Citations

According to the current WHO classification, noninvasive germ cell neoplasia of the testis comprises germ cell neoplasia in situ (GCNIS), specific forms of intratubular germ cell neoplasia, and gonadoblastoma. Because type II germ cell tumors (GCT, type II) arise from GCNIS, accurate detection of precursor lesions is diagnostically important. In preparation for the 2024 International Society of Urological Pathology (ISUP) Consensus Conference on genitourinary precursor lesions, which took place in Florence, Italy, an anonymous survey was distributed to ISUP members to assess current diagnostic practices regarding testicular precursor lesions. The literature and current WHO classification affirm the significance of precursor lesions in testicular tumours. Working Group 4—Precursor Lesions of the Testis—focused on their practical application by individual pathologists rather than establishing consensus from scientific data. There is strong agreement that GCNIS is the preferred and appropriate term for GCT precursor lesions and that its presence should be reported in cases of invasive GCT. Respondents also agree that “seminoma with intratubular nonseminoma” is the appropriate terminology for seminoma with an associated noninvasive nonseminomatous (embryonal carcinoma, yolk sac tumor, trophoblasts, or teratoma) component. Most pathologists prefer to use OCT3/4 as the primary immunohistochemical marker, and a panel was generally not considered necessary. No consensus is reached regarding the requirement for immunohistochemistry to confirm GCT precursor lesions in the testis. Three questions remain open: the value of subtyping intratubular lesions, the immunohistochemical approach to gonadoblastoma, and the criteria distinguishing Sertoli cell nodules from Sertoli cell tumors.

Abstract Objective To investigate the ability of artificial intelligence‐enabled electrocardiogram (AI‐ECG) atrial fibrillation (AF) prediction model output and delta age, defined as AI‐estimated age minus chronological age, to predict adverse vascular outcomes in patients with migraine. Background Migraine, especially migraine with aura, is associated with an increased risk of cardiovascular events. Using normal sinus rhythm ECG, our institution has developed AI‐ECG models that predict the probability of AF and estimate patients' age, and from that, delta age (estimated age minus actual age) has been shown to reflect cardiovascular health and physiologic aging. Methods We conducted a retrospective cohort study that included adult patients with migraine who had at least one digital, standard 12‐lead ECG from 2000 to 2020 at any Mayo Clinic site. The first normal sinus rhythm ECG was defined as the index ECG, and those with adverse vascular events or AF prior to, or within 3 days after, index ECG were excluded. AI‐ECG AF prediction model output and delta age were obtained from the index ECG. The primary outcome was a composite endpoint of adverse vascular events that included acute myocardial infarction, acute ischemic stroke, venous thromboembolism, and death. New‐onset AF was also recorded as a secondary outcome. Results A total of 29,928 patients were included. The mean age was 44.3 ± 14.5 years, and the median follow‐up time was 54 months. During the study period, 4662 (15.6%) patients had adverse vascular events, and 1384 (4.6%) patients developed new‐onset AF. A higher AF prediction model output was associated with a higher risk of adverse vascular outcomes (adjusted hazard ratio [aHR]:1.15 [95% confidence interval: 1.12 to 1.18] for every 10% increase in prediction model output), as was a larger delta age (aHR:1.16 [1.12 to 1.21] for every 10‐year increase in delta age). Moreover, AI‐ECG AF prediction model outputs of ≥1% (aHR: 1.45 [1.36 to 1.54]) and delta age ≥−1 years (aHR: 1.09 [1.02 to 1.16]) were found to be the optimal cutoffs to dichotomize patients into high‐risk and low‐risk groups for adverse vascular events. Higher AI‐ECG AF prediction model output at baseline also predicted a higher likelihood of having new‐onset AF during the study period (aHR: 1.31 [1.26 to 1.37]), and the development of new‐onset AF was associated with a higher risk of adverse vascular events (aHR: 2.43 [2.17 to 2.73]). Conclusions For patients with migraine, a higher AI‐ECG AF prediction model output and delta age are predictive of adverse vascular outcomes. A higher AF prediction model output is also predictive of future AF development. Furthermore, we identified the cutoffs for both AI‐ECG models that can distinguish patients between high‐ and low‐risk groups. Our results showed that AI‐ECG models could inform clinical practice and identify patients with migraine at risk for future adverse vascular events.

