Title

Authors

Affiliation

¹Department of Bioinformatics, Sri Ramachandra University, Porur, Chennai – 600 116, India; ²Department of Bioinformatics,Sathyabama University, Jeppiar Nagar Chennai – 600 119, India; ³Computational Neuroscience Laboratory, Indian Institute of Technology, Madras. Tamil Nadu, India.

Email

sru.bioinformatics.research2@gmail.com; *Corresponding author

Article Type

Hypothesis

Date

Received April 02, 2012; Accepted April 27, 2012; Published April 30, 2012

Breast cancer is a malignant neoplasm originating from breast tissue, most commonly from the inner lining of milk ducts or the lobules that supply the ducts with milk. ILCs and IDCs vary from each other with respect to various histological, biological and clinical features. Remarkably, ductal tumors tending to form glandular structures, whereas lobular tumors are less cohesive and tends to invade in single file. The high degree of similarity in the prognoses of IDC and ILC makes it beneficial to develop a differential diagnostic protocol to classify the two conditions. The main goal of the study is to construct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences, in order to explore the potential significant gene regulatory networks that can differentiate IDC and ILC and thereby understand the complex interactions that are influenced by the genetic networks. Out of the 54676 genes present on the GPL570 platform- 29 genes exhibited 4 fold up regulation in case of IDC and 22 in the case of ILC. The ductal and lobular tumors displayed a striking difference in the expression of genes associated with cell adhesion, protein folding, and protein phosphorylation and invasion. Construction of separate gene regulation networks for IDC and ILC on the basis of gene expression altercation can be utilized in understanding the distinction in the possible mechanism that underlies the pathological differences between the two, which can be exploited in identifying diagnostic or therapeutic targets.

Keywords

Invasive (or infiltrating) ductal carcinoma (IDC), Invasive lobular carcinoma (ILC), Differential diagnosis, Gene expression profiling, Pathoinformatics, Systems biology, Gene Networks.

Citation

Ragunath et al. Bioinformation 8(8): 359-364 (2012)
 

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.