Pancreatic adenocarcinoma (PAAD) has an extremely poor prognosis, and existing prognostic markers fail to fully capture the complex heterogeneity of the tumor microenvironment. This study aimed to integrate ligand–receptor (L–R) interactions, multi-omics data, and deep learning-based pathological images to construct an interpretable multimodal prognostic model and to elucidate the mechanisms underlying the cancer-associated fibroblast (CAF) microenvironment. Significant L–R interactions were identified using BulkSignalR, followed by sequential Cox, least absolute shrinkage and selection operator (LASSO)–Cox, and random survival forest analyses to construct a prognostic model. Multi-omics profiling characterized molecular distinctions between risk groups. Key L–R pairs were evaluated with single-cell and spatial transcriptomics, validated in 39 paired clinical specimens via immunofluorescence, and linked to histopathological features through deep learning on hematoxylin and eosin-stained whole-slide images. We identified 236 significant L–R pairs, with 47 associated with prognosis. Integration of LASSO–Cox and random survival forest analyses yielded five key pairs: IL16_KCND1, PLAU_ITGA5, FN1_ITGB3, GNAS_ADCY1, and CALM1_PDE1B. The resulting risk model effectively stratified overall survival. The high-risk group showed higher tumor mutational burden, more frequent KRAS and TP53 mutations, and enrichment of extracellular matrix remodeling, transforming growth factor‑β signaling, and glycolysis pathways. Single-cell and spatial analyses revealed preferential enrichment of PLAU_ITGA5 and FN1_ITGB3 in fibroblast-related compartments. Immunofluorescence confirmed upregulation of these pairs in tumor tissues, and deep learning identified fibroblast-associated histopathological features with strong concordance to the risk axes. This study established the first multimodal prognostic framework integrating L–R interactions and histopathological features, revealing the central role of CAF-mediated L–R signaling in remodeling the PAAD microenvironment and providing a novel strategy for precise prognostic stratification and targeted microenvironmental therapy.

Purpose:Hypertriglyceridemia-associated acute pancreatitis (HTG-AP) has become the second leading cause of acute pancreatitis (AP) in China. Compared with other etiologies, patients with HTG-AP are more likely to develop severe acute pancreatitis (SAP). This study aimed to develop and validate a prediction model for severe HTG-AP. Patients and Methods:The derivation cohort consisted of 478 HTG-AP patients collected in a multicenter, prospective observational study (PERFORM study, 2020-2023, involving 36 tertiary hospitals in China). The external validation cohort included 145 prospectively enrolled HTG-AP patients from the General Hospital of Ningxia Medical University (from January 2024 to May 2025). Clinical variables were collected within 24 hours of enrollment. After excluding variables with more than 20% missing data, least absolute shrinkage and selection operator (LASSO) regression was used to select predictors. An XGBoost-based prediction model was constructed. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA), and compared with traditional scoring systems. SHapley Additive exPlanations (SHAP) analysis was employed to assess model interpretability. Results:A total of 113 patients (23.6%) in the derivation cohort and 23 patients (15.9%) in the validation cohort developed SAP, respectively. LASSO regression identified seven predictors: serum calcium (Ca2⁺), heart rate (HR), C-reactive protein (CRP), D-dimer (D-D), respiratory rate (RR), serum creatinine (SCr), and pleural effusion. The XGBoost model achieved an AUC of 0.873 in both the derivation and external validation cohorts, thereby significantly outperforming APACHE II (0.708, 0.701), SOFA (0.699, 0.685), SIRS (0.656, 0.649), and CTSI (0.661, 0.658) (all P < 0.05). The model showed good calibration (Hosmer-Lemeshow test P > 0.05) and provided a superior net clinical benefit across a wide range of threshold probabilities in DCA. SHAP analysis revealed that Ca2⁺ was the most influential predictor, followed by HR and CRP. To enhance clinical usability, we developed an interactive web-based calculator using the R Shiny framework. Conclusion:This study developed and validated an XGBoost-based prediction model that uses seven easily obtained clinical variables for early identification of severe HTG-AP. The model demonstrated favorable discrimination, good calibration, and meaningful clinical utility, and outperformed traditional scoring systems. It offers a promising tool to improve risk stratification in HTG-AP.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, encompassing a continuum ranging from simple steatosis to steatohepatitis, hepatic fibrosis, and cirrhosis. Despite the complex and heterogeneous pathogenesis, effective therapeutic targets remain elusive. In this study, we sought to identify and validate critical genes implicated in MASLD progression through multi-omics integration and machine learning algorithms. Analysis revealed considerable activation of lipid metabolism, oxidative stress, and inflammation-related pathways throughout disease progression, with notable upregulation of AKR1B10, COL1A2, and SPP1 and downregulation of CYP2C19. These expression patterns were consistently verified across in vivo and in vitro models. Functional assays indicated that AKR1B10 knockdown or CYP2C19 overexpression substantially attenuated hepatocellular lipid accumulation, alleviated oxidative stress and inflammatory responses, and suppressed key lipogenic gene expression. Collectively, these findings elucidate key molecular axes in MASLD progression and provide mechanistic insights and theoretical foundations for the development of targeted therapies.

Background 3-Hydroxybutyrate, also known as β-hydroxybutyrate, is a major ketone body involved in energy metabolism, mitochondrial function, oxidative stress, and inflammatory regulation. Previous clinical and experimental studies have suggested that ketogenic interventions may reduce hepatic fat accumulation and improve metabolic parameters related to non-alcoholic fatty liver disease (NAFLD). However, whether circulating ketone bodies, particularly 3-hydroxybutyrate, have a causal relationship with NAFLD remains unclear. Materials and methods We performed two-sample Mendelian randomization (MR) analyses to investigate the potential causal associations of three ketone bodies—3-hydroxybutyrate, acetoacetate, and acetone—with NAFLD. Summary-level genome-wide association study data for ketone bodies were obtained from publicly available metabolomics GWAS datasets, and NAFLD GWAS data were obtained from the IEU Open GWAS database. The inverse-variance weighted method was used as the primary analysis, with MR-Egger, weighted median, simple mode, and weighted mode methods applied as complementary analyses. Reverse MR and multivariable MR analyses were further conducted. Sensitivity analyses, including heterogeneity assessment, pleiotropy testing, MR-PRESSO, and leave-one-out analysis, were performed to evaluate the robustness of the findings. Results In the forward MR analysis, genetically predicted 3-hydroxybutyrate was significantly associated with a lower risk of NAFLD using the inverse-variance weighted method (OR = 0.448, 95% CI 0.249–0.805, P = 0.007). In contrast, genetically predicted acetoacetate and acetone were not significantly associated with NAFLD risk. Reverse MR analyses did not provide evidence that genetic liability to NAFLD causally affected circulating levels of acetoacetate, acetone, or 3-hydroxybutyrate. In multivariable MR analysis including the three ketone bodies, 3-hydroxybutyrate remained significantly associated with a reduced risk of NAFLD (OR = 0.407, 95% CI 0.200–0.829, P = 0.013), whereas acetoacetate and acetone showed no significant associations. Leave-one-out analysis indicated that the findings were not driven by any single SNP. Conclusion This MR study suggests that genetically predicted higher 3-hydroxybutyrate levels may be associated with a reduced risk of NAFLD. However, these findings should not be interpreted as direct evidence that ketogenic diets or exogenous ketone supplementation can prevent or treat NAFLD. Further experimental studies, prospective cohorts, and clinical trials are needed to validate the biological mechanisms and clinical implications.

Zinc is an essential trace element that links coordination chemistry, redox regulation, and immune homeostasis. In inflammation and oxidative stress related diseases, zinc acts through multiple distinct forms, including systemic supplementation, soluble zinc salts and complexes, zinc-based nanoparticles, zinc-containing coordination nanoplatforms and metal-organic frameworks, drug-loaded zinc nanocarriers, and biodegradable zinc alloys or implantable devices. This review organizes around this classification framework and summarizes zinc-related mechanisms across cardiovascular, gastrointestinal, urogenital, immune, infectious, and oncologic contexts, and then compare material-enabled application modes. At the molecular level, zinc can suppress excessive IKK/NF-κB activation, regulate MAPK and JAK/STAT signaling, influence macrophage polarization, support ZIP/ZnT-mediated zinc fluxes, stabilize antioxidant enzymes and metallothioneins, and activate the Nrf2/HO-1 pathway. At the materials level, therapeutic performance depends not only on Zn2+ availability but also on coordination environment, dissolution kinetics, particle size, surface defects, protein corona formation, cargo release, corrosion behaviour, biodistribution, and local tissue microenvironment. Finally, we discuss translational constraints, including the narrow therapeutic window of zinc, redox effects, attribution of efficacy, pharmacokinetics, long-term toxicity, and the need for standardized evaluation of zinc release and tissue distribution. A mechanistic and materials-design perspective may support safer and more predictable development of zinc-based anti-inflammatory and antioxidant interventions.

Introduction:Colorectal cancer liver metastasis (CRLM) is the leading cause of death in colorectal cancer, and nonalcoholic fatty liver disease (NAFLD) promotes CRLM. Lycium barbarum polysaccharides (LBPs), bioactive metabolites of the traditional medicinal plant Lycium barbarum L, inhibit the progression of colorectal cancer and NAFLD by regulating gut microbiota composition. However, their roles in preventing CRLM under NAFLD conditions remain unclear. This study aimed to investigate the preventive effect of LBPs on liver metastasis of colorectal cancer in the context of NAFLD and explore its potential mechanisms. Methods:An NAFLD mouse model was established, followed by prophylactic oral administration of LBPs by gavage for 28 days before splenic injection of MC38 colorectal cancer cells to establish liver metastasis. Pseudo-germ-free mice combined with fecal microbiota transplantation were constructed to explore the role of the gut microbiota in the preventive effect of LBPs on CRLM. Gut microbiota and fecal short-chain fatty acids were analyzed by 16S rRNA sequencing and liquid chromatography-mass spectrometry. Spearman's correlation analysis was used to explore the correlation between bacterial genera and liver lipid metabolism indicators. Serum non-targeted metabolomic profiling and transcriptomic analysis of CRLM cells were performed to elucidate metabolic and molecular mechanisms. Results:Under NAFLD conditions, LBPs markedly reduced hepatic metastatic burden, liver weight, and liver-to-body weight ratio. LBPs ameliorated hepatic lipid metabolism and restored colonic barrier integrity in NAFLD mice. The gut microbiota was identified as a critical mediator of LBPs-induced protection against CRLM, and depletion of the microbiota completely abrogated the anti-metastatic effects of LBPs. LBPs enhanced microbial diversity and richness, enriched of short-chain fatty acid-producing bacterial genera, such as Cryptobacteroides, Evtepia, and Bacteroides-H, and elevated colonic butyrate levels. Metabolomic profiling revealed reduced serum acylcarnitines and increased organic acids. Transcriptomic profiling showed upregulation of fibroblast growth factor 21, activation of the PI3K-AKT signaling pathway, and promotion of epithelial-mesenchymal transition in colorectal cancer cells, while LBPs reverse these changes. Discussion:LBPs prevent CRLM associated with NAFLD by modulating the gut microbiota, enhancing butyrate production, improving hepatic metabolic homeostasis, and suppressing prometastatic signaling pathways. These findings highlight LBPs as promising preventive agents against CRLM in the setting of metabolic liver disease.

Background:Belonging to the RNA-binding protein family, Pumilio RNA binding family member 1 (PUM1) modulates gene expression post-transcriptionally through the recognition of particular motifs within the 3' untranslated region of its target transcripts. The present investigation seeks to elucidate PUM1's contribution to HCC pathogenesis and advancement, while also probing the molecular mechanisms that underpin its function. Methods:Publicly available datasets were employed to examine PUM1 transcript abundance in hepatocellular carcinoma, along with its relationship to clinicopathological parameters and prognostic outcomes. PUM1 protein levels were subsequently corroborated in clinical HCC specimens via immunoblotting and immunohistochemical staining. To explore the biological functions of PUM1, we established HCCLM3 cell lines with PUM1 overexpression and knockdown. We then evaluated proliferation via EdU, colony formation, and CCK‑8 assays; apoptosis via TUNEL and flow cytometry; mitochondrial membrane integrity and calcium balance using JC‑1, Mito‑Tracker, and Rhod‑2; and oxygen species (ROS) accumulation via MitoSOX and DCFH‑DA. The downstream molecular pathways were further examined by Western blotting. Results:HCC tissues exhibit markedly upregulated PUM1 levels, a feature tightly correlated with poor prognosis. In vitro, PUM1 preserved mitochondrial membrane integrity and calcium homeostasis in HCC cells, while suppressing the accumulation of reactive oxygen species (ROS). Additionally, PUM1 inhibited programmed cell death and promoted cell proliferation. These biological activities were closely associated with the PI3K-AKT signaling pathway. Conversely, knockdown of PUM1 significantly impaired HCC cell proliferation and induced apoptosis. Conclusion:PUM1 promotes HCC cell proliferation and suppresses mitochondria‑mediated apoptosis, effects that are closely associated with activation of the PI3K-AKT pathway.

BACKGROUND:Mediator complex subunit 10 (MED10) serves as a critical regulator of eukaryotic gene expression by facilitating RNA polymerase II activity. Our investigation aims to characterize MED10's functional contributions and underlying molecular pathways in hepatocellular carcinoma (HCC) development. METHODS:MED10 expression patterns in HCC and their correlation with clinicopathological parameters and patient outcomes were examined using bioinformatics databases and immunohistochemistry. Subsequently, we systematically investigated the biological functions of MED10 in the malignant progression of HCC through comprehensive in vitro experiments, including assessments of cell migration (transwell and wound healing assays), proliferative capacity (cell counting kit-8, colony formation, and 5-Ethynyl-2'-deoxyuridine assays), and cell cycle progression (flow cytometry analysis). Furthermore, we elucidated the underlying molecular mechanisms using real-time quantitative PCR (RT-qPCR), western blotting, immunofluorescence staining, and public database analyses. Furthermore, an in vivo subcutaneous xenograft model was employed to validate MED10's impact on tumor growth. RESULTS:The results revealed a marked increase in MED10 expression levels within HCC tissues, showing a strong association with unfavorable clinical outcomes. Mechanistically, MED10 induced the epithelial-mesenchymal transition (EMT) and enhanced HCC cell migration. Moreover, MED10 overexpression drives HCC cell cycle progression and proliferation by activating rapidly accelerated fibrosarcoma 1 (RAF1), a process potentially mediated through the mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK)/cellular myelocytomatosis oncogene (c-Myc) signaling axis. CONCLUSION:MED10 promotes HCC cell migration and EMT but, more importantly, also drives cell cycle progression and proliferation via RAF1 activation, and is related to the MEK/ERK/c-Myc axis.

Early recurrence remains a major challenge in the management of hepatocellular carcinoma (HCC), yet its molecular mechanisms are not fully understood. In this study, we applied an integrative multi-omics strategy at single-cell resolution to explore potential drivers of early HCC recurrence (recurrence time < 2 years) and to develop a predictive framework. By combining single-cell RNA sequencing, proteomics, transcriptomics, and clinical feature analysis, we identified 14 relapse-associated proteins, including CD274, B2M, MYC, and CASP3, as candidate risk factors. Transcriptomic profiling suggested the enrichment of pathways such as MYC-TARGETS-V2 and INTERFERON-GAMMA-RESPONSE. Single-cell analysis indicated reduced immune cell infiltration in recurrent tumors, with myeloid cells (particularly cDC2 and macrophages) showing B2M-associated reprogramming characterized by HLA downregulation and altered GAS6/PROS1 signaling, consistent with tumor-associated macrophage-like phenotypes. A LASSO regression model based on cDC2 and macrophage signature genes demonstrated moderate predictive performance in both the training and validation cohorts (AUC > 0.65). Drug sensitivity analyses further suggested that vandetanib may have the potential to inhibit recurrence by targeting B2M-related pathways. These findings provide evidence that B2M may contribute to remodeling of the immune microenvironment in recurrent HCC. Our integrative single-cell multi-omics approach highlights a possible mechanism of early recurrence and offers a preliminary predictive tool with therapeutic implications.

We report a rare earth (RE)-doped quantum dot-based nanoplatform that regulates lysosomal acidification and enhances macrophage-mediated clearance of intracellular pathogens. By co-doping cadmium selenide quantum dots (CdSe QDs) with ytterbium (Yb3+), erbium (Er3+), and europium (Eu3+), we engineered mixed-phase CdSe:Yb/Er/Eu QDs with tailored crystal field symmetry, broad spectral responsiveness (340-800 nm), and efficient upconversion luminescence. These nanoprobes exhibit strong light-harvesting via RE f-f transitions, size-tunable properties, and dual-mode fluorescence imaging capabilities (upconversion/downconversion). In RAW264.7 macrophages, the QDs demonstrated efficient intracellular localization and, upon near-infrared (800 nm) irradiation, produced a robust photothermal effect (Delta T = 12.8 +/- 0.5 degrees C). Photothermal activation for 48 h selectively upregulated lysosomal acidification-related genes-ATP6V1A (1.39 +/- 0.27-fold) and LAMP1 (1.65 +/- 0.39-fold; P < 0.01)-and significantly increased lysosomal enzymatic activity, including a 68 % rise in cathepsin B activity. This physically triggered "photothermal-gene regulation" approach offers a promising therapeutic avenue for restoring lysosomal function and combating intracellular infections such as Brucella.

Background: Since its introduction in 2008, sorafenib has remained the standard first-line systemic treatment for advanced hepatocellular carcinoma (HCC). Nevertheless, its clinical benefits are often compromised by the rapid emergence of drug resistance. This study explores the molecular mechanisms underlying sorafenib resistance, with particular emphasis on the involvement of connective tissue growth factor (CCN2/CTGF) in the regulation of c-Met signaling pathways. Methods: We began by evaluating CCN2 expression levels in HCC tissue samples via immunohistochemistry and analyzing their correlation with clinicopathological characteristics. To functionally characterize CCN2, we established stable HCC cell lines with either knockdown or overexpression of the gene using lentiviral transduction. The effects of CCN2 on cellular proliferation and drug resistance were evaluated using cell counting kit-8 (CCK-8) and colony formation assays. To elucidate the downstream signaling mechanisms, a tyrosine kinase PCR array was employed to identify expression changes within the tyrosine kinase superfamily after CCN2 knockdown. Further investigation into the molecular mechanism by which CCN2 promotes sorafenib resistance was conducted using real-time quantitative PCR (RT-qPCR), western blotting, and immunofluorescence. Finally, the therapeutic potential of co-targeting CCN2 and sorafenib was validated in a nude mouse xenograft tumor model. Results: Our results establish that CCN2 overexpression significantly enhances HCC proliferation, while also inducing resistance to sorafenib. Mechanistically, we identified that CCN2 binds to integrin αV, triggering focal adhesion kinase (FAK) phosphorylation, which in turn promotes yes-associated protein (YAP) nuclear translocation and leads to the transcriptional upregulation of c-Met. This proposed signaling axis was consistently supported by tyrosine kinase PCR array, co-immunoprecipitation, and western blot analyses. Ultimately, in vivo experiments confirmed that simultaneously targeting CCN2 and administering sorafenib produces a synergistic effect, markedly inhibiting tumor growth and restoring therapeutic sensitivity. Conclusion: These results not only elucidate a novel CCN2/FAK/YAP/c-Met axis in sorafenib resistance but also provide a mechanistic rationale for dual-targeting strategies to improve outcomes in advanced HCC.

Patients with malignant biliary obstruction (MBO) are often treated with endoscopic retrograde cholangiopancreatography (ERCP) combined with biliary stent placement for tumor progression. However, certain patients die within 30 days after the procedure, increasing healthcare resource consumption and patient burden. Therefore, the development of early mortality prediction models is important for optimizing treatment decisions. The present study retrospectively analyzed the clinical data of 285 patients with MBO, including demographic information, laboratory indicators and tumor-related factors. Logistic regression and artificial neural network (ANN) models were used to construct a prediction tool, and the model performance was evaluated using area under the curve (AUC), accuracy, sensitivity and specificity. The logistic regression model, which identified the cancer antigen 19-9 (CA19-9) level and a history of previous ERCP surgery as independent risk factors, had an AUC of 0.727 and an accuracy of 65.0%. The ANN model, which combined five variables, namely CA19-9, history of previous ERCP surgery, neutrophil-lymphocyte ratio (NLR), liver metastasis and carcinoembryonic antigen, demonstrated that NLR was the most weighted predictor. Furthermore, the ANN model had an AUC of 0.813, an accuracy of 88.2% and a specificity that was markedly higher than that of the logistic regression model (95.5 vs. 83.3%). However, the ANN model was revealed to be slightly less sensitive compared with the logistic regression model (61.1 vs. 61.2%). In conclusion, compared with logistic regression, the ANN model had a greater performance level in terms of predictive power and specificity, and is suitable for capturing complex non-linear relationships. However, its complexity and risk of overfitting need to be further optimized. The present study provides a new tool for the accurate prediction of the risk of early death after ERCP in patients with MBO, which could help improve individualized treatment strategies.

Primary liver cancer (PLC) and metformin are not well understood to be associated. We conducted a Mendelian randomization (MR) analysis using genetic data from IEU OpenGWAS and FinnGen R10, with metformin as the exposure and PLC as the outcome. The inverse variance weighting (IVW) method was the primary analytical approach, with heterogeneity assessed by Cochran's Q test, pleiotropy by MR-Egger intercept, and outliers by MR-PRESSO. Bioinformatics analyses further explored potential mechanisms, including differential gene expression, protein-protein interactions (PPI), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, immune cell infiltration analysis, and drug sensitivity analysis. MR results demonstrated a significant association between metformin use and reduced risk of PLC (β = -5.6046, OR = 0.0037, p = 0.026), with a Benjamini-Hochberg false discovery rate (FDR) adjusted p value of 0.13. However, no causal effect was observed for hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICC). By cross-referencing transcriptome data from the GEO database GSE241466 with metformin-related gene loci, 34 overlapping genes were identified. Differentially expressed genes (DEGs) were filtered using |log2FC| > 0 and p < 0.05, with five hub genes (DDX52, KIF11, GCDH, MRPL45, and TICRR) being particularly prominent. Functional enrichment analysis revealed involvement in cGMP-PKG signaling and fatty acid metabolism pathways. Further validation with GEPIA2, TIMER, and TISCH showed correlations between these genes and immune infiltration, while GSCA-based drug sensitivity analysis suggested therapeutic relevance. In summary, these findings indicate that metformin may reduce PLC risk by modulating metabolic and immune-related pathways, supporting its potential value as an adjunct therapeutic agent. However, further validation through large-scale clinical and basic research is warranted.

Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors worldwide. Brahma-related gene 1 (BRG1), as a catalytic ATPase, is a major regulator of gene expression and is known to mutate and overexpress in HCC. The purpose of this study was to investigate the mechanism of action of BRG1 in HCC cells. In our study, BRG1 was silenced or overexpressed in human HCC cell lines. Transwell and wound healing assays were used to analyze cell invasiveness and migration. Mitochondrial membrane potential (MMP) and mitochondrial permeability transition pore (mPTP) detection were used to evaluate mitochondrial function in HCC cells. Colony formation and cell apoptosis assays were used to evaluate the effect of BRG1/TOMM40/ATP5A1 on HCC cell proliferation and apoptosis/death. Immunocytochemistry (ICC), immunofluorescence (IF) staining and western blot analysis were used to determine the effect of BRG1 on TOMM40, ATP5A1 pathway in HCC cells. As a result, knockdown of BRG1 significantly inhibited cell proliferation and invasion, promoted apoptosis in HCC cells, whereas BRG1 overexpression reversed the above effects. Overexpression of BRG1 can up-regulate MMP level, inhibit mPTP opening and activate TOMM40, ATP5A1 expression. Our results suggest that BRG1, as an oncogene, promotes HCC progression by regulating TOMM40 affecting mitochondrial function and ATP5A1 synthesis. Targeting BRG1 may represent a new and effective way to prevent HCC development.

This study mainly shows the role of endoplasmic reticulum transmembrane and coiled coil domains 1 (TMCO1) in the regulatory mechanism of hepatocellular carcinoma (HCC). Invasion and migration capacity were detected by Transwell and wound healing after TMCO1 and TOMM20 overexpression and knockdown, and mitochondrial function was detected through reactive oxygen species (ROS), mitochondrial permeability transition pore (mPTP), mitochondrial membrane potential (MMP), and ATP production. A model of subcutaneous tumor formation in nude mice was established to detect the effect of TMCO1 on tumor formation. The results showed that overexpression of TMCO1 significantly promoted HCC cell metastasis, promoted cell proliferation and ATP production, inhibited cell apoptosis, mPTP opening and ROS production, mediated the increase of MMP level and cytoskeletal remodeling. However, knocking down TMCO1 can have the opposite effect. More importantly, knocking down TOMM20 can block the regulation effect of TMCO1, and TOMM20 overexpression can alleviate the inhibitory effect of knocking down TMCO1 on the development of liver cancer cells. In animal models, knockdown of TMCO1 expression significantly inhibited the growth of subcutaneous implant tumors. This suggests that TMCO1 may be a potential and valuable therapeutic target for liver cancer.

Hepatocellular carcinoma (HCC) is a malignant tumor that affects the liver and poses a significant threat to human health. Further investigation is necessary to fully understand the role of SIRT1, a protein linked to tumorigenesis, in HCC development. To investigate the effect of SIRT1 on HCC and elucidate the underlying mechanism. Eight pairs of HCC and paracancerous normal tissue specimens were collected. The levels of SIRT1 and GSDME in tissue samples were assessed using immunohistochemistry and western blotting. SIRT1 levels were determined in HCC (Huh7, HepG2, SNU-423, SNU-398, and HCCLM3) and L-02 cells using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting. SNU-423 and HCCLM3 cells were transfected with si-SIRT1 and/or si-GSDME to knock down SIRT1 or GSDME expression. RT-qPCR and western blotting were performed to measure the expression of SIRT1, pro-casp-3, cl-casp-3, GSDME, GSDME-N, PGC-1α, Bax, and cytochrome c (Cyto C). Cell proliferation, migration, invasion, and apoptosis were assessed using the cell counting kit-8 (CCK-8), wound healing assay, Transwell invasion assay, and flow cytometry, respectively. The release of lactate dehydrogenase (LDH) was evaluated using an LDH kit. SIRT1 was upregulated in HCC tissues and cells, and a negative correlation was observed between SIRT1 and GSDME-N. SIRT1 silencing suppressed the proliferation, migration, and invasion of HCC cells while also promoting apoptosis and inducing mitochondrial damage. Additionally, the silencing of SIRT1 resulted in the formation of large bubbles on the plasma membrane of HCC cells, leading to cellular swelling and aggravated GSDME-dependent pyroptosis, resulting in an increase in LDH release. Inhibition of GSDME reduced SIRT1 silencing-induced cell swelling, decreased LDH release rate, and promoted apoptosis. SIRT1 silencing promotes GSDME-dependent pyroptosis in HCC cells by damaging mitochondria.