TY - JOUR
T1 - Gene-expression data integration to squamous cell lung cancer subtypes reveals drug sensitivity
AU - Wu, D.
AU - Pang, Y.
AU - Wilkerson, M. D.
AU - Wang, D.
AU - Hammerman, P. S.
AU - Liu, J. S.
N1 - Funding Information:
We thank Drs Neil Hayes at the University of North Carolina at Chapel Hill for providing the SqCC subtype information of the samples in Raponi et al (2006), Alan Dabney at Department of Statistics, Texas A&M University for providing the R code of ClaNC, Heidi Greulich for helping to find the CCLE data sets, Ke Deng and Simeng Han at Harvard Statistics for their discussion, Catherine Wu for proof reading, Laurent Jacob and Terry Speed at the Statistics Department UC Berkely for their suggestion about classification methods, Gordon Smyth and Charity Law at the Walter and Eliza Hall Institute for providing suggestions on how to use ‘voom’, Robert Plenge at Brigham Women Hospital, Tianxi Cai at Harvard Biostatistics, Bryan Williams at Monash Institute of Medical Research and Matthew Meyerson at Dana Farber Cancer Institute for being supportive. This work was supported by grants from the Australian National Health and Medical Research Council (1036541 to Di Wu), and National Science Foundation (NSF IIS-1017967 for publication).
PY - 2013/9/17
Y1 - 2013/9/17
N2 - Background:Squamous cell lung cancer (SqCC) is the second most common type of lung cancer in the United States. Previous studies have used gene-expression data to classify SqCC samples into four subtypes, including the primitive, classical, secretory and basal subtypes. These subtypes have different survival outcomes, although it is unknown whether these molecular subtypes predict response to therapy.Methods:Here, we analysed RNAseq data of 178 SqCC tumour samples and characterised the features of the different SqCC subtypes to define signature genes and pathway alterations specific to each subtype. Further, we compared the gene-expression features of each molecular subtype to specific time points in models of airway development. We also classified SqCC-derived cell lines and their reported therapeutic vulnerabilities.Results:We found that the primitive subtype may come from a later stage of differentiation, whereas the basal subtype may be from an early time. Most SqCC cell lines responded to one of five anticancer drugs (Panobinostat, 17-AAG, Irinotecan, Topotecan and Paclitaxel), whereas the basal-type cell line EBC-1 was sensitive to three other drugs (PF2341066, AZD6244 and PD-0325901).Conclusion:Compared with the other three subtypes of cell lines, the secretory-type cell lines were significantly less sensitive to the five most effective drugs, possibly because of their low proliferation activity. We provide a bioinformatics framework to explore drug repurposing for cancer subtypes based on the available genomic profiles of tumour samples, normal cell types, cancer cell lines and data of drug sensitivity in cell lines.
AB - Background:Squamous cell lung cancer (SqCC) is the second most common type of lung cancer in the United States. Previous studies have used gene-expression data to classify SqCC samples into four subtypes, including the primitive, classical, secretory and basal subtypes. These subtypes have different survival outcomes, although it is unknown whether these molecular subtypes predict response to therapy.Methods:Here, we analysed RNAseq data of 178 SqCC tumour samples and characterised the features of the different SqCC subtypes to define signature genes and pathway alterations specific to each subtype. Further, we compared the gene-expression features of each molecular subtype to specific time points in models of airway development. We also classified SqCC-derived cell lines and their reported therapeutic vulnerabilities.Results:We found that the primitive subtype may come from a later stage of differentiation, whereas the basal subtype may be from an early time. Most SqCC cell lines responded to one of five anticancer drugs (Panobinostat, 17-AAG, Irinotecan, Topotecan and Paclitaxel), whereas the basal-type cell line EBC-1 was sensitive to three other drugs (PF2341066, AZD6244 and PD-0325901).Conclusion:Compared with the other three subtypes of cell lines, the secretory-type cell lines were significantly less sensitive to the five most effective drugs, possibly because of their low proliferation activity. We provide a bioinformatics framework to explore drug repurposing for cancer subtypes based on the available genomic profiles of tumour samples, normal cell types, cancer cell lines and data of drug sensitivity in cell lines.
UR - http://www.scopus.com/inward/record.url?scp=84884593313&partnerID=8YFLogxK
U2 - 10.1038/bjc.2013.452
DO - 10.1038/bjc.2013.452
M3 - Article
C2 - 24002593
AN - SCOPUS:84884593313
SN - 0007-0920
VL - 109
SP - 1599
EP - 1608
JO - British Journal of Cancer
JF - British Journal of Cancer
IS - 6
ER -