Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of oral cavity samples from human squamous cell carcinoma patients

ABSTRACT: Metastasis via the lymphatics is a major risk factor in squamous cell carcinoma of the oral cavity (OSCC). We sought to determine whether the presence of metastasis in the regional lymph node could be predicted by a gene expression signature of the primary tumor. A total of 18 OSCCs were characterized for gene expression by hybridizing RNA to Affymetrix U133A gene chips. Genes with differential expression were identified using a permutation technique and verified by quantitative RT-PCR and immunohistochemistry. A predictive rule was built using a support vector machine, and the accuracy of the rule was evaluated using crossvalidation on the original data set and prediction of an independent set of four patients. Metastatic primary tumors could be differentiated from nonmetastatic primary tumors by a signature gene set of 116 genes. This signature gene set correctly predicted the four independent patients as well as associating five lymph node metastases from the original patient set with the metastatic primary tumor group. We concluded that lymph node metastasis could be predicted by gene expression profiles of primary oral cavity squamous cell carcinomas. The presence of a gene expression signature for lymph node metastasis indicates that clinical testing to assess risk for lymph node metastasis should be possible.

ORGANISM(S): Homo sapiens

SUBMITTER: Rebekah O'Donnell

PROVIDER: E-GEOD-2280 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Gene expression signature predicts lymphatic metastasis in squamous cell carcinoma of the oral cavity.

O'Donnell Rebekah K RK Kupferman Michael M Wei S Jack SJ Singhal Sunil S Weber Randal R O'Malley Bert B Cheng Yi Y Putt Mary M Feldman Michael M Ziober Barry B Muschel Ruth J RJ

Oncogene 20050201 7

Metastasis via the lymphatics is a major risk factor in squamous cell carcinoma of the oral cavity (OSCC). We sought to determine whether the presence of metastasis in the regional lymph node could be predicted by a gene expression signature of the primary tumor. A total of 18 OSCCs were characterized for gene expression by hybridizing RNA to Affymetrix U133A gene chips. Genes with differential expression were identified using a permutation technique and verified by quantitative RT-PCR and immun ...[more]

PMID: 15558013

Similar Datasets

Project description:Objective: The purpose of this study was to investigate the molecular basis of tumorigenesis and regional lymph node metastasis in LSCC, and provide a set of genes that may be useful for the development of novel diagnostic markers and/or more effective therapeutic strategies. Methods: A total number of 10 patients who underwent surgery for primary laryngeal squamous cell carcinoma were recruited for microarray analysis. LSCC tissues compared with corresponding adjacent non-neoplastic tissues were analysed by Illumina mRNA microarrays,and LSCC tissues with regional lymph node metastasis and LSCC tissues without regional lymph node metastasis were analyzed in the same manner.The most frequently differently expressed genes screened by microarrays were also validated by qRT-PCR in another 42 patients diagnosed for LSCC . Results: Analysed by Illumina mRNA microarrays,there were 361 genes significantly related to tumorigenesis while 246 genes significantly related to regional lymph node metastasis in LSCC. We found that the six genes (CDK1,CDK2,CDK4,MCM2,MCM3,MCM4) were most frequently differently expressed functional genes related to tumorigenesis while eIF3a and RPN2 were most frequently differently expressed functional genes related to regional lymph node metastasis in LSCC. The expressions of these genes were also validated by qRT-PCR. Conclusions: The research revealed a gene expression signature of tumorigenesis and regional lymph node metastasis in laryngeal squamous cell carcinoma.Of the total, the deregulation of several genes (CDK1, CDK2, CDK4, MCM2, MCM3, MCM4, EIF3a and RPN2) were potentially associated with disease development and progression. The result will contribute to the understanding of the molecular basis of LSCC and help to improve diagnosis and treatment. A total number of 10 patients who underwent surgery for primary laryngeal squamous cell carcinoma were recruited for microarray analysis. LSCC tissues compared with corresponding adjacent non-neoplastic tissues were analysed by Illumina mRNA microarrays,and LSCC tissues with regional lymph node metastasis and LSCC tissues without regional lymph node metastasis were analyzed in the same manner.The most frequently differently expressed genes screened by microarrays were also validated by qRT-PCR in another 42 patients diagnosed for LSCC .

Project description:Lymph node involvement is the most important prognostic factor in breast cancer, but little is known about the underlying molecular changes. First, to identify a molecular signature associated with nodal metastasis, gene expression analysis was performed on a homogeneous group of 96 primary breast tumors, balanced for lymph node involvement. Each tumor was diagnosed as a poorly differentiated, estrogen positive, her2-neu negative invasive ductal cancer. (Affymetrix Human U133 Plus 2.0 microarray chips). A model, including 241 genes was built and validated on an internal and external dataset performed with Affymetrix technology. All samples used for validation had the same characteristics as the initial tumors. The area under the ROC curve (AUC) for the internal dataset was 0.646 and 0.651 for the external datasets. Thus, the molecular profile of a breast tumor reveals information about lymph node involvement, even in a homogeneous group of tumors. However, an AUC of 0.65 indicates only a weak correlation. Our model includes multiple kinases, apoptosis related and zinc ion binding genes. Pathway analysis using the Molecular Signatures Database revealed relevant gene sets (BAF57, Van 't Veer). Next, miRNA profiling was performed on 82/96 tumors using Human MiRNA microarray chips (Illumina). Eight miRNAs were significantly differentially expressed according to lymph node status at a significance level of 0.05, without correcting for multiple testing. The analysis of the inverse correlation between a miRNA and its computationally predicted targets point to general deregulation of the miRNA machinery potentially responsible for lymph node invasion. In conclusion, our results provide evidence that lymph node involvement in breast cancer is not a random process. Gene expression profiling: A training set of 96 patients and an independent internal dataset of 20 patients balanced for lymph node involvement was selected from the multidisciplinary breast centre database miRNA profiling not provided in this Series.

Dataset Information

Transcription profiling of oral cavity samples from human squamous cell carcinoma patients

Publications

Gene expression signature predicts lymphatic metastasis in squamous cell carcinoma of the oral cavity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets