TY - JOUR
T1 - Comparative Analysis of Protein-Protein Interactions in Cancer-Associated Genes
AU - Guda, Purnima
AU - Chittur, Sridar V.
AU - Guda, Chittibabu
N1 - Funding Information:
This work was partly supported by the startup funds to CG from SUNY-Albany, and partly by the Academic Research Enhancement Award ( 1R15GM080681-01 ) to CG from NIGMS/NIH.
PY - 2009/6
Y1 - 2009/6
N2 - Protein-protein interactions (PPIs) have been widely studied to understand the biological processes or molecular functions associated with different disease systems like cancer. While focused studies on individual cancers have generated valuable information, global and comparative analysis of datasets from different cancer types has not been done. In this work, we carried out bioinformatic analysis of PPIs corresponding to differentially expressed genes from microarrays of various tumor tissues (belonging to bladder, colon, kidney and thyroid cancers) and compared their associated biological processes and molecular functions (based on Gene Ontology terms). We identified a set of processes or functions that are common to all these cancers, as well as those that are specific to only one or partial cancer types. Similarly, protein interaction networks in nucleic acid metabolism were compared to identify the common/specific clusters of proteins across different cancer types. Our results provide a basis for further experimental investigations to study protein interaction networks associated with cancer. The methodology developed in this work can also be applied to study similar disease systems.
AB - Protein-protein interactions (PPIs) have been widely studied to understand the biological processes or molecular functions associated with different disease systems like cancer. While focused studies on individual cancers have generated valuable information, global and comparative analysis of datasets from different cancer types has not been done. In this work, we carried out bioinformatic analysis of PPIs corresponding to differentially expressed genes from microarrays of various tumor tissues (belonging to bladder, colon, kidney and thyroid cancers) and compared their associated biological processes and molecular functions (based on Gene Ontology terms). We identified a set of processes or functions that are common to all these cancers, as well as those that are specific to only one or partial cancer types. Similarly, protein interaction networks in nucleic acid metabolism were compared to identify the common/specific clusters of proteins across different cancer types. Our results provide a basis for further experimental investigations to study protein interaction networks associated with cancer. The methodology developed in this work can also be applied to study similar disease systems.
KW - GO similarity analysis
KW - cancer bioinformatics
KW - cancer-associated genes
KW - protein-protein interaction
UR - http://www.scopus.com/inward/record.url?scp=67649637502&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67649637502&partnerID=8YFLogxK
U2 - 10.1016/S1672-0229(08)60030-3
DO - 10.1016/S1672-0229(08)60030-3
M3 - Article
C2 - 19591789
AN - SCOPUS:67649637502
SN - 1672-0229
VL - 7
SP - 25
EP - 36
JO - Genomics, Proteomics and Bioinformatics
JF - Genomics, Proteomics and Bioinformatics
IS - 1-2
ER -