Dataset Information

A prototype tobacco-associated oral squamous cell carcinoma classifier using RNA from brush cytology.

ABSTRACT: Oral cancer in the form of squamous cell carcinoma (OSCC) is typically detected in advanced stages when treatment is complex and may not be curative. The need for surgical biopsy may contribute to delays in diagnosis and impede early detection. Multiple studies of RNA from surgically obtained tumor samples have revealed many genes differentially expressed with this disease. We sought to determine whether the identified mRNAs could be used as markers by a non-invasive detection system for OSCC using RNA from brush cytology.Levels of mRNAs from 21 genes known to be differentially expressed in head and neck squamous cell carcinoma surgical samples, compared with controls, were shown to be quantifiable in oral brush cytology samples. These mRNAs were quantified in a training set of 14 tumor and 20 non-malignant brush cytology samples from tobacco/betel nut users. With the measurement of two additional mRNAs and analysis using support vector machines algorithm for class prediction of these cancers was produced.This OSCC classifier based on the levels of 5 mRNAs in RNA from brush cytology initially showed 0.93 sensitivity and 0.91 specificity in differentiating OSCC from benign oral mucosal lesions based on leave-one-out cross-validation. When used on a test set of 19 samples from 6 OSCCs and 13 non-malignant oral lesions, we found misclassification of only one OSCC and one benign lesion.This shows the promise of using RNA from brush cytology for early OSCC detection and the potential for clinical usage of this non-invasive classifier.

SUBMITTER: Kolokythas A

PROVIDER: S-EPMC3740027 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A prototype tobacco-associated oral squamous cell carcinoma classifier using RNA from brush cytology.

Kolokythas Antonia A Bosman Mitchell J MJ Pytynia Kristen B KB Panda Suchismita S Sroussi Herve Y HY Dai Yang Y Schwartz Joel L JL Adami Guy R GR

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology 20130417 9

<h4>Background</h4>Oral cancer in the form of squamous cell carcinoma (OSCC) is typically detected in advanced stages when treatment is complex and may not be curative. The need for surgical biopsy may contribute to delays in diagnosis and impede early detection. Multiple studies of RNA from surgically obtained tumor samples have revealed many genes differentially expressed with this disease. We sought to determine whether the identified mRNAs could be used as markers by a non-invasive detection ...[more]

PMID: 23590359

Similar Datasets

Project description:Background: HPV-positive oral squamous cell carcinomas (OSCCs) are specific biological and clinical entities, characterized by a more favorable prognosis compared to HPV-negative OSCCs and occurring generally in non-smoking and non-drinking younger individuals. However, poor information is available on the molecular and the clinical behavior of HPV-positive oral cancers occurring in smoking/drinking subjects. Thus, this study was designed to compare, at molecular level, two OSCC cell lines, both derived from drinking and smoking individuals and differing for presence/absence of HPV infection. Methods: HPV-negative UPCI-SCC-131 and HPV16-positive UPCI-SCC-154 cell lines were compared by whole genome gene expression profiling and subsequently studied for activation of Wnt/βCatenin signaling pathway by the expression of several Wnt-target genes, βCatenin intracellular localization, stem cell features and miRNA let-7e. Gene expression data were validated in head and neck squamous cell carcinoma (HNSCC) public datasets. Results: Gene expression analysis identified Wnt/βCatenin pathway as the unique signaling pathway more active in HPV-negative compared to HPV-positive OSCC cells and this observation was confirmed upon evaluation of several Wnt-target genes (i.e., Cyclin D1, Cdh1, Cdkn2a, Cd44, Axin2, c-Myc and Tcf1). Interestingly, HPV-negative OSCC cells showed higher levels of total βCatenin and its active form, increase of its nuclear accumulation and more prominent stem cell traits. Furthermore, miRNA let-7e was identified as potential upstream regulator responsible for the downregulation of Wnt/βCatenin signaling cascade since its silencing in UPCI-SCC-154 cell resulted in upregulation of Wnt-target genes. Finally, the analysis of two independent gene expression public datasets of human HNSCC cell lines and tumors confirmed that Wnt/βCatenin pathway is more active in HPV-negative compared to HPV-positive tumors derived from individuals with smoking habit. Conclusions: These data suggest that lack of HPV infection is associated with more prominent activation of Wnt/βCatenin signaling pathway and gain of stem-like traits in tobacco-related OSCCs.

