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Biomedical subjects

Nana Zhang

Publications and source records attributed to Nana Zhang.

2 recordsLinked to original sources

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer

[State Changes and Stability Grading of Driver Genes in Non-small Cell Lung Cancer Based on Repeated NGS Testing].

BACKGROUND: Next-generation sequencing (NGS)-based driver gene testing has become a routine component of molecular subtyping and precision therapy for non-small cell lung cancer (NSCLC). Dynamic genomic monitoring facilitates early detection of resistance-related molecular alterations and informs timely therapeutic adjustments. However, standardized criteria for evaluating the stability of serial NGS testing are currently lacking, and the applicability of NGS using formalin-fixed paraffin-embedded (FFPE) specimens for dynamic monitoring remains poorly defined. This study aims to establish a stability grading system for driver gene status alterations based on repeated NGS testing, and to provide evidence-based support for clinical repeat biopsy strategies. METHODS: Data from 1232 patients with NSCLC who underwent two or more NGS tests on FFPE tissue specimens at Beijing Chest Hospital between June 2019 and April 2026 were collected retrospectively. Patients with an interval of &#x2265;4 months between the initial and last tests were included to ensure the representativeness of temporal analysis, resulting in a main analysis cohort of 942 patients. The Kappa consistency test was used to evaluate the state stability of nine core driver genes [epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homolog (KRAS), anaplastic lymphoma kinase (ALK), ROS proto-oncogene 1, receptor tyrosine kinase (ROS1), mesenchymal&#x2011;epithelial transition factor (MET), rearranged during transfection (RET), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), erb&#x2011;b2 receptor tyrosine kinase 2 (ERBB2), and phosphatidylinositol&#x2011;4,5&#x2011;bisphosphate 3&#x2011;kinase catalytic subunit alpha (PIK3CA)] and to construct a five&#x2011;level grading system. Paired variant allele frequency (VAF) differences were compared using the Wilcoxon signed&#x2011;rank test. Independent influencing factors for mutation accumulation were identified by binary Logistic regression. RESULTS: The state stability of the nine genes was classified into five levels: EGFR showed high stability (Kappa=0.838), ROS1/ALK/KRAS good stability, BRAF/PIK3CA/RET moderate stability, and ERBB2 low stability, and MET showed high instability. MET exhibited the highest rate of state change (9.3%) with a raw observed agreement of 90.7%. Its Kappa value (0.172) was influenced by the low prevalence (3.7%) compression effect and should therefore be interpreted alongside the observed agreement (90.7%) and the prevalence-adjusted and bias-adjusted Kappa (PABAK). The VAF of PIK3CA increased significantly (P=0.005). T790M positivity increased from 5.8% to 10.8%, and 30 new C797S mutations were detected at the last test (13 with T790M, 17 without). The overall rate of new driver gene variants in the main cohort was 18.0%. Binary Logistic regression showed that a lower number of initial mutated genes was the only independent predictor of new variants [odds ratio (OR)=0.399, P<0.001], while sex and detection interval showed no independent association. CONCLUSIONS: A five level stability grading system for state changes of driver genes in NSCLC based on repeated NGS testing has been established. MET showed the most frequent state changes, which should be interpreted in conjunction with the prevalence effect. The VAF increase of PIK3CA is an observational finding, and its clinical significance requires further prospective validation. A lower initial mutation burden may reflect tumor clonal complexity and was associated with a higher likelihood of subsequent acquisition of new variants. FFPE based NGS is applicable for repeated testing at clinical treatment decision nodes.

Humans