Untargeted Metabolomics Analysis of Pancreatic Cancer Using LC/QTOF

User Benefits

- LC/QTOF method for untargeted metabolomics with flexible workflows for Data Independent Acquisition (DIA) or Data Dependent Acquisition (DDA). - Data are compatible with all major third-party tools for data processing and statistical analysis of metabolomics data. - The workflow delivers an end-to-end solution for untargeted metabolomics research.

Introduction

Metabolomics is the study of a metabolic phenotype and its impact on a biological system. It involves the measurement of small molecules and can be applied to disease aetiology, discovering potential disease markers in human medicine, but also to other disciplines such as translational and precision medicine, untargeted analyses, nutritional assessment, fermentative optimisations, and agricultural productivity. Metabolomics studies are designed to detect and identify metabolites that are considered to be drivers of a biological process and understand their role in phenotype modulation. In this application, an LC/QTOF data acquisition method was developed for routine, robust metabolomics research requiring minimal MS expertise which can be applied to the untargeted metabolomics studies of biological tissues and biofluids. Data were processed using commonly used open-source software applications cited in the literature. This study used MS-DIAL (principally for raw data access to detect and align features in each sample) and MetaboAnalyst (for advanced statistical analysis to find features that were differentially expressed in the study).

July 21, 2026 GMT