Pacheco-Spann, Laura M.

Abstract STUDY QUESTION What is the fertility preservation (FP) utilization rate among transgender and gender diverse (TGD) patients at the Transgender and Intersex Specialty Care Clinic (TISCC) within the Mayo Clinic? SUMMARY ANSWER The rate of utilization of FP services by TGD patients at Mayo Clinic’s TISCC was determined to be 6.62%. WHAT IS KNOWN ALREADY TGD patients encounter several barriers when pursuing FP, which may contribute to a lower utilization rate of these services. These barriers include financial constraints and lack of insurance coverage, as well as societal and healthcare provider attitudes; TGD individuals face discrimination or lack of understanding, making it uncomfortable or difficult to discuss FP options. Additionally, there continues to be a lack of inclusive policies and support within healthcare systems that can further impede access to FP services for TGD individuals. STUDY DESIGN, SIZE, DURATION The study was executed in two phases. In the first phase, a retrospective cohort study was completed with TGD patients who provided electronic health record (EHR) research authorization from Mayo Clinic’s TISCC in Rochester, MN between 1 January 2015 and 30 July 2021. Search terms related to FP were used to determine the FP utilization rate among this patient population. In the second phase of the study, two sets of patients, (i) patients who were included in the cohort study in Phase 1, and (ii) members of JASMYN, a community organization specializing in care and wellness coordination for Lesbian, Gay, Bisexual, and Transgender (LGBT) teens and young adults in North Florida. Individuals were invited to participate in a qualitative interview exploring their cumulative healthcare experiences accessing gender-affirming care. Interviews were conducted from January 2023 to June 2023. Interviews examined participants’ perceptions of FP options, motivations for pursuing FP, and barriers to accessing both gender and fertility care. When applicable, participants also discussed their experiences pursuing FP and reflected on their satisfaction with their fertility and family planning decisions. PARTICIPANTS/MATERIALS, SETTING, METHODS In phase 1, a total of N = 1189 patients sought care from Mayo Clinic’s TISCC in Rochester, MN. Out of these patients, N = 589 patients provided research authorization and were included in the retrospective cohort study. The study team assessed whether FP terms were mentioned in each patient’s EHR, and whether patients scheduled and attended appointments with either the Department of Reproductive Endocrinology or the Department of Urology. FP search terms included sperm cryopreservation, sperm extraction, sperm aspiration, testicular tissue cryopreservation, oocyte cryopreservation, embryo cryopreservation, and ovarian tissue cryopreservation. In phase 2, N = 36 participants were interviewed, with N = 25 participants recruited from Mayo Clinic’s TISCC in Rochester, MN, and N = 11 participants recruited from JASMYN in Jacksonville, FL. Participants recruited from the Mayo Clinic participated in a video-call-based interview and those enrolled from JASMYN were interviewed in person. MAIN RESULTS AND THE ROLE OF CHANCE The study team observed a 6.62% utilization rate of FP services among N = 589 patients (median age: 28 years; age range: 8–78 years) included in the retrospective cohort study. N = 39 patients completed FP, with N = 14 receiving these services at other institutions before seeking care with the TISCC at Mayo Clinic. N = 25 patients pursued FP services within the Mayo Clinic. Patients with testes were more likely to complete FP via sperm cryopreservation when compared to the utilization of egg cryopreservation among patients with ovaries. Participants who completed an interview in Phase 2 (median age 27 years; age range: 22–80 years) reflected on their decision on whether to preserve their fertility and what factors influenced these decisions, and how their satisfaction with this decision has changed over their lifespan. The major themes reported here include the desire for biological children, planning gender care around fertility desires, conversations about FP options, physical and psychosocial barriers to pursuing FP, reflections on personal FP decisions, and reflections on having to make decisions about FP at a young age. LIMITATIONS, REASONS FOR CAUTION All participants who completed an interview have done so voluntarily; as such, there is a possibility of selection and recall bias. WIDER IMPLICATIONS OF THE FINDINGS Findings suggest that there is a need for more structured conversations around FP when TGD patients seek medical and surgical gender-affirming care. Accessibility, including financial barriers and limited insurance coverage, continues to limit the utilization of FP services among TGD patients. Increased affordability through insurance coverage may additionally improve FP utilization. STUDY FUNDING/COMPETING INTEREST(S) This project was funded by the Mayo Clinic Department of Obstetrics and Gynecology and the Mayo Clinic Center for Clinical and Translational Science (CCaTS), grant number UL1TR002377. This project was also supported by Clinical and Translational Science Award (CTSA) Grant Number TL1TR002380 from the National Center for Advancing Translational Sciences (NCATS). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. Felicity Enders reports grants from the National Institutes of Health and the Agency for Healthcare Research and Quality paid to her institution; speakers’ fees for lectures or presentations from Mount Sinai, University of Washington, University of Minnesota, University of Rochester, Cincinnati University, the National Institutes of Health, Duke University, Wake Forest University, the Patient Centered Outcomes Research Institute, Johns Hopkins University; travel support from the Association for Clinical and Translational Science and Cold Spring Harbor Laboratory; and an unpaid leadership role on the Board of Directors of the Association for Clinical and Translational Science. All other authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.

