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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Weighted gene co-expression network analysis of colorectal patients to identify right drug-right target for potent efficacy of targeted therapy

Tripathi, Anamika 10 December 2017 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Colon rectal cancer (CRC) is one of the most common cancers worldwide. It is characterized by the successive accumulation of mutations in genes controlling epithelial cell growth and differentiation leading to genomic in-stability. This results in the activation of proto-oncogene(K-ras), loss of tumor suppressor gene activity and ab-normality in DNA repair genes. Targeted therapy is a new generation of cancer treatment in which drugs attack targets which are specific for the cancer cell and are critical for its survival or for its malignant behavior. Survival of metastatic CRC patients has approximately doubled due to the development of new combinations of stan-dard chemotherapy, and the innovative targeted therapies, such as monoclonal antibodies against epidermal growth factor receptor (EGFR) or monoclonal antibodies against vascular endothelial growth factor (VEGFR).The study is to exhibit the need for right drug-right target and provides a proof of principle for potent efficacy of molecular targeted therapy for CRC. We have performed the weighted gene co-expression network analysis for three different patient cohort treated with different targeted therapy drugs. The results demonstrates the variation across different treatment regime in context of transcription factor networks. New significant tran-scription factors have been identified as potential biomarker for CRC cancer including EP300, STAT6, ATF3, ELK1, HNF4A, JUN, TAF1, IRF1, TP53, ELF1 and YY1. The results provides guidance for future omic study on CRC and additional validation work for potent biomarker for CRC.

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