Biomedical subjects

Hui Zhao

Publications and source records attributed to Hui Zhao.

5 recordsLinked to original sources

PubMed2026

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2↗

PubMed2026

A Biomimetic Dual-Targeting Nano-APA-Editor Reprograms the 3'UTR Landscape for Tongue Squamous Cell Carcinoma Therapy.

Targeting post-transcriptional dysregulation of tumor suppressors represents a new frontier in cancer therapy. Here, we identify the alternative polyadenylation (APA) regulator NUDT21 as a pivotal therapeutic target in oral squamous cell carcinoma (OSCC). NUDT21 is highly upregulated, correlating strongly with poor survival and advanced clinical stage. We outline a pathogenic mechanism whereby NUDT21 drives this phenotype by forcing a network of tumor suppressor transcripts, notably PTEN, into translationally-repressed, long-3'UTR isoforms. To therapeutically "re-engineer" this APA switch, we design a "Nano-APA-editor." This platform features an HMSN core with an sgRNA-NUDT21 payload and a hierarchical targeting strategy: a cancer-educated dendritic cell (DC) membrane for biomimetic camouflage and homotypic affinity, "gated" by a TA-aptamer for final precision. This system enables potent and selective NUDT21 silencing, driving a shift toward short-3'UTR isoforms. Consequently, the Nano-APA-editor effectively reinstates PTEN and associated suppressors and inhibits multiple malignant phenotypes in vitro. In an orthotopic OSCC model, it demonstrates profound tumor regression, outperforming conventional chemotherapy (PTX) with excellent biocompatibility. In vivo analysis confirmed target engagement (NUDT21-down) and functional restoration (PTEN-, WEE1-, TGF-β-up). This work validates a "post-transcriptional re-engineering" strategy, executed by a logically designed nanoplatform, as a powerful and safe modality for precision gene therapy.

Humans↗

PubMed2026

Ivonescimab plus chemotherapy versus placebo plus chemotherapy in patients with advanced EGFR-mutated non-small-cell lung cancer after disease progression on EGFR tyrosine kinase inhibitor therapy (HARMONi): a multicentre, randomised, double-blind, phase 3 trial.

