Four hub genes regulate tumor infiltration by immune cells, antitumor immunity in the tumor microenvironment, and survival outcomes in lung squamous cell carcinoma patients

Lysosomal transmembrane protein 5: Impact on immune cell function and implications for immune-related deficiencies

Lysosomal transmembrane protein 5 (LAPTM5) is a lysosomal-associated protein that interacts with surface receptors on various immune cells, including B cells, T cells, macrophages and dendritic cells. Dysregulated expression of LAPTM5 is implicated in the development of multiple immune system-related diseases. In the context of tumors, elevated LAPTM5 levels in immune cells are associated with decreased cell membrane levels of T cell receptors (TCR) or B cell receptors (BCR), leading to impaired antigen presentation and immune escape, thereby promoting tumor progression. Besides, LAPTM5 is critical for inducing non-apoptotic cell death in tumor parenchymal cells since its downregulation leads to inhibition of the cell death pathway in the tumor parenchyma and subsequent enhanced tumorigenesis. LAPTM5 also affects the cell cycle as the elevated LAPTM5 expression in solid tumors causes its inability to block the G0/G1 stage. In non-solid tumors, abnormal LAPTM5 expression disrupts blood cell development and causes irregular proliferation. Furthermore, in the nervous system, aberrant LAPTM5 expression in microglia is correlated with Alzheimer's disease severity. In this context, further preclinical research is essential to validate LAPTM5 as a potential target for diagnosis, therapy, and prognosis in immune-related disorders and tumors. This review summarized the current insights into LAPTM5's role in tumors and immune-related deficits, highlighting its potential as a valuable biomarker and therapeutic target.

The function and mechanism of LAPTM5 in diseases

The Lysosomal Protein Transmembrane 5 (LAPTM5) is a lysosomal transmembrane protein preferentially expressed in hematopoietic cells. The human LAPTM5 gene is located at position 1p34 and extends approximately 25 kb. Its protein includes five transmembrane domains, three PY motifs, and one UIM. The PY and UIM motifs can interact with various substrates, mediating sorting of proteins from Golgi to lysosome and subsequently participating in intracellular substrate transport and lysosomal stability regulation. Overexpression of LAPTM5 can induce lysosomal cell death (LCD), although the integrity of LAPTM5 protein is necessary for maintaining lysosome stability. Furthermore, LAPTM5 plays a role in autophagy activation during disease processes and has been confirmed to be closely associated with the regulation of immunity and inflammation. Therefore, LAPTM5 regulates a wide range of physiological processes and is involved in various diseases. This article summarizes the characteristics of the LAPTM5 gene and protein structure and provides a comprehensive review of the mechanisms involved in cell death, autophagy, immunity, and inflammation regulation. It emphasizes the significance of LAPTM5 in the clinical prevention and treatment of cardiovascular diseases, immune system disorders, viral infections, cancer, and other diseases, which could provide new therapeutic ideas and targets for human diseases.

C1QC is a prognostic biomarker with immune-related value in kidney renal clear cell carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is a representative histologic subtype of renal cell carcinoma (RCC). RCC exhibits a strong immunogenicity with a prominent dysfunctional immune infiltration. Complement C1q C chain (C1QC) is a polypeptide in serum complement system and is involved in tumorigenesis and the modulation of tumor microenvironment (TME). However, researches have not explored the effect of C1QC expression on prognosis and tumor immunity of KIRC. Methods: The difference in a wide variety of tumor tissues and normal tissues in terms of the C1QC expression was detected using TIMER and TCGA portal databases, and further validation of protein expression of C1QC was conducted via Human Protein Atlas. Then, the associations of C1QC expression with clinicopathological data and other genes were studied with the use of UALCAN database. Subsequently, the association of C1QC expression with prognosis was predicted by searching the Kaplan-Meier plotter database. A protein-protein interaction (PPI) network with the Metascape database was built using STRING software, such that the mechanism underlying the C1QC function can be studied in depth. The TISCH database assisted in the evaluation of C1QC expression in different cell types in KIRC at the single-cell level. Moreover, the association of C1QC and the infiltration level of tumor immune cell was assessed using TIMER platform. The TISIDB website was selected to deeply investigate the Spearman correlation between C1QC and immune-modulator expression. Lastly, how C1QC affected the cell proliferation, migration, and invasion in vitro was assessed using knockdown strategies. Results: KIRC tissues had notably upregulated C1QC level in comparison with adjacent normal tissues, with showed a positive relevance to clinicopathological features including tumor stage, grade, and nodal metastasis, and a negative relevance to clinical prognosis in KIRC. C1QC knockdown inhibited KIRC cell proliferation, migration, and invasion, as indicated by the results of the in vitro experiment. Furthermore, functional and pathway enrichment analysis demonstrated that C1QC was involved in immune system-related biological processes. According to single-cell RNA analysis, C1QC exhibited a specific upregulation in macrophages cluster. Additionally, there was an obvious association of C1QC and a wide variety of tumor-infiltrating immune cells in KIRC. Also, high C1QC expression presented inconsistent prognosis in different enriched immune cells subgroups in KIRC. Immune factors might contribute to C1QC function in KIRC. Conclusion: C1QC is qualified to predict KIRC prognosis and immune infiltration biologically. Targeting C1QC may bring new hope for the treatment of KIRC.

