LINE 3 – cancer genomics and big data

Supervisor

Prof. PierFranco Conte

Description

The goal of the Cancer Genomics and Big Data research line is to validate methods and pathways that will allow the clinical oncologist to have, at the time of diagnosis, a detailed view of the mutational structure of the tumor, in other words, the molecular footprint of the tumor. The availability of massive parallel sequencing techniques (NGS) will allow the Veneto Institute of Oncology to not only be an active part of the broader ACC Genomics program, initiated by the national IRCCS oncology network Alleanza Contro Cancro (ACC), but also to develop and validate NGS methods for the study of tumor DNA from liquid biopsy or circulating tumor cells.

Background

The notion that cancer is a genetic disease, or rather a disease of the genes, has led to the concept that each tumor is characterized by different mutations or combinations of mutations. The acquisitions in this field have been supported by an acceleration in the availability of technology necessary for DNA analysis, and it is now economically possible to analyze the entire genome of a tumor, paving the way for an intensive use of genetic information in oncology. In fact, several drugs have been developed by virtue of the presence of particular mutations. The challenge before us is to obtain and use complex information, such as the genomic analysis of the tumor, to ensure the most effective therapy for each patient. IOV has accepted this challenge within the ACC genomics program, together with the other members of the IRCCS oncology network.

Rationale

The institute-wide availability of a technology platform for the analysis of tumor genomics, the significant knowledge and experience of IOV in the field of genetics, and the great interest expressed by our clinical oncologists are the indispensable prerequisites for the implementation of this line of research.
Researchers will be able to analyze panels containing all the “actionable” mutations for which present and potential anticancer drugs exist, and all the variants capable of conditioning the efficacy and tolerability of these drugs. This will allow oncologists to choose the most appropriate therapies for that particular tumor and to follow innovative therapeutic protocols. The analysis of tumor genomics will produce a significant amount of data and a formidable informational heritage that will require specific methods of data retention and transmission.

Global goals

1. To create and validate a path from tumor biopsy to the clinical use of the mutational tumor structure;
2. To validate the use of the new ACC GENOMICS platform in the study of various tumors, including liquid biopsy;
3. To validate new platforms for the acquisition and exchange of Big Data.

Expected results

• the provision of timely and systematic data on the molecular structure of tumors for the appropriate targeted therapy choices;
• the development of a genomic tool for the study of liquid biopsy able to reveal progressive mutational changes;
• the identification of new ways to share and transfer Big Data.