Abstract Background: Stromal tumor infiltrating lymphocytes (sTILs) are associated with improved response to chemotherapy and better overall survival (OS) in triple-negative breast cancer (TNBC). Quantification of sTILs via hematoxylin and eosin (H&E) tumor slides offers a widely available method to define a simple, effective surrogate for host anti-tumor immunity. Digitization of H&E slides has rapidly gained acceptance for use in diagnostic pathology and research, opening the door for image-based computational approaches to enumerate sTILs, among other features. Methods: We describe QuTILs - a multilayer perceptron-based framework to detect/enumerate TILs trained on >700,000 cells via The Cancer Genome Atlas Program (TCGA) slide images, implemented in the widely used open-source QuPath digital pathology suite. QuTILs was applied to digital H&E images using standard computing in primary breast tumors from phase 3 breast cancer clinical trials - CALGB 40502 (testing), CALGB 40601 and 40603 (validation) - in total 1,729 total images from 962 unique patients. The aims of this investigation were: 1) to assess the relationship between TIL patterns with overall or event-free survival outcomes; 2) to benchmark diverse image-based characteristics of TIL abundance and spatial architecture; and 3) to evaluate the association between image-based TIL levels and RNA-seq-based immune deconvolution metrics (CIBERSORT, EPIC, quanTIseq). Results: QuTILs average processing time was 7.9 minutes for whole-slide total TIL count and area density on a standard laptop workstation. In CALGB 40502, there was positive but modest correlation between pathologist TILs and QuTILs total TILs %, higher in the TNBC subgroup of CALGB 40502 (Pearson r = 0.55). In Cox proportional hazards models, the CALGB 40502 TNBC cohort showed significant univariate association for total TILs % with increasing decile (higher total TIL%) associated with reduced hazard (hazard ratio [HR]: 0.712, 95% CI: 0.559-0.906; P = 0.006), which remained significant in multivariable model incorporating age, race, and treatment arm (HR: 0.713, 95% CI: 0.556-0.915; P = 0.008). In validation TNBC clinical trial CALGB 40603, marginal TILs % was significant in the univariable Cox model (HR: 0.786, 95% CI: 0.639-0.966). Evaluation of TILs % by QuTILs with RNAseq-based deconvolution metrics in cohort-stratified and deconvolution method-stratified multivariable models showed that decile total TILs % by QuTILs was shown to significantly predict outcome in the EPIC (HR: 0.668, 95% CI: 0.466-0.957) and quanTIseq (HR: 0.646, 95% CI: 0.446-0.936) sets, with a similar magnitude as in clinical Cox, suggesting that RNA-based deconvolution estimates may not supplement the prognostic power of image-based TIL estimates. Exploratory analyses of pre- versus post-neoadjuvant therapy H&E images in CALGB 40603 and CALGB 40601 revealed a significant decrease in QuTILs total TIL% in CALGB 40603 for all pairs (n = 118 pairs, pre-median=9.52%, post-median=6.33%; Wilcoxon signed rank P < 0.001) but no significant change in QuTILs total TIL% among all pairs in CALGB 40601 (n = 82 pairs, pre-median=15.92%, post-median=15.10%; P = 0.886). Conclusions: QuTILs provides a computationally efficient open-source workflow for sTIL identification from digital H&E images that can be deployed on a standard laptop. We present the first evaluation of digital sTIL enumeration in CALGB 40502, CALGB 40603, and CALGB 40601 phase III breast cancer clinical trials and demonstrate significant prognostic association with QuTIL total TIL % among TNBCs across studies. Citation Format: M. Vater, R. Salgado, E. Blige, H. Lefebvre, A. Strahan, M. Gatti-Mays, H. Rugo, K. Ballman, M. Watson, Y. Wen, R. Leon-Ferre, K. Niazi, W. Symmans, L. Carey, K. AbdulJabbar, Z. Li, D. Stover. Qutils: open-source image-based infiltrating immune cell detection and outcomes in calgb 40502, calgb 40603, and calgb 40601 phase iii breast cancer clinical trials [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 PS2-07-27.

