Yueguo Li

Malnutrition is a common complication of cirrhosis and is associated with adverse outcomes. However, current nutritional risk assessment tools may not fully incorporate objective laboratory biomarkers. This study aimed to develop a biomarker-based prediction model for nutritional risk assessment in patients with cirrhosis. We retrospectively collected the clinical data of 551 patients with liver cirrhosis from two centers between April 2023 and April 2026. The Royal Free Hospital–Nutritional Prioritizing Tool (RFH-NPT) classification was used as the reference standard for nutritional risk categorization. Candidate predictors were selected using univariate logistic regression and feature selection methods. Model performance was evaluated by discrimination, calibration, and clinical utility. Model interpretability was evaluated using SHapley Additive exPlanations (SHAP). The added predictive value of the predictors was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Hepatic decompensation was assessed using survival analysis. The laboratory-based approach incorporating growth differentiation factor 15 (GDF15), carbohydrate antigen 19 − 9 (CA19-9), gamma-glutamyl transferase (GGT), Child–Turcotte–Pugh (CTP) score, estimated glomerular filtration rate (eGFR), and triglyceride–glucose (TyG) index demonstrated satisfactory discrimination for nutritional risk stratification in cirrhosis (area under the receiver operating characteristic curve [AUROC] = 0.857). Calibration showed acceptable agreement, and decision curve analysis (DCA) suggested potential clinical utility. GDF15 demonstrated the strongest association with nutritional risk. Its addition improved discrimination (AUROC: 0.850 to 0.862; NRI = 0.2273, IDI = 0.0236; P < 0.05). Higher GDF15 levels were associated with increased risk of hepatic decompensation (hazard ratio [HR] = 2.4). We developed and externally validated a laboratory-based approach for nutritional risk assessment in patients with cirrhosis. This approach integrates routinely available laboratory indicators with clinical parameters and may serve as a complementary approach to support nutritional risk stratification in clinical settings.

Background: Digestive malignancies remain a major cause of cancer-related mortality worldwide. Current diagnostic approaches are often limited by invasiveness, cost, and accessibility. We aimed to develop a blood-based risk stratification model for identifying individuals at increased risk of digestive malignancies. Methods: We retrospectively collected clinical data from 667 patients with digestive malignancies and 795 non-cancer controls. A machine learning model was developed by integrating GDF15 with selected routine blood biomarkers. Model performance was evaluated using measures of discrimination, risk reclassification, and SHAP analysis. Blood GDF15 levels were measured by chemiluminescent immunoassay, and tissue expression was assessed by immunohistochemistry. Results: The GDF15-based machine learning model showed favourable performance in the independent validation cohort (AUROC = 0.886). Compared with conventional tumor markers alone, the addition of GDF15 improved model discrimination (AUROC, 0.856 vs. 0.777; P < 0.001) and significantly enhanced risk reclassification (NRI = 0.858; IDI = 0.151). GDF15 also contributed to the identification of patients with negative conventional tumor markers and was among the most influential variables in the model according to SHAP analysis. Higher circulating GDF15 levels were associated with larger tumor size, shorter progression-free survival (HR = 2.68), and increased expression in tumor tissues. Conclusion: Integrating GDF15 with routine blood biomarkers enables effective risk stratification of individuals at increased risk of digestive malignancies. This blood-based model may provide a practical approach for risk stratification and help identify individuals who may benefit from further diagnostic evaluation.

Background: Non-small cell lung cancer (NSCLC) is one of the frequently occurring cancers characterized by molecular heterogeneity and multiple immune cell infiltration patterns, which are associated with treatment sensitivity and resistance. However, the specific microenvironmental cells and their mechanisms that lead to treatment resistance in patients need to be explored in greater depth. Methods: On the basis of patients receiving neoadjuvant therapy in our center, a multicenter, multicohort NSCLC spatial transcriptome, single-cell transcriptome, T-cell receptor repertoire sequencing, bulk RNA transcriptome, phosphorylated proteome, genome mutation, and clinical data were included for a comprehensive assessment of the therapeutic and prognostic impact of HIF1A ⁺ CSF3R ⁺ neutrophils in NSCLC. In vitro experiments validated the functional phenotype of HIF1A ⁺ CSF3R ⁺ neutrophils and co-localization interactions with other cellular subpopulations. Gradient boosting machine (GBM) constructed region of interest (ROI) models for evaluation. Computer-aided drug design (CADD) was used to predict targeted small molecule drugs, and in vivo mouse models were constructed to assess the effectiveness of the combination treatment regimen. Results: Centered on HIF1A ⁺ CSF3R ⁺ neutrophils, recruited exhausted T cells and stromal cells form a hypoxic niche within the tumor region, which was enriched in non-response patients. ROI composed of these specific cellular subpopulations, associated with senescence and glycolysis, accurately predicting NSCLC progression, prognosis, and microenvironment composition. CADD analysis identified that platycodin-D2 specifically targeted CSF3R, reducing HIF1A expression and inhibiting neutrophil activity. Combining navitoclax, platycodin-D2 with anti-programmed cell death protein 1 (PD-1) significantly suppressed tumor proliferation and improved the immunosuppressive microenvironment. Conclusion: Our study emphasized the role of HIF1A ⁺ CSF3R ⁺ neutrophils in immunotherapeutic resistance of NSCLC, constructed a microenvironmental immune dysregulation network in a hypoxic ecological niche with HIF1A ⁺ CSF3R ⁺ neutrophils as the center. Platycodin-D2 specifically targeted HIF1A ⁺ CSF3R ⁺ neutrophils, enhancing the efficacy of anti-PD-1 therapy in NSCLC.