Abstract Background: Artificial intelligence (AI) algorithms based on deep learning approaches show promise in improving breast cancer (BC) detection on mammography and may also improve prediction of future BC risk compared with clinical risk prediction models. Historical clinical risk prediction models underperform among women with BBD; however, AI models for BC detection on mammography have not been tested among women at elevated BC risk due to benign breast disease (BBD). We evaluated if an AI cancer detection algorithm can aid BC risk prediction among women with BBD. Methods: We examined women without a prior BC who had an initial BBD biopsy at Mayo Clinic, Rochester, between 2002 and 2013. Incident BC occurring after BBD was identified using the Mayo Tumor Registry and supplemented by follow-up questionnaires. Only women with a full field digital mammogram at least 2 years prior to BC diagnosis were eligible. A breast pathologist evaluated BBD according to increasing severity, as non-proliferative (NP), proliferative disease without atypia (PDWA) or atypical hyperplasia (AH). AI malignancy scores derived from the Transpara detection algorithm (1-10) and volumetric percent density (VPD) from Volpara (per one standard deviation, SD) were assessed from mammograms close to BBD diagnosis. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) with 95% Confidence Intervals (CIs), adjusted for age and BMI. C-statistics were estimated to assess the contribution of each factor to BC risk prediction. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance with the addition of AI malignancy score. Results: The BBD cohort with mammography consisted of 3,125 women followed for a median 12.9 years, with 250 incident BC. Of these, 221 BC occurred at least two years after the mammogram and were used in analyses. As expected, increased BC risk was associated with BBD severity [for AH HR=3.18 (95%CI: 2.04, 4.95) and for PDWA HR=1.59 (95%CI: 1.17, 2.14) compared to NP] and with higher VPD [HR=1.24 per SD (95% CI: 1.05, 1.45)] (Table ). The AI-malignancy score alone was also associated with BC risk [HR=1.16 per 1 unit score (95%CI: 1.09,1.23)] and showed similar discriminatory accuracy [C-statistic=0.626 (95%CI: 0.586, 0.665)] as the model with BBD severity and VPD combined [C-statistic=0.627, (95%CI: 0.585, 0.669)] (Table ). In models with BBD severity and VPD, the AI-malignancy score was an independent risk factor for BC [HR=1.14 (95%CI: 1.07, 1.21); PLRT<0.001] but only achieved a marginally significant improvement in discriminatory accuracy [C-statistic=0.651 (0.609, 0.693), ΔC-statistic=0.024 (95% CI: 0.000, 0.047)]. Conclusion: In this preliminary study, an AI BC detection algorithm achieved similar performance in predicting future BC risk compared to established risk factors. Citation Format: C. M. Vachon, S. Winham, M. Jensen, D. Hursh, L. Pacheco-Spann, A. Norman, J. Fischer, S. Schrup, L. Seymour, D. Gehling, S. Nyante, M. Troester, N. Karssemeijer, R. Vierkant, D. Radisky, C. Scott, S. I. Maimone, A. Degnim, M. Sherman. An AI algorithm for breast cancer detection improves future BC risk prediction among women with benign breast disease [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 PD4-02.

