| dc.description.abstract | Breast cancer is the most common cancer in women worldwide, and is the second most common cancer in the world, responsible for more than 500 000 deaths annually. Estimates are that 1 in 8 women will develop breast cancer in their lifetime. In South Africa, breast cancer in women affects about 16.6 % of the population and could see a 78 % increase in cases by 2030. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effects. The Chemotherapy resistance against anticancer drugs is an emerging concern. Biomarkers have been identified as a viable option for early detection and progression of disease.
Examples of biological indicators for disease could be the ATP-binding cassette (ABC) drug transporters that utilizes the energy derived from ATP hydrolysis to efflux many chemically diverse compounds across the plasma membrane, thereby playing a critical and important physiological role in protecting cells from xenobiotics. These transporters are also implicated in the development of multidrug resistance (MDR) in cancer cells that have been treated with chemotherapeutics.
High expression of these membrane proteins as a family of ABC drug transporters are one of the main reasons for drug resistance by increasing the efflux rate of the anti-cancer drug from cancer cells. ABC drug transporters are considered to be one of the largest protein families in living organisms. There are 48 genes in the human genome that encode ABC transporters, which are divided into seven subfamilies (ABCA-ABCG). Studies revealed that ABC transporter genes has been shown to be associated with tumour development, progression and response to therapy, suggesting their possible use as diagnostic, prognostic and predictive biomarkers.
The aim of this study was to investigate and identify novel ABC transporter genes that could be implicated in breast cancer and MDR and potentially would be a therapeutic target for successful chemotherapy treatment and disease progression and survival in breast cancer patients.
An in silico approach was used to identify 10 ABC transporter genes (ABCB2, ABCB9, ABCB10, ABCC1, ABCC4, ABCC5, ABCC10, ABCC11, ABCC12, ABCD1) implicated in breast cancer by conferring drug resistance through over-expression in cancer cells. The in silico study investigated the tissue expression specificity, protein interaction/s, pathways, and comparative toxicogenomics of the identified ABC transporter genes using several computational software such as Tissue-specific Gene Expression and Regulation (TiGER), the Human Protein Atlas (HPA), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and The Comparative Toxicogenomics Database (CTD).
The 48 ABC transporter genes were shortlisted through very selective criteria that narrowed the genes down to 10. Differential expression analysis of the genes using TiGER and HPA compared expression in normal versus cancerous tissue of the candidate genes. The result showed that ABCC11 was preferentially expressed in breast tissue with an enrichment value higher than 10.0. The results also showed ABCC10 overexpressed in breast cancer tissue, making these two genes top candidates for further analysis.
Result from STRING database showed a strong functional interaction network between the prioritized genes through protein homology, co-expression and text mining as evidence for the observed interactions. Furthermore, the prioritized list of genes was submitted to the CTD for intersectional analysis to obtain the toxicity relationship between the genes and the Tamoxifen as the first line chemotherapeutic treatment for breast cancer. Venn diagrams obtained from CTD showed intersectional relation between ABCB2, ABCC1, ABCC4, ABCC11, and ABCD1 genes and Tamoxifen.
Furthermore, an in silico validation of the prognostic/predictive values of the 10 prioritized genes (list 2) was carried out using an online biomarker validation tool and database for cancer gene expression data using survival analysis (SurvExpress) and gene expression based survival analysis web application for multiple cancer (PROGGENE). Results obtained from the PROGGENE survival and predictive analysis showed good prognostic values for the genes ABCB2, ABCC1, ABCC4, ABCC10 and ABCC12 with their significance measured by the probability value (Pv) (0.053, 0.001118, 0.01286, 0.00604, 0.00157 respectively).
From this study ABCC1, ABCC4, ABCC5, ABCC10, and ABCC11 genes could serve as putative therapeutic target biomarkers for breast cancer treatment following further in depth analysis. However, the variance in the effectiveness of individual genes suggests that the set of genes would perform better than individual gene in the management of breast cancer. The modulating roles of ABCC4, ABCC5 ABCC10, and ABCC11 in drug induced apoptosis, suggest they could probably play an important role in personalized medicine and could serve as biomarkers to monitor the prognosis and/or therapeutic outcome of chemotherapy drugs in breast cancer patients.
The use of modern genomics, proteomics, bioinformatics, and systems biology approaches has resulted in a substantial increase in our ability to identify molecular mechanisms that are involved in MDR in cancer and to find drugs that may block or reverse the development of drug resistance. By using an in silico approach in this study, a list of five ABC transporter genes were identified, of which two (ABCC10 and ABCC11) could potentially serve as prognostic and predictive biomarkers for the management of breast cancer treatment. | en_US |
