Providence St. Joseph Health Digital Commons
Not a member yet
12290 research outputs found
Sort by
Outcomes of CD19 CAR T in Transformed Indolent Lymphoma Compared to De Novo Aggressive Large B-Cell Lymphoma.
No full textChimeric antigen receptor (CAR) T-cell therapy has revolutionized treatment of aggressive large B-cell lymphoma (aLBCL). Patients with transformed indolent non-Hodgkin lymphoma (tiNHL) were included in key CAR trials, but outcomes of CAR for this distinct, historically high-risk group are poorly understood. We conducted a multicenter retrospective study of 1182 patients with aLBCL receiving standard-of-care CAR T between 2017 and 2022, including 338 (29%) with tiNHL. Rates of grade ≥ 3 cytokine release syndrome (CRS) were similar between tiNHL and de novo cohorts (7% vs. 8%, p = 0.6), while grade ≥ 3 immune effector cell-associated neurotoxicity syndrome was lower in tiNHL (21% vs. 27%, p = 0.02). Overall response rate was similar in both cohorts (83% vs. 81%, p = 0.3), while complete response rate was higher in tiNHL (67% vs. 59%, p = 0.017). With a median follow-up of 22.3 months, the progression/relapse-free (PFS) and overall survival (OS) were similar between the tiNHL and de novo cohorts (24-month PFS 41% [95% CI: 35%-46%] vs. 38% [95% CI: 35%-42%]; 24-month OS 58% [95% CI: 52%-63%] vs. 52% [95% CI: 48%-56%], respectively). After adjusting for key risk factors, there was a trend toward a lower hazard of disease progression, relapse or death post-CAR for tiNHL patients compared to de novo aLBCL patients (HR: 0.84 [95% CI: 0.69-1.0], p = 0.07). Elevated LDH, advanced stage, prior bendamustine within 12 months of CAR, receipt of bridging therapy, CNS involvement, and ≥ 3 prior lines of therapy were each associated with inferior PFS. In conclusion, CAR T therapy is highly effective with an acceptable toxicity profile in patients with tiNHL
The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation.
No full textPharmacogenetics promises to optimize treatment-related outcomes by informing optimal drug selection and dosing based on an individual\u27s genotype in conjunction with other important clinical factors. Despite significant evidence of genetic associations with drug response, pharmacogenetic testing has not been widely implemented into clinical practice. Among the barriers to broad implementation are limited guidance for how to successfully integrate testing into clinical workflows and limited data on outcomes with pharmacogenetic implementation in clinical practice. The Pharmacogenomics Global Research Network Implementation Working Group seeks to engage institutions globally that have implemented pharmacogenetic testing into clinical practice or are in the process or planning stages of implementing testing to collectively disseminate data on implementation strategies, metrics, and health-related outcomes with the use of genotype-guided drug therapy to ultimately help advance pharmacogenetic implementation. This paper describes the goals, structure, and initial projects of the group in addition to implementation priorities across sites and future collaborative opportunities
The responses of HNSCC patients to immunotherapy are shown by two novel co-expression patterns.
No full textTreatment of head and neck squamous cell carcinoma (HNSCC) is complex, with immunotherapy demonstrating potential yet facing challenges due to the tumor\u27s unique immune microenvironment. Biomarker expression has been employed to predict immune responses, albeit with limited efficacy. We predicted that due to the complexity of the immune response, no singular biomarker could consistently forecast the efficacy of immunotherapy. Consequently, we implemented a multi-index strategy that encompassed a comprehensive study of the networks associated with HNSCC. Secretomes from 72 explants obtained from six HNSCC patients (comprising 72 secretome profiles: 18 untreated and 54 treated) were subjected to an information-theoretic analysis. The resultant phenotypes were corroborated in two external cohorts (TCGA, n = 518; GEO GSE159067, n = 102). This methodology revealed two reproducible co-expression phenotypes-Activation (Act) and Infiltration (Inf)-that were significantly correlated with T-cell functionality. Only tissues exhibiting both Act and Inf phenotypes demonstrated a favorable response to anti-PD-1 and anti-GITR ex vivo, and displayed an increased presence of CD8+ T-cells in proximity to cancer cells. External validation in two different RNA-seq cohorts reproduced the two phenotypes and verified that patients possessing both signatures had significantly prolonged overall survival following PD-1/PD-L1 therapy. This study emphasizes the importance of multiple-index characterization of HNSCC tissues in enhancing patient classification and predicting immunotherapy efficacy
Deciphering difficult-to-treat psoriatic arthritis: insights from an international survey of patients with psoriatic arthritis.