BACKGROUND: While health systems have implemented resources to improve lipid management in people with atherosclerotic cardiovascular disease, the population-level effectiveness is unclear. METHODS: Electronic health record data from patients with atherosclerotic cardiovascular disease between January 1, 2021, and December 31, 2023, across 16 US academic health systems were analyzed. Atherosclerotic cardiovascular disease (defined by diagnosis and procedure codes) was established on or before the index date defined as the date of the most recent LDL-C (low-density lipoprotein-cholesterol) or the last day of the study period for those without an LDL-C available. Systems were surveyed to identify lipid management programs (eg, prevention/lipid clinic, electronic health record–based tools, and lipid management algorithms). Sequential multilevel multivariable logistic regression modeling was used to (1) assess the system-level association between an LDL-C <70 mg/dL and the presence of lipid management programs, adjusting for patient-level demographic and clinical characteristics, and (2) whether system-level uptake of statin or nonstatin lipid-lowering therapy was associated with an LDL-C <70 mg/dL. RESULTS: We included 1 738 042 patients with atherosclerotic cardiovascular disease (median, 88 365 per system; range, 17 086–2 48 371). About 81% of the health systems had prevention or lipid clinics. The proportion of those on statins ranged from 31.0% to 60.4% across health systems (median, 46.3%). Lower proportions were observed in the use of high-intensity statins (16.2%–33.1%), nonstatins (2.6%–8.1%), and combination lipid-lowering therapy (1.7%–6.3%). Among those with an LDL-C level available (n=890 521), 42.5% had an LDL-C <70 mg/dL, ranging 35.8% to 49.4% across systems. There was no association between the odds of achieving LDL-C <70 mg/dL and health system lipid management algorithm, prevention clinics/lipid clinics, or electronic health record–based tools. Neither system-level high-intensity statin utilization nor nonstatin use was associated with an LDL-C <70 mg/dL. CONCLUSIONS: Despite variability in lipid management resources and lipid-lowering therapy use across systems, many did not reach an LDL-C <70 mg/dL, and there was low uptake of lipid-lowering therapy. Innovative implementation strategies are needed for system-level lipid management.

Intramedullary screw fixation (ISF) of metacarpal fractures is a well-established technique. Prior techniques either involve placement of the intramedullary screw in a retrograde fashion or placement of the guidewire in a retrograde fashion before placing the screw in an antegrade fashion. While effective, previously described techniques have risks of extensor tendon irritation, articular cartilage disruption, and limited access to multiple metacarpals from a single incision. We present a novel antegrade intramedullary screw placement and antegrade guidewire technique for ISF that avoids disruption of the metacarpal head and allows for access to multiple metacarpals through a single incision. Cadaveric evaluation confirmed consistent sparing of the distal carpal row and demonstrated the feasibility of this technique across the index through small finger metacarpals. Compared with previously described methods, this technique offers improved soft tissue preservation, reduced risk of tendon scarring, and enhanced surgical efficiency. Level of Evidence: Level IV—case report; cadaveric study.

