SiRNA-HIF-1α delivered by attenuated Salmonella enhances the efficacy of Lenvatinib against hepatocellular carcinoma.

The treatment of hepatocellular carcinoma (HCC) remains a major challenge in the medical field. Lenvatinib, a multi-target tyrosine kinase inhibitor, has demonstrated anti-HCC effects by targeting and inhibiting pathways such as vascular endothelial growth factor receptor 1-3 (VEGFR1-3). However, the therapeutic efficacy of Lenvatinib is subject to various influences, with the hypoxic microenvironment of the tumor being a pivotal factor. Consequently, altering the hypoxic milieu of the tumor emerges as a viable strategy to augment the efficacy of Lenvatinib. Hypoxia-inducible factor-1α (HIF-1α), synthesized by tumor cells in response to oxygen-deprived conditions, regulates the expression of resistance genes, promotes tumor angiogenesis and cell proliferation, enhances tumor cell invasion, and confers resistance to radiotherapy and chemotherapy. Thus, we constructed a self-designed siRNA targeting HIF-1α to suppress its expression and improve the efficacy of Lenvatinib in treating HCC. The therapeutic efficacy of siRNA-HIF-1α in combination with Lenvatinib on HCC were evaluated through in vivo and in vitro experiments. The results showed that the recombinant Salmonella delivering siRNA-HIF-1α in combination with Lenvatinib effectively inhibited tumor growth and prolonged the survival of tumor-bearing mice. This treatment approach reduced cell proliferation and angiogenesis in HCC tissues while promoting tumor cell apoptosis. Additionally, this combined therapy significantly increased the infiltration of T lymphocytes and M1 macrophages within the tumor microenvironment, as well as elevated the proportion of immune cells in the spleen, thereby potentiating the host's immune response against the tumor.

Structural and biochemical characterization of active sites mutant in human inorganic pyrophosphatase.

Inorganic pyrophosphatases (PPases) are enzymes that catalyze the conversion of inorganic pyrophosphate (PPi) into phosphate (Pi). Human inorganic pyrophosphatase 1 (Hu-PPase) exhibits high expression levels in a variety of tumors and plays roles in cell proliferation, apoptosis, invasion and metastasis, making it a promising prognostic biomarker and a target for cancer therapy. Despite its widespread presence, the catalytic mechanism of Hu-PPase in humans remains inadequately understood. The signature motif amino acid sequence (DXDPXD) within the active sites of PPases is preserved across different species. In this research, an enzymatic activity assay revealed that mutations led to a notable reduction in enzymatic function, although the impact of the four amino acids on the activity of the pocket varied. To investigate the influence of these residues on the substrate binding and enzymatic function of PPase, the crystal structure of the Hu-PPase-ED quadruple mutant (D116A/D118A/P119A/D121A) was determined at 1.69 Å resolution. The resulting structure maintained a barrel-like shape similar to that of the wild-type, albeit lacking Mg2+ ions. Molecular docking analysis demonstrated a decreased ability of Hu-PPase-ED to bind to PPi. Further, molecular dynamics simulation analysis indicated that the mutation rendered the loop of Mg2+ ion-binding residues less stable. Therefore, the effect on enzyme activity did not result from a change in the gross protein structure but rather from a mutation that abolished the Mg2+-coordinating groups, thereby eliminating Mg2+ binding and leading to the loss of enzyme activity.

Autophagy-related gene PXN as a prognostic marker: Promotion of ovarian cancer progression by suppressing the p110ß/Vps34/Beclin1 pathway.

Among gynecological malignancies, ovarian cancer has the highest mortality rate and has sparked widespread interest in studying the mechanisms underlying ovarian cancer development. Based on TCGA and GEO databases, we investigated the highly expressed autophagy-related genes that determine patient prognosis using limma differential expression and Kaplan-Meier survival analyses. The biological processes associated with these genes were also predicted using GO/KEGG functional enrichment analysis. CCK-8, cell scratch, and transwell assays were used to investigate the effects of PXN on the proliferation, migration, and invasion abilities of ovarian cancer cells. Transmission electron microscopy was used to observe the autophagosomes. The expression of autophagy proteins and the PI3K/Akt/mTOR and p110ß/Vps34/Beclin1 pathway proteins in ovarian cancer cells was detected using western blot; autophagy protein expression was further detected and localized using cellular immunofluorescence. A total of 724 autophagy-related genes were found to be overexpressed in ovarian -cancer tissues, with high expression of PEX3, PXN, and RB1 associated with poor prognosis in patients (p < .05). PXN activates and regulates signaling pathways related to cellular autophagy, ubiquitination, lysosomes, PI3K-Akt, and mTOR. Autophagosomes were observed in all cell groups. The increase in PXN gene expression promoted the proliferation, migration, and invasion of ovarian cancer cells, increased the expression of SQSTM1/p62 protein, decreased LC3II/LC3Ⅰ, inhibited the phosphorylation of Akt and mTOR proteins, and suppressed the expression of PI3K(p110ß) and Beclin1 proteins. The decrease in PXN expression also confirmed these changes. Thus, PXN is highly expressed during ovarian cancer and is associated with poor patient prognosis. It may promote ovarian cancer cell proliferation, migration, and invasion by inhibiting cellular autophagy via suppression of the p110ß/Vps34/Beclin1 pathway.

