Title

Detection and analysis of stable and flexible genes towards a genome signature framework in cancer

Authors

Emir Sehovic^1,*, Adem Hadrovic², Senol Dogan³

Affiliation

¹International Burch University Sarajevo, Francuske Revolucije BB, 71210 Sarajevo; ²Sarajevo School of Science and Technology, Hrasnicka Cesta 3a, 71210 Sarajevo; ³The University of Leipzig, Faculty of Physics and Earth Science, Peter Debye Institute for Soft Matter Physics, LinnestraBe 5, 04103 Leipzig, Germany.

Email

Emir Sehovic - emir.sehovic@gmail.com; Tel number; +38762244529; *Corresponding author

Article Type

Research Article

Date

Received October 29, 2019; Revised November 5, 2019; Accepted November 9, 2019; Published November 10, 2019

Comparison and detection of stable cancer genes across cancer types is of interest. The gene expression data of 6 different cancer types (colon, breast, lung, ovarian, brain and renal) and a control group from The Cancer Genome Atlas (TCGA) database were used in this study. The comparison of gene expression data together with the calculation standard deviations of such data was completed using a statistical model for the detection of stable genes. Genes having similar expression (referred as flexible genes) pattern to the control group in four out of six cancer types are PATE, NEUROD4 and TRAFD1. Moreover, 13 genes showed low difference compared to the control group with low standard deviation across cancer types (referred as stable genes). Among them, genes GDF2, KCNT1 and RNF151 showed consistent low expression while ODF4, OR5I1, MYOG and OR2B11 showed consistent high expression. Thus, the detection and analysis of stable and flexible cancer genes help towards the design and development of a framework (outline) for specific genome signature (biomarker) in cancer.

Keywords

Cancer, gene expression, pattern, cancer types, analysis, statistics, model, gene expression, stable, flexible

Citation

Sehovic et al. Bioinformation 15(10): 772-779 (2019)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.