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Poster Discussion session - Basic science

4275 - Automatic interpretation of cancer genomes creates the largest repository of tumor genetic driver events


29 Sep 2019


Poster Discussion session - Basic science


Francisco Martínez Jiménez


Annals of Oncology (2019) 30 (suppl_5): v1-v24. 10.1093/annonc/mdz238


F. Martínez Jiménez, F. Muiños, O. Pich, A. González-Perez, N. López-Bigas

Author affiliations

  • Biomedical Genomics, Institute for Research in Biomedicine (IRB Barcelona), 8028 - Barcelona/ES


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Abstract 4275


Tumor genome sequencing is becoming widely available in the clinical setting. However, the interpretation of tumor somatic variants remains an important challenge to implement precision cancer medicine.


Here, we present IntOGen, a platform aimed for tumor genome interpretation. The first component of the platform is an automatic pipeline for cancer driver gene identification across cohorts. This pipeline implements several bioinformatics methods to detect driver genes, on the basis of signals of positive selection in their mutational pattern across tumor cohorts. It also annotates several oncogenomic features that shed light onto the role of driver genes in the development of each malignancy. The second component of the platform leverages these features to identify the somatic mutations that drive the tumor of each patient providing additional information about the possible effect of driver mutations on treatment response.


We have applied the framework to more than 50,000 tumors across more than 60 tumors types creating the largest repository of tumor genetic driver events. This comprehensive oncogenomics repository is the third component of IntOGen.


All the results and framework are available online to the cancer genomics research community at www.intogen.org, which we envision can support a broad range of oncology use cases.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Institute for Research in Biomedicine (IRB, Barcelona).


Ministerio de Educación y Ciencia de España (SAF-2015-R-66084 and RTI2018-094095-B-I00) Instituto Nacional de Bioinformática (INB) - PT17/0009/0013.


All authors have declared no conflicts of interest.

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