Biomedical subjects

Zhihong Zhang

Publications and source records attributed to Zhihong Zhang.

3 recordsLinked to original sources

PubMed2026

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and potential therapeutic targets. Multi-source transcriptomic datasets (TCGA-COAD, GSE39582, GSE17536) and single-cell RNA-seq data were analyzed. Ten machine learning algorithms were integrated to construct an acRG-based prognostic signature (acRGBS). Immune microenvironment (TME) and genomic profiling were performed, with in vitro functional experiments validating TUBA1C's role. acRGBS, comprising four hub genes (SARAF, CDC42SE2, TSPYL2, TUBA1C), effectively stratified COAD patients into high- and low-risk groups with distinct survival outcomes and was an independent prognostic factor. High-risk patients exhibited increased genomic instability and immunosuppressive TME, while low-risk patients had favorable immunotherapy response. TUBA1C was overexpressed in COAD cells, and its knockdown inhibited proliferation/migration and induced apoptosis. The acRGBS is a robust prognostic tool for COAD, and TUBA1C serves as a candidate therapeutic target, providing new insights for personalized COAD management.

Humans↗

PubMed2026

Chinese expert consensus on precision testing and molecular diagnosis of pancreatic cancer (2025).

This consensus by the CSCO Pancreatic Cancer Expert Committee establishes evidence-based guidelines for molecular testing in pancreatic ductal adenocarcinoma. It details recommendations for biomarkers (e.g., KRAS, BRCA, MSI), liquid biopsy, and precision imaging to direct targeted therapies and immunotherapy, aiming to standardize diagnosis and optimize individualized patient care. Pancreatic ductal adenocarcinoma (PDAC) is the most common pathological type of primary pancreatic malignancy, accounting for ~95% of cases and generally referred to as pancreatic cancer [1]. Its prognosis is extremely poor and its incidence continues to rise [2]. According to the most recent global cancer statistics, the incidence of pancreatic cancer ranks 12th among all cancers, and its mortality ranks 6th, making it one of the deadliest malignancies worldwide [3]. Approximately 57% of patients have metastatic disease at diagnosis and require systemic therapy, for which chemotherapy remains the standard first-line option [1]. However, the overall response rate to currently available systemic regimens is low, and the 5-year survival rate for patients with metastatic disease remains below 5% [3]. Although most pancreatic cancers harbor canonical driver mutations, they exhibit marked heterogeneity at the molecular level. Whole-genome sequencing (WGS) and integrative genomic analyses have identified molecular subtypes of PDAC with potential clinical relevance [4-9]. With the increasing implementation of precision oncology, the Chinese Society of Clinical Oncology (CSCO) Guidelines for the Diagnosis and Treatment of Pancreatic Cancer give a level 1 recommendation to perform genetic and other molecular testing on tissue or cytologic specimens as part of the pathological diagnostic work-up, in order to guide individualized treatment, including targeted therapy and immunotherapy [10]. To further promote the use of genetic and molecular testing in the precision treatment of pancreatic cancer, the CSCO Pancreatic Cancer Expert Committee convened a multidisciplinary panel to develop the present Chinese Expert Consensus on Precision Testing and Molecular Diagnosis of Pancreatic Cancer (2025), aiming to provide clinicians with an authoritative reference for precision diagnostics and treatment decision-making.

Humans↗

PubMed2021

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

Circulating Tumor DNA↗