Biomedical subjects

Haitao Wang

Publications and source records attributed to Haitao Wang.

3 recordsLinked to original sources

PubMed2026

Therapeutic-drug-monitoring-based ATG Targeted Dosing Strategy in Unmanipulated Haploidentical Haematopoietic Stem Cell Transplantation: a randomized, multicenter, phase 3 clinical trial.

Anti-thymocyte globulin (ATG) has been a standard prophylaxis for graft-versus-host disease (GVHD). However, the pharmacokinetics of ATG in vivo vary significantly, and weight-based fixed dosing may not optimize efficacy while minimizing toxicity. We investigated the clinical results of a therapeutic-drug-monitoring (TDM)-based, dose-optimized ATG strategy versus weight-based fixed dosing in haploidentical haematopoietic stem cell transplantation (NCT05166967). Patients were randomly assigned in a 1:1 ratio to receive a targeted dose of ATG or a fixed dose of 10 mg/kg. The primary endpoint was the 365-day graft-versus-host disease-free and relapse-free survival (GRFS). From January 1, 2022, to January 16, 2024, 204 patients were enrolled, with 102 patients in each group. The 365-day GRFS was higher in the targeted dose group (66.7%) than in the fixed dose group (50.0%; hazard ratio [HR], 0.666; 95% confidence interval [CI], 0.4456 to 0.9954; P = 0.048). The cumulative incidence of moderate to severe chronic GVHD at day 365 was significantly lower in the targeted dose group (9.8%; 95% CI, 5.0 to 16.5) compared with the fixed dose group (22.5%; 95% CI, 15.0 to 31.1; P = 0.026). Fewer grade 3-5 infections were reported in the targeted dose group (44.1%) than in the fixed dose group (70.6%; P < 0.001). More patients in the targeted dose group achieved optimal ATG exposure (P = 0.007) and superior CD4+ T-cell reconstitution (P = 0.002). These findings support the clinical utility of a TDM-based individualized ATG dosing strategy that balances efficacy and toxicity for GVHD prophylaxis in allogeneic stem cell transplantation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05166967.

Humans↗

PubMed2026

EGFR-Mutant Non-Small Cell Lung Cancer With Small Cell Transformation: Clinicopathological Features, Treatment Landscape, and Biomarker Profiles.

INTRODUCTION: Transformed small-cell lung cancer (tSCLC) is a clinically important resistance mechanism to EGFR tyrosine kinase inhibitors in EGFR-mutant non-small cell lung cancer. This study characterizes clinical features, treatment outcomes, and biomarker profiles in patients with tSCLC. METHODS: Data from 45 patients with EGFR-mutant NSCLC who developed tSCLC between 2014 and 2023 were analyzed. Demographic characteristics, treatment histories, and delta-like ligand 3 (DLL3) and B7-H3 expression were collected. Objective response rate, progression-free survival (PFS), and posttransformation survival (PTS) were assessed. Spatial transcriptomic profiling was performed in selected cases. RESULTS: Most patients were women (60%) and never-smokers (75.6%). Exon 19 deletion was the predominant EGFR mutation (57.8%). Median PFS and PTS were 3.3 and 9.2 months, respectively. Etoposide plus platinum (EP) was the predominant first-line regimen (69.8%), with 23.2% of the patients receiving EP plus immune checkpoint or tyrosine kinase inhibitors. EP-based combination regimens yielded a numerically higher objective response rate and a significantly longer PFS than EP alone (7.5 versus 2.8 months, p = 0.002). PTS was longer with EP-based regimens than with other regimens (10.4 versus 6.4 months, p = 0.035). DLL3 and B7-H3 were expressed in 87.5% and 66.7% of tumors, respectively, without prognostic significance. Multivariable analysis identified brain metastasis and liver progression at transformation as adverse prognostic factors. Spatial transcriptomic analysis revealed neuroendocrine lineage reprogramming, stromal depletion, and immune exclusion. CONCLUSIONS: tSCLC remains an aggressive resistance phenotype with poor outcomes. EP-based combination strategies may provide clinical benefit, whereas frequent DLL3 expression supports further evaluation of targeted therapies.

Delta-like ligand 3↗

PubMed2025

Noninvasive detection and differentiation of gastric malignancy using cell-free DNA biomarkers.

INTRODUCTION: Gastric cancer remains a major global health burden, with high mortality driven by late-stage diagnoses that limit treatment options and reduce survival. Current diagnostic methods such as endoscopy and biopsy are invasive, resource-intensive, and impractical for large-scale early detection. OBJECTIVES: This study aimed to develop and validate an ensemble machine learning model integrating four cell-free DNA (cfDNA) fragmentomic feature classes derived from 5 × whole genome sequencing (WGS) data to non-invasively differentiate malignant gastric cancer from benign gastric lesions in high-risk or symptomatic patients. METHODS: A total of 681 plasma samples were prospectively collected, comprising 329 from patients with gastric cancer or high-grade intraepithelial neoplasia (HGIN) and 352 from individuals with benign gastric conditions. The dataset was divided into a training cohort (n = 333) and a temporally independent validation cohort (n = 348). An external validation cohort of 305 participants was also included. RESULTS: The ensemble model achieved an AUROC of 0.920 in cross-validation testing on the training cohort, 0.912 in the independent validation cohort, and 0.896 (95% CI 0.860-0.932) in the external cohort. At a pre-specified prediction threshold of 0.402, the model demonstrated 93.3% sensitivity and 71.9% specificity in the validation cohort, yielding a PPV of 71.3% and an NPV of 93.5%. In the external cohort, sensitivity and specificity were 91.7% and 69.1%, respectively (PPV 75.7%, NPV 88.8%). Model scores correlated with clinical stage, tumor grade, and histopathological subtype. Approximately 71% of non-cancer patients could have been spared unnecessary endoscopy. CONCLUSIONS: The cfDNA fragmentomics-based ensemble model enables accurate, non-invasive differentiation between gastric cancer and benign gastric lesions in high-risk or symptomatic patients. This approach demonstrates strong potential as a pre-endoscopy triage tool, supporting earlier detection and more efficient use of diagnostic resources.

Humans↗