No full textOBJECTIVES: Psoriatic arthritis (PsA) is a heterogeneous inflammatory disease in which a significant proportion of patients remain refractory to existing therapies. The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) initiated a project aimed at unravelling the reasons for treatment failures in PsA, culminating in the establishment of definitions for difficult-to-treat PsA (D2T-PsA) and complex-to-manage PsA (C2M-PsA). This study explores patient perspectives on treatment-resistant PsA, incorporating a broader patient perspective into the overarching GRAPPA project.
METHODS: A multilingual (10 languages), online survey to explore PsA patients\u27 perspectives on treatment inefficacies was used. It was developed collaboratively by GRAPPA members and patient research partners. It included sections on demographic data, structured questions about treatment failures, and open-ended questions. Data analysis used descriptive statistics and inductive coding of qualitative responses via Dedoose.
RESULTS: Among 570 respondents, most were female (68.8%) and White (72.6%), with an average PsA diagnosis delay of 4.3 years. Key contributors to D2T- and C2M-PsA were persistent joint pain and psoriasis (65.7%), fatigue (52.8%) and medication side effects (41.7%). Ranked by impact, arthritis was the most debilitating symptom. Quality of life concerns were notable, with sleep impairment and reduced life enjoyment being reported by 66.4%. Language differences emerged; for instance, Dutch and Italian respondents prioritized fatigue and daily life impact, respectively.
CONCLUSION: This is the first international study to highlight patient-driven insights in the management of resistant PsA, emphasizing a multidimensional approach that considers biological and psychosocial factors. These insights will inform the ongoing GRAPPA initiative to standardize definitions for treatment-resistant PsA, ultimately improving patient care
Credible inferences in microbiome research: ensuring rigour, reproducibility and relevance in the era of AI.
No full textThe microbiome has critical roles in human health and disease. Advances in high-throughput sequencing and metabolomics have revolutionized our understanding of human gut microbial communities and identified plausible associations with a variety of disorders. However, microbiome research remains constrained by challenges in establishing causality, an over-reliance on correlative studies, and methodological and analytical limitations. Artificial intelligence (AI) has emerged as a powerful tool to address these challenges; however, the seamless integration of preclinical models and clinical trials is crucial to maximizing the translational impact of microbiome studies. This manuscript critically evaluates best methodological practices and limitations in the field, focusing on how emerging AI tools can bridge the gap between microbial insights and clinical applications. Specifically, we emphasize the necessity of rigorous, reproducible methodologies that integrate multiomics approaches, preclinical models and clinical trials in the AI-driven era. We propose a practical framework for applying AI to microbiome studies, alongside strategic recommendations for clinical trial design, regulatory pathways, and best practices for microbiome-based informed diagnostics, AI training and clinical interventions. By establishing these guidelines, we aim to accelerate the translation of microbiome research into clinical practice, enabling precision medicine approaches informed by the human microbiome
Evaluation of the use of convoluted neural network for detecting early gastric cancer and predicting its invasion depth: A systematic review and meta-analysis.
No full textBACKGROUND AND AIMS: Identification and assessment of early gastric cancer (EGC) has important prognostic implications. We aimed to review the role of artificial intelligence (AI) assisted endoscopy in the diagnosis and depth assessment of EGC.
METHODS: We searched Pubmed, EMBASE, Web of Science, and Cochrane Library database for studies assessing the role of AI in EGC. Included studies were pooled to obtain summary receiver operator characteristics curve (sROC), pooled sensitivity and specificity. Risk of bias was estimated using QUADAS-2 assessment tool and publication bias was assessed using funnel plots.
RESULTS: We included 19 studies, of which 11 evaluated the role of AI in detection of EGC and 10 evaluated depth of invasion. AI-assisted endoscopy was accurate in detecting EGC with area under sROC of 0.95 (95 % CI:0.93-0.98), pooled sensitivity of 84 % (95 % CI 84-85 %) and pooled specificity of 92 % (95 % CI 92-93 %). Similarly, depth of invasion could be assessed with area under sROC of 0.89 (95 % CI:0.86-0.92), pooled sensitivity of 84 % (95 % CI 82-86 %), and pooled specificity of 89 % (95 %CI 87-90 %). No significant experimental or publication bias was found.
CONCLUSIONS: AI assisted endoscopy has a promising role in diagnosis of EGC and deciding its further management
Applying a Conservation-Based Approach for Predicting Novel Phosphorylation Sites in Eukaryotes and Evaluating Their Functional Relevance.