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: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements across benign lobules and breast cancers (BCs), and how well DSP aligns with standard immunoassays. Methods: We performed a pilot using tissues from the Mayo Clinic BBD cohort using TMAs representing four contexts: terminal duct lobular units (TDLUs) from BBD biopsies preceding BC and matched BBD-controls, subsequent BCs, and BC-associated TDLUs. We profiled 79 proteins by DSP (37 retained after QC) and benchmarked against chromogenic IHC and OPAL immunofluorescence. Reproducibility was evaluated using intraclass correlation coefficients (ICCs), cross-platform agreement (weighted kappa), marker correlations, and mixed-effects models with false-discovery-rate (FDR) control. Results: We analyzed 368 BBD-TDLU cores (88 cases; 88 controls), 204 BC cores and 110 BC-associated TDLU cores. ICCs were highest in BC tissues, and lower in BC-associated TDLUs and BBD-TDLUs. Agreement was slight–to-fair in TDLUs but moderate (ER/PR) to substantial (BCL2) in BC. DSP recapitulated expected immunologic correlations (CD45 with T-cell, B-cell, and macrophage markers) and tissue-type gradients (BC > BC-associated TDLUs > BBD-TDLUs). Exploratory case–control differences in BBD-TDLUs did not persist after FDR control. Conclusions: TMA-based DSP is feasible in archival breast tissues and yields biologically coherent, cross-platform-benchmarked profiles that are particularly robust in BC, while conserving scarce TDLUS and clarifying current limits of single-marker risk stratification from benign lobules. These data provide a foundation for refined sampling and expanded panels in future TDLU-focused studies.

Abstract Background: Black women continue to face disproportionate mortality and long-term challenges after breast cancer treatment, including gaps in follow-up care, culturally relevant support, and access to survivorship resources. Digital tools designed with Black survivors in mind remain limited, despite their potential to reduce disparities in post-treatment engagement. Objective: To address these gaps, we developed HERCaRE (Health Equity Resources for Breast Cancer Responsive Education), a progressive web application (PWA) designed to deliver culturally responsive survivorship education and engagement tools to Black breast cancer survivors. HERCaRE was designed to meet the need for a culturally responsive, easily accessible resource that empowers survivors to engage more confidently in their post-treatment care. Methods: The concept for HERCaRE was informed by a previous pilot study on virtual breast health education, in which participants expressed the need for more sustained and accessible support for survivors. Building on that insight, the platform was developed with advisory input from Black breast cancer survivors and community advocates through informal, discussion-based feedback. While not a formal co-design process, this input helped ensure cultural relevance in tone, structure, and visual language. HERCaRE includes three core features: educational modules on key survivorship topics, interactive behavior-prompting activities, and a notes section for self-reflection and goal tracking. The platform is grounded in the Health Promotion Model and RE-AIM framework, providing a foundation for future implementation and evaluation. The platform is currently being prepared for pilot testing, which will assess usability, perceived relevance, and engagement frequency among Black breast cancer survivors. Mixed-method surveys and platform analytics will guide refinement ahead of broader implementation. Preliminary Insights: Early input emphasized the importance of affirming, plain-language content and simple navigation. Activities were designed to promote exploration of the educational material and personal health behaviors through simple, self-guided prompts. Current efforts are focused on content finalization, participant recruitment, and platform readiness for testing. Conclusion: HERCaRE offers a responsive, theory-informed approach to digital survivorship support for Black women. While still in the pre-implementation phase, its development reflects a commitment to accessible design, cultural alignment, and future scalability. The platform lays important groundwork for reducing disparities in survivorship care and expanding digital health tools that center the needs of historically underserved populations. HERCaRE’s modular design and emphasis on user experience position it for adaptation across diverse clinical and community settings, including integration into survivorship programs serving other medically underserved populations. Citation Format: Manisha Salinas, Timethia Bonner, Laura Pacheco-Spann, Oluwadamilola Oladeru, Dianne Townsend, Che Ngufor. A culturally tailored digital health platform to improve breast cancer survivorship for Black women: HERCaRE [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr B048.

