Citations

Abstract Chromosome 5p15.33 harbors several independent association signals which demonstrate antagonistic pleiotropy across cancer types, with causal mechanisms largely unresolved. To identify functional variants and enhancer elements at this locus, we performed statistical fine-mapping followed by massively parallel reporter assays (MPRA) and proliferation based CRISPRi screens. This approach identified eight multi-cancer functional variants (MCFVs) across three GWAS signals. Targeting rs421629 (part of the CLPTM1L signal marked by rs465498) with CRISPRi revealed opposing effects on TERT expression in pancreatic versus lung cancer cells, consistent with the antagonistic pleiotropy observed for this signal. Furthermore, CRISPRi nominated an intronic CLPTM1L variable number tandem repeat (VNTR) as a potent enhancer. Long-read sequencing established VNTR polymorphisms as potential causal variants for the rs465498 signal. We showed that Hippo-pathway transcription factors mediate VNTR enhancer activity in lung and pancreatic cancer cells. Together, these findings indicate that cancer susceptibility at 5p15.33 may be mediated by both SNPs and VNTRs and provide an integrated framework for resolving complex pleiotropic loci.

(1) Background: Mammographic breast density (MBD) is a well-established predictor of breast cancer risk, yet the biological mechanisms underlying this association remain incompletely understood. MBD is characterized by alterations in breast stromal architecture, including increased collagen deposition and changes in immune cell composition. Given emerging evidence that the breast harbors a resident microbiome, we investigated whether the breast tissue microbiome correlates with MBD. (2) Methods: Adjacent normal breast tissue was collected under sterile conditions from 33 women undergoing surgery for benign or malignant breast disease. DNA was extracted and subjected to 16S rRNA gene sequencing (Illumina MiSeq). (3) Results: We observed a non-significant trend toward lower α-diversity in high-MBD samples compared to low-MBD samples, p = 0.13. β-Diversity analyses identified a modest association between MBD and microbial community composition (MiRKAT p = 0.049). A random forest-based model incorporating genus-level relative abundances improved prediction of MBD over clinical characteristics alone, identifying Corynebacterium (Actinobacteria) and other genera as key predictors. (4) Conclusions: Breast tissue microbial features vary with mammographic breast density, suggesting a potential association with density-associated breast cancer risk. These exploratory findings warrant validation in larger cohorts to better elucidate biological mechanisms and clinical relevance.

Abstract Objectives Sarcomatoid urothelial carcinoma (sUC) is associated with poor clinical outcomes. Herein, we evaluated clinicopathologic features (including PD-L1 expression) for institutional cases. Methods Sixty-five patients with sUC treated by radical cystectomy were matched for age, sex, and pathologic stage to 190 patients with pure urothelial carcinoma (UC). Outcomes were evaluated using the Kaplan-Meier method. Immunohistochemistry (IHC) results for tumor-specific PD-L1 expression in sUC were quantified using H-scores (range, 0-300). Cases with constitutive PD-L1 expression (cPD-L1; H-score ≥240) were evaluated for amplification events using fluorescence in situ hybridization (n = 28), mate-pair sequencing (Mpseq; n = 6), RNA sequencing (n = 5), and targeted next-generation sequencing (n = 8). PD-L1 regulatory pathways were evaluated using gene set enrichment analysis in the Cancer Hallmark dataset. Results Most patients with sUC had advanced disease (≥pT2, 62/65, 95%), without significant differences in overall and cancer-specific survival, when matched to pure UC. Median PD-L1 H-scores using different clones were 100 (SP142), 120 (SP263), and 195 (22C3). cPD-L1 was seen in 43% (28/65) of cases of sUC that were enriched for TP53, TERT, and CDKN2A/B alterations. PD-L1 amplification was identified in 7 (of 28, 25%) of these cases. Bionformatics analysis consistently identified IL6-JAK-STAT3 and interferon α/γ signaling in sUC with cPD-L1 expression. Conclusions Our results suggest that cPD-L1 expression in most sUC occurs secondary to IL6-JAK-STAT3 and interferon α/γ signaling. This provides a biologic rationale for evaluating response to immunotherapy in this patient population.