No full textProtein phosphorylation, a key post-translational modification, is central to cellular signaling and disease pathogenesis. The development of high-throughput proteomics pipelines has led to the discovery of large numbers of phosphorylated protein motifs and sites (phosphosites) across many eukaryotic species. However, the majority of phosphosites are reported from human samples, with most species having a few experimentally confirmed or computationally predicted phosphosites. Furthermore, only a small fraction of the characterized human phosphoproteome has an annotated functional role. A common way of predicting functional phosphosites is through conservation-based sequence analysis, but large-scale evolutionary studies are scarce. In this study, we explore the conservation of 20,751 confident human phosphosites across 100 eukaryotic species and investigate the evolution of associated protein domains and kinases. We categorize protein functions based on phosphosite conservation patterns and demonstrate the importance of conservation analysis in identifying organisms suitable as biological models for studying conserved signaling pathways relevant to human biology and disease. Finally, we use human protein sequences as a reference for propagating over 1,000,000 potential phosphosites to other eukaryotes. Our results can improve proteome annotations of several species and help direct research aimed at exploring the evolution and functional relevance of phosphorylation
Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization.
No full textAbsolute bacterial biomass estimation in the human gut is crucial for understanding microbiome dynamics and host-microbe interactions. Current methods for quantifying bacterial biomass in stool, such as flow cytometry, quantitative polymerase chain reaction (qPCR), or spike-ins, can be labor-intensive, costly, and confounded by factors like water content, DNA extraction efficiency, PCR inhibitors, and other technical challenges that add bias and noise. We propose a simple, cost-effective approach that circumvents some of these technical challenges: directly estimating bacterial biomass from metagenomes using bacterial-to-host (B:H) read count ratios. We compared B:H ratios to the standard methods outlined above, demonstrating that B:H ratios are useful proxies for bacterial biomass in stool and possibly in other host-associated substrates. B:H ratios in stool were correlated with bacterial-to-diet (B:D) read count ratios, but B:D ratios exhibited a substantial number of outlier points. Host read depletion methods reduced the total number of human reads in a given sample, but B:H ratios were strongly correlated before and after host read depletion, indicating that host read depletion did not reduce the utility of B:H ratios. B:H ratios showed expected variation between health and disease states and were generally stable in healthy individuals over time. Finally, we showed how B:H and B:D ratios can be used to track antibiotic treatment response and recovery. B:H ratios offer a convenient alternative to other absolute biomass quantification methods, without the need for additional measurements, experimental design considerations, or machine learning, enabling robust absolute biomass estimates directly from stool metagenomic data.IMPORTANCEIn this study, we asked whether normalization by host reads alone was sufficient to estimate absolute bacterial biomass directly from stool metagenomic data, without the need for synthetic spike-ins, additional experimental biomass measurements, or training data. The approach assumes that the contribution of host DNA to stool is more constant or stable than biologically relevant fluctuations in bacterial biomass. We find that host read normalization is an effective method for detecting variation in gut bacterial biomass. Absolute bacterial biomass is a key metric that often gets left out of gut microbiome studies, and empowering researchers to include this measure more broadly in their metagenomic analyses should serve to improve our understanding of host-microbiota interactions
Infectious Dermatological Conditions Among Refugee and Immigrant Populations: A Systematic Review.
No full textRefugees, migrants, asylum seekers, and internally displaced persons face significant barriers to healthcare access, particularly dermatologic services. Infectious skin diseases are especially prevalent in these populations due to multiple intersecting risk factors. This systematic review aimed to identify common infectious dermatologic conditions among these populations, their associated risk factors, and implications for clinical and public health management. A comprehensive literature search was conducted across multiple databases through September 2024, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were eligible if they reported on infectious skin diseases in refugee and migrant populations. Two independent reviewers screened articles, with discrepancies resolved by a third reviewer. Across 63 studies including 5210 individuals, 3647 (70.0%) were diagnosed with infectious skin conditions. Among the 2772 cases specifying disease type, the most common were fungal infections (1084; 39.1%), leprosy (719; 25.9%), and leishmaniasis (397; 14.3%). Other diagnoses included viral skin infections (171; 6.2%), scabies (165; 6.0%), parasitic infections (126; 4.5%), bacterial infections (106; 3.8%), and tuberculid eruptions (4; 0.1%). The study populations represented migrants from 73 countries who relocated to 23 different host nations. Key risk factors included migration from endemic regions, overcrowded living conditions, and poor hygiene. These findings underscore the disproportionate burden of infectious skin disease in displaced populations and the need for targeted screening, culturally appropriate education, and improved access to dermatologic care. Addressing modifiable risk factors is essential to improving outcomes in these vulnerable groups