Project description:BackgroundThe exact etiology of non-tobacco associated oral squamous cell carcinoma (NT-OSCC) is still unknown. The lack of established biomarkers for oral NT-OSCC has resulted in less effective management and poor prognosis. Here, we report for the first time a panel of potential markers identified from the quantitative proteomic analysis of NT-OSCC using two-dimensional gel-electrophoresis (2D-GE) using matrix-assisted laser desorption/ionization - time of flight (MALDI-TOF) coupled with mass spectrometry (MS) and further analysis using protein analysis through evolutionary relationships (PANTHER) database.ObjectiveTo quantitatively analyze the proteomic profile of non-tobacco associated oral squamous cell carcinoma.MethodsTwenty fresh tissue samples were collected from healthy controls and NT-OSCC, ten each, and were subjected to proteomic analysis. Sample quantification for the presence of protein was done using Bradford assay and bovine serum albumin was used as a standard protein to obtain the standard graph. Fractionation of protein was done using sodium dodecyl sulphate - polyacrylamide gel electrophoresis (SDS-PAGE) and they were separated based on their molecular weight. MS analysis was done and the purified peptides were analysed using MALDI-TOF. PANTHER database for functional classification and pathway analysis was done for identification of protein expression.ResultsOur approach of combining 2D-GE with MS identified four candidate proteins including keratin, alpha-1-antitrypsin (AAT), S100 and serpin B5 with significant differential expression in NT-OSCC as compared with healthy controls. The results showed that the levels of these proteins were significantly upregulated in NT-OSCC when compared to the healthy controls that suggests that these proteins can be used as candidate targets for NT-OSCC therapeutics.ConclusionThe differentially expressed proteins are found to be involved in apoptotic signalling pathways, cytoskeletal dynamics and are known to play a critical role in oral tumorigenesis. Put together, the results provide available baseline information for understanding the development and progression of NT-OSCC. These identified proteins on further validation may be used as potential biomarkers in future for early detection and predicting therapeutic outcome of patients with NT-OSCC.

Project description:Oral squamous cell carcinoma (OSCC) is a highly aggressive cancer and the fourth leading malignancy among males in Taiwan. Some pathogenic bacteria are associated with periodontitis and oral cancer. However, the comprehensive profile of the oral microbiome during the cancer's progression from the early stage to the late stage is still unclear. We profiled the oral microbiota and identified bacteria biomarkers associated with OSCC. The microbiota of an oral rinse from 51 healthy individuals and 197 OSCC patients at different stages were investigated using 16S rRNA V3V4 amplicon sequencing, followed by bioinformatics and statistical analyses. The oral microbiota communities from stage 4 patients showed significantly higher complexity than those from healthy controls. The populations also dynamically changed with the cancer's progression from stage 1 to stage 4. The predominant phyla in the oral samples showed variation in the relative abundance of Fusobacteria, Bacteroidetes, and Actinobacteria. The abundance of Fusobacteria increased significantly with the progression of oral cancer from the healthy controls (2.98%) to OSCC stage 1 (4.35%) through stage 4 (7.92%). At the genus level, the abundance of Fusobacterium increased, while the number of Streptococcus, Haemophilus, Porphyromonas, and Actinomyces decreased with cancer progression. Fusobacterium periodonticum, Parvimonas micra, Streptococcus constellatus, Haemophilus influenza, and Filifactor alocis were associated with OSCC, and they progressively increased in abundance from stage 1 to stage 4. The abundances of Streptococcus mitis, Haemophilus parainfluenzae, and Porphyromonas pasteri were inversely associated with OSCC progression. We selected a bacterial marker panel of three bacteria (upregulated F. periodonticum, down-regulated S. mitis, and P. pasteri), which had an AUC of 0.956 (95% CI = 0.925-0.986) in discriminating OSCC stage 4 from the healthy controls. Furthermore, the functional prediction of oral bacterial communities showed that genes involved in carbohydrate-related metabolism, such as methane metabolism, and energy-metabolism-related parameters, such as oxidative phosphorylation and carbon fixation in photosynthetic organisms, were enriched in late-stage OSCC, while those responsible for amino acid metabolism, such as folate biosynthesis and valine, leucine, and isoleucine biosynthesis, were significantly associated with the healthy controls. In conclusion, our results provided evidence of oral bacteria community changes during oral cancer progression and suggested the possibility of using bacteria as OSCC diagnostic markers.

Dataset Information

A prototype tobacco-associated oral squamous cell carcinoma classifier using RNA from brush cytology.

Publications

A prototype tobacco-associated oral squamous cell carcinoma classifier using RNA from brush cytology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets