Pre-treatment amino acids and risk of paclitaxel-induced peripheral neuropathy in SWOG S0221.

BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a treatment-limiting and debilitating neurotoxicity of many commonly used anti-cancer agents, including paclitaxel. The objective of this study was to confirm the previously found inverse association between pre-treatment blood concentrations of histidine and CIPN occurrence and examine relationships of other amino acids with CIPN severity. METHODS: Pre-treatment serum concentrations of 20 amino acids were measured in the SWOG S0221 (NCT00070564) trial of patients with early-stage breast cancer receiving paclitaxel. The associations between amino acids and CIPN severity were tested in regression analysis adjusted for paclitaxel schedule, age, self-reported race, and body mass index with Bonferroni correction. The network of metabolic pathways of amino acids was analyzed using over-representation analysis. The partial correlation network of amino acids was evaluated using a debiased sparse partial correlation algorithm. RESULTS: In the primary analysis, histidine concentration was not associated with CIPN occurrence (odds ratio (OR) = 0.97 [0.83, 1.13], p = 0.72). In secondary analyses, higher concentrations of four amino acids, glutamate (ß = 0.58 [0.23, 0.93], p = 0.001), phenylalanine (ß = 0.54 [0.19, 0.89], p = 0.002), tyrosine (ß = 0.57 [0.23, 0.91], p = 0.001), and valine (ß = 0.58 [0.24, 0.92], p = 0.001) were associated with more severe CIPN, but none of these associations retained significance after adjustment. In the over-representation analysis, no amino acid metabolic pathways were significantly enriched (all FDR > 0.05). In the network of enriched pathways, glutamate metabolism had the highest centrality. CONCLUSIONS: This analysis showed that pre-treatment serum amino acid concentrations are not strongly predictive of CIPN severity. Prospectively designed studies that assess non-amino acid metabolomics predictors are encouraged.

Pathological Gait Analysis With an Open-Source Cloud-Enabled Platform Empowered by Semi-Supervised Learning-PathoOpenGait.

We present PathoOpenGait, a cloud-based platform for comprehensive gait analysis. Gait assessment is crucial in neurodegenerative diseases such as Parkinson's and multiple system atrophy, yet current techniques are neither affordable nor efficient. PathoOpenGait utilizes 2D and 3D data from a binocular 3D camera for monitoring and analyzing gait parameters. Our algorithms, including a semi-supervised learning-boosted neural network model for turn time estimation and deterministic algorithms to estimate gait parameters, were rigorously validated on annotated gait records, demonstrating high precision and consistency. We further demonstrate PathoOpenGait's applicability in clinical settings by analyzing gait trials from Parkinson's patients and healthy controls. PathoOpenGait is the first open-source, cloud-based system for gait analysis, providing a user-friendly tool for continuous patient care and monitoring. It offers a cost-effective and accessible solution for both clinicians and patients, revolutionizing the field of gait assessment. PathoOpenGait is available at https://pathoopengait.cmdm.tw.

Vitamin D Insufficiency as a Risk Factor for Paclitaxel-Induced Peripheral Neuropathy in SWOG S0221.

BACKGROUND: Prior work suggests that patients with vitamin D insufficiency may have a higher risk of chemotherapy-induced peripheral neuropathy (CIPN) from paclitaxel. The objective of this study was to validate vitamin D insufficiency as a CIPN risk factor. METHODS: We used data and samples from the prospective phase III SWOG S0221 (ClinicalTrials.gov identifier: NCT00070564) trial that compared paclitaxel-containing chemotherapy regimens for early-stage breast cancer. We quantified pretreatment 25-hydroxy-vitamin D in banked serum samples using a liquid chromatography-tandem mass spectrometry targeted assay. We tested the association between vitamin D insufficiency (≤20 ng/mL) and grade ≥3 sensory CIPN via multiple logistic regression and then adjusted for self-reported race, age, body mass index, and paclitaxel schedule (randomization to weekly or every-2-week dosing). We also tested the direct effect of vitamin D deficiency on mechanical hypersensitivity in mice randomized to a regular or vitamin D-deficient diet. RESULTS: Of the 1,191 female patients in the analysis, 397 (33.3%) had pretreatment vitamin D insufficiency, and 195 (16.4%) developed grade ≥3 CIPN. Patients with vitamin D insufficiency had a higher incidence of grade ≥3 CIPN than those who had sufficient vitamin D (20.7% vs 14.2%; odds ratio [OR], 1.57; 95% CI, 1.14-2.15; P=.005). The association retained significance after adjusting for age and paclitaxel schedule (adjusted OR, 1.65; 95% CI, 1.18-2.30; P=.003) but not race (adjusted OR, 1.39; 95% CI, 0.98-1.97; P=.066). In the mouse experiments, the vitamin D-deficient diet caused mechanical hypersensitivity and sensitized mice to paclitaxel (both P<.05). CONCLUSIONS: Pretreatment vitamin D insufficiency is the first validated potentially modifiable predictive biomarker of CIPN from paclitaxel. Prospective trials are needed to determine whether vitamin D supplementation prevents CIPN and improves treatment outcomes in patients with breast and other cancer types.

Pre-treatment Amino Acids and Risk of Paclitaxel-induced Peripheral Neuropathy in SWOG S0221.

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a treatment-limiting and debilitating neurotoxicity of many commonly used anti-cancer agents, including paclitaxel. The objective of this study was to confirm the previously found inverse association between pre-treatment blood concentrations of histidine and CIPN occurrence and examine relationships of other amino acids with CIPN severity. Methods: Pre-treatment levels of 20 amino acid concentrations were measured via a targeted mass spectrometry assay in banked serum from the SWOG S0221 (NCT00070564) trial of patients with early-stage breast cancer receiving paclitaxel. The associations between amino acid levels and CIPN occurrence or severity were tested in regression analysis adjusted for paclitaxel schedule, age, self-reported race, and body mass index with Bonferroni correction for multiple comparisons. The network of metabolic pathways of amino acids was analyzed using over-representation analysis in MetaboAnalyst. The partial correlation network of amino acids was evaluated using a debiased sparse partial correlation algorithm and Cytoscape. Results: In the primary analysis, histidine concentration was not associated with CIPN occurrence (odds ratio (OR) = 0.97 [0.83, 1.13], p = 0.72). In a secondary analysis, no amino acid was associated with CIPN occurrence (all p > 0.0025). Higher concentrations of four amino acids, glutamate (ß = 0.58 [0.23, 0.93], p = 0.001), phenylalanine (ß = 0.54 [0.19, 0.89], p = 0.002), tyrosine (ß = 0.57 [0.23, 0.91], p = 0.001), and valine (ß = 0.58 [0.24, 0.92], p = 0.001) were associated with more severe CIPN, but none of these associations retained significance after adjustment. In the over-representation analysis, no amino acid metabolic pathways were significantly enriched (all FDR > 0.05). In the network of enriched pathways, glutamate metabolism had the highest centrality. Conclusions: This analysis showed that pre-treatment serum amino acid concentrations are not strongly predictive of CIPN severity. Future prospectively designed studies that assess non-amino acid metabolomics predictors are encouraged.

Chemotherapy-Induced Peripheral Neuropathy.

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating side effect of many common anti-cancer agents that can lead to dose reduction or treatment discontinuation, which decrease chemotherapy efficacy. Long-term CIPN can interfere with activities of daily living and diminish the quality of life. The mechanism of CIPN is not yet fully understood, and biomarkers are needed to identify patients at high risk and potential treatment targets. Metabolomics can capture the complex behavioral and pathophysiological processes involved in CIPN. This chapter is to review the CIPN metabolomics studies to find metabolic pathways potentially involved in CIPN. These potential CIPN metabolites are then investigated to determine whether there is evidence from studies of other neuropathy etiologies such as diabetic neuropathy and Leber hereditary optic neuropathy to support the importance of these pathways in peripheral neuropathy. Six potential biomarkers and their putative mechanisms in peripheral neuropathy were reviewed. Among these biomarkers, histidine and phenylalanine have clear roles in neurotransmission or neuroinflammation in peripheral neuropathy. Further research is needed to discover and validate CIPN metabolomics biomarkers in large clinical studies.

Co-occurrence and metabolic biomarkers of sensory and motor subtypes of peripheral neuropathy from paclitaxel.

PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is the major treatment-limiting toxicity of paclitaxel, which predominantly presents as sensory symptoms, with motor symptoms in some patients. Differentiating CIPN into subtypes has been recommended to direct CIPN research. The objective of this study was to investigate whether sensory and motor CIPN are distinct subtypes with different predictive biomarkers in patients with breast cancer receiving paclitaxel. METHODS: Data were from a prospective cohort of 60 patients with breast cancer receiving up to 12 weekly infusions of 80 mg/m2 paclitaxel (NCT02338115). European Organisation for Research and Treatment of Cancer Quality of Life questionnaire CIPN20 was used to evaluate CIPN. Clusters of the time course of sensory (CIPNS), motor (CIPNM), and the difference between sensory and motor (CIPNS-CIPNM) were identified using k-means clustering on principal component scores. Predictive metabolomic biomarkers of maximum CIPNS and CIPNM were investigated using linear regressions adjusted for baseline CIPN, paclitaxel pharmacokinetics, and body mass index. RESULTS: More sensory than motor CIPN was found (CIPNS change: mean = 10.8, ranged [-3.3, 52.1]; CIPNM change: mean = 3.5, range: [-7.5, 35.0]). Three groups were identified with No CIPN, Mixed CIPN, and Sensory-dominant CIPN (maximum CIPNS: mean = 12.7 vs. 40.9 vs. 74.3, p < 0.001; maximum CIPNM: mean = 5.4 vs. 25.5 vs. 36.1, p < 0.001; average CIPNS-CIPNM: mean = 2.8 vs. 5.8 vs. 24.9, p < 0.001). Biomarkers of motor CIPN were similar to previously identified biomarkers of sensory CIPN, including lower serum histidine (p = 0.029). CONCLUSION: Our findings suggest that sensory and motor CIPN co-occur and may not have differentiating metabolic biomarkers. These findings need to be validated in larger cohorts of patients treated with paclitaxel and other neurotoxic agents to determine the optimal approach to predict, prevent, and treat CIPN and improve patients' outcomes.

