Cancer bioinformatics: A new approach to systems clinical medicine

Duojiao Wu,Catherine M Rice,Xiangdong Wang

doi:10.1186/1471-2105-13-71

Abstract

Cancer is one of the commonest causes of patient death in the clinic and a complex disease occurring in multiple organs per system, multiple systems per organ, or both, in the body. The poor diagnoses, therapies and prognoses of the disease could be mainly due to the variation of severities, durations, locations, sensitivity and resistance against drugs, cell differentiation and origin, and understanding of pathogenesis. With increasing evidence that the interaction and network between genes and proteins play an important role in investigation of cancer molecular mechanisms, it is necessary and important to introduce a new concept of Systems Clinical Medicine into cancer research, to integrate systems biology, clinical science, omics-based technology, bioinformatics and computational science to improve diagnosis, therapies and prognosis of diseases. Cancer bioinformatics is a critical and important part of the systems clinical medicine in cancer and the core tool and approach to carry out the investigations of cancer in systems clinical medicine. “Thematic Series on Cancer Bioinformatics” gather the strength of BMC Bioinformatics, BMC Cancer, Genome Medicine and Journal of Clinical Bioinformatics to headline the application of cancer bioinformatics for the development of bioinformatics methods, network biomarkers and precision medicine. The Series focuses on new developments in cancer bioinformatics and computational systems biology to explore the potential of clinical applications and improve the outcomes of patients with cancer.

Highlights

Cancer is one of the commonest causes of patient death in the clinic and a complex disease occurring in multiple organs per system, multiple systems per organ, or both, in the body
The applicability, specificity, and integration of methodologies, software, computational tools, and databases which can be used to explore the molecular mechanisms of cancer and identify and validate novel biomarkers, network biomarkers, and individualized medicine in cancer should be seriously considered. miRTrail is an integrative tool for analyzing comprehensive interactions of genes and miRNAs based on expression profiles to generate more robust and reliable results on deregulated pathogenic processes
The algorithm described by Haustein and Schumacher in the Thematic Series on Cancer Bioinformatics in Journal of Clinical Bioinformatics [6] can simulate tumor growth and detect the formation of some metastases in advance of clinical detection in cells, on basis of clinical breast cancer data

Summary

Introduction

Cancer is one of the commonest causes of patient death in the clinic and a complex disease occurring in multiple organs per system, multiple systems per organ, or both, in the body. The applicability, specificity, and integration of methodologies, software, computational tools, and databases which can be used to explore the molecular mechanisms of cancer and identify and validate novel biomarkers, network biomarkers, and individualized medicine in cancer should be seriously considered.

Results

Conclusion