Abstract Objective To assess the role of small‐molecule calcitonin gene–related peptide receptor antagonists (gepants) in the acute treatment of migraine, particularly in relation to triptan treatments. Background Triptans have established efficacy and are widely prescribed for the acute treatment of migraine. However, triptans may not be recommended for some individuals due to cardiovascular contraindications and precautions, as well as other comorbidities, and many may discontinue triptans because of inadequate or inconsistent symptom relief or poor tolerability. Several gepants are also indicated for the treatment of migraine (both acute and preventive), and their demonstrated efficacy and safety may address some challenges associated with triptans. Methods This narrative review addresses considerations for the acute treatment of migraine through summarizing literature and data from preclinical studies and clinical trials of triptans and gepants. Results We consider triptans and gepants, where available, first‐line treatment options for the acute treatment of migraine. Triptans may be prescribed in the absence of contraindications, significant risk of cardiovascular disease, or risk for or history of medication‐overuse headache. In those who have contraindications or precautions for triptans, those who do not have an adequate response to triptans, and those unable to tolerate them, gepants are often an appropriate option. The efficacy and safety of gepants for the acute treatment of migraine has been established through clinical trials and open‐label extension studies and based on real‐world evidence. Gepants have demonstrated efficacy and tolerability in triptan insufficient responders, perhaps because of their distinct mechanisms of action. Additionally, the safety of gepants, including relative cardiovascular safety, is supported in pivotal controlled trials and open‐label extension trials. In experimental settings and through their use as preventive treatment for migraine, gepants appear unlikely to produce medication‐overuse headache. In addition, one gepant (ubrogepant) has demonstrated efficacy in preventing headache onset when given during the prodrome, a finding that has not been demonstrated for triptans. A single‐arm, open‐label study of naratriptan given during the prodrome suggested fewer subsequent headaches, but interpretation is limited because there was no contemporaneous control group. Limited head‐to‐head clinical trials comparing gepants and triptans have not demonstrated significant differences. Prescribers of both triptans and gepants should be mindful of potential drug–drug interactions. Conclusions Key advantages of gepants include their favorable tolerability, efficacy for the acute treatment of both the prodromal/premonitory phase (ubrogepant) and the headache phase of migraine (ubrogepant, rimegepant, zavegepant), lack of cardiovascular contraindications, and lack of association with medication‐overuse headache. Disadvantages include limitations due to cost and access and CYP3A4 drug interactions for most gepants. Together, the advantages may help to optimize patient care and lead to better persistence and effectiveness in a real‐world setting. Head‐to‐head studies are needed to clarify the comparative effectiveness of triptans and gepants.

Abstract Few prospective benchmark studies exist to characterize the evolving contemporary real-world practice for peripheral T-cell lymphoma (PTCL). We report the patterns of first-line care and outcomes for 720 patients with systemic PTCL enrolled in 2 related prospective cohort studies, Lymphoma Epidemiology of Outcomes (LEO) from 2015 to 2020 and Molecular Epidemiology Resource (MER) from 2002 to 2015, both followed to 2024. The primary end points were event-free survival (EFS) and overall survival (OS) using Kaplan-Meier estimator and Cox regression model. Secondary end points included correlations of clinical and treatment factors with survival. The most common induction regimens were CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone) based (70%), given as CHOP (36%), CHOP plus etoposide (23%), or CHOP-like plus novel agents (11.5%, including 5% BV-CHP [brentuximab plus cyclophosphamide, doxorubicin, and prednisone]). Consolidative autologous stem cell transplant was performed in 102 patients (14%). Within nodal PTCL, EFS and OS were adversely associated with International Prognostic Index 2 to 5, prognostic index for T-cell lymphoma score 1 to 4, and non–anaplastic large-cell lymphoma (ALCL) subtypes. Within LEO, which captured increasing first-line etoposide and brentuximab vedotin, adding etoposide to CHOP was associated with better OS in anaplastic lymphoma kinase-negative ALCL. BV-CHP showed a trend toward OS improvement in ALCL. Patients failing EFS6 and EFS24 had 5-year subsequent OS of 12% and 17%, respectively. The inferior outcomes in non-ALCL subtypes and patients failing EFS6 and EFS24 highlight unmet needs with CHOP-based induction, where clinical trials with targeted therapy should be prioritized. This trial was registered at www.clinicaltrials.gov as NCT02736357.

