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.

Icariin Ameliorates D-galactose-induced Cell Injury in Neuron-like PC12 Cells by Inhibiting MPTP Opening.

OBJECTIVE: Icariin (ICA) has a good neuroprotective effect and can upregulate neuronal basal autophagy in naturally aging rats. Mitochondrial dysfunction is associated with brain aging-related neurodegenerative diseases. Abnormal opening of the mitochondrial permeability transition pore (mPTP) is a crucial factor in mitochondrial dysfunction and is associated with excessive autophagy. This study aimed to explore that ICA protects against neuronal injury by blocking the mPTP opening and down-regulating autophagy levels in a D-galactose (D-gal)-induced cell injury model. METHODS: A cell model of neuronal injury was established in rat pheochromocytoma cells (PC12 cells) treated with 200 mmol/L D-gal for 48 h. In this cell model, PC12 cells were pre-treated with different concentrations of ICA for 24 h. MTT was used to detect cell viability. Senescence associated ß-galactosidase (SA-ß-Gal) staining was used to observe cell senescence. Western blot analysis was performed to detect the expression levels of a senescence-related protein (p21), autophagy markers (LC3B, p62, Atg7, Atg5 and Beclin 1), mitochondrial fission and fusion-related proteins (Drp1, Mfn2 and Opa1), and mitophagy markers (Pink1 and Parkin). The changes of autophagic flow were detected by using mRFP-GFP-LC3 adenovirus. The intracellular ultrastructure was observed by transmission electron microscopy. Immunofluorescence was used to detect mPTP, mitochondrial membrane potential (MMP), mitochondrial reactive oxygen species (mtROS) and ROS levels. ROS and apoptosis levels were detected by flow cytometry. RESULTS: D-gal treatment significantly decreased the viability of PC12 cells, and markedly increased the SA-ß-Gal positive cells as compared to the control group. With the D-gal stimulation, the expression of p21 was significantly up-regulated. Furthermore, D-gal stimulation resulted in an elevated LC3B II/I ratio and decreased p62 expression. Meanwhile, autophagosomes and autolysosomes were significantly increased, indicating abnormal activation of autophagy levels. In addition, in this D-gal-induced model of cell injury, the mPTP was abnormally open, the ROS generation was continuously increased, the MMP was gradually decreased, and the apoptosis was increased. ICA effectively improved mitochondrial dysfunction to protect against D-gal-induced cell injury and apoptosis. It strongly inhibited excessive autophagy by blocking the opening of the mPTP. Cotreatment with ICA and an mPTP inhibitor (cyclosporin A) did not ameliorate mitochondrial dysfunction. However, the protective effects were attenuated by cotreatment with ICA and an mPTP activator (lonidamine). CONCLUSION: ICA inhibits the activation of excessive autophagy and thus improves mitochondrial dysfunction by blocking the mPTP opening.

PANoptosis-based molecular subtyping and HPAN-index predicts therapeutic response and survival in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a highly prevalent and fatal cancer. The role of PANoptosis, a novel form of programmed cell death, in HCC is yet to be fully understood. This study focuses on identifying and analyzing PANoptosis-associated differentially expressed genes in HCC (HPAN_DEGs), aiming to enhance our understanding of HCC pathogenesis and potential treatment strategies. Methods: We analyzed HCC differentially expressed genes from TCGA and IGCG databases and mapped them to the PANoptosis gene set, identifying 69 HPAN_DEGs. These genes underwent enrichment analyses, and consensus clustering analysis was used to determine three distinct HCC subgroups based on their expression profiles. The immune characteristics and mutation landscape of these subgroups were evaluated, and drug sensitivity was predicted using the HPAN-index and relevant databases. Results: The HPAN_DEGs were mainly enriched in pathways associated with the cell cycle, DNA damage, Drug metabolism, Cytokines, and Immune receptors. We identified three HCC subtypes (Cluster_1, SFN+PDK4-; Cluster_2, SFN-PDK4+; Cluster_3, SFN/PDK4 intermediate expression) based on the expression profiles of the 69 HPAN_DEGs. These subtypes exhibited distinct clinical outcomes, immune characteristics, and mutation landscapes. The HPAN-index, generated by machine learning using the expression levels of 69 HPAN_DEGs, was identified as an independent prognostic factor for HCC. Moreover, the high HPAN-index group exhibited a high response to immunotherapy, while the low HPAN-index group showed sensitivity to small molecule targeted drugs. Notably, we observed that the YWHAB gene plays a significant role in Sorafenib resistance. Conclusion: This study identified 69 HPAN_DEGs crucial to tumor growth, immune infiltration, and drug resistance in HCC. Additionally, we discovered three distinct HCC subtypes and constructed an HPAN-index to predict immunotherapeutic response and drug sensitivity. Our findings underscore the role of YWHAB in Sorafenib resistance, presenting valuable insights for personalized therapeutic strategy development in HCC.

Uncovering the mechanism of Kang-ai injection for treating intrahepatic cholangiocarcinoma based on network pharmacology, molecular docking, and in vitro validation.

Objective: Kang-ai injection (KAI) has been a popular adjuvant treatment for solid tumors, but its anti-tumor mechanism in intrahepatic cholangiocarcinoma (ICC) remains poorly understood. This study applied a network pharmacology-based approach to unveil KAI's anti-tumor activity, key targets, and potential pharmacological mechanism in ICC by integrating molecular docking and in vitro validation. Methods: The KAI-compound-target-ICC network was constructed to depict the connections between active KAI compounds and ICC-related targets based on the available data sources. The crucial ingredients, potential targets, and signaling pathways were screened using GO, KEGG enrichment analysis, and the PPI network. Molecular docking was performed to visualize the interactions between hub targets and components. In vitro experiments were carried out to validate the findings. Results: Among the 87 active components of KAI and 80 KAI-ICC-related targets, bioinformatics analysis identified quercetin as a possible candidate. GO and KEGG enrichment analysis indicated that the PI3K-AKT signaling pathway might be essential in ICC pharmacotherapy. The PPI network and its sub-networks screened 10 core target genes, including AKT1 and IL1ß. Molecular docking results showed stable binding between AKT1 and IL1ß with KAI active ingredients. The in vitro experiments confirmed that KAI might suppress the proliferation of ICC cell lines by inhibiting the PI3K/AKT signaling pathway, consistent with the network pharmacology approach and molecular docking predictions. Conclusion: The study sheds light on KAI's biological activity, potential targets, and molecular mechanisms in treating ICC and provides a promising strategy for understanding the scientific basis and therapeutic mechanisms of herbal treatments for ICC. This research has important implications for developing new, targeted therapies for ICC and highlights the importance of network pharmacology-based approaches in investigating complex herbal formulations.