Abstract Spatial transcriptomics data play a crucial role in cancer research, providing a nuanced understanding of the spatial organization of gene expression within tumor tissues. Unraveling the ...spatial dynamics of gene expression can unveil key insights into tumor heterogeneity and aid in identifying potential therapeutic targets. However, in many large-scale cancer studies, spatial transcriptomics data are limited, with bulk RNA-seq and corresponding Whole Slide Image (WSI) data being more common (e.g. TCGA project). To address this gap, there is a critical need to develop methodologies that can estimate gene expression at near-cell (spot) level resolution from existing WSI and bulk RNA-seq data. This approach is essential for reanalyzing expansive cohort studies and uncovering novel biomarkers that have been overlooked in the initial assessments. In this study, we present STGAT (Spatial Transcriptomics Graph Attention Network), a novel approach leveraging Graph Attention Networks (GAT) to discern spatial dependencies among spots. Trained on spatial transcriptomics data, STGAT is designed to estimate gene expression profiles at spot-level resolution and predict whether each spot represents tumor or non-tumor tissue, especially in patient samples where only WSI and bulk RNA-seq data are available. Comprehensive tests on two breast cancer spatial transcriptomics datasets demonstrated that STGAT outperformed existing methods in accurately predicting gene expression. Further analyses using the TCGA breast cancer dataset revealed that gene expression estimated from tumor-only spots (predicted by STGAT) provides more accurate molecular signatures for breast cancer sub-type and tumor stage prediction, and also leading to improved patient survival and disease-free analysis. Availability: Code is available at https://github.com/compbiolabucf/STGAT.
Abstract Chimeric antigen receptor (CAR) therapy has emerged as a ground-breaking advancement in cancer treatment, harnessing the power of engineered human immune cells to target and eliminate cancer ...cells. The escalating interest and investment in CAR therapy in recent years emphasize its profound significance in clinical research, positioning it as a rapidly expanding frontier in the field of personalized cancer therapies. A crucial step in CAR therapy design is choosing the right target as it determines the therapy’s effectiveness, safety and specificity against cancer cells, while sparing healthy tissues. Herein, we propose a suite of tools for the identification and analysis of potential CAR targets leveraging expression data from The Cancer Genome Atlas and Genotype-Tissue Expression Project, which are implemented in CARTAR website. These tools focus on pinpointing tumor-associated antigens, ensuring target selectivity and assessing specificity to avoid off-tumor toxicities and can be used to rationally designing dual CARs. In addition, candidate target expression can be explored in cancer cell lines using the expression data for the Cancer Cell Line Encyclopedia. To our best knowledge, CARTAR is the first website dedicated to the systematic search of suitable candidate targets for CAR therapy. CARTAR is publicly accessible at https://gmxenomica.github.io/CARTAR/.
Abstract Thyroid cancer incidences endure to increase even though a large number of inspection tools have been developed recently. Since there is no standard and certain procedure to follow for the ...thyroid cancer diagnoses, clinicians require conducting various tests. This scrutiny process yields multi-dimensional big data and lack of a common approach leads to randomly distributed missing (sparse) data, which are both formidable challenges for the machine learning algorithms. This paper aims to develop an accurate and computationally efficient deep learning algorithm to diagnose the thyroid cancer. In this respect, randomly distributed missing data stemmed singularity in learning problems is treated and dimensionality reduction with inner and target similarity approaches are developed to select the most informative input datasets. In addition, size reduction with the hierarchical clustering algorithm is performed to eliminate the considerably similar data samples. Four machine learning algorithms are trained and also tested with the unseen data to validate their generalization and robustness abilities. The results yield 100% training and 83% testing preciseness for the unseen data. Computational time efficiencies of the algorithms are also examined under the equal conditions.
Abstract Breast cancer (BC) is the most common malignancy affecting Western women today. It is estimated that as many as 10% of BC cases can be attributed to germline variants. However, the genetic ...basis of the majority of familial BC cases has yet to be identified. Discovering predisposing genes contributing to familial BC is challenging due to their presumed rarity, low penetrance, and complex biological mechanisms. Here, we focused on an analysis of rare missense variants in a cohort of 12 families of Middle Eastern origins characterized by a high incidence of BC cases. We devised a novel, high-throughput, variant analysis pipeline adapted for family studies, which aims to analyze variants at the protein level by employing state-of-the-art machine learning models and three-dimensional protein structural analysis. Using our pipeline, we analyzed 1218 rare missense variants that are shared between affected family members and classified 80 genes as candidate pathogenic. Among these genes, we found significant functional enrichment in peroxisomal and mitochondrial biological pathways which segregated across seven families in the study and covered diverse ethnic groups. We present multiple evidence that peroxisomal and mitochondrial pathways play an important, yet underappreciated, role in both germline BC predisposition and BC survival.
Abstract With the increasing prevalence of age-related chronic diseases burdening healthcare systems, there is a pressing need for innovative management strategies. Our study focuses on the gut ...microbiota, essential for metabolic, nutritional, and immune functions, which undergoes significant changes with aging. These changes can impair intestinal function, leading to altered microbial diversity and composition that potentially influence health outcomes and disease progression. Using advanced metagenomic sequencing, we explore the potential of personalized probiotic supplements in 297 older adults by analyzing their gut microbiota. We identified distinctive Lactobacillus and Bifidobacterium signatures in the gut microbiota of older adults, revealing probiotic patterns associated with various population characteristics, microbial compositions, cognitive functions, and neuroimaging results. These insights suggest that tailored probiotic supplements, designed to match individual probiotic profile, could offer an innovative method for addressing age-related diseases and functional declines. Our findings enhance the existing evidence base for probiotic use among older adults, highlighting the opportunity to create more targeted and effective probiotic strategies. However, additional research is required to validate our results and further assess the impact of precision probiotics on aging populations. Future studies should employ longitudinal designs and larger cohorts to conclusively demonstrate the benefits of tailored probiotic treatments.
PUBLIC HEALTH AND CARE DELIVERY THEME ISSUE: Through partnerships with trusted community-based organizations, health systems and public health are able to expand access to care for the vulnerable ...segments of the population. The experience of Saint Paul – Ramsey County Public Health, Fairview Health Services, and many local community and faith-based partners has implications for ongoing teamwork in care delivery.
In Minnesota, age-adjusted case incidence rates of Covid-19 infection were significantly higher among Black and Latine communities compared with non-Hispanic white communities. The siloed nature of public health and health care delivery emerged as a critical obstacle to equitable Covid-19 testing and vaccination. Fragmented care delivery due to varying funding models, complicated administrative frameworks, and systemic barriers to accessing services impeded a rapid, equity-focused response. Saint Paul – Ramsey County Public Health (SPRCPH), Fairview Health Services (Fairview), and many local community and faith-based partners recognized the need to work together to ensure that underserved populations had equitable access to Covid-19 testing and vaccination. The authors describe how these entities, collectively serving a population of about 550,000, sought to establish equitable, low-barrier Covid-19 testing and vaccinations that were accessible, free, and available within a trusted space and given appropriate language and cultural considerations to address long-standing health disparities revealed and exacerbated by the pandemic. The partnership’s strength lay in integrating SPRCPH’s logistics capability with Fairview’s clinical expertise and the community partners’ trusted status, enhancing the credibility and effectiveness of public health initiatives. SPRCPH provided the supplies and operations personnel needed to establish drive-through testing sites capable of serving more than 1,500 patients in a 6-hour operational period. Fairview brought teams of medical staff and colleagues who supported in nonclinical roles and engaged with community partners. Over the course of the response, this cadre of participants learned to function less as a partnership between separate entities and more like one team with staff from multiple organizations. From 2020 to 2023, this initiative set up 38 community mass-testing clinics and organized 210 Covid-19 vaccination clinics across 71 diverse community-based sites, including fire stations, consulates, schools, shelters, and faith-based organizations. Notably, 56 of the sites were situated within census tracts exhibiting a social vulnerability index (SVI) of 0.500 or higher, with 35 sites having an SVI score surpassing 0.800, indicating greater vulnerability. Through this effort, 18,059 Covid-19 tests were conducted and processed, and 16,367 Covid-19 vaccinations were administered, averaging 78 per clinic. Many community members who received services were recent immigrants and persons whose preferred language was not English. The success of this pandemic response depended largely on a common mission and shared sense of purpose among previously infrequent or unfamiliar partners. However, operations were not seamless; if these relationships had existed and been fostered during nonemergency periods, the responsiveness among participants could have produced better results. Although much was accomplished, it is sobering to remember the many lives lost during the pandemic. The authors describe an approach to eliminate silos to maintain and strengthen teamwork between public health and care delivery to improve care and be better prepared for future public health emergencies.
Poser le diagnostic de crise non épileptique est difficile en absence de vidéo-électroencéphalogramme. La commission d´expert de la ligue international contre l´épilepsie propose une démarche ...diagnostic permettant de poser le diagnostic selon un degré de certitude avec ou en absence de vidéo-électroencéphalogramme. Notre objectif était de déterminer la fréquence hospitalière des crises non épileptiques psychogènes en absence de vidéo-électroencéphalogramme. A l´aide du registre de consultation externe, nous avons identifié les patients suivis pour épilepsie avec deux électroencéphalographies inter-critiques normaux, entre janvier 2020 et octobre 2021. Un examen des dossiers médicaux des patients et une évaluation de la validité du diagnostic ont été effectués. Sur 64 patients évalués avec électroencéphalogramme intercritique normal, 19 ont été inclus comme souffrant de crise non épileptique psychogène, soit 26,68%. La moyenne d´âge était de 23,94 +/- 9,4 ans. Les femmes représentaient 68,4%. Les patients suivis en neurologie ont représenté 84%. Un antécédent de traumatisme dans l´enfance était retrouvé dans (47,4 %). La première crise était précédée d´événements stressants dans 47,36%. Le trouble stress posttraumatique était le plus représenté avec 73,7% des cas. L´âge moyen était de 20,95 +/-9,8 ans pour la première la crise et la durée moyenne d´évolution des crises était de 3 ans +/- 2 ans. Cette étude illustre la possibilité de poser un diagnostic présomptif de crise non-épileptique psychogène en absence de vidéo-EEG.
