Local sparse bump hunting reveals molecular heterogeneity of colon tumors

• Published in: Statistics in medicine Vol. 31; no. 11-12; pp. 1203 - 1220
• Main Authors: Dazard, Jean-Eudes, Sunil Rao, J., Markowitz, Sanford
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 20.05.2012; Wiley Subscription Services, Inc
• Subjects: Adenocarcinoma - epidemiology; Adenocarcinoma - genetics; Algorithms; class discovery; colon cancer patient subtyping; Colonic Neoplasms - epidemiology; Colonic Neoplasms - genetics; Colorectal cancer; early diagnosis and prognosis; Female; Gene expression; Gene Expression Profiling - statistics & numerical data; Genetic Heterogeneity; Genetics; Genotype & phenotype; Humans; local sparse bump hunting; Male; mixture density; Models, Genetic; Models, Statistical; Molecular biology; Neoplasm Metastasis; Neoplasm Staging; Tumors
• ISSN: 0277-6715; 1097-0258; 1097-0258
• DOI: 10.1002/sim.4389

The question of molecular heterogeneity and of tumoral phenotype in cancer remains unresolved. To understand the underlying molecular basis of this phenomenon, we analyzed genome‐wide expression data of colon cancer metastasis samples, as these tumors are the most advanced and hence would be anticipated to be the most likely heterogeneous group of tumors, potentially exhibiting the maximum amount of genetic heterogeneity. Casting a statistical net around such a complex problem proves difficult because of the high dimensionality and multicollinearity of the gene expression space, combined with the fact that genes act in concert with one another and that not all genes surveyed might be involved. We devise a strategy to identify distinct subgroups of samples and determine the genetic/molecular signature that defines them. This involves use of the local sparse bump hunting algorithm, which provides a much more optimal and biologically faithful transformed space within which to search for bumps. In addition, thanks to the variable selection feature of the algorithm, we derived a novel sparse gene expression signature, which appears to divide all colon cancer patients into two populations: a population whose expression pattern can be molecularly encompassed within the bump and an outlier population that cannot be. Although all patients within any given stage of the disease, including the metastatic group, appear clinically homogeneous, our procedure revealed two subgroups in each stage with distinct genetic/molecular profiles. We also discuss implications of such a finding in terms of early detection, diagnosis and prognosis. Copyright © 2011 John Wiley & Sons, Ltd.