Dataset Information

Identification of Novel FAM134B (JK1) Mutations in Oesophageal Squamous Cell Carcinoma.

ABSTRACT: Mutation of FAM134B (Family with Sequence Similarity 134, Member B) leading to loss of function of its encoded Golgi protein and has been reported induce apoptosis in neurological disorders. FAM134B mutation is still unexplored in cancer. Herein, we studied the DNA copy number variation and novel mutation sites of FAM134B in a large cohort of freshly collected oesophageal squamous cell carcinoma (ESCC) tissue samples. In ESCC tissues, 37% (38/102) showed increased FAM134B DNA copies whereas 35% (36/102) showed loss of FAM134B copies relative to matched non-cancer tissues. Novel mutations were detected in exons 4, 5, 7, 9 as well as introns 2, 4-8 of FAM134B via HRM (High-Resolution Melt) and Sanger sequencing analysis. Overall, thirty-seven FAM134B mutations were noted in which most (31/37) mutations were homozygous. FAM134B mutations were detected in all the cases with metastatic ESCC in the lymph node tested and in 14% (8/57) of the primary ESCC. Genetic alteration of FAM134B is a frequent event in the progression of ESCCs. These findings imply that mutation might be the major driving source of FAM134B genetic modulation in ESCCs.

SUBMITTER: Haque MH

PROVIDER: S-EPMC4931577 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Novel FAM134B (JK1) Mutations in Oesophageal Squamous Cell Carcinoma.

Haque Md Hakimul MH Gopalan Vinod V Chan Kwok-Wah KW Shiddiky Muhammad J A MJ Smith Robert Anthony RA Lam Alfred King-Yin AK

Scientific reports 20160704

Mutation of FAM134B (Family with Sequence Similarity 134, Member B) leading to loss of function of its encoded Golgi protein and has been reported induce apoptosis in neurological disorders. FAM134B mutation is still unexplored in cancer. Herein, we studied the DNA copy number variation and novel mutation sites of FAM134B in a large cohort of freshly collected oesophageal squamous cell carcinoma (ESCC) tissue samples. In ESCC tissues, 37% (38/102) showed increased FAM134B DNA copies whereas 35% ...[more]

PMID: 27373372

Similar Datasets

Project description:BackgroundOesophageal squamous cell carcinoma (ESCC) is the predominant subtype of oesophageal carcinoma in China, with the overall 5-year survival rate of <10%. The current tumour-node-metastasis (TNM) staging system has become so complex that it is not easy to use in the life expectancy assessment. We aim to combine clinical variables and biomarkers to develop and validate a relative simple and reliable model, named the FENSAM, for ESCC prognosis.MethodsTo build the FENSAM, we analysed 22 potential prognostic factors from 461 patients, including 9 biomarkers (Ezrin, Fascin, desmocollin 2 (DSC2), pFascin, activating transcription factor 3 (ATF3), connective-tissue growth factor (CTGF), neutrophil gelatinase-associated lipocalin (NGAL), NGAL receptor (NGALR), and cysteine-rich angiogenic protein 61 (CYR61)) and other 13 clinical variables. We selected significant factors associated with survival of ESCC patients, and used them to build our FENSAM model. We then obtained the hazard risk score of the model to classify ESCC patients. In addition, we validated the model in an independent cohort of 290 patients from the same hospital. The predictive performance of the model was assessed by the Area under the Receiver Operating Characteristic Curve (AUC) and Kaplan-Meier survival analysis.ResultsWe found six markers significantly associated with survival of ESCC patients (Ezrin, Fascin, ATF3, surgery extent, N-stage, and M-stage). They were combined to create a novel four-stage FENSAM model for patients' classification. FENSAM possessed a high classification precision similar to the TNM staging system, but with a much simpler model. The efficiency of FENSAM was evaluated by different quantiles of AUC and the results of survival analysis. The validation result demonstrated the potential of the FENSAM model to improve classification accuracy for ESCC patients.ConclusionsFENSAM provides an alternative classifier for ESCC patients with a high classification precision using a simple model.

Dataset Information

Identification of Novel FAM134B (JK1) Mutations in Oesophageal Squamous Cell Carcinoma.

Publications

Identification of Novel FAM134B (JK1) Mutations in Oesophageal Squamous Cell Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure