Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts.

BACKGROUND: Tumor heterogeneity presents a formidable challenge in understanding the mechanisms driving tumor progression and metastasis. The heterogeneity of hepatocellular carcinoma (HCC) in cellular level is not clear. METHODS: Integration analysis of single-cell RNA sequencing data and spatial transcriptomics data was performed. Multiple methods were applied to investigate the subtype of HCC tumor cells. The functional characteristics, translation factors, clinical implications and microenvironment associations of different subtypes of tumor cells were analyzed. The interaction of subtype and fibroblasts were analyzed. RESULTS: We established a heterogeneity landscape of HCC malignant cells by integrated 52 single-cell RNA sequencing data and 5 spatial transcriptomics data. We identified three subtypes in tumor cells, including ARG1+ metabolism subtype (Metab-subtype), TOP2A+ proliferation phenotype (Prol-phenotype), and S100A6+ pro-metastatic subtype (EMT-subtype). Enrichment analysis found that the three subtypes harbored different features, that is metabolism, proliferating, and epithelial-mesenchymal transition. Trajectory analysis revealed that both Metab-subtype and EMT-subtype originated from the Prol-phenotype. Translation factor analysis found that EMT-subtype showed exclusive activation of SMAD3 and TGF-ß signaling pathway. HCC dominated by EMT-subtype cells harbored an unfavorable prognosis and a deserted microenvironment. We uncovered a positive loop between tumor cells and fibroblasts mediated by SPP1-CD44 and CCN2/TGF-ß-TGFBR1 interaction pairs. Inhibiting CCN2 disrupted the loop, mitigated the transformation to EMT-subtype, and suppressed metastasis. CONCLUSION: By establishing a heterogeneity landscape of malignant cells, we identified a three-subtype classification in HCC. Among them, S100A6+ tumor cells play a crucial role in metastasis. Targeting the feedback loop between tumor cells and fibroblasts is a promising anti-metastatic strategy.

Construction of a Cancer Stem Cell related Histone Acetylation Regulatory Genes Prognostic Model for Hepatocellular Carcinoma via Bioinformatics Analysis: Implications for Tumor Chemotherapy and Immunity.

BACKGROUND: Cancer stem cells (CSC) play an important role in the development of Liver Hepatocellular Carcinoma (LIHC). However, the regulatory mechanisms between acetylation- associated genes (HAGs) and liver cancer stem cells remain unclear. OBJECTIVE: To identify a set of histone acetylation genes (HAGs) with close associations to liver cancer stem cells (LCSCs), and to construct a prognostic model that facilitates more accurate prognosis assessments for LIHC patients. METHODS: LIHC expression data were downloaded from the public databases. Using mRNA expression- based stemness indices (mRNAsi) inferred by One-Class Logistic Regression (OCLR), Differentially Expressed Genes (DEGs) (mRNAsi-High VS. mRNAsi-Low groups) were intersected with DEGs (LIHC VS. normal samples), as well as histone acetylation-associated genes (HAGs), to obtain mRNAsi-HAGs. A risk model was constructed employing the prognostic genes, which were acquired through univariate Cox and Least Shrinkage and Selection Operator (LASSO) regression analyses. Subsequently, independent prognostic factors were identified via univariate and multivariate Cox regression analyses and then a nomogram for prediction of LIHC survival was developed. Additionally, immune infiltration and drug sensitivity analysis were performed to explore the relationships between prognostic genes and immune cells. Finally, the expressions of selected mRNAsi-HAGs were validated in the LIHC tumor sphere by quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) assay and western blot analysis. RESULTS: Among 13 identified mRNAsi-HAGs, 3 prognostic genes (HDAC1, HDAC11, and HAT1) were selected to construct a risk model (mRNAsi-HAGs risk score = 0.02 * HDAC1 + 0.09 * HAT1 + 0.05 * HDAC11). T-stage, mRNAsi, and mRNAsi-HAGs risk scores were identified as independent prognostic factors to construct the nomogram, which was proved to predict the survival probability of LIHC patients effectively. We subsequently observed strongly positive correlations between mRNAsi-HAGs risk score and tumor-infiltrating T cells, B cells and macrophages/monocytes. Moreover, we found 8 drugs (Mitomycin C, IPA 3, FTI 277, Bleomycin, Tipifarnib, GSK 650394, AICAR and EHT 1864) had significant correlations with mRNAsi-HAGs risk scores. The expression of HDAC1 and HDAC11 was higher in CSC-like cells in the tumor sphere. CONCLUSION: This study constructed a mRNAsi and HAGs-related prognostic model, which has implications for potential immunotherapy and drug treatment of LIHC.

Study on the Efficacy and Safety of the Huangqi Guizhi Wuwu Decoction in the Prevention and Treatment of Chemotherapy-Induced Peripheral Neuropathy: Meta-Analysis of 32 Randomized Controlled Trials.