Background and Purpose: Investigating the assessment of innovative serum indicators with elevated sensitivity and specificity is crucial for enhancing the early diagnosis and prognosis of HCC (Hepatocellular carcinoma). This study aimed to evaluate the efficacy of COPA (Coatomer Subunit Alpha) in diagnosing hepatocellular carcinoma and assessing the effectiveness of immunotherapy. Methods: This study included two cohorts: a diagnostic cohort comprising 81 healthy controls, 118 patients with benign liver diseases, and 81 patients with pathologically confirmed HCC, and an immunotherapy cohort comprising 131 HCC patients treated with PD-1/PD-L1 inhibitors. Serum COPA was measured by ELISA, while AFP and PIVKA-II were measured by electrochemiluminescence. Diagnostic performance and immunotherapy monitoring efficacy were then evaluated. Results: COPA is upregulated in serum and HCC tumor samples. The ROC analysis indicated that the diagnostic efficacy of COPA (AUC = 0.911) surpassed that of traditional biomarkers. Importantly, COPA retained favorable diagnostic performance in both AFP-negative and PIVKA-II-negative HCC patients. Dynamic monitoring revealed that when comparing PIVKAII and AFP with imaging-based efficacy assessments, serum COPA changes demonstrated superior consistency pre- and post-immunotherapy (Kappa of COPA = 0.73, P < 0.01). COPA expression was significantly elevated in HCC tissues compared with adjacent non-tumor tissues. Conclusion: This study established that COPA outperforms AFP and PIVKAII in diagnostic and immunotherapeutic monitoring reliability, offering a novel technique for the precise diagnosis and treatment of hepatocellular carcinoma.

Objective: Adaptive therapeutic tolerance frequently limits first-line lenvatinib efficacy in hepatocellular carcinoma (HCC). This study explored the C2H2-type zinc finger (ZNF) protein family (the largest class of transcription factors) and hypothesized that specific members of the ZNF protein family are hijacked by cancer cells to orchestrate pro-survival defenses against lenvatinib-induced ferroptosis. Methods: We implemented a hypothesis-driven integrative multi-omics strategy to identify clinically relevant ZNF drivers. The top candidate, ZNF768, was functionally investigated using lentiviral modulation in HCC cell lines and subcutaneous xenograft models. Mechanistic elucidation was performed through ChIP-qPCR, luciferase reporter assays, and upstream signaling pathway analysis. The therapeutic synergy of an AAV-shZNF768 vector combined with lenvatinib was evaluated in vivo. Results: ZNF768 was identified as a potent transcriptional driver of pro-survival programs in HCC; high expression correlated with poor patient prognosis. ZNF768 knockdown suppressed proliferation and robustly sensitized HCC cells to ferroptosis, which was marked by uncontrolled lipid peroxidation and GSH depletion. ZNF768 directly transactivated the SLC7A11 promoter, reinforcing the cellular antioxidant shield. We uncovered a paradoxical therapy-induced feedback loop in which lenvatinib inhibits AKT signaling, leading to EGR1 accumulation and transcriptional activation of ZNF768. This adaptive response limits the efficacy of lenvatinib. Consequently, disrupting this loop via ZNF768 knockdown synergizes with lenvatinib to trigger robust ferroptosis and profoundly suppress tumor growth in vivo. Conclusions: The EGR1-ZNF768-SLC7A11 axis constitutes a critical adaptive shield limiting lenvatinib efficacy in HCC. ZNF768 serves as a predictive biomarker and a high-value therapeutic target. Disrupting this axis offers a rational strategy to overcome therapeutic resistance and maximize the clinical potential of lenvatinib.

