Journal article
Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment
Current Genomics, Vol.15(5), pp.349-356
10/2014
DOI: 10.2174/138920291505141106102854
PMCID: PMC4245695
PMID: 25435798
Abstract
By measuring gene expression at an unprecedented resolution and throughput, RNA-seq has played a pivotal role in studying biological functions. Its typical application in clinical medicine is to identify the discrepancies of gene expression between two different types of cancer cells, sensitive and resistant to chemotherapeutic treatment, in a hope to predict drug response. Here we modified and used a mechanistic model to identify distinct patterns of gene expression in response of different types of breast cancer cell lines to chemotherapeutic treatment. This model was founded on a mixture likelihood of Poisson-distributed transcript read data, with each mixture component specified by the Skellam function. By estimating and comparing the amount of gene expression in each environment, the model can test how genes alter their expression in response to environment and how different genes interact with each other in the responsive process. Using the modified model, we identified the alternations of gene expression between two cell lines of breast cancer, resistant and sensitive to tamoxifen, which allows us to interpret the expression mechanism of how genes respond to metabolic differences between the two cell types. The model can have a general implication for studying the plastic pattern of gene expression across different environments measured by RNA-seq.
Details
- Title: Subtitle
- Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment
- Creators
- Ningtao Wang - Department of Pharmacology, The Pennsylvania State University, Hershey, PA 17033, USAYaqun Wang - Department of Pharmacology, The Pennsylvania State University, Hershey, PA 17033, USAHao Han - Department of Pharmacology, The Pennsylvania State University, Hershey, PA 17033, USAKathryn J Huber-Keener - University of Iowa, Obstetrics and GynecologyJin-Ming YangRunze Li - Department of Pharmacology, The Pennsylvania State University, Hershey, PA 17033, USARongling Wu - Department of Pharmacology, The Pennsylvania State University, Hershey, PA 17033, USA
- Resource Type
- Journal article
- Publication Details
- Current Genomics, Vol.15(5), pp.349-356
- Publisher
- Bentham Science Publishers
- DOI
- 10.2174/138920291505141106102854
- PMID
- 25435798
- PMCID
- PMC4245695
- ISSN
- 1389-2029
- eISSN
- 1875-5488
- Language
- English
- Date published
- 10/2014
- Academic Unit
- Obstetrics and Gynecology
- Record Identifier
- 9983930274702771
Metrics
12 Record Views