Autophagy-related gene LAPTM4B promotes the progression of renal clear cell carcinoma and is associated with immunity

HDAC2 promotes autophagy-associated HCC malignant progression by transcriptionally activating LAPTM4B

Hepatocellular carcinoma (HCC) is a significant global health challenge. The activation of autophagy plays an essential role in promoting the proliferation and survival of cancer cells. However, the upstream regulatory network and mechanisms governing autophagy in HCC remain unclear. This study demonstrated that histone deacetylase 2 (HDAC2) regulates autophagy in HCC. Its expression was elevated in HCC tissues, and high HDAC2 expression was strongly associated with poor prognosis in individuals with HCC. Integrated in vitro and in vivo investigations confirmed that HDAC2 promotes autophagy and autophagy-related malignant progression in HCC. Mechanistically, HDAC2 bound specifically to the lysosome-associated protein transmembrane 4-β (LAPTM4B) promoter at four distinct binding sites, enhancing its transcriptional activation and driving autophagy-related malignant progression in HCC. These findings establish LAPTM4B as a direct target gene of HDAC2. Furthermore, the selective inhibitor of HDAC2 effectively alleviated the malignant development of HCC. In addition, multivariate Cox regression analysis of 105 human HCC samples revealed that HDAC2 expression is an independent predictor of HCC prognosis. This study underscores the crucial role of the HDAC2-LAPTM4B axis in regulating autophagy in the malignant evolution of HCC and highlights the potential of targeting HDAC2 to prevent and halt the malignant progression of HCC.

Prognostic Risk Models Using Epithelial Cells Identify β-Sitosterol as a Potential Therapeutic Target Against Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is an aggressive and fatal malignancy that leads to epithelial cancer. The association between epithelial cell heterogeneity, prognosis, and immune response in this cancer remains uncertain. This study aimed to investigate epithelial cell heterogeneity in ESCC and develop a predictive risk model using the identified cell types.

Methods

Single-cell RNA sequencing (scRNA-seq) and differential ESCC gene data were accessed from the Gene Expression Omnibus. Functional enrichment analysis, inferCNV, cell development trajectories, and intercellular communication were analyzed following epithelial cell characterization. Differentially expressed ESCC (n = 773) and epithelial cell marker genes (n = 3407) were intersected to obtain core genes, and epithelial cell-related prognostic genes were identified. LASSO regression analysis was used to construct a prognostic model. The external dataset GSE53624 was used to further validate the stability of the model. Drug sensitivity predictions, and immune cell infiltration were analyzed. Molecular docking clarified the possible therapeutic role of β-sitosterol in ESCC. Finally, wound healing assay, cell colony, and transwell assay were constructed to detect the effects of the core gene PDLIM2 on ESCC cell proliferation, invasion, and migration.

Results

Eight cell clusters were identified, and epithelial cells were categorized into tumor and paratumor groups. The tumor group possessed more chromosomal variants than the paratumor group. Epithelial cells were associated with multiple cell types and significantly correlated with the Wnt, transforming growth factor, and epidermal growth factor signaling pathways. From 231 intersected genes, five core genes were screened for use in the risk model: CTSL, LAPTM4B, MYO10, NCF2, and PDLIM2. These genes may contribute to the cancerous transformation of normal esophageal epithelial cells and thereby act as biomarkers and potential therapeutic targets in patients with ESCC. β-Sitosterol furthermore displayed excellent docking potential with these genes. Meanwhile, further experiments demonstrated that the gene PDLIM2 plays a major role in the progression of oesophageal squamous carcinoma.

Conclusion

We successfully developed a risk model for the prognosis of ESCC based on epithelial cells that addresses the response of ESCC to immunotherapy and offers novel cancer treatment options.

The significance of targeting lysosomes in cancer immunotherapy

Lysosomes are intracellular digestive organelles that participate in various physiological and pathological processes, including the regulation of immune checkpoint molecules, immune cell function in the tumor microenvironment, antigen presentation, metabolism, and autophagy. Abnormalities or dysfunction of lysosomes are associated with the occurrence, development, and drug resistance of tumors. Lysosomes play a crucial role and have potential applications in tumor immunotherapy. Targeting lysosomes or harnessing their properties is an effective strategy for tumor immunotherapy. However, the mechanisms and approaches related to lysosomes in tumor immunotherapy are not fully understood at present, and further basic and clinical research is needed to provide better treatment options for cancer patients. This review focuses on the research progress related to lysosomes and tumor immunotherapy in these.

Blockade of V-domain immunoglobulin suppressor of T-cell activation reprograms tumour-associated macrophages and improves efficacy of PD-1 inhibitor in gastric cancer

BACKGROUND AND AIMS

In gastric cancer, the response rate of programmed cell death protein-1 (PD-1) inhibitor is far from satisfactory, indicating additional nonredundant pathways might hamper antitumour immunity. V-domain immunoglobulin suppressor of T-cell activation (VISTA) has been reported in several malignancies as a novel immune-checkpoint. Nevertheless, the role of VISTA in gastric cancer still remains obscure. Our purpose is to explore the clinical significance and potential mechanism of VISTA in affecting gastric cancer patients' survival and immunotherapeutic responsiveness.

METHODS

Our study recruited eight independent cohorts with a total of 1403 gastric cancer patients. Immunohistochemistry, multiplex immunofluorescence, flow cytometry or intracellular flow cytometry, quantitative polymerase chain reaction, western blotting, fluorescence-activated cell sorting, magnetic-activated cell sorting, smart-seq2, in vitro cell co-culture and ex vivo tumour inhibition assays were applied to investigate the clinical significance and potential mechanism of VISTA in gastric cancer.

RESULTS

VISTA was predominantly expressed on tumour-associated macrophages (TAMs), and indicated poor clinical outcomes and inferior immunotherapeutic responsiveness. VISTA+ TAMs showed a mixed phenotype. Co-culture of TAMs and CD8+ T cells indicated that VISTA+ TAMs attenuated effective function of CD8+ T cells. Blockade of VISTA reprogrammed TAMs to a proinflammatory phenotype, reactivated CD8+ T cells and promoted apoptosis of tumour cells. Moreover, blockade of VISTA could also enhance the efficacy of PD-1 inhibitor, suggesting that blockade of VISTA might synergise with PD-1 inhibitor in gastric cancer.

CONCLUSIONS

Our data revealed that VISTA was an immune-checkpoint associated with immunotherapeutic resistance. Blockade of VISTA reprogrammed TAMs, promoted T-cell-mediated antitumour immunity, and enhanced efficacy of PD-1 inhibitor, which might have implications in the treatment of gastric cancer.

Genes associated with inflammation for prognosis prediction for clear cell renal cell carcinoma: a multi-database analysis

Background

Clear cell renal cell carcinoma (ccRCC) is the largest subtype of kidney tumour, with inflammatory responses characterising all stages of the tumour. Establishing the relationship between the genes related to inflammatory responses and ccRCC may help the diagnosis and treatment of patients with ccRCC.

Methods

First, we obtained the data for this study from a public database. After differential analysis and Cox regression analysis, we obtained the genes for the establishment of a prognostic model for ccRCC. As we used data from multiple databases, we standardized all the data using the surrogate variable analysis (SVA) package to make the data from different sources comparable. Next, we used a least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model of genes related to inflammation. The data used for modelling and internal validation came from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (GSE29609) databases. ccRCC data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Tumour data from the E-MTAB-1980 cohort were used for external validation. The GSE40453 and GSE53757 datasets were used to verify the differential expression of inflammation-related gene model signatures (IRGMS). The immunohistochemistry of IRGMS was queried through the Human Protein Atlas (HPA) database. After the adequate validation of the IRGM, we further explored its application by constructing nomograms, pathway enrichment analysis, immunocorrelation analysis, drug susceptibility analysis, and subtype identification.

Results

The IRGM can robustly predict the prognosis of samples from patients with ccRCC from different databases. The verification results show that nomogram can accurately predict the survival rate of patients. Pathway enrichment analysis showed that patients in the high-risk (HR) group were associated with a variety of tumorigenesis biological processes. Immune-related analysis and drug susceptibility analysis suggested that patients with higher IRGM scores had more treatment options.

Conclusions

The IRGMS can effectively predict the prognosis of ccRCC. Patients with higher IRGM scores may be better candidates for treatment with immune checkpoint inhibitors and have more chemotherapy options.