Lung disease diagnosis from gene expression profiles

Lung diseases include some of the most widespread and deadly conditions known to affect people in the US today. One of the main challenges in treating lung disease is the difficulty of diagnosis. Clinical diagnosis remains largely dependent upon symptomatic-based diagnoses; many cases can be either misdiagnosed or undiagnosed until disease has progressed to a more severe stage. Most studies aimed at finding molecular-based diagnostics have focused on one or two diseases at a time, yielding limited success. Instead, we searched for biomarkers reflective of the global health state of the lung by studying data taken from a broad range of lung diseases. We used gene expression microarray data from five different lung diseases—lung adenocarcinoma, lung squamous cell carcinoma, large cell lung carcinoma, chronic obstructive pulmonary disease, and asthma—as well as a non-diseased phenotype, to train a classification tree scheme based on the Top Scoring Pair algorithm (Geman et al., Stat Appl Genet Mol Biol. 2004; 3: Article 19). The algorithm identified a 32 gene-pair panel that classified all of the phenotypes considered and another panel of 21 gene pair classifiers that classified the three cancers explicitly with sensitivity of 67±8% and 79±6% in ten-fold cross validation (p < 0.001), respectively. Several of the markers have been previously cited in literature as linked to these cancers. Thus, a TSP-based classification tree scheme accurately identifies lung diseases from the relative expression of a parsimonious set of diagnostic gene pairs.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Chemical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Ma, Shuyi

Contributors dc:contributor

• Price, Nathan D.

• lung disease
• lung cancer
• asthma
• Chronic obstructive pulmonary disease (COPD)
• disease diagnosis
• systems biology
• Top Scoring Pair algorithm

Statement dc:rights

• Copyright 2011 Shuyi Ma

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/24449

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/24449