gene expression from ALTERNATE was analyzed to identify differentially expressed (DE) genes (Wilcoxon test, P<0.05) and Hallmark pathways associated with ETR, both across and within individual treatment arms. Feature selection was performed using mixOmics. A Pan-Endocrine Therapy Signature (PETS) was developed by uniting DE genes identified across all three ALTERNATE arms and Z1031B. All statistical analyses were conducted in R (P<0.05). Results: Overall ETR rate in the ALTERNATE RNA-seq cohort (n=733) was 26%. ETR was associated with high Risk of Recurrence (ROR), Oncotype RS, and Mammaprint scores (calculated from RNA-seq data in research setting). In luminal tumors (n=649), ETR was linked to chr 3q13.33, 8q24.13, and 20q13.12 cytoband upregulation and 17q21, 18q23, 3p21.1, and 10q24.32 cytoband downregulation. ETR tumors showed T-cell, E2F target, and interferon-γ enrichment; sensitive tumors favored early estrogen response and muscle differentiation. At individual gene level, high MYBL2 , PIF1 , TROAP and with low HJURP predicted ETR across all samples (AUC>0.70). A deep learning model using all protein-coding genes achieved AUC 0.82 (training) and 0.79 (test) in predicting ETR. Cross-trial integration identified ETR-associated PETS, enriched for genomic instability. PETS performed comparably to established signatures and strongly correlated with MYBL2 signature (r=0.93). Top ETR predictors were MYBL2 , AURKB , and EME1 for Arm A and IL4I1 , TNFAIP6 , and ANLN for Arm AF. AF-resistant tumors were enriched for systemic lupus and RIG-I–like receptor signaling; sensitive tumors favored PI3K–AKT, EGFR TKI resistance, AMPK, and insulin signaling. Conclusions: Baseline transcriptomics identify shared and therapy-specific ETR markers. The 15-gene PETS defines a convergent resistance signature, performing similar to established signatures in predicting ETR and correlating with MYBL2. Enrichment of cell-cycle and immune pathways in resistant tumors may suggest patient stratification approach for alternative or combinatorial strategies to overcome early ETR in ER+ breast cancer. Acknowledgement: https://acknowledgments.alliancefound.org. Support: U10CA180821, U10CA180882, U24CA1. Clinical trial information: NCT01953588 .

Introduction The unproven stem cell intervention (SCI) industry markets stem cell products to patients navigating chronic and serious conditions who seek alternative options when conventional treatments no longer offer relief or improvement. This market is often characterized by providers using deceptive advertising to misinform potential consumers to seek stem cells that have not been shown to be safe and/or effective through clinical studies. Objective This study examines how patients describe interpersonal and institutional trust in relation to their interest in and decisions about unproven SCIs among two distinct and divergent chronic disease patient groups: patients with little or no interest in unproven SCIs (low seekers) and those with high interest or have undertaken an unproven SCI (high seekers). Methods A semi-structured interview guide was developed deductively and modified inductively based on the Unified Theory of Health Behavior. Qualitative interviews among 36 patients and carers were conduct and transcripts were analyzed using constant comparison based on the principles of grounded theory. Results Trust varies across social contexts as low seekers expressed strong reservations about the commercialization elements of the SCI industry placing greater confidence in conventional medicine. In contrast, high seekers questioned the advice of conventional providers and motives of medical regulators. Across both, personal relationships were commonly described as influential in how participants evaluated unproven SCIs. Conclusion These findings suggest that communication efforts in clinical settings should account for the relational and emotional dimensions of trust. Interventions aimed at countering misleading information and promoting informed choices should engage trusted messengers and address the broader social and psychological contexts in which patients may seek unproven SCIs.

PURPOSE Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Early-stage, high-risk patients with TNBC are treated with chemotherapy and pembrolizumab per the KEYNOTE-522 regimen. This report examines real-world clinical effectiveness and toxicity of this regimen. METHODS This 19-site retrospective analysis included all patients who received at least one dose of the KEYNOTE-522 regimen. Safety, efficacy, and health care encounters were collected. RESULTS 675 patients from 19 sites in the United States who received chemotherapy and pembrolizumab for early-stage TNBC were included. 547 (81.0%) patients underwent surgery and 250 (54.7%) patients had a pathologic complete response (pCR). No baseline characteristics were predictive of pCR status. 224 patients (33.2%) had an adverse drug event resulting in ≥1 dose reduction of chemotherapy and were significantly more likely to have residual disease. Immune-related adverse events (irAEs) were observed in 388 (57.5%) patients and grade 3+ irAEs were observed in 176 (26.1%) patients. There was no difference in pCR status between provider's choice chemotherapy schedules. There was no difference of pCR rate between Black and White patients (55.6% v 51.6%, P = .489). White patients were significantly more likely to have any grade and grade 3+ irAEs. Older patients (age ≥65 years) had similar pCR rates compared with younger patients; however, older patients were significantly more likely to have grade 3+ irAEs. CONCLUSIONS In this multi-institutional real-world cohort, we observed a lower pCR rate, higher rates of toxicity, frequent emergency health care utilization, and the reporting of rare irAEs at higher frequency than the KEYNOTE-522 regimen. These findings have important implications for clinical management of patients with early-stage TNBC and warrant further validation with real-world data sets.

