Identification of gene expression models for laryngeal squamous cell carcinoma using co-expression network analysis
نویسندگان
چکیده
منابع مشابه
Identification of gene expression models for laryngeal squamous cell carcinoma using co-expression network analysis
One of the most common head and neck cancers is laryngeal squamous cell carcinoma (LSCC). LSCC exhibits high mortality rates and has a poor prognosis. The molecular mechanisms leading to the development and progression of LSCC are not entirely clear despite genetic and therapeutic advances and increased survival rates. In this study, a total of 116 differentially expressed genes (DEGs), includi...
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Background & Objective: Laryngeal squamous cell carcinoma (LSCC) is considered to be one of the most common cancers of the head and neck, accounting for roughly 90% of all malignant tumors of the larynx. To have a timely diagnosis for a better and practical therapy, molecular markers have to be investigated. The aim of this study was to determine the expression of Cyclin D1 (CD...
متن کاملGene expression analysis of laryngeal squamous cell carcinoma
Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignancies of the head and neck tumors Zhang et al., 2013 [1]). Previous studies have associated its occurrence with social activities, such as tobacco and alcohol consumption (Hashibe et al., 2007a [2]; Hashibe et al., 2007b [3]; Shangina et al., 2006 [4]). Here, we performed a genome-wide gene expression profiling in thirty-...
متن کاملProteomic Analysis of Gene Expression in Basal Cell Carcinoma
Background: Basal Cell Carcinoma (BCC) is a type of non-melanoma skin cancer. Alteration in gene expression is the important event that happens in cancer cell. Detection of this event is possible by proteomics techniques. Methods: Normal and tumor tissues were taken from BCC patient. Total proteins were purified by standard methods, and proteins were separated by two-dimensional electrophoresis...
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We performed a gene co-expression analysis on Lung Squamous Cell Carcinoma data to find modules (groups) of genes that may highly impact the growth of these type of tumors. Additionally, we used cancer survival data to relate modules to prognostic significance in terms of survival time. Analysis on RNA-seq data revealed modules which are significant in gene enrichment analysis. Specifically, tw...
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ژورنال
عنوان ژورنال: Medicine
سال: 2018
ISSN: 0025-7974
DOI: 10.1097/md.0000000000009738