2 research outputs found
Paclitaxel Neuropathy: A Glycoproteomic Approach to Predictive Biomarkers in Breast Cancer.
Paclitaxel, a potent chemotherapeutic agent, is extensively used in the treatment of breast cancer,
one of the most prevalent forms of cancer worldwide. Despite its efficacy, a significant challenge in the
clinical use of paclitaxel is its association with peripheral neuropathy, a severe and often debilitating
side effect that can dramatically affect patients' quality of life. This neuropathy is characterized by
numbness, tingling, or pain in the patient's hands and feet, limiting their daily activities and often
necessitating dose reduction or treatment discontinuation.
Currently, the capacity to predict which patients are more likely to develop Paclitaxel-induced PN is
lacking. This inability to forecast this adverse effect hampers the clinicians' ability to personalize
treatment plans, potentially compromising treatment efficacy and patient quality of life.
To address this critical gap, our project aims to explore the blood serum glycoproteome of patients prior
to paclitaxel treatment who had acquired paclitaxel neuropathy or whose treatment had not caused these
issues. Glycoproteomics, the study of changes in the glycosylation status of proteins, holds promise in
uncovering potential biomarkers for disease states and responses to treatment. We hypothesize that
distinct patterns of protein glycosylation could signal an elevated risk of developing peripheral
neuropathy in response to paclitaxel treatment.
Following our in-depth glycoproteomic investigation, our plan is to use machine learning methods to
determine whether there is a particular combination of these proteoforms that could serve as a predictive
model for paclitaxel-induced peripheral neuropathy