ABSTRACT Importance Rural-urban disparities in chronic disease prevalence are well established; however, the extent to which individual-level socioeconomic status (SES) contributes to these disparities remains unclear. Objective To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design We conducted a retrospective cross-sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E-REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014-2019). Setting Population based Participants Adults over 18 years residing in the 27 E-REP counties, excluding those missing rural-urban residence status. Exposure HOUSES index, an individual-level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014–2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural-urban and SES differences for prevalence of each chronic disease. Results Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural-urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance Individual-level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.

Abstract Introduction: The National Cancer Institute estimated almost 317,000 new breast cancer and over 13,000 new cervical cancer cases in 2025. While the National Breast and Cervical Cancer Early Detection Program has served millions of women over the past two decades, inequities in cancer screening, subsequently delayed diagnosis, and timely and appropriate treatment remain a public health challenge in the United States. Despite the substantial impact of social determinants of health (SDOH) on cancer screening, few studies have accounted for SDOH at the individual level when assessing breast and cervical cancer screening adherence. The primary objective of this study is to examine whether the individual-level SDOH, measured using HOUsing-based SocioEconomic Status (HOUSES) index, is associated with breast and cervical cancer screening non-adherence (not current on respective USPSTF recommendations for age and frequency). Methods: In this retrospective study, patients were identified as those receiving primary care in the Mayo Clinic Health System and Mayo Clinic (Rochester, MN). The Midwest Quality Metrics panel was then used to assess patients due for screening for breast or cervical cancer in July 2023. The HOUSES, using home address and publicly available data on the residence which measures and categorizes housing status into quartiles, was obtained using the electronic health records (EHRs)-linkable patient-level information. Logistic regression analyses were conducted, controlling for Census block group-level adverse social exposome from the Area Deprivation Index, age, and comorbidities. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (CI). Results: For breast cancer, among 128,462 eligible patients, 20.1% (n= 25,857) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.20 (95% CI=1.15, 1.25), Q2 OR=1.45; (95% CI=1.40, 1.53), and Q1 OR=1.90 (95% CI=1.81, 1.99). For cervical cancer, among 175,712 eligible patients, 29.9% (n=52,533) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.07 (95% CI=1.03, 1.10), Q2 OR=1.16; (95% CI=1.12, 1.20), and Q1 OR=1.36 (95% CI=1.31, 1.41). Conclusions: A clinically meaningful association between the HOUSES index and cancer screening adherence was observed. A lower HOUSES index was associated with higher odds of non-adherence for both breast and cervical cancer screening, even after accounting for neighborhood-level risk, age, and comorbidities. Incorporating HOUSES into EHRs can be a practical “screening-for-screening” tool that enables close monitoring of higher-risk patients without additional burden of surveys. Citation Format: Eunice Y. Park, Madison Beenken, Dave Watson, Chung Il Wi, Tufia Haddad, Gladys Asiedu, Karla BALLMAN, James R. Cerhan, Carolyn Flock, Brian Lynch, Folakemi T. Odedina, Scott H. Okuno, Young J Juhn, . HOUSES as a screening tool for cancer screening: Patient-level housing-based socioeconomic status and breast and cervical cancer screening adherence [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 7599.

Abstract In epilepsy patients lacking magnetic resonance imaging‐visible lesions such as focal cortical dysplasia (FCD), surgical resections target regions with abnormal electroencephalographic (EEG) activity. However, histopathological identification of subtle cortical architectural abnormalities in these specimens remains challenging. We investigated whether artificial intelligence (AI)‐based morphometric and spatial analysis of NeuN‐stained cortical sections could detect neuronal architectural disorganization in epilepsy resections, including regions without definitive histologic dysplasia. Whole slide images were generated from 83 FCD regions and 19 neurologically normal autopsy controls. Regions of interest were annotated in QuPath as FCD, FCD‐adjacent, FCD‐distant, apparently normal (abnormal EEG without histologic dysplasia), and true normal (autopsy controls). NeuN‐positive neurons were detected using QuPath (90% sensitivity, 12% false positive rate). Spatial and morphometric features—including neuronal clustering, distribution inhomogeneity, and nuclear morphology—were extracted and used to train a multinomial, Least Absolute Shrinkage and Selection Operator‐regularized regression classifier. The classifier achieved 70.6% accuracy in subregion classification and 88.2% accuracy in overall specimen diagnosis. Notably, regions with abnormal EEG but lacking histologic dysplasia exhibited quantifiable architectural disorganization similar to those seen in areas adjacent to FCD and distinct from control tissue. AI‐driven analysis of neuronal morphology and spatial distribution reveals subtle cortical disorganization in epilepsy resections, including in histologically ambiguous regions. Further investigation is warranted to determine if this methodology can enhance the diagnostic yield of neuropathological evaluation and support more precise surgical targeting in epilepsy.