J Proteome Res. 2025 Aug 2. doi: 10.1021/acs.jproteome.5c00385. Online ahead of print.

ABSTRACT

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors have transformed lung adenocarcinoma (LUAD) treatment in EGFR-mutant (MT) patients, but strategies targeting wild-type (WT) EGFR tumors remain necessary. This study analyzed a diverse LUAD patient cohort with EGFR mutation statuses and wild-type profiles for ALK and KRAS to identify stage-specific biomarkers. Using quantitative proteomics and multiomics, we discovered 21 dysregulated proteins in early-stage EGFR-WT LUAD, identifying myeloid-derived growth factor (MYDGF) as a key candidate biomarker. Elevated MYDGF levels in tissue (n = 117) and serum (n = 196) correlated significantly with cancer stage in EGFR-WT patients but not EGFR-MT cases. Notably, a higher tumor-to-normal MYDGF ratio predicted a favorable prognosis in early-stage EGFR-WT LUAD. Functional studies demonstrated that MYDGF exerts distinct roles in cell viability and migration depending on its cellular localization and the invasive potential of cancer cells. Specifically, secreted MYDGF promoted a protumorigenic phenotype, whereas excess intracellular MYDGF appeared to suppress the oncogenic capacity of aggressive cancer cells. MYDGF knockdown and subsequent proteomic analysis provided further insights into these context-dependent functions. These findings highlight EGFR status- and stage-specific proteomic profiles in LUAD, emphasizing the importance of context-dependent biomarker assessment for personalized treatment strategies.

PMID:40752010 | DOI:10.1021/acs.jproteome.5c00385

Respir Res. 2025 Mar 26;26(1):115. doi: 10.1186/s12931-025-03185-x.

ABSTRACT

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of global mortality, with acute exacerbations of COPD (AECOPD) significantly increasing the disease's morbidity and mortality. Among the pathogens implicated in AECOPD, Pseudomonas aeruginosa (P. aeruginosa) is increasingly recognized as a major co-infecting bacterium. Despite its clinical importance, the molecular mechanisms and therapeutic targets underlying AECOPD with P. aeruginosa infection remain inadequately understood.

METHODS: We employed a multi-omics approach, integrating proteomic analyses of bronchoalveolar lavage fluid (BALF) and plasma with transcriptomic analysis of peripheral blood. A discovery cohort of 40 AECOPD with P. aeruginosa infection patients and 20 healthy controls was analyzed, followed by validation in an independent cohort of 20 patients and 10 controls. Differentially expressed proteins (DEPs) and genes (DEGs) were identified and subjected to protein-protein interaction (PPI) network analysis, weighted gene co-expression network analysis (WGCNA), and immune infiltration analysis. Molecular docking simulations were conducted to explore potential therapeutic agents.

RESULTS: Our integrative analysis identified key biomarkers, which played critical roles in oxidative stress and neutrophil extracellular trap (NET) formation, both of which were pivotal in the pathogenesis of AECOPD with P. aeruginosa infection. The combined analysis of BALF, plasma, and peripheral blood underscored the interplay between local lung changes and systemic immune responses. Functional enrichment analyses highlighted significant pathways related to bacterial defense, inflammation, and immune activation. Validation in an independent cohort confirmed the diagnostic value of three key proteins (AZU1, MPO, and RETN), with high area under the curve (AUC) values in ROC analyses. Molecular docking indicated strong binding affinities of these proteins with Pioglitazone and Rosiglitazone, suggesting potential therapeutic utility.

CONCLUSIONS: This study provides a comprehensive understanding of the molecular mechanisms underlying AECOPD with P. aeruginosa infection, highlighting the pivotal roles of oxidative stress and NET formation in disease progression. The identified biomarkers offer promising diagnostic and therapeutic targets. Our findings pave the way for novel strategies to improve outcomes for AECOPD patients with P. aeruginosa infection. While the study design limits our ability to establish causality, these results provide important insights that warrant further investigation, particularly through longitudinal studies, to confirm the specific contributions of P. aeruginosa in exacerbations.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40140846 | PMC:PMC11948814 | DOI:10.1186/s12931-025-03185-x

Front Immunol. 2025 Feb 17;16:1510503. doi: 10.3389/fimmu.2025.1510503. eCollection 2025.

ABSTRACT

BACKGROUND: UBA1 and UBA6 are classic ubiquitin-activating E1 enzymes, which participate in the ubiquitination degradation of intracellular proteins and are closely related to the occurrence and development of various diseases and tumors. However, at present, comprehensive analysis has not been used to study the role of UBA family in cancers.

METHODS: We extracted the relevant data of cancer patients from the TCGA database and studied the relationship between the expression patterns of UBA family and the survival rate, and stage of patients in pan-cancer, especially breast cancer (BRCA), colorectal cancer (COAD), renal cancer (KIRC) and lung adenocarcinoma (LUAD). In addition, we also evaluated their impact on immune infiltration using TISIDB database and R packages.

RESULTS: UBA1 and UBA6 are highly expressed in most cancer types, which may be associated with poor prognosis of patients. This study also investigated their expression had a closely tie with clinical stages in some specific tumors. Furthermore, this study also demonstrated that these genes were closely related to immune score, immune subtypes and tumor infiltrating immune cells.

CONCLUSIONS: Our study demonstrated that the differential expression of the UBA family, along with their associated survival landscape and immune infiltration across various cancer types, holds potential as biomarkers linked to cancer immune infiltration. This finding offers a novel perspective for informing the direction of cancer treatment strategies.

PMID:40046044 | PMC:PMC11880792 | DOI:10.3389/fimmu.2025.1510503

Nat Comput Sci. 2025 Feb 7. doi: 10.1038/s43588-024-00764-8. Online ahead of print.

ABSTRACT

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally scalable analytical pipeline for functionally informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits in 61,838 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered and replicated new associations with lipid traits missed by single-trait analysis.

PMID:39920506 | DOI:10.1038/s43588-024-00764-8