BACKGROUND: Ivonescimab has shown clinical efficacy in non-small-cell lung cancer (NSCLC). We aimed to assess the efficacy and safety of ivonescimab plus chemotherapy versus placebo plus chemotherapy in patients with advanced EGFR-mutated NSCLC whose disease progressed after third-generation EGFR tyrosine kinase inhibitor (TKI) therapy. METHODS: HARMONi is a randomised, placebo-controlled, double-blind, phase 3 trial done at 114 cancer centres and hospitals across Asia, Europe, and North America. Eligible patients were aged at least 18 years (upper limit: 75 years in Asia) with stage IIIB/IIIC or IV non-squamous EGFR-mutated NSCLC, disease progression after treatment with a third-generation EGFR-TKI, and an Eastern Cooperative Oncology Group performance status score of 0 or 1. Patients were randomly assigned (1:1) via a centralised interactive voice response system or interactive web response system to receive ivonescimab (20 mg/kg) or placebo plus pemetrexed (500 mg/m2) and carboplatin (target area under the curve 5 mg/mL per min) intravenously every 3 weeks. Randomisation was stratified by brain metastases status at enrolment and geographical region. The primary endpoints were progression-free survival by blinded independent radiology review committee and overall survival in the intention-to-treat population. Safety was assessed in patients who received at least one dose of trial treatment. This study is registered with ClinicalTrials.gov (NCT06396065), has completed enrolment, and is ongoing for treatment and follow-up. FINDINGS: From Jan 25, 2022, to Oct 1, 2024, 660 individuals were screened for eligibility; of these, 438 were enrolled and randomly assigned to receive ivonescimab plus chemotherapy or placebo plus chemotherapy (219 per group). Of enrolled patients, 257 (59%) were female and 181 (41%) were male; 306 (70%) reported race as Asian, and 105 (24%) as White. At a median follow-up of 22·3 months (95% CI 21·5-23·0), 275 progression or death events had occurred in 345 patients (129 events among 172 patients in the ivonescimab plus chemotherapy group and 146 events among 173 patients in the placebo plus chemotherapy group). Median progression-free survival was 6·8 months (95% CI 5·7-7·1) in the ivonescimab plus chemotherapy group versus 4·4 months (4·1-5·5) in the placebo plus chemotherapy group (hazard ratio [HR] 0·52; 95% CI 0·41-0·66; p<0·0001). At a median follow-up of 29·7 months (95% CI 27·7-31·0), 262 deaths occurred in 438 patients (122 in the ivonescimab plus chemotherapy group and 140 in the placebo plus chemotherapy group). Median overall survival was 16·8 months (14·3-19·0) in the ivonescimab plus chemotherapy group versus 14·0 months (12·8-15·7) in the placebo plus chemotherapy group (HR 0·79; 0·62-1·01). The most common grade 3-4 treatment-related adverse events in the ivonescimab plus chemotherapy versus the placebo plus chemotherapy group were decreased neutrophil count (42 [19%] of 218 vs 36 [17%] of 218), decreased white blood cell count (28 [13%] vs 24 [11%]), decreased platelet count (27 [12%] vs 14 [6%]), and anaemia (22 [10%] vs 27 [12%]). Serious treatment-related adverse events occurred in 61 (28%) patients in the ivonescimab plus chemotherapy group and 33 (15%) patients in the placebo plus chemotherapy group. Treatment-related adverse events led to death in four patients (disease progression, multiple organ dysfunction syndrome, and hepatic failure, each in one patient; gastrointestinal haemorrhage and pulmonary embolism in one patient) in the ivonescimab plus chemotherapy group and five patients (pneumonitis, myocardial infarction, cerebrovascular accident, cognitive disorder, and embolic stroke, each in one patient) in the placebo plus chemotherapy group. INTERPRETATION: Ivonescimab plus chemotherapy showed a clinically meaningful and statistically significant progression-free survival benefit in patients with EGFR-mutated NSCLC after progression on EGFR-TKI therapy. The clinical benefit and lack of new safety signals of ivonescimab with chemotherapy support the potential for the combination as a new treatment option in this patient population. FUNDING: Summit Therapeutics.

Humans↗

PubMed2025

Long COVID in Elderly COPD Patients: Clinical Features, Pulmonary Function Decline, and Proteomic Insights.

BACKGROUND: Elderly patients with chronic obstructive pulmonary disease (COPD) face a heightened risk of developing long coronavirus disease (COVID); however the exact clinical characteristics and underlying mechanisms remain unclear. METHODS: We enrolled 85 elderly COPD patients, of whom 43 reported newly onset persistent fatigue (the most dominant complaint of long COVID) within 1 year after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and they were allocated to the Long-COVID group. The remaining 42 patients were assigned to the Control group. Patients completed questionnaires, pulmonary function tests, chest CT, routine laboratory tests, and blood proteomic analysis. RESULTS: Long-COVID patients had a longer course of COPD (> 5 years, 76.8% vs 52.4%) and duration of SARS-CoV-2 infection (10.0 days vs 7.0 days) (All P < 0.05), higher symptom burden, worse pulmonary ventilation function and a more rapid decrease in DLCO (All P < 0.05). Proteomic analysis indicated disruptions in inflammation and energy metabolism, potentially underlying long COVID in these patients. The machine learning model identified wheezing, the duration of SARS-CoV-2 infection, EIF2S3 (eukaryotic translation initiation factor 2 subunit gamma), current FEV1/FVC (%), and the course of COPD as key features distinguishing Long-COVID patients, and exhibited excellent performance. CONCLUSION: Elderly COPD patients with a longer COPD course and duration of COVID-19 are more prone to develop long COVID, with decreased pulmonary ventilation and diffusion ability. Disordered inflammation regulation and energy metabolism may be the potential mechanisms, highlighting the importance of monitoring inflammation and metabolic dysregulation in elderly COPD patients after recovery from COVID-19.

Humans↗

PubMed2024

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

Proteomics↗