Citations

Triple-negative breast cancer (TNBC) represents the most malignant subtype of breast cancer. The clinical application of PARP inhibitors (PARPi) is limited by the low frequency of BRCA1/2 mutations in TNBC. Here, we identified that MTAP deletion sensitized genotoxic agents in our clinical cohort of metastatic TNBC. Further study demonstrated that MTAP deficiency or inhibition rendered TNBC susceptibility to chemotherapeutic agents, particularly PARPi. Mechanistically, targeting MTAP that synergized with PARPi by disrupting the METTL16-MAT2A axis involved in methionine metabolism and depleting in vivo s-adenosylmethionine (SAM) levels. Exhausted SAM in turn impaired PARPi-induced DNA damage repair through attenuation of MRE11 recruitment and end resection by diminishing MRE11 methylation. Notably, brain metastatic TNBC markedly benefited from a lower dose of PARPi and MTAP deficiency/inhibition synergy due to the inherently limited methionine environment in the brain. Collectively, our findings revealed a feed-forward loop between methionine metabolism and DNA repair through SAM, highlighting a therapeutic strategy of PARPi combined with MTAP deficiency/inhibition for TNBC.

Abstract Aggregation and nuclear depletion of the RNA binding protein TDP-43 are the crucial pathological features of amyotrophic lateral sclerosis (ALS) and inclusion body myositis (IBM), two degenerative diseases of the CNS and muscle. The loss of TDP-43 nuclear function results in the aberrant inclusion of cryptic exons in mRNA transcripts, leading to the expression of de novo proteins. Clonally expanded and highly differentiated CD8 + T cells have been observed in individuals with TDP-43 proteinopathies and therapeutics modulating the T cell response have recently been found to extend survival. However, the target antigens mediating T cell activation have remained elusive. Here, we investigate whether the de novo proteins induced by aberrant cryptic splicing due to TDP-43 nuclear loss can act as neo-antigens. We detect the HDGFL2 cryptic peptide and multiple other TDP-43 cryptic exons in IBM skeletal muscle, where their presence correlates with enrichment of T cells and class I antigen presentation pathways. Furthermore, we identify epitopes deriving from HDGFL2 and IGLON5 cryptic peptides which are recognized by clonally expanded and functionally differentiated populations of CD8 + T cells in ALS and IBM Patients. Finally, we demonstrate that T cells engineered to express the identified TCRs can bind and activate in response to the cryptic peptide derived epitopes (cryptic epitopes) and are able to kill TDP-43 deficient astrocytes. This work identifies for the first time specific T cell antigens in ALS and IBM, directly linking adaptive immune response to TDP-43 pathology.

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.

AbstractPurposeThe Collaborative care model (CoCM) is the leading model for integrating behavioral health into primary care for patients with major depressive disorder (MDD). However, CoCM requires engagement and ongoing participation. We aimed to assess whether two area‐based measures, the area‐deprivation index (ADI) and rurality, were associated with enrollment, participation, and outcomes with CoCM.MethodsThis was an observational analysis of Mayo Clinic patients eligible for CoCM: adults aged ≥18 years, empaneled in primary care, and with a PHQ‐9 of ≥10. We operationalized ADI as quintiles with Q1 being least deprived and Q5 being most deprived and rurality using RUCA codes with two categories: urban and rural. We evaluated enrollment in CoCM, drop out defined by leaving the program early, the count and type of contacts with the care coordinator, and clinical improvement measured using the PHQ‐9.FindingsWe identified 54,030 individuals with 16,532 (30.6%) residing in rural areas and 11,122 (20.6%) residing in the most deprived ADI quintile (Q5). Living in a rural area was associated with lower enrollment in CoCM (–2.3 percentage points [95% confidence interval (CI): –2.5, 2.2]), longer length in CoCM (18.6 days [95% CI: 5.7, 31.5]), more contacts with the care coordinator (1.1 contacts [95% CI: 0.2, 2.0]), and worse response and remission. In contrast, ADI Q5 was only associated with worse response and remission.ConclusionsRurality was associated with lower enrollment, greater engagement, and worse clinical outcomes. More work may be needed to address enrollment barriers for individuals living in rural areas to improve clinical outcomes.

Abstract Single‐molecule immunoassay is a reliable technique for the detection and quantification of low‐abundance blood biomarkers, which are essential for early disease diagnosis and biomedical research. However, current single‐molecule methods predominantly rely on endpoint detection and necessitate signal amplification via labeling, which brings a variety of unwanted effects, like matrix effect and autofluorescence interference. This study introduces a real‐time mass imaging‐based label‐free single‐molecule immunoassay (LFSMiA). Featuring plasmonic scattering microscopy‐based mass imaging, a 2‐step sandwich assay format enables background reduction, minimization of matrix effect by dynamic tracking of single binding events, and fully leveraging real‐time data for improved measurement precision through a Bayesian Gaussian process model, the LFSMiA enables ultra‐sensitive and direct protein detection at the single‐molecule level in neat blood sample matrices. LFSMiA measurement is demonstrated for interleukin‐6 and prostate‐specific antigen in buffer, undiluted serum, and whole blood with sub‐femtomolar detection limits and eight logs of dynamic ranges. Moreover, comparable performance is achieved with an inexpensive miniaturized setup. To show its translational potential to clinical settings and point‐of‐care diagnostics, N‐terminal pro‐B‐type natriuretic peptide is examined in patient whole blood samples using the LFSMiA and results in a strong linear correlation (r > 0.99) with standard clinical lab results.