Purpose: Chemotherapy-induced peripheral neuropathy (CIPN) still lacks efficient therapeutic drugs. This study aimed to systematically evaluate the effects of Huangqi Guizhi Wuwu Decoction (HGWD) alone or combined with positive drugs on CIPN prevention and treatment. Methods: The PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure (CNKI), Wan Fang Data, China Science and Technology Journal (VIP) and Chinese Biomedical (CBM) databases were searched for randomized controlled trials (RCTs) of HGWD for CIPN prevention and treatment. The search time ranged from database establishment to October 17, 2023. The Cochrane risk-of-bias assessment tool was used for quality assessment, Review Manager 5.3 and STATA 12.0 were used for meta-analysis, and GRADEprofiler was used for evidence level assessment. Results: A total of 32 RCTs involving 1987 patients were included. The meta-analysis results revealed the following: 1. In terms of the total CIPN incidence, that in the HGWD group was lower than that in the blank control group. The incidence in both the HGWD and HGWD+positive drug groups was lower than that in the monotherapy-positive drug group. 2. In terms of the incidence of severe CIPN, that in the HGWD group was lower than that in the blank control and positive drug groups. There was no statistically significant difference between the HGWD+positive drug and positive drug groups. Sensitivity analysis revealed that the results of severe incidence in the HGWD group was lower than that in the positive drug group were unstable 3. HGWD did not increase the number of chemotherapy-related adverse events. Conclusion: HGWD can safely and effectively prevent CIPN, reduce symptoms, improve quality of life and reduce the impact of chemotherapy drugs on sensory nerve conduction. However, more high-quality RCTs are needed to compare the efficacy of HGWD with that of positive control drugs in preventing severe CIPN.

Anlotinib potentiates anti-PD1 immunotherapy via transferrin receptor-dependent CD8+ T-cell infiltration in hepatocellular carcinoma.

BACKGROUND: The therapeutic potential of immune checkpoint blockade (ICB) extends across various cancers; however, its effectiveness in treating hepatocellular carcinoma (HCC) is frequently curtailed by both inherent and developed resistance. OBJECTIVE: This research explored the effectiveness of integrating anlotinib (a broad-spectrum tyrosine kinase inhibitor) with programmed death-1 (PD-1) blockade and offers mechanistic insights into more effective strategies for treating HCC. METHODS: Using patient-derived organotypic tissue spheroids and orthotopic HCC mouse models, we assessed the effectiveness of anlotinib combined with PD-1 blockade. The impact on the tumour immune microenvironment and underlying mechanisms were assessed using time-of-flight mass cytometry, RNA sequencing, and proteomics across cell lines, mouse models, and HCC patient samples. RESULTS: The combination of anlotinib with an anti-PD-1 antibody enhanced the immune response against HCC in preclinical models. Anlotinib remarkably suppressed the expression of transferrin receptor (TFRC) via the VEGFR2/AKT/HIF-1α signaling axis. CD8+ T-cell infiltration into the tumour microenvironment correlated with low expression of TFRC. Anlotinib additionally increased the levels of the chemokine CXCL14, crucial for attracting CD8+ T cells. CXCL14 emerged as a downstream effector of TFRC, exhibiting elevated expression following the silencing of TFRC. Importantly, low TFRC expression was also associated with a better prognosis, enhanced sensitivity to combination therapy, and a favourable response to anti-PD-1 therapy in patients with HCC. CONCLUSIONS: Our findings highlight anlotinib's potential to augment the efficacy of anti-PD-1 immunotherapy in HCC by targeting TFRC and enhancing CXCL14-mediated CD8+ T-cell infiltration. This study contributes to developing novel therapeutic strategies for HCC, emphasizing the role of precision medicine in oncology. HIGHLIGHTS: Synergistic effects of anlotinib and anti-PD-1 immunotherapy demonstrated in HCC preclinical models. Anlotinib inhibits TFRC expression via the VEGFR2/AKT/HIF-1α pathway. CXCL14 upregulation via TFRC suppression boosts CD8+ T-cell recruitment. TFRC emerges as a potential biomarker for evaluating prognosis and predicting response to anti-PD-1-based therapies in advanced HCC patients.

Early detection and prognosis evaluation for hepatocellular carcinoma by circulating tumour DNA methylation: A multicentre cohort study.

BACKGROUND: Early diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood-based assay to aid in the diagnosis, detection and prognostic evaluation of HCC. METHODS: A three-phase multicentre study was conducted to screen, optimise and validate HCC-specific differentially methylated regions (DMRs) using next-generation sequencing and quantitative methylation-specific PCR (qMSP). RESULTS: Genome-wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre- and postoperative plasma samples from 103 HCC patients and correlated with 2-year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p < .001). CONCLUSIONS: HepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC-specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at-risk populations.