SwissTumorScreen: Integrating Genetic Screenings and Machine Learning to Guide Personalized Oncology

Short Summary
In this project, we propose to use experimental techniques called genetic screenings to anticipate what is the effect of genomic alterations on the tumor and on the immune system of the patient, which has become a key player in fighting the disease thanks to modern immunotherapies. Genetic screenings generate large and complex data, to better interpret and use this data we will develop and apply mathematical and computational methods to predict which alterations are the most important. Lastly, we will develop a Web-portal that could be used by clinicians to better anticipate how each patient will respond to specific therapies
Goals
The goal of this project is to provide new information and develop new tools to help clinicians to choose the most promising anti-cancer therapy for each patient.
Significance
The new data and methods that we will develop will integrate genetic and functional information to guide the clinicians to select the most promising therapies.
Background
The analyses of the DNA obtained from multiple different tumors revealed that the tumor of each patient has several alterations in its DNA sequence. These so-called “genomic alterations” can be different among patients, even when tumors originated in the same organ. This diversity results in different response to therapy. In Switzerland, oncologists from multiple hospitals routinely meet to discuss which therapies are most suitable for each patient, based on which genomic alterations were found in his/her tumor.

Technology Translation

2019_PhD-Postdoc-Day_05-scaled

Prof. Dr. Elisa Oricchio

EPFL
Co-Investigators
  • Giovanni Ciriello, UNIL
  • Olivier Michielin, CHUV

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