Biomedical subjects

Yan Zhu

Publications and source records attributed to Yan Zhu.

4 recordsLinked to original sources

PubMed2026

Tumor-Infiltrating Clonal Hematopoiesis Is Associated with Adverse Clinical Outcomes in Diffuse Large B-cell Lymphoma.

UNLABELLED: Tumor-infiltrating clonal hematopoiesis (TI-CH) contributes to the progression of nonhematologic cancers. CH is prevalent in the peripheral blood of patients with diffuse large B-cell lymphoma (DLBCL), but TI-CH prevalence and clinical relevance remain largely unexplored. In this study, through genome- and exome-wide sequencing of DLBCL biopsies and blood samples from 304 treatment-naïve patients, we identified TI-CH in 13.5% of cases, which emerged as an independent risk indicator for disease progression and death. TI-CH cases had an enrichment of inflammatory myeloid signatures revealed by gene expression profiling of tumor biopsies. In addition, we developed a TI-CH-associated prognostic signature (CAPS) based on 24 differentially expressed genes. A high CAPS score correlated with poor survival across four patient cohorts and remained significant in three cohorts after adjustment for patient age, sex, International Prognostic Index score, and cell-of-origin classification. Collectively, these findings establish a link between TI-CH and clinical outcomes and implicate the inflammatory signature as the potential underlying basis. SIGNIFICANCE: TI-CH correlates with disease progression and death in patients and with the inflammatory modeling of the DLBCL tumor microenvironment. Our results underscore the clinical and biological relevance of TI-CH and suggest its potential as a biomarker for risk stratification and as a target for therapeutic intervention in DLBCL.

Humans↗

PubMed2026

Attribution of PM2.5-Induced Transcriptomic Perturbation to Toxic Components.

Ambient fine particulate matter (PM2.5) is a chemically complex mixture whose health impacts are not fully captured by particle mass. Here, we developed an interpretable chemotranscriptomic framework to attribute PM2.5-induced molecular perturbations to toxicity-relevant components. PM2.5 collected from urban roadside and coastal environments was separated into whole, extractable, and unextractable fractions, characterized by LC/GC × GC-HRMS-based nontarget analysis and inductively coupled plasma mass spectrometry (ICP-MS), and evaluated using cytotoxicity testing and transcriptomic profiling in human bronchial epithelial cells. Urban PM2.5 exhibited greater cytotoxic potency per unit mass than coastal PM2.5, with extractable fractions accounting for most cytotoxic and pathway-level responses. Transcriptomics revealed distinct site-specific modes of action: urban PM2.5 preferentially induced oxidative stress, xenobiotic metabolism, and cell cycle suppression, consistent with acute, nonapoptotic injury, whereas coastal PM2.5 elicited weaker cytotoxicity but stronger interferon-mediated immune and apoptosis-related signaling. Integrating chemical abundance with pathway activity using random forest regression, SHAP interpretation, and mechanistic corroboration reduced 5,033 detected features to 444 pathway-linked candidate drivers. Fewer than 5% of features explained ∼95% of cumulative model contribution. Standard-confirmed contributors included plasticizer-related compounds, aromatic and heteroaromatic combustion products, and copper for urban PM2.5 and secondary/aged organics and nickel for coastal PM2.5. These findings support mechanism-informed prioritization of hazardous PM2.5 components beyond mass-based assessment.

Particulate Matter↗

PubMed2025

Radiogenomic MRI biomarkers for noninvasive prediction of GPC3 expression and tumor microenvironment in hepatocellular carcinoma.

BACKGROUND: Glypican-3 (GPC3) is frequently overexpressed in hepatocellular carcinoma (HCC) and plays a key role in immune and metabolic remodeling of the tumor microenvironment. Reliable noninvasive biomarkers for predicting GPC3 status could improve patient stratification and support precision immunotherapy. METHODS: This multicenter retrospective study included 274 patients with pathologically confirmed hepatocellular carcinoma from three institutions, 34 external cases with MRI from The Cancer Imaging Archive, and 363 transcriptomic profiles from The Cancer Genome Atlas. Contrast-enhanced T1-weighted imaging and diffusion-weighted imaging were analyzed. Tumor and peritumoral regions were segmented manually and radiomic features extracted using PyRadiomics. Feature selection was performed with correlation filtering and least absolute shrinkage and selection operator regression. Machine learning classifiers including logistic regression, random forest, support vector machine, k-nearest neighbor, and decision tree were trained with 10-fold cross-validation and tested on independent external cohorts. A radiomics score was calculated for each patient. Radiogenomic analysis correlated radiomics scores with transcriptomic data using weighted gene co-expression network analysis. Hub genes and enriched pathways were identified, and immune infiltration and predicted immunotherapy response were assessed using computational methods. RESULTS: The random forest model using contrast-enhanced T1-weighted imaging achieved an area under the curve of 0.966 in training and 0.935 in internal validation. The integrated contrast-enhanced T1-weighted imaging plus diffusion-weighted imaging model reached an internal validation area under the curve of 0.979. In external testing, the best performance was obtained with a support vector machine model (area under the curve 0.756). Radiomics scores were significantly correlated with GPC3 expression (R = 0.78, p < 0.05). Transcriptomic analysis identified a 10-gene signature enriched in hypoxia and lipid metabolism pathways that stratified patients into prognostic subgroups (concordance index 0.720, hazard ratio 4.07, p < 0.0001). High-risk patients had greater immune infiltration and a lower predicted immune evasion score, suggesting a potential benefit from immunotherapy. CONCLUSIONS: MRI-based radiomics models can noninvasively predict GPC3 expression in hepatocellular carcinoma. Radiomics scores reflect underlying hypoxia and lipid metabolism pathways and stratify patients by prognosis and predicted immunotherapy response. These findings support radiogenomics as a translational approach to imaging-guided precision treatment in hepatocellular carcinoma.

Humans↗

PubMed2025

Population-Specific Immunogenomic Alterations in Gallbladder Cancer and Prognostic Significance.

Gallbladder carcinoma is a deadly disease with a poor prognosis, and recent clinical data suggest only a modest benefit of PD1/PDL1 inhibitors in this disease. Optimizing immunotherapeutic approaches will require a detailed understanding of the immunogenomic landscape of this disease worldwide. We combined targeted next-generation sequencing and immunohistochemistry to create detailed immunogenomic landscapes from 2 cohorts of gallbladder cancer cases from the United States (n = 60) and Chile (n = 62). Mutations in TP53, SMAD4, KRAS, PIK3CA, ARID2, ARID1A, ATM, FBXW7, ERBB2, and NF1 were found in both the US and Chilean primary cohorts, as well as amplifications in ERBB2, CCNE1, MDM2/CDK4, and CCND1. Despite similar mutation profiles, the immune profiles were distinct, with the Latin American cohort having higher densities of biomarkers associated with CD4+ T cells and PD-1 but lower densities of CD68+ macrophages compared with the North American cohort. Clustering and correlation analyses suggest novel immune subgroups and clinical associations independently of any specific mutations. Additionally, supported by multiplexed single-cell imaging technology, we identified low CD4 and high V-domain Ig suppressor of T cell activation as a candidate biomarker pair of poor outcomes. In summary, our findings highlight the importance of sensitivity to geographic location when considering therapeutic developments and pave a path for further immune investigations of this understudied disease.

Humans↗