title: CrossLink: a novel method for cross-condition classification of cancer subtypes.
abstract: We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another.
  
  
  
  To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature.
  
  
  
  We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles.
  
  
  
  A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.
authors.affiliation: Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA.
authors.forename: Chifeng
authors.initials: C
authors.lastname: Ma
authors.affiliation: Weill Cornell Medicine-Qatar, Doha, Qatar.|Division of Translational Medicine, Sidra Medical and Research Center, Doha, Qatar.
authors.forename: Konduru S
authors.initials: KS
authors.lastname: Sastry
authors.affiliation: Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA.
authors.forename: Mario
authors.initials: M
authors.lastname: Flore
authors.affiliation: Hamad Medical Corporation, Doha, Qatar.
authors.forename: Salah
authors.initials: S
authors.lastname: Gehani
authors.affiliation: Hamad Medical Corporation, Doha, Qatar.
authors.forename: Issam
authors.initials: I
authors.lastname: Al-Bozom
authors.affiliation: Department of Mechanical Engineering, University of Texas at San Antonio, San Antonio, TX, USA.
authors.forename: Yusheng
authors.initials: Y
authors.lastname: Feng
authors.affiliation: Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
authors.forename: Erchin
authors.initials: E
authors.lastname: Serpedin
authors.affiliation: Weill Cornell Medicine-Qatar, Doha, Qatar.
authors.forename: Lotfi
authors.initials: L
authors.lastname: Chouchane
authors.affiliation: Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.|Greehey Children Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
authors.forename: Yidong
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA. yufei.huang@utsa.edu.|Greehey Children Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA. yufei.huang@utsa.edu.
authors.forename: Yufei
authors.initials: Y
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000235:genetics* / Q000473:pathology; D016000:Cluster Analysis; D005260:Female; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D006801:Humans; D059467:Transcriptome / Q000235:genetics*