title: Integrated network analysis and logistic regression modeling identify stage-specific genes in Oral Squamous Cell Carcinoma.
abstract: BACKGROUND
  Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity but, OSCC can be difficult to detect at its earliest stage due to its molecular complexity and clinical behavior. Therefore, identification of key gene signatures at an early stage will be highly helpful.
  
  
  METHODS
  The aim of this study was to identify key genes associated with progression of OSCC stages. Gene expression profiles were classified into cancer stage-related modules, i.e., groups of genes that are significantly related to a clinical stage. For prioritizing the candidate genes, analysis was further restricted to genes with high connectivity and a significant association with a stage. To assess predictive power of these genes, a classification model was also developed and tested by 5-fold cross validation and on an independent dataset.
  
  
  RESULTS
  The identified genes were enriched for significant processes and functional pathways, and various genes were found to be directly implicated in OSCC. Forward and stepwise, multivariate logistic regression analyses identified 13 key genes whose expression discriminated early- and late-stage OSCC with predictive accuracy (area under curve; AUC) of ~0.81 in a 5-fold cross-validation strategy.
  
  
  CONCLUSIONS
  The proposed network-driven integrative analytical approach can identify multiple genes significantly related to an OSCC stage; the classification model that is developed with these genes may help to distinguish cancer stages. The proposed genes and model hold promise for monitoring of OSCC stage progression, and our findings may facilitate cancer detection at an earlier stage, resulting in improved treatment outcomes.
authors.affiliation: Functional Genomics and Complex Systems Laboratory, Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Council of Scientific and Industrial Research, Palampur, Himachal Pradesh, India. vinay.plp@gmail.com.|Academy of Scientific and Innovative Research (AcSIR), New Delhi, India. vinay.plp@gmail.com.
authors.forename: Vinay
authors.initials: V
authors.lastname: Randhawa
authors.affiliation: Functional Genomics and Complex Systems Laboratory, Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Council of Scientific and Industrial Research, Palampur, Himachal Pradesh, India. vishal@ihbt.res.in.|Academy of Scientific and Innovative Research (AcSIR), New Delhi, India. vishal@ihbt.res.in.
authors.forename: Vishal
authors.initials: V
authors.lastname: Acharya
mesh_terms: D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000473:pathology*; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D052138:Genes, Neoplasm / Q000235:genetics*; D006801:Humans; D016015:Logistic Models; D009062:Mouth Neoplasms / Q000235:genetics* / Q000473:pathology*; D009367:Neoplasm Staging; D010641:Phenotype