Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrumental in the progression of HCC. Nevertheless, the precise mechanisms through which lipid metabolism impacts HCC and its viability as a therapeutic target have yet to be fully elucidated. In the current investigation, single-cell RNA sequencing in conjunction with weighted gene co-expression network analysis (WGCNA) was utilized to delineate lipid metabolism-related genes correlated with the prognostic outcomes of hepatocellular carcinoma (HCC). Data procurement encompassed transcriptomic and clinical datasets from HCC patients, sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories. Subsequent to this, consensus clustering analysis was implemented to stratify patients into distinct subgroups, contingent upon the expression patterns of lipid metabolism genes. Further analytical procedures involved functional enrichment analysis, evaluation of immune infiltration, and examination of the mutation landscape.PTGES3 was identified as a pivotal gene associated with lipid metabolism. Subsequent to its identification, cellular communication analysis was employed to assess the immunological attributes of PTGES3 within the tumor microenvironment. The functional role of PTGES3 was further corroborated through molecular docking simulations and in vitro experimental assays. We identified 27 genes associated with lipid metabolism, 18 of which exhibited significant correlation with overall survival in HCC patients. PTGES3 emerged as a central gene, demonstrating a robust association with immune cell infiltration and unfavorable prognosis. Cellular communication analysis revealed that PTGES3 exhibits the highest communication intensity with T cells, modulating the tumor microenvironment by potentiating the FN1/CD44 + MDK/NCL signaling pathway. Elevated expression of PTGES3 was linked to immunosuppressive cascades, diminished responsiveness to immunotherapy, and inferior overall survival outcomes. Molecular docking analysis indicated that etoposide, methotrexate, and doxorubicin could effectively bind to PTGES3. In vitro experiments confirmed that PTGES3 knockdown significantly impaired the proliferation, invasion, and migration of HCC cells. This study highlights the pivotal role of lipid metabolism in HCC progression and identifies PTGES3 as a potential prognostic biomarker and therapeutic target. These findings offer new insights into the development of targeted therapies for HCC, particularly in patients with high PTGES3 expression.

Dai H ，Tao X ，Shu Y ，Liu F ，Cheng X ，Li X ，Shu B ，Luo H ，Chen X ，Cheng Z ... -  《Scientific Reports》

Integrated single-cell and bulk transcriptome analysis of R-loop score-based signature with regard to immune microenvironment, lipid metabolism and prognosis in HCC.

Hepatocellular carcinoma (HCC) is one of the most prevalent causes of cancer-related morbidity and mortality worldwide. Late-stage detection and the complex molecular mechanisms driving tumor progression contribute significantly to its poor prognosis. Dysregulated R-loops, three-stranded nucleic acid structures associated with genome instability, play a key role in the malignant characteristics of various tumors. However, the detailed role and mechanism of R-loops in HCC progression remain elusive and require further exploration. This study aimed to construct an R-loop scoring signature centered on prognosis and lipid metabolism, thereby enhancing our understanding of HCC progression and identifying potential therapeutic targets. In this study, we utilized the single-cell RNA-sequencing (scRNA-seq) data from HCC patients (GSE149614 and CRA002308) to construct an R-loop scoring model based on the identified R-loop regulator genes (RLRGs) related to HBV infection through WGCNA analysis. We also explored the tumor microenvironment and intercellular communication related to R-loop score. Additionally, a prognostic risk model based on the fatty acid metabolism-associated RLRGs was constructed using data from the TCGA database, and its association with immune infiltration, mutations, and drug sensitivity was analyzed. In vitro and in vivo experiments were performed to investigate the role of RLRG CLTC in lipid metabolism and HCC progression. Using scRNA-seq data from HCC, we established an R-loop scoring model based on identified RLRGs related to HBV infection. Moreover, the more suppressive tumor immune microenvironment and stronger intercellular communication were displayed in malignant cells with high R-loop scores. The cell trajectory and cellular metabolism analysis exhibited a significant association between lipid metabolism and RLRGs. Additionally, we constructed a prognostic risk model consisting of 8 RLRGs related to fatty acid metabolism, which effectively evaluated the prognostic value, status of tumor immune microenvironment, gene mutations, and chemotherapeutic drug sensitivity for HCC patients. Notably, validation experiments suggested that CLTC could regulate lipid metabolism through R-loop formation and facilitate tumor progression in HCC. Collectively, our study proposes an R-loop scoring model associated with tumor immune microenvironment, lipid metabolism and prognostic value. CLTC, an R-loop regulator, emerges as a promising prognostic biomarker and therapeutic target, offering new insights into potential treatment strategies for HCC patients.

Chen L ，Yang H ，Wei X ，Liu J ，Han X ，Zhang C ，Liu Y ，Zhang Y ，Xu Y ，Li Y ，Wang G ，Feng J ... -  《Frontiers in Immunology》

Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data.

Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the "Seurat" R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model's robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.

Li B ，Zeng T ，Chen C ，Wu Y ，Huang S ，Deng J ，Pang J ，Cai X ，Lin Y ，Sun Y ，Chong Y ，Li X ，Gong J ，Tang G ... -  《-》

Integrative single cell transcriptomic analysis reveals 3p deletion associated tumor microenvironment and chemoresistance in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) remains a prevalent and lethal malignancy, with a five-year survival rate of just 50% for cases of locally advanced disease. Chromosomal aberrations, particularly the deletion of the short arm of chromosome 3 (3p), have been strongly associated with poor prognosis and more aggressive tumor phenotypes. The tumor microenvironment (TME) plays a pivotal role in tumor progression and resistance to therapy. This study aims to elucidate the impact of 3p deletion on the TME, immune cell infiltration, and treatment response in HNSCC, to identify novel therapeutic targets to improve patient outcomes. We analyzed single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and bulk transcriptome data from The Cancer Genome Atlas (TCGA). Pseudo-time trajectory and cell-cell communication analyses were performed with the Monocle and CellChat packages. The Wilcoxon test was used to evaluate the differential gene expression between wild-type (wt) and mutant (mut) groups. Prognostic models were developed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Cox regression analyses to find the genes related to survival, with survival analysis conducted via Kaplan-Meier curves. Gene set enrichment analysis (GSEA) was employed to investigate pathway dysregulation, and immune cell infiltration was assessed using various immune scoring methodologies to explore the differences immune environment. The Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to predict the potential efficacy of immune checkpoint inhibitors. mRNA and protein expression levels of SPP1 were examined by RT-qPCR and Western blotting, while cell proliferation was assessed using the CCK8 assay. The mut group demonstrated significant alterations in cellular composition, characterized by increased endothelial cells and macrophages and decreased fibroblasts and CD8 + T cells, indicative of an immunosuppressive TME. Differential expression analysis revealed downregulation of immune pathways, including antigen processing and presentation, T cell receptor signaling, and B cell receptor signaling pathways in the mut group, along with enhanced metabolic activity in glycolysis and lipid metabolism. The prognostic model identified nine key genes associated with poor survival in HNSCC. The mut group exhibited poorer overall survival and a more immunosuppressive microenvironment compared to the wt group, which correlated with the outcomes observed in high-risk versus low-risk groups. High-risk patients also showed a diminished response to immunotherapy compared to low-risk patients. Additionally, SPP1 emerged as a critical gene associated with chemotherapy resistance and macrophage M2 polarization. This study demonstrates that 3p deletion significantly reshapes the TME, contributing to poor prognosis in HNSCC by fostering an immunosuppressive environment and enhancing chemoresistance. These findings highlight the potential for developing targeted therapies that address the genetic and immunological landscape of HNSCC.

Chen X ，Xu S ，Pan J ，Xu W ，Yang H ，Chen X ，Chen R ，Wang Y ，Qiu S ... -  《Scientific Reports》

TMEM101 expression and its impact on immune cell infiltration and prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a cancer caused by inflammation, which affects the immune response and treatment outcomes. Finding new immune-related targets could improve HCC immunotherapy. New research suggests that TMEM family proteins can act as either tumor suppressors or oncogenes, but the role of TMEM101 in HCC development is unclear. This study conducted an analysis of TMEM101 mRNA expression and its correlation with clinical outcomes in HCC patients using RNA sequencing data from various open databases. Additionally, differences in TMEM101 expression in HCC cell lines and HCC tissue microarrays were examined using RT-qPCR, western blotting, and in situ hybridization staining. The findings presented herein offer initial evidence indicating a significant upregulation of TMEM101 mRNA expression in HCC, which is linked to a poorer prognosis. Furthermore, TMEM101 expression was found to be positively associated with the histological grade and clinical stage of HCC patients. Moreover, a notable reduction in promoter methylation of TMEM101 was observed in HCC patients. Cox regression analysis indicated that TMEM101 was an independent prognostic factor for overall survival (OS) in HCC patients. A nomogram incorporating TMEM101 and tumor stage was constructed and assessed. Comparative analysis with four established HCC diagnostic biomarkers (AFP, EFNA3, MDK, and SMYD5) using ROC curve and time-dependent ROC curves demonstrated the diagnostic potential of TMEM101 in HCC. Gene set enrichment analysis (GSEA) revealed a correlation between TMEM101 and the cell cycle, DNA replication, and repair signaling pathways, which were differentially enriched in the TMEM101 high expression phenotype. The findings from CIBERSORT analysis suggest that TMEM101's pro-tumor effect may be due to decreasing the number of anti-tumor immune cells (M1 macrophages and resting memory CD4+ T cells) and promoting M0 macrophage infiltration in the tumor microenvironment (TME). Overall, our study indicates that TMEM101 could serve as a promising diagnostic and prognostic biomarker for HCC.

Kuang L ，Pang Y ，Fang Q 《Scientific Reports》