The most popular approach to explain cancer is based on the discovery of oncogenes and tumor suppressor genes as a preliminary step in estimating their impact on altered pathways. The present paper proposes a pipeline which aims at detecting "weak" or "indirect" functions impacted by Copy Number Variations (CNVs) of cancer-related genes, integrating such signals over all known oncogenes/tumor suppressor genes of a cancer type. We applied the pipeline to the task of detecting the aberrant functional effects of these alterations across ovarian cancer patients from The Cancer Genome Atlas (TCGA) data.

A transcriptional study of oncogenes and tumor suppressors altered by copy number variations in ovarian cancer

Giacomini G;Pellegrini M;D'Aurizio R;
2020

Abstract

The most popular approach to explain cancer is based on the discovery of oncogenes and tumor suppressor genes as a preliminary step in estimating their impact on altered pathways. The present paper proposes a pipeline which aims at detecting "weak" or "indirect" functions impacted by Copy Number Variations (CNVs) of cancer-related genes, integrating such signals over all known oncogenes/tumor suppressor genes of a cancer type. We applied the pipeline to the task of detecting the aberrant functional effects of these alterations across ovarian cancer patients from The Cancer Genome Atlas (TCGA) data.
2020
Istituto di informatica e telematica - IIT
Copy number variations
Cancer genomics
Bi-clustering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/390921
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