Huang, Ruiqi
(2015)
Investigation and implementation Gene signature development using microarray data
– A case study on early stage non-small cell lung cancer.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
Purpose
Gene signature development using microarrays has started more than 15 years ago, yet there are still common mistakes made by researchers. The goal of this research is to investigate and implement gene signature using affymetrix array data. It aims to establish a working flow with well-justified steps for gene signature development.
Methods
Gene expression data from surgery samples of 62 early stage un-treated NSCLC patients in JBR10 trial was used for training model development. Individual genes were selected using univariate cox regression analysis, and then the gene set was summarized by principle components, which were then served as the inputs to the Cox regression model. A multi-layer internal validation was conducted for modeling evaluation. The performance of the gene signature was evaluated by testing on three independent data sets.
Results
A signature of 88 genes was developed that can identify patients with significantly different survival prognosis (Hazard Ratio, 95% CI, P). The signature was successfully validated in independent datasets (Hazard Ratio, 95% CI, P; Hazard Ratio, 95% CI, P; Hazard Ratio, 95% CI, P).
Conclusion
A working flow of gene signature development composed of preliminary gene filtering, individual gene selection, predictive model construction using supervised principle component analysis and further internal/external validation, has been constructed.
Using gene expression of 62 patients from affymetrix array data in JBR.10 trials, an 88-gene signature was obtained and validated in independent datasets.
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Details
Item Type: |
University of Pittsburgh ETD
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Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
29 June 2015 |
Date Type: |
Publication |
Defense Date: |
23 April 2015 |
Approval Date: |
29 June 2015 |
Submission Date: |
10 April 2015 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
50 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
School of Public Health > Biostatistics |
Degree: |
MS - Master of Science |
Thesis Type: |
Master's Thesis |
Refereed: |
Yes |
Uncontrolled Keywords: |
NSCLC, gene signature, Principle component analysis |
Date Deposited: |
29 Jun 2015 13:57 |
Last Modified: |
15 Nov 2016 14:27 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/24761 |
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