title: Development of multigene expression signature maps at the protein level from digitized immunohistochemistry slides.
abstract: Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC) is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps) of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions.
authors.affiliation: Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Metzger
authors.forename: Stephen C
authors.initials: SC
authors.lastname: Dankbar
authors.forename: Jonathan
authors.initials: J
authors.lastname: Henriksen
authors.forename: Anthony E
authors.initials: AE
authors.lastname: Rizzardi
authors.forename: Nikolaus K
authors.initials: NK
authors.lastname: Rosener
authors.forename: Stephen C
authors.initials: SC
authors.lastname: Schmechel
mesh_terms: D000135:Acid Phosphatase; D018952:Antigens, CD34 / Q000235:genetics / Q000378:metabolism; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D007150:Immunohistochemistry / Q000379:methods* / Q000706:statistics & numerical data; D019394:Ki-67 Antigen / Q000235:genetics / Q000378:metabolism; D008297:Male; D010751:Phosphopyruvate Hydratase / Q000235:genetics / Q000378:metabolism; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000235:genetics / Q000378:metabolism; D040081:Protein Array Analysis / Q000379:methods* / Q000706:statistics & numerical data; D017027:Protein Tyrosine Phosphatases / Q000235:genetics / Q000378:metabolism; D012984:Software
chemical_list: D018952:Antigens, CD34; D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen; D000135:Acid Phosphatase; C428439:prostatic acid phosphatase; D017027:Protein Tyrosine Phosphatases; D010751:Phosphopyruvate Hydratase