A novel lysosome-related gene signature coupled with gleason score for prognosis prediction in prostate cancer

Interferon Gamma Inducible Protein 30: from biological functions to potential therapeutic target in cancers

Interferon Gamma Inducible Protein 30 (IFI30), also known as Gamma-Interferon-Inducible Lysosomal Thiol Reductase (GILT), is predominantly found in lysosomes and the cytoplasm. As the sole enzyme identified to catalyze disulfide bond reduction in the endocytic pathway, IFI30 contributes to both major histocompatibility complex (MHC) class I-restricted antigen cross-presentation and MHC class II-restricted antigen processing by decreasing the disulfide bonds of endocytosed proteins. Remarkably, emerging research has revealed that IFI30 is involved in tumorigenesis, tumor development, and the tumor immune response. Targeting IFI30 may provide new strategies for cancer therapy and improve the prognosis of patients. This review provided a comprehensive overview of the research progress on IFI30 in tumor progression, cellular redox status, autophagy, tumor immune response, and drug sensitivity, with a view to providing the theoretical basis for pharmacological intervention of IFI30 in tumor therapy, particularly in immunotherapy.

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.

Molecular subtype identification and prognosis stratification based on lysosome-related genes in breast cancer

Background

Lysosomes are known to have a significant impact on the development and recurrence of breast cancer. However, the association between lysosome-related genes (LRGs) and breast cancer remains unclear. This study aims to explore the potential role of LRGs in predicting the prognosis and treatment response of breast cancer.

Methods

Breast cancer gene expression profile data and clinical information were downloaded from TCGA and GEO databases, and prognosis-related LRGs were screened for consensus clustering analysis. Lasso Cox regression analysis was used to construct risk features derived from LRGs, and immune cell infiltration, immune therapy response, drug sensitivity, and clinical pathological feature differences were evaluated for different molecular subtypes and risk groups. A nomogram based on risk features derived from LRGs was constructed and evaluated.

Results

Our study identified 176 differentially expressed LRGs that are associated with breast cancer prognosis. Based on these genes, we divided breast cancer into two molecular subtypes with significant prognostic differences. We also found significant differences in immune cell infiltration between these subtypes. Furthermore, we constructed a prognostic risk model consisting of 7 LRGs, which effectively divides breast cancer patients into high-risk and low-risk groups. Patients in the low-risk group have better prognostic characteristics, respond better to immunotherapy, and have lower sensitivity to chemotherapy drugs, indicating that the low-risk group is more likely to benefit from immunotherapy and chemotherapy. Additionally, the risk score based on LRGs is significantly correlated with immune cell infiltration, including CD8 T cells and macrophages. This risk score model, along with age, chemotherapy, clinical stage, and N stage, is an independent prognostic factor for breast cancer. Finally, the nomogram composed of these factors has excellent performance in predicting overall survival of breast cancer.

Conclusions

In conclusion, this study has constructed a novel LRG-derived breast cancer risk feature, which performs well in prognostic prediction when combined with clinical pathological features.

Integrating Lysosomal Genes and Immune Infiltration for Multiple Myeloma Subtyping and Prognostic Stratification

Lysosomes are crucial in the tumour immune microenvironment, which is essential for the survival and homeostasis in multiple myeloma (MM). Here, we aimed to identify lysosome-related genes for the prognosis of MM and predicted their regulatory mechanisms. Gene expression profiles of MM from the GSE2658 and GSE57317 datasets were analysed. Lysosome-related differentially expressed genes (DEGs) were identified and used for molecular subtyping of MM patients. A prognostic model was constructed using univariate Cox regression and LASSO regression analyses. The relationship between prognostic genes, immune cell types, and autophagy pathways was assessed through correlation analysis. RT-qPCR was performed to validate the expression of prognostic genes in MM cells. A total of 9,954 DEGs were identified between high and low immune score groups, with 213 intersecting with lysosomal genes. Molecular subtyping revealed two distinct MM subtypes with significant differences in immune cell types and autophagy pathway activities. Five lysosome-related DEGs (CORO1A, ELANE, PSAP, RNASE2, and SNAPIN) were identified as significant prognostic markers. The prognostic model showed moderate predictive accuracy with AUC values up to 0.723. Prognostic genes demonstrated significant correlations with various immune cell types and autophagy pathways. Additionally, CORO1A, PSAP and RNASE2 expression was up-regulated in MM cells, while ELANE and SNAPIN were down-regulated. Five lysosomal genes in MM were identified, and a new risk model for prognosis was developed using these genes. This research could lead to discovering important gene markers for the treatment and prognosis of MM.