A Neural network approach to multi-biomarker panel development based on LC/MS/MS proteomics profiles: A case study in breast cancer

Fan Zhang, Jake Y. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Liquid chromatography tandem mass spectrometry (LC/MS/MS) based plasma proteomics profiling technique is a promising technology platform to study candidate protein biomarkers for complex human diseases such as cancer. Factors such as inherent variability, protein detectability limitation, and peptide discovery biases among LC/MS/MS platforms have made the classification and prediction of proteomics profiles challenging. In this paper, we developed a proteomics data analysis method to identify multiprotein biomarker panels for breast cancer diagnosis based on artificial neural networks. Using this method, we first applied standard analysis of variance (ANOVA) to derive a list of single candidate biomarkers that significantly changed from plasma proteomics profiles between breast cancer and controls. Next, we constructed a feed forward neural network (FFNN) for each combination of single marker proteins and trained with plasma proteomics results derived from 40 breast cancer women and 40 control women. We evaluated the results for best fivemarker panel and ten-marker panels on a testing data set of similar cohort of 80 plasma proteomics profiles, of which half are breast cancer women and half are controls, using both statistical methods (receiver operating characteristics curve comparisons) and biological literature validation. We found that fivemarker panel using two-variable FFNN output achieved the best prediction performance in testing data set, with 82.5% in sensitivity and 82.5% in specificity. Our computational method can serve as a general model for multi-biomarker panel discovery applications in other diseases.

Original languageEnglish
Title of host publication2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009
DOIs
StatePublished - 2009
Event2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009 - Albuquerque, NM, United States
Duration: 2 Aug 20095 Aug 2009

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)1063-7125

Conference

Conference2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009
CountryUnited States
CityAlbuquerque, NM
Period2/08/095/08/09

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