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This article is part of the supplement: Proceedings of the 8th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-meeting 2012)

Open Access Research

A novel in silico reverse-transcriptomics-based identification and blood-based validation of a panel of sub-type specific biomarkers in lung cancer

Debmalya Barh1*, Neha Jain12, Sandeep Tiwari1, John K Field3, Elena Padin-Iruegas4, Alvaro Ruibal5, Rafael López4, Michel Herranz6, Antaripa Bhattacharya1, Lucky Juneja12, Cedric Viero17, Artur Silva8, Anderson Miyoshi9, Anil Kumar2, Kenneth Blum110, Vasco Azevedo9, Preetam Ghosh111 and Triantafillos Liloglou3

Author Affiliations

1 Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, WB-721172, India

2 School of Biotechnology, Devi Ahilya University, Khandwa Road Campus, Indore, MP, India

3 University of Liverpool, Department of Molecular and Clinical Cancer Medicine, 200 London Road, Liverpool L3 9TA, UK

4 Medical Oncology Department, Complejo Hospitalario Universitario, Santiago de Compostela, A Coruña, Spain

5 Nuclear Medicine Service, Complejo Hospitalario Universitario. Fundación Tejerina. Santiago de Compostela, A Coruña, Spain

6 Molecular Oncology and Imaging Program, Complejo Hospitalario Universitario, Santiago de Compostela, A Coruña, Spain

7 Institute of Molecular and Experimental Medicine, Cardiff University, Cardiff CF14 4XN, Wales, UK

8 Instituto de Ciências Biológicas, Universidade Federal do Pará, Rua Augusto Corrêa, 01 - Guamá, Belém, PA, Brazil

9 Laboratorio de Genetica Celular e Molecular, Departmento de Biologia Geral, Instituto de Ciencias Biologics, Universidade Federal de Minas Gerais CP 486, CEP 31270-901 Belo Horizonte, Minas Gerais, Brazil

10 Department of Psychiatry and Mcknight Brain Institute, College of Medicine, University of Florida, University Ave., Gainesville, FL 32601, USA

11 Department of Computer Science and Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA

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BMC Genomics 2013, 14(Suppl 6):S5  doi:10.1186/1471-2164-14-S6-S5

Published: 25 October 2013


Lung cancer accounts for the highest number of cancer-related deaths worldwide. Early diagnosis significantly increases the disease-free survival rate and a large amount of effort has been expended in screening trials and the development of early molecular diagnostics. However, a gold standard diagnostic strategy is not yet available. Here, based on miRNA expression profile in lung cancer and using a novel in silico reverse-transcriptomics approach, followed by analysis of the interactome; we have identified potential transcription factor (TF) markers that would facilitate diagnosis of subtype specific lung cancer. A subset of seven TF markers has been used in a microarray screen and was then validated by blood-based qPCR using stage-II and IV non-small cell lung carcinomas (NSCLC). Our results suggest that overexpression of HMGA1, E2F6, IRF1, and TFDP1 and downregulation or no expression of SUV39H1, RBL1, and HNRPD in blood is suitable for diagnosis of lung adenocarcinoma and squamous cell carcinoma sub-types of NSCLC. Here, E2F6 was, for the first time, found to be upregulated in NSCLC blood samples. The miRNA-TF-miRNA interaction based molecular mechanisms of these seven markers in NSCLC revealed that HMGA1 and TFDP1 play vital roles in lung cancer tumorigenesis. The strategy developed in this work is applicable to any other cancer or disease and can assist in the identification of potential biomarkers.