The identification of biomarkers for the estimation of cancer patients’ survival is a crucial problem in oncology. The Affymetrix DMET microarray platform allows to determine the ADME gene variants of a patient and to correlate them with drug-dependent adverse events. We present a bioinformatics tool devoted to the discovery of gene variants correlated to a different response of cancer patients to drugs and able to compute the overall survival (OS) and progression-free survival (PFS) of cancer patients. The tool is based on the integration of DMET-Miner and OSAnalyzer. DMET-Miner is a data mining tool able to extract Association Rules from DMET datasets and OSAnalyzer is a software tool able to perform an automatic analysis of DMET data enriched with survival events. After presenting DMET-Miner and OSAnalyzer, we discuss a case study to highlight the usefulness of the pipeline constituted by DMET-Miner and OSAnalyzer when analyzing a large cohort of patients.

Efficient Data Mining Analysis of Genomics and Clinical Data for Pharmacogenomics Applications

Giuseppe Agapito;Pietro Hiram Guzzi;Cannataro M
2017-01-01

Abstract

The identification of biomarkers for the estimation of cancer patients’ survival is a crucial problem in oncology. The Affymetrix DMET microarray platform allows to determine the ADME gene variants of a patient and to correlate them with drug-dependent adverse events. We present a bioinformatics tool devoted to the discovery of gene variants correlated to a different response of cancer patients to drugs and able to compute the overall survival (OS) and progression-free survival (PFS) of cancer patients. The tool is based on the integration of DMET-Miner and OSAnalyzer. DMET-Miner is a data mining tool able to extract Association Rules from DMET datasets and OSAnalyzer is a software tool able to perform an automatic analysis of DMET data enriched with survival events. After presenting DMET-Miner and OSAnalyzer, we discuss a case study to highlight the usefulness of the pipeline constituted by DMET-Miner and OSAnalyzer when analyzing a large cohort of patients.
2017
Genotyping microarrays; ADME genes ; Pharmacogenomics; Overall survival; Progression-free survival
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12317/19466
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact