| Title: |
Oncological Treatment Adverse Reaction Prediction: Development and Initial Validation of a Pharmacogenetic Model in Non-Small-Cell Lung Cancer Patients |
| Authors: |
Concetta Cafiero; Raffaele Palmirotta; Canio Martinelli; Alessandra Micera; Luciano Giacò; Federica Persiani; Andrea Morrione; Cosimo Pastore; Claudia Nisi; Gabriella Modoni; Teresa Galeano; Tiziana Guarino; Ilaria Foggetti; Cecilia Nisticò; Antonio Giordano; Salvatore Pisconti |
| Source: |
Genes ; Volume 16 ; Issue 3 ; Pages: 265 |
| Publisher Information: |
Multidisciplinary Digital Publishing Institute |
| Publication Year: |
2025 |
| Collection: |
MDPI Open Access Publishing |
| Subject Terms: |
pharmacogenomics; individual variability; supportive care; pharmacogenetics; cancer; oncology; symptom management; personalized medicine |
| Subject Geographic: |
agris |
| Description: |
Background/Objectives: The accurate prediction of adverse drug reactions (ADRs) to oncological treatments still poses a clinical challenge. Chemotherapy is usually selected based on clinical trials that do not consider patient variability in ADR risk. Consequently, many patients undergo multiple treatments to find the appropriate medication or dosage, enhancing ADR risks and increasing the chance of discontinuing therapy. We first aimed to develop a pharmacogenetic model for predicting chemotherapy-induced ADRs in cancer patients (the ANTIBLASTIC DRUG MULTIPANEL PLATFORM) and then to assess its feasibility and validate this model in patients with non-small-cell lung cancer (NSCLC) undergoing oncological treatments. Methods: Seventy NSCLC patients of all stages that needed oncological treatment at our facility were enrolled, reflecting the typical population served by our institution, based on geographic and demographic characteristics. Treatments followed existing guidelines, and patients were continuously monitored for adverse reactions. We developed and used a multipanel platform based on 326 SNPs that we identified as strongly associated with response to cancer treatments. Subsequently, a network-based algorithm to link these SNPs to molecular and biological functions, as well as efficacy and adverse reactions to oncological treatments, was used. Results: Data and blood samples were collected from 70 NSCLC patients. A bioinformatic analysis of all identified SNPs highlighted five clusters of patients based on variant aggregations and the associated genes, suggesting potential susceptibility to treatment-related toxicity. We assessed the feasibility of the platform and technically validated it by comparing NSCLC patients undergoing the same course of treatment with or without ADRs against the cluster combination. An odds ratio analysis confirmed the correlation between cluster allocation and increased ADR risk, indicating specific treatment susceptibilities. Conclusions: The ANTIBLASTIC DRUG MULTIPANEL ... |
| Document Type: |
text |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
Human Genomics and Genetic Diseases; https://dx.doi.org/10.3390/genes16030265 |
| DOI: |
10.3390/genes16030265 |
| Availability: |
https://doi.org/10.3390/genes16030265 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.2A0A5AFB |
| Database: |
BASE |