Several anticancer agents cause a side effect known as peripheral neuropathy that can permanently diminish
patient’s functional ability and quality of life. Since there are no effective strategies to prevent or treat
peripheral neuropathy, clinical practice guidelines recommend withholding or dose-reducing chemotherapy,
which reduces patient survival. Clinical and lifestyle factors do not adequately predict risk of taxane-induced
peripheral neuropathy (TIPN). Therefore, there is a critical need to validate clinically useful and mechanistically
informative predictive TIPN biomarkers in order to develop effective TIPN prevention strategies that improve
taxane treatment outcomes. Dysregulation of nutrients including vitamin D, histidine, and sphingomyelin, and
variants in genes linked to hereditary neuropathy conditions, have been identified as candidate biomarkers of
TIPN. Confirming these biomarker candidates as predictors of TIPN risk requires a large cohort of taxane-
treated patients with biospecimens and detailed TIPN data. The overarching objective of this proposal is to
identify clinically-useful and mechanistically-informative TIPN biomarkers and develop an Integrated TIPN Risk
Prediction Model that can predict an individual patient’s TIPN risk. We will extend the value of SWOG 1714
(S1714), which is a large (n=1,336) NCI-funded prospective clinical study that collected biospecimens and
detailed TIPN data to create a Clinical TIPN Prediction Model. Our central hypothesis is that our physiologic
(e.g., vitamin D, histidine, sphingomyelin) and genetic (e.g., EPHA5) biomarker candidates are predictive TIPN
biomarkers and will enrich the Clinical TIPN Prediction Model. We will conduct targeted and comprehensive
“omics” analyses of S1714 biospecimens to validate clinically useful and mechanistically informative predictive
TIPN biomarkers and develop an Integrated TIPN Risk Prediction Model to complete the following specific
aims: Aim 1: Assess the predictive value of key nutrients and lipids on TIPN risk. Aim 2: Determine
genetic features that contribute to TIPN risk. Aim 3: Develop an Integrated TIPN Prediction Model. The
primary expected outcomes of this research are the: 1) confirmation of clinically useful predictive TIPN
biomarkers, 2) generation of new knowledge of the mechanistic processes that contribute to TIPN, and 3)
creation of an Integrated TIPN Prediction Model. These outcomes will provide critical insight to develop novel
agents and biomarker-informed treatment strategies that the study team can test in prospective clinical trials to
prevent TIPN. If successful, these strategies could be translated into clinical practice to prevent TIPN and
improve long-term clinical outcomes in the nearly one million patients with cancer who receive taxane
treatment each year in the United States.
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