Abstract Background: Treatment for patients with triple-negative breast cancer (TNBC) relies on non-specific chemotherapy, underscoring the need for precision-based approaches. Our lab discovered that MALT1, the effector protein of the CARMA3-BCL10-MALT1 (CBM) signaling complex, is activated downstream of several oncogenic G protein-coupled receptors (GPCRs) implicated in breast cancer, including the thrombin (PAR1), angiotensin II (AGTR1), and lysophosphatidic acid (LPAR) receptors. When activated, MALT1 functions as a protease to cleave select protein substrates. Based on our finding that CBM activity in TNBC cells promotes tumor growth in immunocompetent but not in immunodeficient mouse models, we hypothesized that MALT1 protease activity induces a pro-tumor secretome that creates an immune-suppressed tumor immune microenvironment (TIME). Methods/Results: We confirmed by western that MALT1 protease is active in multiple human and mouse TNBC cell lines. Next, to identify MALT1-dependent secreted factors, we performed transcriptomic and proteomic analyses comparing TNBC cells treated with or without MALT1 protease inhibitors. We found that several secreted factors, including GM-CSF, CXCL1, and Pentraxin 3, were reduced by MALT1 protease inhibition. To assess the functional impact of the MALT1 protease-dependent secretome, we performed media transfer experiments comparing the effects of conditioned media (CM) from TNBC cells treated with or without MALT1 protease inhibitors. To account for species differences, experiments were performed evaluating human TNBC cell CM added to human PBMCs and mouse TNBC cell CM added to murine bone marrow cells. We found that the MALT1 protease-dependent secretome reduces the expression of iNOS in both human and murine macrophages. For use in validating our findings in human TNBC clinical specimens, we developed a “MALT1 protease active gene signature” using RNA-seq analysis. Conclusions/Future Directions: Our studies indicate that MALT1 protease activity in TNBC cells promotes expression of numerous immune-suppressive factors. In both human and mouse systems, blockade of MALT1 protease alters the tumor cell secretome and promotes an increase in expression of the anti-tumor M1-like marker iNOS in macrophages. Future studies will evaluate how this change in iNOS expression impacts functional properties of TNBC-associated macrophages. We will also assess the influence of the TNBC MALT1-dependent secretome on the TIME in vivo by comparing the effects of intratumoral injection of CM from MALT1 wild-type or MALT1 protease-deficient TNBC cells. Finally, we will utilize our MALT1 activity gene signature to evaluate TNBC clinical specimens for an association between MALT1 activity and tumor immune contexture, with an emphasis on tumor-associated macrophages. Our studies could nominate MALT1 protease as a potential therapeutic target for improving anti-tumor immunity in TNBC. Since multiple MALT1 protease inhibitors are in clinical trial, our findings could be rapidly translated to improve outcomes for patients with TNBC. Citation Format: John W. Little IV, Jeffrey A. Meridew, Dong Hu, Juliana Hofstätter Azambuja, Linda M. McAllister-Lucas, Peter C. Lucas. The GPCR-MALT1 protease signaling axis drives an immunosuppressive secretome in triple-negative breast cancer [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr B046.

Abstract The adoption of electronic health records (EHRs) has transformed health care, improving efficiency and chart accessibility. However, the widespread reliance on unstructured data entry and the lack of standardized documentation frameworks have resulted in significant data fragmentation across health care systems. The prevalence of unstructured data in EHRs limits their potential for clinical decision support, trial matching, real‐world evidence (RWE) generation, and quality measurement. Data fragmentation in health care triggers a cascade of challenges that ultimately compromise patient care. Clinicians face an excessive documentation burden and struggle to locate critical information buried in unstructured notes. Researchers encounter difficulties in extracting reliable clinical data. EHR vendors grapple with standardizing unstructured information for interoperability, and payers are unable to process unstructured clinical data efficiently to support value‐based care models. These challenges are particularly acute in oncology, where complex clinical elements like cancer staging, disease status, and treatment changes require precise, structured documentation. Emerging artificial intelligence (AI) technologies, such as large language models (LLMs) and ambient listening, offer a path to automate structured data generation while reducing the workload on providers. Here, the authors propose LLM‐based workflows that balance automation with clinician verification, streamlining data entry without compromising accuracy. Realizing these benefits requires coordinated efforts among clinicians, researchers, EHR vendors, payers, and policymakers to align regulatory frameworks with AI‐driven innovations. This article outlines a strategy to enhance structured data capture within EHRs, ultimately improving patient care, research, and health care efficiency.