Cancerome: A hidden informative subnetwork of the diseasome

Comput Biol Med. 2016 Sep 1:76:173-7. doi: 10.1016/j.compbiomed.2016.07.010. Epub 2016 Jul 20.

Abstract

Neoplastic disorders are a leading cause of mortality and morbidity worldwide. Studying the relationships between different cancers using high throughput-generated data may elucidate undisclosed aspects of cancer etiology, diagnosis, and treatment. Several studies have described relationships between different diseases based on genes, proteins, pathways, gene ontology, comorbidity, symptoms, and other features. In this study, we first constructed an integrated human disease network based on nine different biological aspects, including molecular, functional, and clinical features. Next, we extracted the cancerome as a cancer-related subnetwork. Further investigation of cancerome could reveal hidden mechanisms of cancer and could be useful in developing new diagnostic tests and effective new drugs.

Keywords: Cancerome; Disease similarity network; Disease–disease network; Diseasome; Integrated human disease network.

MeSH terms

  • Computational Biology / methods*
  • Gene Expression Profiling
  • Humans
  • Neoplasms* / chemistry
  • Neoplasms* / genetics
  • Neoplasms* / metabolism
  • Neoplasms* / physiopathology
  • Protein Interaction Mapping