Identification of Potential Prognostic Biomarkers Associated with Monocyte Infiltration in Lung Squamous Cell Carcinoma

The five-year survival rate of lung squamous cell carcinoma is significantly lower than that of other cancer types. It is therefore urgent to discover novel prognosis biomarkers and therapeutic targets and understand their correction with infiltrating immune cells to improve the prognosis of patients with lung squamous cell carcinoma. In this study, we employed robust rank aggregation algorithms to overcome the shortcomings of small sizes and potential bias in each Gene Expression Omnibus dataset of lung squamous cell carcinoma and identified 513 robust differentially expressed genes including 220 upregulated and 293 downregulated genes from six microarray datasets. Functional enrichment analysis showed that these robust differentially expressed genes were obviously involved in the extracellular matrix and structure organization, epidermis development, cell adhesion molecule binding, p53 signaling pathway, and interleukin-17 signaling pathway to affect the progress of lung squamous cell carcinoma. We further identified six hub genes from 513 robust differentially expressed genes by protein-protein interaction network and 10 topological analyses. Moreover, the results of immune cell infiltration analysis from six integrated Gene Expression Omnibus datasets and our sequencing transcriptome data demonstrated that the abundance of monocytes was significantly lower in lung squamous cell carcinoma compared to controls. Immune correlation analysis and survival analysis of hub genes suggested that three hub genes, collagen alpha-1(VII) chain, mesothelin, and chordin-like protein 1, significantly correlated with tumor-infiltrating monocytes as well as may be potential prognostic biomarkers and therapy targets in lung squamous cell carcinoma. The investigation of the correlation of hub gene markers and infiltrating monocytes can also improve to well understand the molecular mechanisms of lung squamous cell carcinoma development.

Identifying crucial biomarkers in peripheral blood of schizophrenia and screening therapeutic agents by comprehensive bioinformatics analysis

Schizophrenia (SCZ) is a sophisticated neurodevelopmental disorder, but the mechanisms remain ambiguous. Thus, we analyzed the transcriptomic datasets to investigate the molecular mechanisms of SCZ to pinpoint novel biomarkers and suggest treatment agents. Four peripheral blood datasets were retrieved from the Gene Expression Omnibus (GEO) database, altogether 27 robust Differentially Expressed Genes (DEGs) were ascertained by robust rank aggregation (RRA) methodology. Enrichment analysis, which performed by Enrichr platform, demonstrated that DEGs are predominantly engaged in immune and inflammatory. Protein-protein interaction (PPI) network was constructed by STRING then visualized by Cytoscape. Hub genes identified by cytohubba plug-in were CXCL2, TLR9, SLPI, LY96, G0S2, EGR2, SELENBP1, NDUFA4, GNLY, CCL22. CIBERSORT algorithm was applied to evaluate the situation of immune infiltration, which revealed differences in T-cell CD8, T-cell CD4 memory resting and macrophage M0. The NetworkAnalyst platform was adopted to detect transcription factors (TFs), microRNAs (miRNAs), diseases and chemicals that interact with DEGs, while drugs interacted with DEGs were detected by Enrichr. TFs such as FOXC1, GATA2, NFIC, USF2, E2F1, miRNAs like mir-16-5p, mir-1-3p, mir-124-3p, mir-155-5p, mir-27a-3p are essential in the regulation of DEGs. mir-367-SMAD7-EGR1, mir-367-SMAD7-ARNT, mir-21-SMAD7-EGR1 may be promising biomarkers for SCZ. DEGs were intimately associated with Myocardial Ischemia, Inflammation, Reperfusion Injury. Chemicals such as VPA, cyclosporine, Aflatoxin B1, arsenic trioxide, drugs like diphenylpyraline, trimethoprim, 4-Aminobenzohydrazide, lanatoside C, may have significant implications for treatment of SCZ. These results would shed light on the molecular mechanisms of SCZ and suggest promising diagnostic biomarkers in peripheral blood and therapeutic tactics.

Application of weighted co-expression network analysis and machine learning to identify the pathological mechanism of Alzheimer's disease

Aberrant deposits of neurofibrillary tangles (NFT), the main characteristic of Alzheimer's disease (AD), are highly related to cognitive impairment. However, the pathological mechanism of NFT formation is still unclear. This study explored differences in gene expression patterns in multiple brain regions [entorhinal, temporal, and frontal cortex (EC, TC, FC)] with distinct Braak stages (0- VI), and identified the hub genes via weighted gene co-expression network analysis (WGCNA) and machine learning. For WGCNA, consensus modules were detected and correlated with the single sample gene set enrichment analysis (ssGSEA) scores. Overlapping the differentially expressed genes (DEGs, Braak stages 0 vs. I-VI) with that in the interest module, metascape analysis, and Random Forest were conducted to explore the function of overlapping genes and obtain the most significant genes. We found that the three brain regions have high similarities in the gene expression pattern and that oxidative damage plays a vital role in NFT formation via machine learning. Through further filtering of genes from interested modules by Random Forest, we screened out key genes, such as LYN, LAPTM5, and IFI30. These key genes, including LYN, LAPTM5, and ARHGDIB, may play an important role in the development of AD through the inflammatory response pathway mediated by microglia.

Targeting histone deacetylase enhances the therapeutic effect of Erastin-induced ferroptosis in EGFR-activating mutant lung adenocarcinoma

Background

Intrinsic or acquired resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) is common, thus strategies for the management of EGFR-TKIs resistance are urgently required. Ferroptosis is a recently discovered form of cell death that has been implicated in tumorigenesis and resistance treatment. Accumulating evidence suggests that ferroptosis can be therapeutically exploited for the treatment of solid tumors; however, whether ferroptosis can be targeted to treat EGFR mutant lung cancer and/or overcome the resistance to EGFR-TKIs is still unknown.

Methods

The effect of ferroptosis inducers on a panel of EGFR mutant lung cancer cell lines, including those with EGFR-TKI intrinsic and acquired (generated by long-term exposure to the third-generation EGFR-TKI osimertinib), was determined using cytotoxicity assays. Further, drug candidates to enhance the effect of ferroptosis inducers were screened through implementing WGCNA (weighted gene co-expression network analysis) and CMAP (connectivity map) analysis. Flow cytometry-based apoptosis and lipid hydroperoxides measurement were used to evaluate the cell fates after treatment.

Results

Compared with EGFR-TKI-sensitive cells, those with intrinsic or acquired resistance to EGFR-TKI display high sensitivity to ferroptosis inducers. In addition, Vorinostat, a clinically used inhibitor targeting histone deacetylase, can robustly enhance the efficacy of ferroptosis inducers, leading to a dramatic increase of hydroperoxides in EGFR mutant lung cancer cells with intrinsic or acquired resistance to EGFR-TKI. Mechanistically, Vorinostat promotes ferroptosis via xCT downregulation.

Conclusions

Ferroptosis-inducing therapy shows promise in EGFR-activating mutant lung cancer cells that display intrinsic or acquired resistance to EGFR-TKI. Histone deacetylase inhibitor (HDACi) Vorinostat can further promote ferroptosis by inhibiting xCT expression.