Feasibility of pharmacometabolomics to identify potential predictors of paclitaxel pharmacokinetic variability.

PURPOSE: Paclitaxel is a commonly used chemotherapy drug with substantial variability in pharmacokinetics (PK) that affects treatment efficacy and toxicity. Pharmacometabolomic signatures that explain PK variability could be used to individualize dosing to improve therapeutic outcomes. The objective of this study was to identify pretreatment metabolites or metabolomic signatures that explain variability in paclitaxel PK. METHODS: This analysis was conducted using data previously collected on a prospective observational study of 48 patients with breast cancer receiving weekly 80 mg/m2 paclitaxel infusions. Paclitaxel plasma concentrations were measured during the first infusion to estimate paclitaxel time above threshold (Tc>0.05) and maximum concentration (Cmax). Metabolites measured in pretreatment whole blood by nuclear magnetic resonance spectrometry were analyzed for an association with Tc>0.05 and Cmax using Pearson correlation followed by stepwise linear regression. RESULTS: Pretreatment creatinine, glucose, and lysine concentrations were positively correlated with Tc>0.05, while pretreatment betaine was negatively correlated and lactate was positively correlated with Cmax (all uncorrected p < 0.05). After stepwise elimination, creatinine was associated with Tc>0.05, while betaine and lactate were associated with Cmax (all p < 0.05). CONCLUSION: This study identified pretreatment metabolites that may be associated with paclitaxel PK variability demonstrating feasibility of a pharmacometabolomics approach for understanding paclitaxel PK. However, identification of more robust pharmacometabolomic predictors will be required for broad and routine application for the clinical dosing of paclitaxel.

Chemotherapy-Induced Peripheral Neuropathy Detection via a Smartphone App: Cross-sectional Pilot Study.

BACKGROUND: Severe chemotherapy-induced peripheral neuropathy (CIPN) can cause long-term dysfunction of the hands and feet, interfere with activities of daily living, and diminish the quality of life. Monitoring to identify CIPN and adjust treatment before it progressing to a life-altering severity relies on patients self-reporting subjective symptoms to their clinical team. Objective assessment is not a standard component of CIPN monitoring due to the requirement for specially trained health care professionals and equipment. Smartphone apps have the potential to conveniently collect both subjective and objective CIPN data directly from patients, which could improve CIPN monitoring. OBJECTIVE: The objective of this cross-sectional pilot study was to assess the feasibility of functional CIPN assessment via a smartphone app in patients with cancer that have received neurotoxic chemotherapy. METHODS: A total of 26 patients who had completed neurotoxic chemotherapy were enrolled and classified as CIPN cases (n=17) or controls (n=9) based on self-report symptoms. All participants completed CIPN assessments within the NeuroDetect app a single time, including patient-reported surveys (CIPN20 [European Organization for Research and Treatment of Cancer Quality of Life Questionnaire for Chemotherapy-induced Peripheral Neuropathy 20-item scale] and PRO-CTCAE [Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events]) and functional assessments (Gait and Balance and 9-Hole Peg Test). Functional assessment data were decomposed into features. The primary analysis was done to identify features indicative of the difference between CIPN cases and controls using partial least squares analyses. Exploratory analyses were performed to test if any features were associated with specific symptom subtypes or patient-reported survey scores. Patient interviews were also conducted to understand the challenges they experienced with the app. RESULTS: Comparisons between CIPN cases and controls indicate that CIPN cases had shorter step length (P=.007), unique swaying acceleration patterns during a walking task, and shorter hand moving distance in the dominant hands during a manual dexterity task (variable importance in projection scores ≥2). Exploratory analyses showed similar signatures associated with symptoms subtypes, CIPN20, and PRO-CTCAE. The interview results showed that some patients had difficulties due to technical issues, which indicated a need for additional training or oversight during the initial app download. CONCLUSIONS: Our results supported the feasibility of remote CIPN assessment via a smartphone app and suggested that functional assessments may indicate CIPN manifestations in the hands and feet. Additional work is needed to determine which functional assessments are most indicative of CIPN and could be used for CIPN monitoring within clinical care.

Human Breathomics Database.

Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database-the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw.