PROJECT SUMMARY Taxanes are among the most efficacious chemotherapeutic agents and are frequently used in the treatment of early stage and metastatic breast cancer, but are known to produce a pain condition known as chemotherapy- induced peripheral neuropathic pain (CIPNP). CIPNP is one of the primary dose-limiting toxicities of taxane administration. No diagnostic tool exists to identify patients that will develop CIPNP in response to taxane therapy. To address this unmet clinical need, this proposal seeks to develop biomarker signatures associated with taxane-induced neuropathic pain to 1) identify patients at risk for developing debilitating taxane neuropathic pain before chemotherapy is initiated and 2) to identify patients on treatment that are at risk of developing neuropathic pain and need dose adjustments to prevent the onset of symptoms. Our long-term goal is to identify biomarker signatures that can identify patients at high risk of developing taxane-induced CIPNP to enable personalized dose adjustments to minimize CIPNP and optimize therapeutic outcomes. During the R61 phase, we will perform genome-wide, epigenome-wide, miRNome-wide, and untargeted metabolome-wide associations of the 11-point pain-intensity Numerical Rating Scale (NRS), Chemotherapy-induced peripheral neuropathy 20- item (CIPN20), the Pain Catastrophizing Scale (PCS), and Patient Reported Outcome Measurement System (PROMIS) scores for physical function, anxiety, depression, and pain interference to identify novel biomarkers associated with identifiable phenotypes (Aim 1A). Next, we will test panels of candidate mRNA and cytokine biomarkers for their association with NRS, CIPN20, PCS, and PROMIS scores (Aim 1B). An added strength of this study is that by collecting samples before, during, and after taxane treatment we will be able to compare those patients who develop CIPNP to those that remain pain free, providing a better understanding of the molecular mechanism predisposing a patient to developing neuropathic pain. R61 milestones include developing biomarker signatures that identify patients at risk of developing neuropathic pain that compromise quality of life (i) before taxane therapy is started and (ii) over the time course of taxane therapy. One rationale is that some patients will have a detectable biomarker profile suggesting a high likelihood of long term (i.e., greater than 1 year) neuropathic pain and a need to either avoid or reduce taxane doses. A second rationale is that some patients may not have a biomarker signature indicating an adverse response to taxane therapy at baseline, but develop one through the course of taxane therapy. This biomarker signature will be used to detect these susceptible patients early and personalize their taxane therapy to minimize CIPNP. In the R33 phase (Aim 2), we will use machine learning to develop and validate algorithms using biomarker signatures from associations with phenotypic changes from Aim 1 (A and B) to predict individuals at risk of developing CIPNP and to identify patients who are at risk of developing an adverse profile as taxane therapy is administered.

PROJECT NARRATIVE The proposed research is relevant to public health because identification of validated biomarker signatures in taxane-treated breast cancer patients associated with increased likelihood of developing neuropathic pain may contribute to the development of novel approaches to personalize chemotherapy in patients, including altering dosing or using a different chemotherapeutic, reducing the risk for developing neuropathic pain and the development of novel approaches to treat or slow the progression of neuropathic pain by modifying pathways prior to taxane-treatment and before initiation of symptoms. The proposed research is relevant to the NIH mission pertaining to the generation of fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability.