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Data Mining Identifies Six Proteins that Can Act as Prognostic Markers for Head and Neck Squamous Cell Carcinoma.

ABSTRACT: Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract affecting the oral cavity, lips, paranasal sinuses, larynx, and nasopharynx. Proteogenomics combines proteomics and genomics and employs mass spectrometry and high-throughput sequencing technologies to identify novel peptides. The aim of this study was to identify potential protein biomarkers for clinical treatment of HNSCC. To achieve this, we utilized two sets of data, one on proteins from The Cancer Proteome Atlas (TCPA) and the other on gene expression from The Cancer Genome Atlas (TCGA) database, to evaluate dysfunctional proteogenomics microenvironment. Univariate Cox regression analysis was performed to examine the relationship between protein signatures and prognosis. A total of 19 proteins were significantly associated with overall survival (OS) of patients, of which E2F transcription factor 1 (E2F1; HR = 4.557, 95% CI = 1.810 to 11.469) and enhancer of zeste homolog 2 (EZH2; HR = 0.430, 95% CI = 0.187 to 0.984) were the most differentially expressed between patients with longer and shorter OS, respectively. Furthermore, multivariate Cox regression analysis on six proteins (ERALPHA, HER3, BRAF, P27, RAPTOR, and E2F1) was performed to build the prognostic model. The receiver operating characteristic curves were used to determine whether the expression pattern of survival-related proteins could provide an early prediction of the occurrence of HNSCC. Herein, we found an AUC of 0.720. Based on an online database, we identified novel protein markers for the prognosis of HNSCC. The findings of the present study may provide new insights into the development of new and reliable tools for precise cancer intervention.

SUBMITTER: Wu ZH

PROVIDER: S-EPMC7563932 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature

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Data Mining Identifies Six Proteins that Can Act as Prognostic Markers for Head and Neck Squamous Cell Carcinoma.

Wu Zeng-Hong ZH Yun-Tang Cheng Qing Q

Cell transplantation 20200101

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract affecting the oral cavity, lips, paranasal sinuses, larynx, and nasopharynx. Proteogenomics combines proteomics and genomics and employs mass spectrometry and high-throughput sequencing technologies to identify novel peptides. The aim of this study was to identify potential protein biomarkers for clinical treatment of HNSCC. To achieve this, we utilized two sets of data, one on proteins from The C ...[more]

PMID: 32452220

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Project description:BackgroundTranscriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.Materials and methodsGene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.ResultsWe identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.ConclusionThe six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making.

Project description:Head and neck squamous cell carcinomas (HNSCCs) are highly aggressive tumors with rapid progression and poor prognosis. Human papillomavirus (HPV) infection has been identified as one of the most important carcinogens for HNSCC. As an early event in HNSCC, infection with HPV leads to altered immune profiles in the tumor microenvironment (TME). The TME plays a key role in the progression and transformation of HNSCC. However, the TME in HNSCC is a complex and heterogeneous mix of tumor cells, fibroblasts, different types of infiltrating immune cells, and extracellular matrix. Biomarkers relevant to the TME, and the biological role of these biomarkers, remain poorly understood. To this end, we performed comprehensive analysis of the RNA sequencing (RNA-Seq) data from tumor tissue of 502 patients with HNSCC and healthy tissue of 44 control samples. In total, we identified 4,237 differentially expressed genes, including 2,062 upregulated and 2,175 downregulated genes. Further in-depth bioinformatic analysis suggested 19 HNSCC tumor tissue-specific genes. In the subsequent analysis, we focused on the biomarker candidates shown to be significantly associated with unfavorable patient survival: ITGA5, PLAU, PLAUR, SERPINE1, TGFB1, and VEGFC. We found that the expression of these genes was negatively regulated by DNA methylation. Strikingly, all of these potential biomarkers are profoundly involved in the activation of the epithelial-mesenchymal transition (EMT) pathway in HNSCCs. In addition, these targets were found to be positively correlated with the immune invasion levels of CD4+ T cells, macrophages, neutrophils, and dendritic cells, but negatively correlated with B-cell infiltration and CD8+ T-cell invasion. Notably, our data showed that the expression levels of ITGA5, PLAU, PLAUR, SERPINE1, and TGFB1 were significantly overexpressed in HPV-positive HNSCCs compared to normal controls, indicating the potential role of these biomarkers as transformation and/or malignant progression markers for HNSCCs in patients with HPV infection. Taken together, the results of our study propose ITGA5, PLAU, PLAUR, SERPINE1, and TGFB1 as potential prognostic biomarkers for HNSCCs, which might be involved in the HPV-related TME remodeling of HNSCC. Our findings provide important implications for the development and/or improvement of patient stratification and customized immunotherapies in HNSCC.

Project description:The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.

Dataset Information

Data Mining Identifies Six Proteins that Can Act as Prognostic Markers for Head and Neck Squamous Cell Carcinoma.

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Data Mining Identifies Six Proteins that Can Act as Prognostic Markers for Head and Neck Squamous Cell Carcinoma.

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