Prognosis-related autophagy genes in female lung adenocarcinoma

Biological mechanisms and clinical significance of endoplasmic reticulum oxidoreductase 1 alpha (ERO1α) in human cancer

A firm link between endoplasmic reticulum (ER) stress and tumors has been wildly reported. Endoplasmic reticulum oxidoreductase 1 alpha (ERO1α), an ER-resident thiol oxidoreductase, is confirmed to be highly upregulated in various cancer types and associated with a significantly worse prognosis. Of importance, under ER stress, the functional interplay of ERO1α/PDI axis plays a pivotal role to orchestrate proper protein folding and other key processes. Multiple lines of evidence propose ERO1α as an attractive potential target for cancer treatment. However, the unavailability of specific inhibitor for ERO1α, its molecular inter-relatedness with closely related paralog ERO1β and the tightly regulated processes with other members of flavoenzyme family of enzymes, raises several concerns about its clinical translation. Herein, we have provided a detailed description of ERO1α in human cancers and its vulnerability towards the aforementioned concerns. Besides, we have discussed a few key considerations that may improve our understanding about ERO1α in tumors.

The diagnostic or prognostic values of FADD in cancers based on pan‑cancer analysis

Previous studies have determined that aberrant expression of the fas-associated death domain (FADD) contributes to the development of cancer. However, no pan-cancer analysis has been reported to explore the relationship between FADD and various cancers. Multiple databases were screened to identify cancer datasets for the present study and to validate the expression of FADD in various tumors. The association of FADD alteration with cancer prognosis, clinical features and tumor immunity was also evaluated. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to confirm the expression of FADD in breast, colon, liver and gastric cancer cells. Analysis of Gene Expression Omnibus database and The Cancer Genome Atlas database indicated that FADD was highly expressed in breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD) and prostate adenocarcinoma, whereas RT-qPCR results revealed that FADD was highly expressed in breast cancer and colon cancer. Further analyses demonstrated that FADD expression was significantly altered in ESCA, head and neck squamous cell carcinoma (HNSC), lung squamous cell carcinoma and BRCA. FADD expression was observed to be a risk factor of the overall survival in patients with HNSC, LIHC and LUAD as demonstrated by Kaplan-Meier and Cox regression analyses. The results of the present study demonstrated that FADD is highly expressed in numerous malignancies and can be utilized as a biomarker for the diagnosis of BRCA, COAD, LIHC and stomach adenocarcinoma. Moreover, FADD expression is a predictive risk factor for the development of HNSC, LIHC and LUAD and can potentially be used as a prognostic marker for these cancers.

Regulation and Functions of α6-Integrin (CD49f) in Cancer Biology

Over the past decades, our knowledge of integrins has evolved from being understood as simple cell surface adhesion molecules to receptors that have a complex range of intracellular and extracellular functions, such as delivering chemical and mechanical signals to cells. Consequently, they actively control cellular proliferation, differentiation, and apoptosis. Dysregulation of integrin signaling is a major factor in the development and progression of many tumors. Many reviews have covered the broader integrin family in molecular and cellular studies and its roles in diseases. Nevertheless, further understanding of the mechanisms specific to an individual subunit of different heterodimers is more useful. Thus, we describe the current understanding of and exploratory investigations on the α6-integrin subunit (CD49f, VLA6; encoded by the gene itga6) in normal and cancer cells. The roles of ITGA6 in cell adhesion, stemness, metastasis, angiogenesis, and drug resistance, and as a diagnosis biomarker, are discussed. The role of ITGA6 differs based on several features, such as cell background, cancer type, and post-transcriptional alterations. In addition, exosomal ITGA6 also implies metastatic organotropism. The importance of ITGA6 in the progression of a number of cancers, including hematological malignancies, suggests its potential usage as a novel prognostic or diagnostic marker and useful therapeutic target for better clinical outcomes.

Poor Prognosis of Oral Squamous Cell Carcinoma Correlates With ITGA6

OBJECTIVES

Oral cancer is the ninth most common cancer worldwide and a leading cause of cancer-related death. Oral squamous cell carcinoma (OSCC) accounts for 90% of all oral cancers. Autophagy is a conserved essential catabolic process related to OSCC. The aim of this study was to elucidate diagnostic and prognostic autophagy-related biomarkers in OSCC.

METHODS

The OSCC gene expression data set was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the OSCC samples and adjacent healthy tissues were identified by R software. The Human Autophagy Database was screened, which revealed 222 autophagy-related genes. The autophagy-related DEGs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied. Protein-protein interaction network analysis was performed in the STRING database. cytoHubba in the Cytoscape software was applied to determine the top 10 hub genes. The data set of patients with OSCC from The Cancer Genome Atlas (TCGA) was used to evaluate the prognostic value of the 10 hub genes. The association between prognosis-related hub genes and immune infiltrates was explored.

RESULTS

Twenty-seven autophagy-related DEGs were identified. The top 10 hub genes were CCL2, CDKN2A, CTSB, CTSD, CXCR4, ITGA6, MAP1LC3A, MAPK3, PARP1, and RAB11A. ITGA6 was identified as the most efficient biomarker. Receiver operating characteristic curve analysis indicated that ITGA6 had the highest diagnostic accuracy for OSCC (area under the curve = 0.925). ITGA6 expression was significantly related to immune infiltrates.

CONCLUSIONS

The autophagy-related gene ITGA6 might be an efficient diagnostic and prognostic biomarker in OSCC.

Comprehensive analysis of autophagy-related gene expression profiles identified five gene biomarkers associated with immune infiltration and advanced plaques in carotid atherosclerosis

BACKGROUND

Autophagy plays an important role in the progression of carotid atherosclerosis (CAS). This study aimed to identify hub autophagy-related genes (ATGs) associated with CAS.

METHODS

GSE43292 and GSE28829 datasets of early and advanced CAS plaques were enrolled from the Gene Expression Omnibus (GEO) database. A comprehensive analysis of differentially expressed ATGs (DE-ATGs) was conducted. Functional enrichment assay was used to explore biological functions of DE-ATGs. The hub ATGs were identified by protein-protein interaction (PPI) network. Immunohistochemistry (IHC) and Real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to validate hub ATGs at the protein level and mRNA level. Correlation analysis of hub ATGs with immune cells was also conducted. In addition, a competitive endogenous RNA (ceRNA) network was constructed, and diagnostic value of hub ATGs was evaluated.

RESULTS

A total of 19 DE-ATGs were identified in early and advanced CAS plaques. Functional enrichment analysis of DE-ATGs suggested that they were closely correlated to autophagy, apoptosis, and lipid regulation. Moreover, 5 hub ATGs, including TNFSF10, ITGA6, CTSD, CCL2, and CASP1, were identified and further verified by IHC. The area under the curve (AUC) values of the 5 hub ATGs were 0.818, 0.732, 0.792, 0.814, and 0.812, respectively. Competing endogenous RNA (ceRNA) networks targeting the hub ATGs were also constructed. In addition, the 5 hub ATGs were found to be closely associated with immune cell infiltration in CAS.

CONCLUSION

In this study, we identified 5 hub ATGs including CASP1, CCL2, CTSD, ITGA6 and TNFSF10, which could serve as candidate diagnostic biomarkers and therapeutic targets.

Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. Many studies suggest that autophagy may be related to disease progression and prognosis in IPF. However, the mechanisms involved have not been fully elucidated.

Methods

We incorporated 232 autophagy-associated genes (AAGs) and two datasets, GSE28042 and GSE27957, from the GEO database. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression were used to construct the autophagy-associated prognostic model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the functions of these autophagy-associated genes. CIBERSORT algorithm was used to calculate the immune cell infiltration between patients in the high-risk score and low-risk score groups. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) was performed to explore the mRNA expression of five genes in the autophagy-associated risk model.

Results

We constructed a 5-autophagy-associated genes signature based on Univariate Cox analysis and LASSO regression. In our autophagy-associated risk model, IPF patients in the high-risk group demonstrated a poor overall survival rate compared to patients in the low-risk group. For 1-, 2-, and 3-year survival rates, the AUC predictive value of the AAG signature was 0.670, 0.787, and 0.864, respectively. These results were validated in the GSE27957 cohort, confirming the good prognostic effect of our model. GO and KEGG pathway analyses enriched immune-related pathways between the high-risk and low-risk groups. And there was also a significant difference in immune cell infiltration between two groups. And the results of qRT-PCR showed that the expression levels of FOXO1, IRGM, MYC, and PRKCQ were significantly decreased in the Peripheral Blood Mononuclear Cell (PBMC) of IPF patient samples.

Conclusion

Our study constructed and validated an autophagy-associated risk model based on MYC, MAPK1, IRGM, PRKCQ, and FOXO1. And those five genes may influence the progression of IPF by regulating immune responses and immune cells.

The Prognostic Significance of FKBP1A and Its Related Immune Infiltration in Liver Hepatocellular Carcinoma

Liver hepatocellular carcinoma (LIHC) remains a global health challenge with poor prognosis and high mortality. FKBP1A was first discovered as a receptor for the immunosuppressant drug FK506 in immune cells and is critical for various tumors and cancers. However, the relationships between FKBP1A expression, cellular distribution, tumor immunity, and prognosis in LIHC remain unclear. Here, we investigated the expression level of FKBP1A and its prognostic value in LIHC via multiple datasets including ONCOMINE, TIMER, GEPIA, UALCAN, HCCDB, Kaplan–Meier plotter, LinkedOmics, and STRING. Human liver tissue microarray was employed to analyze the characteristics of FKBP1A protein including the expression level and pathological alteration in cellular distribution. FKBP1A expression was significantly higher in LIHC and correlated with tumor stage, grade and metastasis. The expression level of the FKBP1A protein was also increased in LIHC patients along with its accumulation in endoplasmic reticulum (ER). High FKBP1A expression was correlated with a poor survival rate in LIHC patients. The analysis of gene co-expression and the regulatory pathway network suggested that FKBP1A is mainly involved in protein synthesis, metabolism and the immune-related pathway. FKBP1A expression had a significantly positive association with the infiltration of hematopoietic immune cells including B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells. Moreover, M2 macrophage infiltration was especially associated with a poor survival prognosis in LIHC. Furthermore, FKBP1A expression was significantly positively correlated with the expression of markers of M2 macrophages and immune checkpoint proteins such as PD-L1, CTLA-4, LAG3 and HAVCR2. Our study demonstrated that FKBP1A could be a potential prognostic target involved in tumor immune cell infiltration in LIHC.