Objectives/Goals: This project will enrich our understanding of basal breast carcinogenesis, highlighting the distinct biological differences in breast cancer risk between non-Hispanic Black (NHB) or non-Hispanic White (NHW) women, but also has the potential to provide real-world solutions thereby contributing to reducing health disparities in breast cancer outcomes Methods/Study Population: In the biological investigation, I am utilizing a unique cohort of normal breast tissues from Mayo Clinic patients who underwent breast reduction surgery that have self-identified as NHB or NHW premenopausal women. From these tissues, we are able to subculture human mammary epithelial cells, which we will use for our consequent experiments. For the qualitative study, I aim to recruit up to 40–50 eligible NHB women identified at increased risk for breast cancer and conduct semi-structured qualitative interviews informed by the National Institute on Minority Health and Health Disparities Research Framework. Results/Anticipated Results: Gene expression profiling on our cohort of 15 NHB and 40 NHW premenopausal women identified a gene expression signature in NHB women indicative of elevated Hedgehog signaling, a key factor in triple-negative breast cancer (TNBC) development and progression. I hypothesize that persistent activation of Hedgehog signaling within NHB women instigates the proliferation and transformation of basal stem cells within the breast, thus fueling TNBC development. Understanding the perceptions and experiences of NHB women that are identified as being at an increased risk for BC will aid in the identification of barriers and facilitators to their risk reduction care and in turn provide implementation strategies that could contribute to alleviating the racial disparity seen in TNBC morbidity, mortality, and preventative care. Discussion/Significance of Impact: The significance of this project lies in its dual approach, uncovering basal breast cancer mechanisms in a high-risk group using normal breast tissue and evaluating the perspectives from NHB women to enhance the practical relevance of our findings.

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

Abstract: Background: Allergic contact dermatitis is a common, pruritic, debilitating skin disease, affecting at least 20% of the population. Objective: To prospectively validate a computer vision algorithm across all Fitzpatrick skin types. Methods: Each participant was exposed to 10 allergens. The reference criterion was obtained 5 days after initial patch placement by a board-certified dermatologist. The algorithm processed photographs of the test site obtained on Day 5. Human performance in reading the photographs was also evaluated. Results: A total of 206 evaluable participants [mean age 39 years, 66% (136/206) female, and 47% with Fitzpatrick skin types IV–VI] completed testing. Forty-two percent (87/206) of participants experienced 1 or more allergic reaction resulting in a total of 132 allergic reactions. The model provided high discrimination (AUROC 0.86, 95% CI: 0.82–0.90) and specificity (93%, 95% CI: 92%–94%) but with lower sensitivity (58%, 95% CI: 49%–67%). Human performance interpreting the photographs ranged from providing similar performance to the algorithm to providing superior performance when combined across readers. There were no serious adverse events. Conclusions: The combination of a smartphone capture of patch testing sites with deep learning yielded high discrimination across a diverse sample.

Abstract Introduction: Although Hispanic White (HW) females have a lower incidence of breast cancer than non-Hispanic White (NHW) females, breast cancer risk is unclear for HW females after benign breast disease (BBD). Methods: We compared BBD characteristics and subsequent breast cancer risk among HW and NHW females in New Mexico using a population-based collection of benign breast biopsies (1996–2007). BBD was categorized as nonproliferative disease (NPD), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH). Breast cancer risk was assessed as absolute risk (AR) using cumulative incidence and RR by comparing the number of breast cancer events in BBDs to non-BBD. Results: This study included 3,684 HW and 6,587 NHW females with BBD. HW females had similar proportions of NPD (58.6% vs. 54.3%), PDWA (21.4% vs. 23.5%), and AH (3.6% vs. 3.3%) as NHW females. Breast cancer risk among all females with BBD was higher than population-based expected rates (RR, 1.87) and was similar for HW and NHW subgroups (RR = 1.99 vs. 1.84). As expected, breast cancer risk increased with increasing BBD severity, both overall [RR, 1.81 (NPD), 1.85 (PDWA), and 3.10 (AH)] and in the HW and NHW subgroups. Adjusted AR of breast cancer at 5 years also increased with the severity of BBD (HW vs. NHW; NPD: 1.4% vs. 2.1%; PDWA: 1.5% vs. 2.7%; AH: 6% vs. 4.8%). Conclusions: We found similar breast cancer RRs and ARs in HW and NHW. Risk counseling should ensure that HW females receive breast cancer clinical management warranted by their similar absolute risks. Impact: The present population-based provides evidence for the clinical management of HW females with BBD for the prevention of breast cancer.