ObjectivesAchalasia is an esophageal motility disorder that impairs quality of life and is often missed (20–50%) on endoscopy. A newly developed computer‐aided detection (CAD) software has shown high accuracy for achalasia diagnosis in preclinical settings. However, its benefit in a clinical setting remains unclear.MethodsBetween February and August 2023, 83 endoscopists from 27 centers assessed 50 randomized endoscopic videos (25 achalasia, 25 nonachalasia) without and with CAD. Endoscopists assessed videos without CAD, then with CAD after 2 months. The primary end‐point was improvement in sensitivity for nonexperienced endoscopists (no endoscopic experience of achalasia). Sensitivity, specificity, and accuracy with and without CAD were compared using the McNemar test.ResultsSensitivity for diagnosing achalasia increased significantly with CAD, rising from 74.2% (95% confidence interval [CI] 72.2–76.0%) to 91.2% (95% CI 89.9–92.4%) for all readers, showing a difference of 17.1% (95% CI 15.1–19.0%). Specifically, sensitivity improved from 66.9% (95% CI 63.6–70.0%) to 91.9% (95% CI 89.9–93.6%) among nonexperienced endoscopists, resulting in a difference of 25.0% (95% CI 21.7–28.4%), and from 79.5% (95% CI 77.1–81.8%) to 90.8% (95% CI 89.0–92.3%) among experienced endoscopists (endoscopic experience of at least one achalasia case), with a difference of 11.3% (95% CI 8.9–13.6%). Accuracy and specificity improved significantly with CAD assistance, regardless of reader's experience.ConclusionCAD improves achalasia detection by 17%, confirming preclinical results. The benefit was higher for nonexperienced endoscopists. CAD assistance may lead to prompt and effective treatment, minimizing the risk of false‐negative diagnosis in clinical practice.Trial registrationThis study was registered in the University Hospital Medical Information Network Clinical Trial Registry (https://www.umin.ac.jp/ctr/) number: UMIN000053047.

BACKGROUND AND OBJECTIVES: Social determinants of health (SDOH), such as education, insurance, race, and income, significantly affect a patient's medical care and surgical outcomes. Additional studies characterizing the impact of SDOH on patients undergoing spine surgery are needed. Accordingly, this study evaluates the impact of SDOH on severity of symptoms at presentation and discharge disposition in patients undergoing surgical treatment of cervical myelopathy. METHODS: A retrospective single-center study identified adult patients undergoing surgical intervention for cervical myelopathy between 2016 and 2020. Cohort characteristics were collected from patient medical records. The t -test, Wilcoxon rank-sum, analysis of variance, Kruskal-Wallis, and χ 2 tests were used to compare variables when appropriate. Multivariable linear and logistic regression analyses were conducted for modified Japanese Orthopaedic Association (mJOA) and discharge disposition. All statistical analysis was performed in MATLAB R2022b (MathWorks, Natick, MA). RESULTS: A total of 480 patients were included in the study with a male predominance of n = 281 (59%) and a mean age of 62 ± 13 years. Racial demographics included 64% White (n = 308) and 36% Non-White (n = 172) patients. On univariable analysis, mJOA at presentation was significantly associated with employment status ( P < .01), annual income ( P < .01), education level ( P < .01), and insurance status ( P = .03). On multivariable analysis, annual income and education level continued to be significant predictors of presenting mJOA. On univariable analysis, discharge disposition was associated with body mass index ( P = .01), mJOA at presentation ( P < .01), employment status ( P = .05), annual income ( P < .01), education level ( P < .01), insurance ( P < .01), approach ( P < .01), and length of stay ( P < .01). On multivariable analysis, mJOA at presentation, education level, insurance, and approach continued to be significant predictors of discharge disposition. CONCLUSION: SDOH affect the severity of symptoms at presentation and discharge disposition in patients undergoing surgery for cervical myelopathy. Understanding these dynamics and uncovering additional SDOH are critical for enhancing surgical care and achieving equitable healthcare outcomes.

ABSTRACT Older adults are susceptible to infections, in part due to waning of immune memory. To determine mechanisms that determine long-lasting versus short-term immunity, we examined varicella zoster virus (VZV) vaccination as a model system. We contrasted VZV antigen-specific T cells several years after vaccination in adults who had been vaccinated at young (<20 years) or older age (>50 years) with a live-attenuated vaccine that confers durable protection only when given at young age, or with an adjuvanted VZV component vaccine that elicits effective, long-lasting immunity in older adults. CD8 + T cells were highly sensitive to age-related changes showing T cell subset shifts, loss in TCR diversity and reduced stem-like features while gaining NK-like signatures without evidence for cellular senescence or exhaustion. VZV-specific CD4 + T cells were largely resilient to age and maintained phenotypic and TCR diversity. Immunization of older adults with the adjuvanted VZV vaccine did not reverse age-associated defects in CD8 + T cells. Instead, it selectively improved the functionality of VZV-specific Th17 CD4 + T cells and prevented their acquisition of Treg features, likely as consequence of lipid metabolic pathways. Collectively, our data indicate that effective vaccination in older adults is supported by the generation of a durable, antigen-specific CD4 + Th17 population that resists mis-differentiation into Tregs and that compensates for age-related defects in CD8 + T cells. One sentence summary Aging primarily impairs the CD8 + T cell VZV vaccine response, while effective VZV vaccination in older adults induces antigen-specific Th17 CD4 + T cells to compensate for aging defects.