Joint analysis of histopathology image features and gene expression in breast cancer.

Popovici, Vlad; Budinská, Eva; Čápková, Lenka; Schwarz, Daniel; Dušek, Ladislav; Feit, Josef; Jaggi, Rolf (2016). Joint analysis of histopathology image features and gene expression in breast cancer. BMC bioinformatics, 17(1), p. 209. BioMed Central 10.1186/s12859-016-1072-z

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BACKGROUND Genomics and proteomics are nowadays the dominant techniques for novel biomarker discovery. However, histopathology images contain a wealth of information related to the tumor histology, morphology and tumor-host interactions that is not accessible through these techniques. Thus, integrating the histopathology images in the biomarker discovery workflow could potentially lead to the identification of new image-based biomarkers and the refinement or even replacement of the existing genomic and proteomic signatures. However, extracting meaningful and robust image features to be mined jointly with genomic (and clinical, etc.) data represents a real challenge due to the complexity of the images. RESULTS We developed a framework for integrating the histopathology images in the biomarker discovery workflow based on the bag-of-features approach - a method that has the advantage of being assumption-free and data-driven. The images were reduced to a set of salient patterns and additional measurements of their spatial distribution, with the resulting features being directly used in a standard biomarker discovery application. We demonstrated this framework in a search for prognostic biomarkers in breast cancer which resulted in the identification of several prognostic image features and a promising multimodal (imaging and genomic) prognostic signature. The source code for the image analysis procedures is freely available. CONCLUSIONS The framework proposed allows for a joint analysis of images and gene expression data. Its application to a set of breast cancer cases resulted in image-based and combined (image and genomic) prognostic scores for relapse-free survival.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > Forschungsbereich Pathologie > Forschungsgruppe Molekularbiologie

UniBE Contributor:

Jaggi, Rolf

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1471-2105

Publisher:

BioMed Central

Language:

English

Submitter:

Peggy Kübler

Date Deposited:

18 Apr 2017 10:03

Last Modified:

23 Apr 2017 02:24

Publisher DOI:

10.1186/s12859-016-1072-z

PubMed ID:

27170365

Uncontrolled Keywords:

Biomarker discovery; Gene expression; Histopathology images; Image analysis; Multimodal data mining

BORIS DOI:

10.7892/boris.95930

URI:

https://boris.unibe.ch/id/eprint/95930

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