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New Genetic Tool Predicts Chemotherapy Side Effects in Precision Oncology

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Newswise — Philadelphia, 24th February 2024 – "Chemotherapy Side Effects can now be predicted with a groundbreaking pharmacogenetic tool developed and validated based on a patient’s genetic profile. This innovative platform, tested in patients with non-small-cell lung cancer (NSCLC), has the potential to revolutionize cancer treatment and extend beyond oncology, allowing individuals to assess their genetic predisposition to chemotherapy-related toxicity before developing cancer.

Published in Genes, the study introduces the ANTIBLASTIC DRUG MULTIPANEL PLATFORM, a patented tool designed to personalize chemotherapy by helping physicians weigh treatment benefits and risks in a precise, patient-specific manner.

Antonio Giordano Sbarro

A Game-Changer in Personalized Therapy

Oncological medicines are frequently chosen based on clinical recommendations that fail to account for individual genetic variances, resulting in unexpected adverse drug reactions (ADRs) that might jeopardize therapy success and patient well-being.
"Our model represents an important step forward in precision oncology," says Dr. Concetta Cafiero, the study's principal author. "By predicting how a patient will respond to chemotherapy before treatment even starts, we can help oncologists select the safest and most effective option for each individual."
Beyond Cancer: A Tool for Proactive Care
Although initially validated in NSCLC patients, this tool is intended to assess genetic susceptibility to chemotherapy toxicity in any patient—cancer or not. It takes a proactive approach to healthcare, allowing people to identify their genetic risk profile.

precision-oncology

Using a dataset of 326 genetic variants (SNPs) associated with chemotherapy response, the research team applied a bioinformatics-based analysis to categorize patients into five genetic clusters. This classification successfully predicted ADR risk, allowing for a more balanced, personalized treatment strategy.

A Collaborative Effort Across Leading Institutions

Dr. Concetta Cafiero, Prof. Raffaele Palmirotta, and Prof. Salvatore Pisconti launched the project at ASL Taranto, where they directed the first development of the predictive platform. The bioinformatics analysis was enhanced in partnership with IRCCS Gemelli Hospital in Rome. Dr. Luciano Giacò contributed significantly to the model's computational and bioinformatics development.

Historic Ruling European Court

The Sbarro Health Research Organization at Temple University in Philadelphia, USA, led by Professor Antonio Giordano and Dr. Canio Martinelli, was in charge of the project's global development and supervision, ensuring that the model met the highest standards of scientific rigor and clinical application.

Clinical Validation and Future Applications

Prof. Salvatore Pisconti led the study at SG Moscati Hospital in Italy, which included 70 NSCLC patients who were followed for chemotherapy adverse effects. The results validated the platform's strong predictive value, pointing to its potential incorporation into normal cancer care.

"With further validation, this tool could become a critical component of personalized medicine," said Prof. Raffaele Palmirotta and Prof. Salvatore Pisconti, Italian oncologists involved in the initiative. "Oncologists will be able to tailor treatments with unprecedented accuracy, reducing toxicity while maximizing therapeutic benefits."

A Personalized Future for Cancer Therapy

This prediction model offers a wide range of applications, from lung cancer to other tumor types and medical disorders that require chemotherapy. As modern medicine shifts toward a more data-driven, tailored approach, technologies like these will assist clinicians in determining the optimum treatment strategy by weighing benefits and drawbacks in the most accurate way possible.
The research team is currently working on expanding the study to include larger patient groups and creating a user-friendly mobile app to smoothly integrate the tool into clinical practice.

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