Expression and Prognostic Analyses of ITGA3, ITGA5, and ITGA6 in Head and Neck Squamous Cell Carcinoma

ITGA5 is associated with prognosis marker and immunosuppression in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a major tumor that seriously threatens the health of the head and neck or mucosal system. It is manifested as a malignant phenotype of high metastasis and invasion caused by squamous cell transformation in the tissue area. Therefore, it is necessary to search for a biomarker that can systematically correlate and reflect the prognosis of HNSCC based on the characteristics of head and neck tumors.

METHODS

Based on TCGA-HNSCC data, R software was used to analyze gene expression, correlation, Venn diagram, immune invasive and immunosuppressive phenotypes respectively. The intrinsic effect of ITGA5 on the malignant phenotype of HNSCC cells was verified by cell experiments. Immunohistochemical images from The Human Protein Atlas (THPA) database display the differences in the expression of related proteins in HNSCC tissues. Based on functional enrichment and correlation analysis, the prognostic value of ITGA5 for HNSCC was explored, and the expression level of ITGA5 may affect the chemotherapy of targeting the PI3K-AKT.

RESULTS

In this study, the target gene ITGA5 may be identified as a valuable prognostic marker for HNSCC. The results of enrichment analysis showed that ITGA5 was mainly involved in the dynamic process of extracellular matrix, which may affect the migration or metastasis of tumor cells. Meanwhile, ITGA5 may be closely related to the infiltration of M2 macrophages, and its secretory phenotypes TGFB1, PDGFA and PDGFB may affect the immunosuppressive phenotypes of tumor cells, which reflects the systemic influence of ITGA5 in HNSCC. In addition, the expression levels of ITGA5 were negatively correlated with the efficacy of targeting PI3K-AKT chemotherapy.

CONCLUSION

ITGA5 can be used as a potential marker to systematically associate with prognosis of HNSCC, which may be associated with HNSCC malignant phenotype, immunosuppression and chemotherapy resistance.

Advanced Analysis and Validation of a microRNA Signature for Fanconi Anemia

Some years ago, we reported the generation of a Fanconi anemia (FA) microRNA signature. This study aims to develop an analytical strategy to select a smaller and more reliable set of molecules that could be tested for potential benefits for the FA phenotype, elucidate its biochemical and molecular mechanisms, address experimental activity, and evaluate its possible impact on FA therapy. In silico analyses of the data obtained in the original study were thoroughly processed and anenrichment analysis was employed to identify the classes of genes that are over-represented in the FA-miRNA population under study. Primary bone marrow mononuclear cells (MNCs) from sixFA patients and sixhealthy donors as control samples were employed in the study. RNAs containing the small RNA fractions were reverse-transcribed and real-time PCR was performed in triplicate using the specific primers. Experiments were performed in triplicate.The in-silico analysis reported six miRNAs as likely contributors to the complex pathological spectrum of FA. Among these, three miRNAs were validated by real-time PCR. Primary bone marrow mononuclear cells (MNCs) reported a significant reduction in the expression level of miRNA-1246 and miRNA-206 in the FA samples in comparison to controls.This study highlights several biochemical pathways as culprits in the phenotypic manifestations and the pathophysiological mechanisms acting in FA. A relatively low number of miRNAs appear involved in all these different phenotypes, demonstrating the extreme plasticity of the gene expression modulation. This study further highlights miR-206 as a pivotal player in regulatory functions and signaling in the bone marrow mesenchymal stem cell (BMSC) process in FA. Due to this evidence, the activity of miR-206 in FA deserves specific experimental scrutiny. The results, here presented, might be relevant in the management of FA.

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.

ACTN1 interacts with ITGA5 to promote cell proliferation, invasion and epithelial-mesenchymal transformation in head and neck squamous cell carcinoma

Objectives

The aim of this study was to detect the expression levels of α-Actinin 1 (ACTN1) and ITGA5 in HNSCC and to explore how ACTN1/ITGA5 regulated the proliferative and invasive abilities, as well as the EMT of Head and neck squamous cell carcinoma (HNSCC) cells.

Materials and Methods

The viability, proliferative, invasive and migrative abilities of HNSCC cells after transfection were, in turn, detected by CCK8 assay, colony formation assay, EdU staining, transwell, as well as wound healing. E-cadherin in transfected cells was assessed utilizing immunofluorescence. RT-qPCR confirmed the transfection effect of ACTN1 and ITGA5 in HNSCC cells and the interaction between ACTN1 and ITGA5 in HNSCC cells was determined by co-immunoprecipitation (Co-IP). With Western blot application, the contents of ACTN1, ITGA5, proliferation-, invasion- and migration-related proteins were estimated. A xenograft model based on nude mice was conducted and Ki-67 content in tumor tissues was evaluated employing immunohistochemistry (IHC) staining.

Results

ACTN1 interacted with ITGA5. The contents of ACTN1 and ITGA5 were found to be abundant in HNSCC tissues and cells and associated with poor prognosis. ACTN1 depletion imparted suppressive impacts on cell proliferative, invasive and migrative abilities as well as EMT of HNSCC cells, which were reversed by ITGA5 overexpression. In addition, ACTN1 deficiency repressed the growth and metastasis of tumor tissues in tumor xenografts of nude mice.

Conclusion

ACTN1 positively interacts with ITGA5 to promote proliferation, invasion and EMT of HNSCC cells. Also, ACTN1 promotes tumor growth and metastasis.

Spatial transcriptomics prediction from histology jointly through Transformer and graph neural networks

The rapid development of spatial transcriptomics allows the measurement of RNA abundance at a high spatial resolution, making it possible to simultaneously profile gene expression, spatial locations of cells or spots, and the corresponding hematoxylin and eosin-stained histology images. It turns promising to predict gene expression from histology images that are relatively easy and cheap to obtain. For this purpose, several methods are devised, but they have not fully captured the internal relations of the 2D vision features or spatial dependency between spots. Here, we developed Hist2ST, a deep learning-based model to predict RNA-seq expression from histology images. Around each sequenced spot, the corresponding histology image is cropped into an image patch and fed into a convolutional module to extract 2D vision features. Meanwhile, the spatial relations with the whole image and neighbored patches are captured through Transformer and graph neural network modules, respectively. These learned features are then used to predict the gene expression by following the zero-inflated negative binomial distribution. To alleviate the impact by the small spatial transcriptomics data, a self-distillation mechanism is employed for efficient learning of the model. By comprehensive tests on cancer and normal datasets, Hist2ST was shown to outperform existing methods in terms of both gene expression prediction and spatial region identification. Further pathway analyses indicated that our model could reserve biological information. Thus, Hist2ST enables generating spatial transcriptomics data from histology images for elucidating molecular signatures of tissues.

Identification of Therapeutic Targets and Prognostic Biomarkers Among Integrin Subunits in the Skin Cutaneous Melanoma Microenvironment

The roles of different integrin alpha/beta (ITGA/ITGB) subunits in skin cutaneous melanoma (SKCM) and their underlying mechanisms of action remain unclear. Oncomine, UALCAN, GEPIA, STRING, GeneMANIA, cBioPortal, TIMER, TRRUST, and Webgestalt analysis tools were used. The expression levels of ITGA3, ITGA4, ITGA6, ITGA10, ITGB1, ITGB2, ITGB3, ITGB4, and ITGB7 were significantly increased in SKCM tissues. The expression levels of ITGA1, ITGA4, ITGA5, ITGA8, ITGA9, ITGA10, ITGB1, ITGB2, ITGB3, ITGB5, ITGB6 and ITGB7 were closely associated with SKCM metastasis. The expression levels of ITGA1, ITGA4, ITGB1, ITGB2, ITGB6, and ITGB7 were closely associated with the pathological stage of SKCM. The expression levels of ITGA6 and ITGB7 were closely associated with disease-free survival time in SKCM, and the expression levels of ITGA6, ITGA10, ITGB2, ITGB3, ITGB6, ITGB7, and ITGB8 were markedly associated with overall survival in SKCM. We also found significant correlations between the expression of integrin subunits and the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells). Finally, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed, and protein-protein interaction (PPI) networks were constructed. We have identified abnormally-expressed genes and gene regulatory networks associated with SKCM, improving understanding of the underlying pathogenesis of SKCM.

Expression and prognostic potential of PLEK2 in head and neck squamous cell carcinoma based on bioinformatics analysis

Background

PLEK2 (pleckstrin) could bind to membrane‐bound phosphatidylinositols and further promote cell spread. Recently, several studies have noted the importance of PLEK2 in tumor metastasis. However, the role of PLEK2 in head and neck squamous cell carcinoma (HNSCC) remains to be elucidated.

Methods

The PLEK2 expression in HNSCC was identified using Oncomine, Gene Expression Omnibus (GEO), UALCAN databases, and western blot analysis. Prognosis analysis was performed using Kaplan–Meier plotter, DriverDBv3, UALCAN, UCSC Xena, and GEO databases. Single‐cell functional analysis was further performed using the cancerSEA database. The PLEK2‐related co‑expressed genes were identified, and gene set enrichment analysis was performed using LinkedOmics. Furthermore, the top 10 hub genes were identified using the cytoHubba plug‐in of Cytoscape. Then, gene enrichment analysis, pathway activity, and drug sensitivity analyses of the hub genes were performed using the R package “clusterProfiler” and GSCAlite. Finally, the UCSC Xena browser was utilized to explore the hub gene most likely to play a synergic role with PLEK2 in HNSCC.