Significance of Immunogenic Cell Death-Related Prognostic Gene Signature in Cervical Cancer Prognosis and Anti-Tumor Immunity.

Background: Immunogenic cell death (ICD) can reshape the immune microenvironment of tumors. Driven by stressful pressure, by directly destroying tumor cells and activating the body's adaptive immunity, ICD acts as a modulator of cell death, enabling the body to generate an anti-tumor immune response that produces a more effective therapeutic effect, while tumor cells are driven to kill. Hence, this research aimed to find and evaluate ICD-related genetic signatures as cervical cancer (CC) prognostic factors. Methods: Data of CC patients from the Tumor Genome Atlas (TCGA) were used as the basis to obtain immunogenic cell-death-related prognostic genes (IPGs) in patients with CC, using the least absolute shrinkage and selection operator and Cox regression screening, and the IPGs scoring system was constructed to classify patients into high- and low-risk groups, with the Gene Expression Omnibus (GEO) dataset as the validation group. Finally, the difference analysis of single-sample gene set enrichment analysis, tumor microenvironment (TME), immune cells, tumor mutational burden, and chemotherapeutic drug sensitivity between the high-risk and low-risk groups was investigated. Results: A prognostic model with four IPGs (PDIA3, CASP8, IL1, and LY96) was developed, and it was found that the group of CC patients with a higher risk score of IPGs expression had a lower survival rate. Single and multifactor Cox regression analysis also showed that this risk score was a reliable predictor of overall survival. In comparison to the low-risk group, the high-risk group had lower TME scores and immune cell infiltration, and gene set variation analysis showed that immune-related pathways were more enriched in the high-risk group. Conclusion: A risk model constructed from four IPGs can independently predict the prognosis of CC patients and recommend more appropriate immunotherapy strategies for patients.

Performance of a PLK1-based immune risk model for prognosis and treatment response prediction in breast cancer.

OBJECTIVE: Polo-like kinase 1 (PLK1), a serine/threonine-protein kinase, functions as a potent oncogene in the initiation and progression of tumor. The aim of this study is to assess potential correlations between PLK1 expression and immune infiltration in breast cancer (BRCA) and construct a PLK1-based immune risk model applicable for prognosis and treatment response prediction in BRCA. METHODS: We collected data on PLK1 gene expression in BRCA patients from The Cancer Genome Atlas (TCGA) database. Thereafter, we analyzed the associations of PLK1 expression with immune cell infiltration and immunomodulators, and established a prognostic risk model based on seven PLK1-associated immunomodulator genes and a nomogram for survival prediction. RESULTS: BRCA prognosis, clinical stage progression, and tumor classification were all shown to be substantially correlated with PLK1 expression. The PLK1 gene was significantly enriched in T cell and B cell receptors and molecules of the chemokine signaling pathways. Specifically, PLK1 expression was positively correlated with the CD8+ T cell and regulatory T cell (Tregs) activation and negatively correlated with M2 macrophage infiltration. The seven-genes-based risk model could serve as an independent prognostic factor of BRCA. The risk model was markedly correlated with the expression of programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1; both p < 0.001) immune checkpoints, and tumor mutation burden (TMB). High- and low-risk BRCA patients identified by the risk model responded differently to anti-PD-1 and/or anti-CTLA4 therapy, as well as common chemotherapy drugs, like cisplatin, paclitaxel, and gemcitabine. CONCLUSION: This PLK1-based immune risk model can effectively predict the prognosis and tumor progression of BRCA, identify gene mutations, and evaluate patient's response toward immunotherapy and chemotherapy regimens.

Altered Gut Microbiota Composition and Its Potential Association in Patients with Advanced Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the second-most-common cause of cancer death. In recent years, studies have suggested that intestinal microbiota dysregulation is closely related to HCC and can affect the therapeutic efficacy of immune checkpoint inhibitors. However, there are few data on the relationship between altered gut microbiota composition and its potential association in patients with advanced hepatocellular carcinoma. Hence, in this study, we aimed to investigate the gut microbiota profile associated with advanced hepatocarcinoma. In total, 20 patients with advanced hepatocarcinoma and 20 matched healthy participants were recruited. Stool samples were collected for 16S rRNA sequencing to confirm intestinal microbiota dysbiosis. The results showed that the Nseqs index in advanced hepatocarcinoma patients was significantly different compared with that in healthy individuals, while the butyrate-producing bacteria decreased and LPS-producing bacteria increased. Meanwhile, Lactobacillus, Anaerostipes, Fusicatenibacter, Bifidobacterium, and Faecalibacterium were significantly correlated with AFP, ALT, AST, and PIVKA. Our findings characterized the gut microbiota composition of advanced hepatocarcinoma, providing an experimental basis and theoretical support for using microbiota to regulate immunotherapy, achieve potential biomarkers for diagnosis, and improve the effect of clinical treatment for patients with advanced hepatocarcinoma.