AIRC-MFAG-22950 - PHENOMENA (DSB.AD008.587)

Thematic area

Biomedical sciences

Project area

Structure responsible for the research project

Institute of biomedical technologies (ITB)

Project manager

FRANCESCA COLOMBO
Phone number: 0226422705
Email: francesca.colombo@itb.cnr.it

Abstract

About one quarter of cancer patients receiving opioid analgesia do not benefit from this therapy. Additionally, a variable percentage of patients treated with opioids for cancer pain experience unpleasant side effects (e.g. nausea and vomiting).Finding reliable markers of drug efficacy and toxicity assumes pivotal importance. With a genome-wide pharmacogenomic approach we will disclose the complex genetic profile that affects individual response to opioid therapy for cancer pain and confers individual risks of developing nausea- vomiting side effects. In addition, this study will be the first to investigate the pharmacometabolomics of opioid treatment and to combine this biochemical information with genomics data, to elucidate the functional roles of the identified genetic variations. My team will use machine-learning algorithms to integrate these omics data in order to identify novel predictors of efficacy and toxicity of opioid analgesics. By the end of the project, we will have defined integrated genetic-metabolic profiles associated with opioid response and nausea-vomiting side effects, providing novel markers to be tested for clinical utility in independent patient series.

Goals

The objective of this project is to combine genome-wide genotyping and metabolic data, using machine learning algorithms, to identify clinically relevant markers for the tailored opioid treatment of cancer patients.
We expect to set the foundation for the pharmacogenomics and pharmacometabolomics of opioid therapy in cancer patients. Moreover, we expect to identify new genetic and metabolic markers, or combinations of them, explaining the interindividual variability in opioid response (in terms of efficacy and toxicity).
This project will identify new predictive markers of opioid response and toxicity, thus providing new tools for the personalized management of advanced cancer patients receiving opioid analgesia, with the aim of improving their quality of life.

Start date of activity

02/01/2020

Keywords

Palliative care, Pharmacogenetics/Pharmacogenomics, Side effects

Last update: 06/08/2025