Background: Preoperative serum inflammatory markers have been correlated with survival outcomes after resection of hepatocellular carcinoma (HCC). Whether they can predict microvascular invasion (MVI) in HCC is still unknown. This study aimed to evaluate the association of inflammatory markers with MVI, and develop a simple and inexpensive preoperative prediction model for MVI. Methods: We developed a novel index using routine laboratory tests to predict MVI. The index was developed based on a study on patients with HCC, and validated in an internal cohort and another external cohort. The infiltration of CD8 + T cells in tumors was measured using immunohistochemistry. The prediction accuracy was evaluated with the area under the receiver operating characteristic curve (AUC). Results: There were 165 patients in the training cohort, 107 patients in the internal validation cohort and 80 patients in the external validation cohort. On multivariable analysis in the training cohort, alkaline phosphatase (ALP) and lymphocyte count were independent predictors of MVI. Thus, the ALP-to-lymphocyte ratio (ALR) was developed. The AUCs of the ALR for MVI were higher than the other conventional clinical indices. An optimal cutoff point for the ALR of 69.9 stratified HCC patients into the high (>= 69.9) and low (< 69.9) groups. An ALR >= 69.9 was significantly associated with worse overall and disease-free survival outcomes. The performance of ALR was validated in the internal and in external cohorts. The CD8(+) T cell counts were significantly higher in HCC in the ALR < 69.9 groups. Conclusion: ALR was a simple, accurate and inexpensive alternative to predict MVI and an independent risk factor of prognosis for HCC patients. The dismal survival outcomes in patients with high ALR scores were related to decreased infiltrations of CD8(+) T cells in tumors.

Background: Cumulating evidence reveals the key role of aberrant lipogenesis and immunogenomic features in hepatocellular carcinoma (HCC). However, there are still obstacles in our understanding of the complicated interaction between metabolic reprogramming and tumor immune microenvironment. Methods: We compared metabolomic, transcriptomic and immunogenomic characteristics of portal vein tumor thrombosis (PVTT) and primary tumor to seek valuable markers. Human HCC samples with PVTT (n = 28) was analyzed through ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Transcript levels of mRNA in two cohorts from published database GEO (n = 60) and TCGA (n = 411) were downloaded to explore differentially expressed genes and functional enriched gene set. Evaluation of immune infiltration was estimated and validated from transcriptomic data in both cohorts through six immune deconvolution algorithms and in a high-resolution mode (CIBERSORTx). Survival analysis (Kaplan–Meier and multivariable Cox regression model) was performed to examine prognostic value of ACLY, related immune checkpoints and immune infiltration levels from TCGA cohort. LASSO regression was further conducted to determine a gene panel to further predict survival outcomes associated with ACLY. Results: We identified a novel signature, ATP citrate lyase, through transcriptomic and metabolomic approaches. We demonstrated that the metabolism adaptations in both fatty acid and cholesterol biosynthesis triggered by ACLY oncogenic activation. We illustrated the crucial function of ACLY in lipogenesis and its potential interaction with immune microenvironment. CD276, a promising target in immune checkpoint blockade, showed correlation to ACLY and differential expression in ACLY risk classification. Combination of ACLY, CD276 and immune infiltration level and a novel ACLY-associated panel from a predictive model retrieved from published database validated the prognostic value to risk stratification in patients with HCC.ACLY blockade to counteract metabolic activation and immunosuppressive status of the tumor microenvironment highlighted attractive prospect for translational application. Conclusions: We investigated ACLY and its indispensable role in metabolism, immune function and a prognostic gene panel in HCC. We anticipate that the multifaced role of ACLY may reveal the potential value for mechanistic research and combinational therapy, suggesting that the combination blockade of ACLY and immune checkpoints may work as a promising strategy.

Background/Objectives: Malignant transformation of hepatocellular adenoma (HCA) represents a clinically significant yet incompletely understood process. Although the pathological and clinical characteristics of HCA have been extensively described, its spatial molecular heterogeneity and spatially organized molecular variation at the tissue level remain insufficiently characterized. This study aimed to establish a spatially integrated multi-omics workflow and to delineate spatially organized molecular variation across histologically defined regions from adenoma to carcinoma. Methods: A sequential dual-layer matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) workflow was developed to acquire small-molecule metabolomic and N-glycan spatial data from the same formalin-fixed paraffin-embedded (FFPE) tissue section. Four rare HCA specimens containing focal carcinoma transformation were included in this study. Pixel-level clustering, region-based co-localization analysis, and diffusion pseudotime modeling were applied to characterize spatial metabolic and N-glycan patterns across normal liver tissue (NL), hepatocellular adenoma (HCA), and carcinoma-transformed regions within adenoma (HCA-HCC). Results: Small-molecule MSI revealed spatial metabolic stratification within HCA, with variation observed in nucleotide-related, lipid-related, sulfur-related, and sugar nucleotide–associated metabolites. Pseudotime analysis revealed a spatial ordering of samples across NL, HCA, and HCA-HCC regions, showing differences in antioxidant-associated metabolites, lipid-related features, and bile acid-related metabolites across regions. N-glycan MSI identified independent glycosylation niches, with increasing structural complexity and enrichment of highly branched glycans in carcinoma-transformed regions. Integration of metabolomic and glycomic data suggested spatially associated patterns between metabolite features and glycan structures across regions. Conclusions: This study provides spatially resolved evidence of spatially organized patterns of molecular variation across histologically defined regions of HCA. The identified metabolic and N-glycan gradients provide insights into spatial molecular organization during malignant transformation of hepatocellular adenoma.