Clear cell renal cell carcinoma (ccRCC), with rising incidence globally, shows heterogeneous responses to immune checkpoint blockade (ICB). DNA methylation dysregulation impacts tumor immunity, necessitating predictive CpG methylation biomarkers for ICB efficacy. Genome-wide methylation profiling (TCGA/GEO) identified prognostic promoter CpG islands linked to CD8⁺ T cell infiltration. Single-CpG resolution analysis guided TaqMan probe design, validated in two independent cohorts: non-ICB (n = 335) for prognosis and ICB-treated (n = 45) for immunotherapy prediction. High-throughput methylation analysis identified hypermethylation at the FBLN2 promoter (chr3:13590414–13591008), which correlated with advanced tumor stage, higher grade, and poorer overall survival (OS) and progression-free survival (PFS). This locus exhibited significant associations with CD8⁺ T cell infiltration and IFNγ pathway activation. In the non-ICB cohort, validation using a 5-CpG TaqMan assay confirmed FBLN2 hypermethylation as an independent prognostic marker for both OS (HR = 3.45, P < 0.001) and PFS (HR = 2.43, P = 0.023). Subsequent IHC analysis of 74 tumor specimens demonstrated strong concordance between FBLN2 percent methylation ratio (PMR) and CD8⁺ T cell density (r = 0.62, P < 0.0001). In the anti-PD-1-treated cohort, high FBLN2 methylation was associated with a favorable immunotherapy response (Cohen’s weighted Kappa = 0.607, P < 0.001) and predicted superior PFS (median 11.2 vs 3.4 months, HR = 0.35, P = 0.006), suggesting its potential as a novel predictive biomarker for ICB efficacy. FBLN2 promoter hypermethylation is a promising prognostic biomarker in ccRCC and a potential predictor of immunotherapy response. These findings warrant further investigation to validate its potential for enhancing personalized patient management.

Background and Aims: Liver fibrosis involves the activation of HSCs and persistent inflammatory responses. Ccl9, a CC chemokine implicated in inflammation, has an undefined role in liver homeostasis. Our study investigates this murine homolog of human CCL15 to elucidate its role in the development of liver fibrosis. Approach and Results: We investigated the expression of Ccl9 and its upstream regulatory elements in liver fibrosis using mouse models induced by carbon tetrachloride (CCl ₄ ), bile–duct ligation, and a high-fat, methionine-deficient and choline-deficient diet. A significant increase in Ccl9 expression was observed in fibrotic liver tissues, predominantly in damaged hepatocytes, with Myc identified as a key driver of this upregulation. The role of Ccl9 was further elucidated through hepatocyte-specific knockout mice, neutralizing antibodies, and in vitro analyses of HSCs and macrophages. Targeted deletion of Ccl9 in hepatocytes mitigated liver fibrosis and injury across multiple models, characterized by reduced inflammation and decreased monocyte/macrophage and neutrophil infiltration. Additionally, neutralizing Ccl9 in CCl ₄ -induced models reduced both fibrosis and liver damage. Mechanistically, Ccl9 modulated macrophage infiltration, promoted M1 polarization, and regulated inflammatory cytokine responses through the Ccr1 receptor in models of hepatic injury induced by CCl ₄ and bile–duct ligation. Furthermore, Ccl9 directly activated HSCs by recruiting Myh9 via Ccr1, thereby enhancing the Wnt signaling pathway through Myh9-mediated Gsk3β ubiquitination. Conclusions: Ccl9 is a significant contributor to liver fibrosis, influencing macrophage behavior and directly activating HSCs. Targeting Ccl9 offers a potential therapeutic approach for treating liver fibrosis.

Glutaminase‐1 (GLS1) has garnered considerable interest as a metabolic target in cancer due to its heightened involvement and activity. However, the precise fate of glutaminolysis catalysed by GLS1 in cancer cells remains elusive. We found that GLS1 knockout led to significant suppression of cancer cell proliferation, which can be reversed or partially restored by supplementation of glutamate or non‐essential amino acids that can be converted into glutamate. The addition of spliceosomal KGA or GAC ameliorates cancer cell growth in vitro and in vivo, providing both simultaneously completely reverse the effect. The primary metabolic fate of glutamate produced through glutaminolysis in cancer cells is mainly used to produce glutathione (GSH) for redox homeostasis, not entering the tricarboxylic acid cycle or synthesising nucleotides. GSH monoethyl ester (GSH‐MEE) effectively rescues the inhibition of cancer cell proliferation caused by GLS1 knockout. Deletion of GLS1 results in an elevation of reactive oxygen species (ROS) and malondialdehyde (MDA), a reduction of NADPH/NADP ⁺ ratio, and an augmented susceptibility of cells to ferroptosis. Glutathione Peroxidase 4 (GPX4) and GPX1 exhibit complementary roles in redox regulation, with GLS1 knockout promoting GPX4 degradation. Pharmacological inhibition of GLS1 synergises with GPX4 inhibitor to suppress tumour growth. Dual targeting of GPX4 and GPX1 presents a potent anti‐cancer strategy. This metabolic mechanism facilitates a deeper comprehension of the abnormal glutamine metabolism in cancer cells, establishing a theoretical basis for the potential clinical utilisation of GLS1 inhibitors and presenting novel perspectives for advancing combinatorial therapeutic approaches.