Literature DB >> 22706119

[DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer].

Przemysław Kwiatkowski1, Piotr Wierzbicki, Andrzej Kmieć, Janusz Godlewski.   

Abstract

Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations. Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment. The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.

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Year:  2012        PMID: 22706119     DOI: 10.5604/17322693.999919

Source DB:  PubMed          Journal:  Postepy Hig Med Dosw (Online)        ISSN: 0032-5449            Impact factor:   0.270


  2 in total

1.  A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

Authors:  Tzu-Hao Chang; Shih-Lin Wu; Wei-Jen Wang; Jorng-Tzong Horng; Cheng-Wei Chang
Journal:  Biomed Res Int       Date:  2014-01-22       Impact factor: 3.411

2.  Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis.

Authors:  Xinyu Chong; Rui Peng; Yan Sun; Luyu Zhang; Zheng Zhang
Journal:  Biomed Res Int       Date:  2020-09-21       Impact factor: 3.411

  2 in total

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