Identifying potential prognostic biomarkers in head and neck cancer based on the analysis of microRNA expression profiles in TCGA database

Promising Biomarkers in Head and Neck Cancer: The Most Clinically Important miRNAs

Head and neck cancers (HNCs) comprise a heterogeneous group of tumors that extend from the oral cavity to the upper gastrointestinal tract. The principal etiologic factors for oral tumors include tobacco smoking and alcohol consumption, while human papillomavirus (HPV) infections have been accused of a high incidence of pharyngeal tumors. Accordingly, HPV detection has been extensively used to categorize carcinomas of the head and neck. The diverse nature of HNC highlights the necessity for novel, sensitive, and precise biomarkers for the prompt diagnosis of the disease, its successful monitoring, and the timely prognosis of patient clinical outcomes. In this context, the identification of certain microRNAs (miRNAs) and/or the detection of alterations in their expression patterns, in a variety of somatic fluids and tissues, could serve as valuable biomarkers for precision oncology. In the present review, we summarize some of the most frequently studied miRNAs (including miR-21, -375, -99, -34a, -200, -31, -125a/b, -196a/b, -9, -181a, -155, -146a, -23a, -16, -29, and let-7), their role as biomarkers, and their implication in HNC pathogenesis. Moreover, we designate the potential of given miRNAs and miRNA signatures as novel diagnostic and prognostic tools for successful patient stratification. Finally, we discuss the currently ongoing clinical trials that aim to identify the diagnostic, prognostic, or therapeutic utility of miRNAs in HNC.

The Prediction of a 3-Protein-Based Model on the Prognosis of Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the commonest malignant tumors. Using high-throughput genomic methods, RNA-based diagnostic and prognostic models for HNSCC with potential clinical value have been developed. However, the clinical utility and reproducibility of these models are uncertain. Because the complex regulatory processes occurring after mRNA is transcribed, the abundance of proteins in a cell can never be fully predicted or explained by their corresponding mRNA expression. We aimed to assume and verify a novel protein signature for checking the HNSCC patients' prognosis.

Methods

The functional proteomic data of 332 HNSCC cases were collected from The Cancer Proteome Atlas (TCPA), and the related follow-up and clinical data were acquired from The Cancer Genome Atlas (TCGA). This study adopted multivariate and univariate Cox regression analysis, Akaike Information Criterion, receiver operating characteristic (ROC) analysis, and Kaplan-Meier method.

Results

Patients' clinical features in both sets were comparable (all, P > 0.05). The area under the ROC curve (AUC) for the 3-protein signature (X4EBP1_pT37T46, HER3_pY1289, and NF2) in the test set was 0.655 and in the combined cohort (all 332 patients combined) was 0.699. In addition, the 3-protein signature exhibited better predictive value for the survival of HNSCC patients as in comparison with conventional clinical factors like age, gender, tumor stage, and smoking history (TNM stage).

Conclusion

The 3-protein signature developed in this study exhibits good performance in predicting the overall survival of with HNSCC patients. The 3-protein signature exhibited better predictive value for survival than conventional clinical factors just like gender, TNM stage, smoking history, and age.

Differential gene expression and network analysis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a poor prognosis, whose biomarkers have not been studied in great detail. We have collected genomic data of HNSCC patients from The Cancer Genome Atlas (TCGA) and analyzed them to get deeper insights into the gene expression pattern. Initially, 793 differentially expressed genes (DEGs) were categorized, and their enrichment analysis was performed. Later, a protein-protein interaction network for the DEGs was constructed using the STRING plugin in Cytoscape to study their interactions. A set of 10 hub genes was selected based on Maximal Clique Centrality score, and later their survival analysis was studied. The elucidated set of 10 genes, i.e., PRAME, MAGEC2, MAGEA12, LHX1, MAGEA3, CSAG1, MAGEA6, LCE6A, LCE2D, LCE2C, referred to as potential candidates to be explored as HNSCC biomarkers. The Kaplan-Meier overall survival of the selected genes suggested that the alterations in the candidate genes were linked to the decreased survival of the HNSCC patients. Altogether, the results of this study signify that the genomic alterations and differential expression of the selected genes can be explored in therapeutic interpolations of HNSCC, exploiting early diagnosis and target-propelled therapy.

Elevated expression of MKRN3 in squamous cell carcinoma of the head and neck and its clinical significance

BACKGROUND

Squamous cell carcinoma of the head and neck (SCCHN) is one of the most common types of cancer that cause a substantial number of cancer-related deaths. Our previous study has revealed that makorin ring finger protein 3 (MKRN3) may act as a key regulator of the SCCHN tumorigenesis; however, its specific role in SCCHN progression has not been reported.

METHODS

The Cancer Genome Atlas (TCGA) data analysis and quantitative polymerase chain reaction (qPCR) were used to quantify the MKRN3 mRNA expression levels in SCCHN; immunohistochemical staining or immunoblotting analyses were performed to detect MKRN3 protein expression. Kaplan-Meier plotter was used to assess the prognostic values of MKRN3 in terms of overall survival and disease-free survival. The expression differences based on various clinicopathological features were evaluated using subgroup analysis and forest map analysis. The regulatory mechanism of MKRN3 was further investigated using gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Subsequently, STRING was used to perform a co-expression and enrichment analysis for MKRN3. Homologous modeling, molecular docking, and western blot analyses were performed to investigate the relationship between MKRN3 and its potential target gene P53.

RESULTS

MKRN3 was ectopically expressed between cancerous and noncancerous SCCHN tissues, and its expression level was tightly associated with high T classifications as well as advanced clinical stages. qPCR analysis revealed that MKRN3 was upregulated in the SCCHN cell line. Moreover, Kaplan-Meier and Cox regression analyses indicated that SCCHN patients with high MKRN3 expression had poorer prognosis and that MKRN3 was a potential prognostic marker for SCCHN. Using gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses, we determined that MKRN3 may be involved in the regulation of synthesis and metabolism and cell growth, death and motility, as well as cancer pathways associated with SCCHN progression. Mechanism investigation further revealed that P53, a potential target of MKRN3, may be involved in the SCCHN tumorigenesis mediated by MKRN3.

CONCLUSIONS

We performed a comprehensive evaluation of the clinical significance of MKRN3 and explored its underlying mechanisms. We concluded that MKRN3 represents a valuable predictive biomarker and potential therapeutic target in SCCHN.

PENK inhibits osteosarcoma cell migration by activating the PI3K/Akt signaling pathway

Background

This article reports the effects of proenkephalin (PENK) on osteosarcoma (OS) cell migration.

Methods

A Gene Expression Omnibus (GEO) dataset was used to identify differentially expressed genes (DEGs) in OS tumor samples and normal human osteoblasts. Tumor tissue and adjacent normal tissue were collected from 40 OS patients. MG63 cells were transfected with si-PENK. Transwell migration assays and wound healing assays were performed to compare the effect of PENK on migration. Moreover, LY294002 was used to identify the potential mechanism. Gene expression was examined via qRT-PCR and Western blotting.

Results

Bioinformatic analysis revealed that PENK was downregulated in OS tumor samples compared with normal human osteoblasts. Moreover, PENK was identified as the hub gene of the DEGs. The PI3K/Akt signaling pathway was significantly enriched in the DEGs. Moreover, PENK was downregulated in OS and MG63 cells compared with the corresponding control cells. Silencing PENK promoted MG63 cell migration; however, treatment with LY294002 partially attenuated PENK silencing-induced OS cell migration.

Conclusion

PENK inhibits OS cell migration by activating the PI3K/Akt signaling pathway.