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Xiaobin Zheng

Publications and source records attributed to Xiaobin Zheng.

2 recordsLinked to original sources

Deconvolution of evolutionary architecture unmasks a high-risk, subclonal-rich subtype in treatment-naive small cell lung cancer.

BACKGROUND: Intratumoral heterogeneity (ITH) drives therapeutic resistance in small cell lung cancer (SCLC). However, conventional single-sample analysis has limited horizontal, cross-patient comparisons, leaving the overarching evolutionary architecture in treatment-naive tumors poorly understood. This study aims to deconvolve these architectures to identify clinically relevant evolutionary subtypes. METHODS: We analyzed whole-exome sequencing data from 41 treatment-naive SCLC patients. To overcome the cross-patient comparability bottleneck, we developed a novel probabilistic framework using a refined Gaussian Mixture Model (GMM). This standardized subclonal structures into four hierarchical strata, enabling the identification of evolutionary subtypes via unsupervised clustering. To address the scarcity of SCLC public data, prognostic concordance was robustly explored in The Cancer Genome Atlas (TCGA) lung squamous cell carcinoma (LUSC) based on shared smoking etiology, with lung adenocarcinoma (LUAD) serving as a negative control. RESULTS: The cohort robustly segregated into "Clonal-dominant" (Group 1, n=28) and "Subclonal-rich" (Group 2, n=13) subtypes. Group 1 evolution was primarily driven by tobacco signatures (SBS4). Conversely, Group 2 exhibited late-stage acquisition of a DNA mismatch repair deficiency (MMRd) signature (SBS15), fueling trace subclonal diversification. Clinically, Group 2 demonstrated a significantly lower objective response rate (ORR) to platinum-based regimens (25.0% vs. 81.3%, P=0.02). Furthermore, the Subclonal-rich architecture independently predicted inferior overall survival (OS) [adjusted hazard ratio (adj. HR) =2.93, P=0.02], driven predominantly by limited-stage disease. Cross-cancer analysis validated this histology-dependent, high-heterogeneity adverse pattern in early-stage LUSC but not in LUAD. CONCLUSIONS: This hypothesis-generating study demonstrates that a "Subclonal-rich" architecture, driven by acquired MMRd, identifies high-risk, chemo-resistant SCLC. Our GMM approach suggests that pre-existing heterogeneity may serve as a potential, histology-dependent prognostic marker that warrants prospective validation for tailoring future therapeutic regimens.

Gaussian Mixture Model (GMM)

Coordinated regulation of glutathione S-transferases confers metabolic flexibility in multi-insecticide-resistant Frankliniella occidentalis (Pergande).

INTRODUCTION: The evolution of multi-insecticide resistance in insect pests threatens global food security. Although glutathione S-transferases (GSTs) are implicated in detoxification, the coordinated mechanism by which specific gene subfamilies interact to confer broad-spectrum resistance remains inadequately characterized. OBJECTIVE: To dissect the functional allocation and cooperation of GST subfamilies in multi-insecticide-resistant strains of Frankliniella occidentalis. METHODS: We integrated comparative genomics (20 GST genes cloned), transcriptomics (qRT-PCR), RNAi-mediated silencing, molecular docking (AutoDock Vina), and in vitro metabolism assays (UPLC-MS/MS) across susceptible and resistant thrips strains. RESULTS: The two resistant strains (NIL-R and FS-R) exhibited moderate to high resistance to five insecticides (chlorfenapyr, emamectin benzoate, spinetoram, spinosad, and thiamethoxam), accompanied by significantly elevated GSTs activity. Phylogenetic analysis indicates that GSTs include 10 conserved delta and 7 diverse sigma members. The sigma subfamily has undergone a marked expansion due to gene duplication. Delta (FoGSTd1, d4, and d9) and sigma (FoGSTs1, s2, and s6) genes were significantly up-regulated in the resistant strains. RNAi showed specialized functional allocation among GSTs: delta GSTs mediated resistance to spinosad and chlorfenapyr, sigma GSTs were responsible for thiamethoxam resistance, and notably, cooperation between these subfamilies contributed to resistance against emamectin benzoate and spinetoram. Molecular docking and in vitro metabolism assays of FoGSTd9 and FoGSTs1 proteins further supported the functional allocation and cooperative roles of GST subfamilies. CONCLUSION: Our results indicate that F. occidentalis may coordinate GST subfamilies to achieve metabolic flexibility in response to multi-insecticide pressure. This survival strategy, mediated by mechanistic functional allocation and cooperative interactions among subfamilies, may contribute to energy conservation and reduced adaptive costs. Disruption of this coordinated mechanism represents a potential approach for overcoming resistance in agricultural pest populations.

Animals