ABSTRACT Meningiomas are the most common primary brain tumors and, despite their benign reputation, often behave aggressively. Meningiomas are morphologically heterogeneous, yet the full significance of their histologic diversity is unclear. This is in large part because many features are not readily quantifiable by traditional observer-based light microscopy. Molecular testing improves prognostic stratification, but is not universally accessible. We therefore sought to determine whether an artificial intelligence (AI)-trained program could predict specific genomic and epigenomic patterns in meningiomas, and whether it could extract more prognostic information out of standard hematoxylin and eosin (H&E) histopathology than the current WHO classification. To do this, we developed Morphologic Set Enrichment (MSE), an interpretable computational pathology framework that quantifies statistical enrichment of morphologic patterns, cells, and tissue architecture from H&E whole-slide images. The MSE meningioma histology program was able to accurately predict DNA methylation subtypes and concurrent chromosome 1p/22q losses, in the process identifying specific morphologic patterns associated with key genomic and epigenomic alterations. It also added prognostic value independent of standard clinical and pathological variables. These results demonstrate that AI-based quantitative morphologic profiling can capture clinically and biologically relevant information that redefines risk stratification for meningiomas, incorporating histological information not included in existing grading schemes.

Functional analyses of mitochondria have been hampered by few effective approaches to manipulate mitochondrial DNA (mtDNA) and a lack of existing animal models. Recently a TALE-derived base editor was shown to induce C-to-T (or G-to-A) sequence changes in mtDNA. We report here the FusX TALE Base Editor (FusXTBE) to facilitate broad-based access to TALE mitochondrial base editing technology. TALE Writer is a de novo in silico design tool to map potential mtDNA base editing sites. FusXTBE was demonstrated to function with comparable activity to the initial base editor in human cells in vitro . Zebrafish embryos were used as a pioneering in vivo test system, with FusXTBE inducing 90+% editing efficiency in mtDNA loci as an example of near-complete induction of mtDNA heteroplasmy in vivo . Gene editing specificity as precise as a single nucleotide was observed for a protein-coding gene. Nondestructive genotyping enables single-animal mtDNA analyses for downstream biological functional genomic applications. FusXTBE is a new gene editing toolkit for exploring important questions in mitochondrial biology and genetics.

Background and Objectives: Despite wide agreement on the importance of building research capacity to the specialty of family medicine, no standard exists for defining or measuring that growth. Previous work to address this gap yielded the Productivity and Capacity Evaluation in Research (PACER) Tool, a list of quantitative research metrics grouped into seven categories. We surveyed family medicine department chairs to understand which categories of PACER metrics they considered most valuable in evaluating their department’s research capacity. We also aimed to compare reported research capacity in 2024 with answers given by family medicine department chairs in 2021. Methods: A cross-sectional survey administered through the Council of Academic Family Medicine Educational Research Alliance (CERA) was used to gather information from family medicine department chairs in the United States and Canada. One question asked chairs to evaluate their department’s research capacity, and nine questions assessed the relative importance of the seven PACER Tool categories. Results: A total of 218 surveys were delivered, with 111 (50.9%) completed. Survey results demonstrated that program chairs determined funding to be the most impactful category. We found no clear trend in the second most important or least important categories. Results also showed no statistically significant change in reported research capacity between 2021 and 2024. Conclusions: Funding emerged as the category of research metrics viewed as most important by the greatest number of family medicine department chairs. Although other categories of metrics also were viewed as important, this survey demonstrated no clear pattern of their relative importance in this population.

Abstract Advancements in the understanding of chronic lymphocytic leukemia (CLL) have transformed patient care, leading to the development of novel targeted therapies. Traditionally, patient fitness for treatment was based on the tolerability of chemoimmunotherapy such as fludarabine–cyclophosphamide–rituximab. As the CLL patient population is predominantly older, age has historically been a major factor in how a physician selects a patient's treatment. However, as a patient's fitness goes beyond age, the definition of patient fitness should also evolve. Here, we provide suggestions for the current best practice on assessing fitness for treating CLL. Considerations for treatment include assessment of polypharmacy, history of infections, cardiovascular and renal comorbidities, functional status, cognitive and psychological status, nutritional status, and social support. The flow of assessments can start with a typical clinical evaluation followed by geriatric, cardiovascular, and renal reviews, if needed, and include collecting a patient's full history to evaluate their risk of complications with specific CLL treatments. The severity of a patient's cardiovascular profile can range from low to high risk; for those at high risk, collaboration with a cardiologist is recommended. Geriatric assessment is advised to determine baseline frailty and resilience to tolerate treatments, to avoid inappropriate treatment or undertreating patients based on chronological age, and to align the patient's fitness status with the most optimal treatment. Continuous monitoring and assessment, regardless of therapy, are recommended. Patient preferences are also integral to this decision‐making process. Looking beyond a patient's age and basing treatment selection on their fitness is key in the new era of treatment in CLL.