PrognoChip is a national biomedical informatics project that aims at the identification of molecular markers for the classification and prognosis of breast cancer, based on the correlation of patients’ clinico-histopathological parameters and therapy response with their tumor gene expression profiles. To achieve this, PrognoChip joins forces from different scientific disciplines: Molecular Biology (FORTH-IMBB), Medicine (PAGNH - Univ. General Hospital of Heraklion and PROLIPSIS - a breast cancer center), and Computer Science (FORTH-ICS). The main medical and molecular biology tasks within PrognoChip are:

• Medicine/ Tissue collection & Histopathology:  surgical specimens are collected from breast cancer patients that undergo any surgical type of treatment. As soon as the specimen is removed from the patient, it is carried immediately to the histopathology department, where sections are taken from the growing edge of the tumor for (a) histopathological and immunohistochemistry analysis, and (b) identification of their gene expression profiles through DNA Microarray technology.
  
  

• Molecular Biology/ Microarrays: A DNA microarray of long oligonucleotide probes has been designed, representing all known human genes, approximately 35,000 different reporters (oligonucleotides) of 27,000 different genes. Oligonucleotide probes are spotted on four activated glass slides (arrays). A common “reference” material has been decided for the study, consisting from a defined set of cell-line extracts, ensuring accurate quantitation of gene expression for most of the genes. Additionally, RNA extraction, amplification, and fluorescent labeling protocols have been developed, allowing the analysis of small samples. After array hybridization, fluorescence intensity images are acquired. From these images, fluorescence intensities (raw hybridization data) are obtained, using dedicated image analysis software. Raw hybridization data are analyzed to generate Gene Expression data, expressing through a Ratio Value (per spotted reporter/gene), if the gene in the cancerous tissue is over-expressed, under-expressed, or equally expressed with respect to the “reference” tissue.

To intelligently correlate clinical and genomic information towards PrognoChip’s goal of individualized medicine, an Integrated Clinico-Genomics Environment has been implemented, consisting of:

• A Clinical Information System to keep patients’ clinical information (i.e., clinical, laboratory, and histopathological information), 
•  A Genomic Information System to manage the specifications of the respective DNA microarray experiments (i.e., microarray design, hybridizations, etc.), analyze the raw hybridization data, and store the samples’ gene expression profiles,
• A middleware layer, called the PrognoChip Mediator, for the integration of the Clinical and Genomic Information Systems, as well as the Gene Ontology (GO) database , and
• a Data Mining layer, realized by an integrated set of tools, for the intelligent processing of the retrieved clinico-genomic data, knowledge extraction, and visualization.

Presentation: ppt