Signaling pathways activation profiles make better markers of cancer than expression of individual genes

Identification of reliable and accurate molecular markers remains one of the major challenges of contemporary biomedicine. We developed a new bioinformatic technique termed OncoFinder that for the first time enables to quantatively measure activation of intracellular signaling pathways basing on transcriptomic data. Signaling pathways regulate all major cellular events in health and disease. Here, we showed that the Pathway Activation Strength (PAS) value itself may serve as the biomarker for cancer, and compared it with the “traditional” molecular markers based on the expression of individual genes. We applied OncoFinder to profile gene expression datasets for the nine human cancer types including bladder cancer, basal cell carcinoma, glioblastoma, hepatocellular carcinoma, lung adenocarcinoma, oral tongue squamous cell carcinoma, primary melanoma, prostate cancer and renal cancer, totally 292 cancer and 128 normal tissue samples taken from the Gene expression omnibus (GEO) repository. We profiled activation of 82 signaling pathways that involve ~2700 gene products. For 9/9 of the cancer types tested, the PAS values showed better area-under-the-curve (AUC) scores compared to the individual genes enclosing each of the pathways. These results evidence that the PAS values can be used as a new type of cancer biomarkers, superior to the traditional gene expression biomarkers.

[1]  V. Amani,et al.  Characterization of Distinct Immunophenotypes across Pediatric Brain Tumor Types , 2013, The Journal of Immunology.

[2]  E. Kilpatrick,et al.  Appropriate requesting of serum tumour markers , 2009, BMJ : British Medical Journal.

[3]  Zu-de Xu,et al.  Loss of PPM1A expression enhances invasion and the epithelial-to-mesenchymal transition in bladder cancer by activating the TGF-β/Smad signaling pathway , 2014, Oncotarget.

[4]  M. Blagosklonny.  Common drugs and treatments for cancer and age-related diseases: revitalizing answers to NCI's provocative questions , 2012, Oncotarget.

[5]  William A. Dembski,et al.  Intelligent Design , 1999 .

[6]  N. Kuzmina,et al.  Handling Complex Rule-Based Models of Mitogenic Cell Signaling (on the Example of ERK Activation upon EGF Stimulation) , 2011 .

[7]  Enrique Parás Chavero.  The past and the future , 1965 .

[8]  Nikolay M. Borisov,et al.  Oncofinder, a new method for the analysis of intracellular signaling pathway activation using transcriptomic data , 2014, Front. Genet..

[9]  M. Blagosklonny.  The power of chemotherapeutic engineering: Arresting cell cycle and suppressing senescence to protect from mitotic inhibitors , 2011, Cell cycle.

[10]  F. Mottaghy,et al.  Hedgehog signaling sensitizes Glioma stem cells to endogenous nano-irradiation , 2014, Oncotarget.

[11]  M. Blagosklonny.  MTOR-driven quasi-programmed aging as a disposable soma theory , 2013, Cell cycle.

[12]  A M Aliper,et al.  Silencing AML1-ETO gene expression leads to simultaneous activation of both pro-apoptotic and proliferation signaling , 2014, Leukemia.

[13]  Kumaran Kandasamy,et al.  An evaluation of human protein-protein interaction data in the public domain , 2006, BMC Bioinformatics.

[14]  R. Gelber,et al.  CA15-3 and alkaline phosphatase as predictors for breast cancer recurrence: a combined analysis of seven International Breast Cancer Study Group trials. , 2006, Annals of oncology : official journal of the European Society for Medical Oncology.

[15]  P. Sved,et al.  Loss of PTEN stabilizes the lipid modifying enzyme cytosolic phospholipase A2α via AKT in prostate cancer cells , 2014, Oncotarget.

[16]  Qingling Li,et al.  Overexpression of HMGB1 in melanoma predicts patient survival and suppression of HMGB1 induces cell cycle arrest and senescence in association with p21 (Waf1/Cip1) up-regulation via a p53-independent, Sp1-dependent pathway , 2014, Oncotarget.

[17]  J. McCubrey,et al.  Inhibition of GSK-3β activity can result in drug and hormonal resistance and alter sensitivity to targeted therapy in MCF-7 breast cancer cells , 2014, Cell cycle.

[18]  T. Werner,et al.  Elevated osteonectin/SPARC expression in primary prostate cancer predicts metastatic progression , 2012, Prostate Cancer and Prostatic Diseases.

[19]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[20]  C. Heldin,et al.  TGFβ-induced invasion of prostate cancer cells is promoted by c-Jun-dependent transcriptional activation of Snail1 , 2014, Cell cycle.

[21]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .

[22]  R. Ramesh,et al.  Mitogen-activated protein kinases and their role in radiation response. , 2013, Genes & cancer.

[23]  M. Blagosklonny,et al.  The purpose of the HIF-1/PHD feedback loop: To limit mTOR-induced HIF-1α , 2011, Cell cycle.

[24]  Nikolay M. Borisov,et al.  The OncoFinder algorithm for minimizing the errors introduced by the high-throughput methods of transcriptome analysis , 2014, Front. Mol. Biosci..

[25]  Stephen L. Abrams,et al.  Deregulation of the EGFR/PI3K/PTEN/Akt/mTORC1 pathway in breast cancer: possibilities for therapeutic intervention , 2014, Oncotarget.

[26]  G. Rayman,et al.  Lesson of the week: Hypothyroidism mimicking intra-abdominal malignancy. , 2002, BMJ.

[27]  Y. Zeng,et al.  Urokinase-type plasminogen activator receptor signaling is critical in nasopharyngeal carcinoma cell growth and metastasis , 2014, Cell cycle.

[28]  Ximing J. Yang,et al.  Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma. , 2007, Cancer research.

[29]  A. Giordano,et al.  FAS/FASL are dysregulated in chordoma and their loss-of-function impairs zebrafish notochord formation , 2014, Oncotarget.

[30]  M. Szyf,et al.  Definition of the landscape of promoter DNA hypomethylation in liver cancer. , 2011, Cancer research.

[31]  Yunpeng Cai,et al.  A Candidate Molecular Biomarker Panel for the Detection of Bladder Cancer , 2012, Cancer Epidemiology, Biomarkers & Prevention.

[32]  J C Boyd,et al.  Mathematical tools for demonstrating the clinical usefulness of biochemical markers. , 1997, Scandinavian journal of clinical and laboratory investigation. Supplementum.

[33]  Elisabeth Brambilla,et al.  Ectopic Activation of Germline and Placental Genes Identifies Aggressive Metastasis-Prone Lung Cancers , 2013, Science Translational Medicine.

[34]  Bryan C. Daniels,et al.  Sloppiness, robustness, and evolvability in systems biology. , 2008, Current opinion in biotechnology.

[35]  S. Barnhill,et al.  CA 125: The past and the Future , 1998, The International journal of biological markers.

[36]  F. Le Pimpec Barthès,et al.  Value of cancer antigen 125 for diagnosis of pleural endometriosis in females with recurrent pneumothorax , 2008, European Respiratory Journal.

[37]  Eduardo Sontag,et al.  Untangling the wires: A strategy to trace functional interactions in signaling and gene networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[38]  S. Eschrich,et al.  The gene expression profiles of primary and metastatic melanoma yields a transition point of tumor progression and metastasis , 2008, BMC Medical Genomics.

[39]  J A Koepke,et al.  Molecular marker test standardization , 1992, Cancer.

[40]  C. Ong,et al.  The NF1 gene revisited – from bench to bedside , 2014, Oncotarget.

[41]  A. Zhavoronkov,et al.  Methods for Structuring Scientific Knowledge from Many Areas Related to Aging Research , 2011, PloS one.

[42]  M. Kuehl,et al.  Novel inhibitors are cytotoxic for myeloma cells with NFkB inducing kinase-dependent activation of NFkB , 2014, Oncotarget.

[43]  Li Mao,et al.  Transcriptomic dissection of tongue squamous cell carcinoma , 2008, BMC Genomics.

[44]  Nikolay M. Borisov,et al.  Signaling pathway cloud regulation for in silico screening and ranking of the potential geroprotective drugs , 2014, Front. Genet..