Results

Elevated expression of PLEK2 was observed in HNSCC and even in HNSCC subgroups based on diverse clinicopathological features, portending a poor prognosis in HNSCC. PLEK2 was correlated with metastasis and hypoxia in HNSCC, and the PLEK2‐related co‐expressed genes were mainly involved in the focal adhesion pathway. The top 10 hub genes were primarily enriched in focal adhesion, HPV infection, ECM‐receptor interaction, and PI3K‐AKT signaling pathway, and epithelial–mesenchymal transition pathway was activated. Furthermore, the expression levels of the hub genes were associated with sensitivity and resistance to various small molecules and anti‐cancer drugs. Further study suggested that ITGA3 and PLEK2 might be viewed as inextricably linked in facilitating HNSCC metastasis.

Conclusions

In general, PLEK2 might serve as a potential biomarker for the diagnosis of HNSCC and guide the development of targeted therapies for HNSCC.

Comprehensive Characterization of Integrin Subunit Genes in Human Cancers

Although integrin subunit genes (ITGs) have been reported to be associated with some human cancer types, a systematic assessment of ITGs across human cancers is lacking. Hence, we performed comprehensive analyses to investigate mRNA expression, copy number variation (CNV), DNA methylation, mutation, and clinical landscapes of ITGs in more than 8000 cancer patients from The Cancer Genome Atlas (TCGA) dataset. Landscapes of ITGs were established across 20 human cancer types. We observed that ITGs are extensively dysregulated with heterogeneity in different system cancer types, part of which are driven by CNV, DNA hypomethylation or mutation. Furthermore, dysregulated prognosis-related ITGs were systematically identified in each cancer type, including ITGA11 in stomach adenocarcinoma (STAD). The models based on dysregulated ITGs with clinical relevance and TNM staging indexes are good indicators in STAD and head and neck squamous cell carcinoma. Finally, ITGA11 is overexpressed and associated with poor survival in STAD cases from the TCGA and additionally Gene Expression Omnibus cohorts. Functionally, ITGA11 knockdown inhibits malignant phenotypes in STAD cell lines AGS and MKN45, demonstrating the oncogenic role of ITGA11 in STAD. Together, this study highlights the important roles of ITGs in tumorigenesis as potential prognostic biomarkers, and provide an effective resource that identifies cancer-related genes of ITGs in human cancers.

Genes involved in the epithelial-mesenchymal transition in oral cancer: A systematic review

OBJECTIVE

Epithelial-mesenchymal transition (EMT) is considered the initial step in the invasion-metastasis cascade. The aim of this systematic review was to study the signature of genes involved in the EMT process in oral cancer (OC) confirmed by protein expression and its possible relationship with oral squamous cell carcinoma (OSCC) prognostic variables.

MATERIALS AND METHODS

A search of the scientific literature was carried out with no start date restriction until 17 September 2020 in the electronic databases Pubmed/MEDLINE, Web of Science, Cochrane Library and Scopus, following specific eligibility criteria. The methodological quality of the included studies was assessed using the Newcastle-Ottawa tool.

RESULTS

A total of 8 retrospective cohort studies were included, all of them performed in China and with low risk of bias. Overexpression of the genes HNRNPC, ITGA5, HMGA2 and SRSF3, and low expression of ALDH3A1 and ARID2 promote EMT in OC. The more advanced clinical stages of the TNM classification were significantly associated with overexpression of HNRNPC, ITGA5, HMGA2 and SRSF3, and low expression of ARID2.

CONCLUSIONS

HNRNPC, ITGA5, HMGA2, SRSF3, ALDH3A1 and ARID2 genes were associated with EMT process. Over- or under-expression of these genes is associated with worse stages of OSCC and/or worse prognosis of the tumor. Further studies on this topic are needed in different countries to be able to confirm these results, since the detection of these genes can help to know which tumors have a worse prognosis.

Guidelines for Regulated Cell Death Assays: A Systematic Summary, A Categorical Comparison, A Prospective

Over the past few years, the field of regulated cell death continues to expand and novel mechanisms that orchestrate multiple regulated cell death pathways are being unveiled. Meanwhile, researchers are focused on targeting these regulated pathways which are closely associated with various diseases for diagnosis, treatment, and prognosis. However, the complexity of the mechanisms and the difficulties of distinguishing among various regulated types of cell death make it harder to carry out the work and delay its progression. Here, we provide a systematic guideline for the fundamental detection and distinction of the major regulated cell death pathways following morphological, biochemical, and functional perspectives. Moreover, a comprehensive evaluation of different assay methods is critically reviewed, helping researchers to make a reliable selection from among the cell death assays. Also, we highlight the recent events that have demonstrated some novel regulated cell death processes, including newly reported biomarkers (e.g., non-coding RNA, exosomes, and proteins) and detection techniques.