This project will perform functional genomic research with a translational approach that will bring new scientific knowledge into the health care system. The project will identify gene polymorphisms and gene expression profiles that may confer developmen t of lung cancer, and act as a prognostic marker for tumor stage and tumor- and symptom treatment. To bridge the gap between genomics and clinics, international endorsed computer assisted standards for symptom assessment and classification will be develop ed and serve as valid and reliable assessment for subjective symptoms. The impact from genotyping, gene expression and computer based symptom assessment/classification will be utilized in an artificial intelligent decision support system. The SNP genotypi ng (Illumina) will be performed on patients with lung cancer and controls from two regional representative health surveys (HUNT II and Tromsø IV), and a consecutive series of 100 lung cancer patients from the Central Norway Lung Cancer Biobank, followed b y a high density SNP mapping of the identified risk associated genes and loci. A similar approach will be used to study gene expression in peripheral blood leucocytes. The genetic information will be combined with clinical information in order to answer t he research questions. Content and type of items for a computer assisted symptom assessment/classification system will be decided from literature reviews and expert opinions. Lung cancer and palliative care patient cohorts will be used as informants to te st the performance of all items, the computer software and to investigate the final assessment tool. A functional specification of an artificial intelligent (AI) system will be developed, tested in lung cancer and palliative care patient cohorts. This wil l lead into a template of an AI decision support system for further research and possible clinical application.
Project leader: Stein Kaasa
Institution: NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU