Dataset Information

Low-molecular-mass secretome profiling identifies HMGA2 and MIF as prognostic biomarkers for oral cavity squamous cell carcinoma.

ABSTRACT: The profiling of cancer cell secretomes is considered to be a good strategy for identifying cancer-related biomarkers, but few studies have focused on identifying low-molecular-mass (LMr) proteins (<15 kDa) in cancer cell secretomes. Here, we used tricine-SDS-gel-assisted fractionation and LC-MS/MS to systemically identify LMr proteins in the secretomes of five oral cavity squamous cell carcinoma (OSCC) cell lines. Cross-matching of these results with nine OSCC tissue transcriptome datasets allowed us to identify 33 LMr genes/proteins that were highly upregulated in OSCC tissues and secreted/released from OSCC cells. Immunohistochemistry and quantitative real-time PCR were used to verify the overexpression of two candidates, HMGA2 and MIF, in OSCC tissues. The overexpressions of both proteins were associated with cervical metastasis, perineural invasion, deeper tumor invasion, higher overall stage, and a poorer prognosis for post-treatment survival. Functional assays further revealed that both proteins promoted the migration and invasion of OSCC cell lines in vitro. Collectively, our data indicate that the tricine-SDS-gel/LC-MS/MS approach can be used to efficiently identify LMr proteins from OSCC cell secretomes, and suggest that HMGA2 and MIF could be potential tissue biomarkers for OSCC.

SUBMITTER: Chang KP

PROVIDER: S-EPMC4650660 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Low-molecular-mass secretome profiling identifies HMGA2 and MIF as prognostic biomarkers for oral cavity squamous cell carcinoma.

Chang Kai-Ping KP Lin Shih-Jie SJ Liu Shiau-Chin SC Yi Jui-Shan JS Chien Kun-Yi KY Chi Lang-Ming LM Kao Huang-Kai HK Liang Ying Y Lin Yu-Tsun YT Chang Yu-Sun YS Yu Jau-Song JS

Scientific reports 20150703

The profiling of cancer cell secretomes is considered to be a good strategy for identifying cancer-related biomarkers, but few studies have focused on identifying low-molecular-mass (LMr) proteins (<15 kDa) in cancer cell secretomes. Here, we used tricine-SDS-gel-assisted fractionation and LC-MS/MS to systemically identify LMr proteins in the secretomes of five oral cavity squamous cell carcinoma (OSCC) cell lines. Cross-matching of these results with nine OSCC tissue transcriptome datasets allo ...[more]

PMID: 26138061

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Project description:BackgroundOral squamous cell carcinoma (OSCC) is the most malignant neoplasm in oral cancer. There is growing evidence that its progression involves altered metabolism. The current method of evaluating prognosis is very limited, and metabolomics may provide a new approach for quantitative evaluation. The aim of the study is to evaluate the use of metabolomics as prognostic markers for patients with OSCC.MethodsAn analytical platform, Ultra-Performance Liquid Chromatography-Quadrupole/Orbitrap High Resolution Mass Spectrometry (UHPLC-Q-Orbitrap HRMS), was used to acquire the serum fingerprinting profiles from a total of 103 patients of OSCC before and after the operation. In total, 103 OSCC patients were assigned to either a training set (n = 73) or a test set (n = 30). The potential biomarkers and the changes of serum metabolites were profiled and correlated with the clinicopathological parameters and survival of the patients by statistical analysis. To further verify our results, we linked them to gene expression using data from the Kyoto Encyclopedia of Genes and Genomes (KEGG).ResultsIn total, 14 differential metabolites and five disturbed pathways were identified between the preoperative group and postoperative group. Succinic acid change-low, hypoxanthine change-high tumor grade, and tumor stage indicated a trend towards improved recurrence-free survival (RFS), whether in a training set or a test set. In addition, succinic acid change-low, hypoxanthine change-high, and tumor grade provided the highest predictive accuracy of the patients with OSCC. KEGG enrichment analysis showed that the imbalance in the amino acid and purine metabolic pathway may affect the prognosis of OSCC.ConclusionsThe changes of metabolites before and after operation may be related to the prognosis of OSCC patients. UHPLC-Q-Orbitrap HRMS serum metabolomics analysis could be used to further stratify the prognosis of patients with OSCC. These results can better understand the mechanisms related to early recurrence and help develop more effective therapeutic targets.

Project description:Differentially methylated oral squamous cell carcinoma (OSCC) biomarkers, identified in-vitro and validated in well-characterized surgical specimens, have shown poor clinical correlation in cohorts with different risk profiles. To overcome this lack of relevance we used the HumanMethylation27 BeadChip, publicly available methylation and expression array data, and Quantitative Methylation Specific PCR to uncover differential methylation in OSCC clinical samples with heterogeneous risk profiles. A two stage-design consisting of Discovery and Prevalence screens was used to identify differential promoter methylation and deregulated pathways in patients diagnosed with OSCC and head and neck squamous cell carcinoma. Promoter methylation of KIF1A (k=0.64), HOXA9 (k=0.60), NID2 (k=0.60), and EDNRB (k=0.60) had a moderate to substantial agreement with clinical diagnosis in the Discovery screen. HOXA9 had 68% sensitivity, 100% specificity and a 0.81 AUC. NID2 had 71% sensitivity, 100% specificity and a 0.79 AUC. In the Prevalence screen HOXA9 (k=0.82) and NID2 (k=0.80) had an almost perfect agreement with histologic diagnosis. HOXA9 had 85% sensitivity, 97% specificity and a 0.95 AUC. NID2 had 87% sensitivity, 95% specificity and a 0.91 AUC. A HOXA9 and NID2 gene panel had 94% sensitivity, 97% specificity and a 0.97 AUC. In saliva from OSCC cases and controls HOXA9 had 75% sensitivity, 53% specificity and a 0.75 AUC. NID2 had 87% sensitivity, 21% specificity and a 0.73 AUC. This Phase I Biomarker Development Trial identified a panel of differentially methylated genes in normal and OSCC clinical samples from patients with heterogeneous risk profiles. This panel may be useful for early detection and cancer prevention studies. The 12 samples analyzed comprise equal numbers of three tissue-types: Primary oral squamous cell carcinoma, Oral leukoplakia and Normal oral mucosa. Gender, age and smoking-status were approximately equally represented in these goups. Normal oral mucosa served as a control.

Dataset Information

Low-molecular-mass secretome profiling identifies HMGA2 and MIF as prognostic biomarkers for oral cavity squamous cell carcinoma.

Publications

Low-molecular-mass secretome profiling identifies HMGA2 and MIF as prognostic biomarkers for oral cavity squamous cell carcinoma.

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