Predicting Survival Within the Lung Cancer Histopathological Hierarchy Using a Multi-Scale Genomic Model of Development

DSpace/Manakin Repository

Predicting Survival Within the Lung Cancer Histopathological Hierarchy Using a Multi-Scale Genomic Model of Development

Citable link to this page

 

 
Title: Predicting Survival Within the Lung Cancer Histopathological Hierarchy Using a Multi-Scale Genomic Model of Development
Author: Sun, Yao; Liu, Hongye; Kho, Alvin Thong-Juak; Kohane, Isaac Samuel

Note: Order does not necessarily reflect citation order of authors.

Citation: Liu, Hongye, Alvin T. Kho, Isaac S. Kohane, and Yao Sun. 2006. Predicting survival within the lung cancer histopathological hierarchy using a multi-scale genomic model of development. PLoS Medicine 3(7): e232.
Full Text & Related Files:
Abstract: Background: The histopathologic heterogeneity of lung cancer remains a significant confounding factor in its diagnosis and prognosis—spurring numerous recent efforts to find a molecular classification of the disease that has clinical relevance. Methods and Findings: Molecular profiles of tumors from 186 patients representing four different lung cancer subtypes (and 17 normal lung tissue samples) were compared with a mouse lung development model using principal component analysis in both temporal and genomic domains. An algorithm for the classification of lung cancers using a multi-scale developmental framework was developed. Kaplan–Meier survival analysis was conducted for lung adenocarcinoma patient subgroups identified via their developmental association. We found multi-scale genomic similarities between four human lung cancer subtypes and the developing mouse lung that are prognostically meaningful. Significant association was observed between the localization of human lung cancer cases along the principal mouse lung development trajectory and the corresponding patient survival rate at three distinct levels of classical histopathologic resolution: among different lung cancer subtypes, among patients within the adenocarcinoma subtype, and within the stage I adenocarcinoma subclass. The earlier the genomic association between a human tumor profile and the mouse lung development sequence, the poorer the patient's prognosis. Furthermore, decomposing this principal lung development trajectory identified a gene set that was significantly enriched for pyrimidine metabolism and cell-adhesion functions specific to lung development and oncogenesis. Conclusions: From a multi-scale disease modeling perspective, the molecular dynamics of murine lung development provide an effective framework that is not only data driven but also informed by the biology of development for elucidating the mechanisms of human lung cancer biology and its clinical outcome.
Published Version: doi:10.1371/journal.pmed.0030232
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1483910/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:5025796
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters