Metabolomics for searching validated biomarkers in cancer studies: a decade in review

ABSTRACT

Introduction

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

Areas covered

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

Expert opinion

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

KEYWORDS:

• Biomarkers
• cancer diagnosis
• clinical significance
• early detection
• metabolomics
• technological advancements
• validation

Article highlights

• Cancer, characterized by complexity and heterogeneity, underscores the paramount importance of early diagnosis for patient survival. With global cancer cases projected to reach nearly 30 million annually by 2040, there is an urgent need for robust diagnostic tools, especially for prevalent cancers like breast, prostate, and cervical cancers.

• Metabolomics emerges as a critical tool in modern healthcare, particularly in diseases like cancer, where early diagnosis significantly influences outcomes. Metabolomics complements the genotype-phenotype landscape, providing essential insights into active metabolic mechanisms and disease-induced dysregulated pathways.

• Advanced technologies such as NMR and MS, coupled with various separation methods, are at the forefront of studying cancer metabolism, aiding in biomarker discovery and therapeutic monitoring.

• Structural diversity and low concentrations of metabolites in biological samples present challenges, driving the need for sophisticated technologies and protocols in metabolomic analysis.

• A comprehensive overview of the state-of-the-art in biomarker discovery through metabolomics, highlights the substantial potential of metabolites as diagnostic markers, with ongoing challenges warranting exploration, emphasizing its role in diagnostics, technological advancements, challenges faced, and the potential impact on patient health.

• Overcoming the lack of a universal analytical platform and the tentative identification of biomarkers due to isomeric diversity pose significant challenges in metabolomics.

• Future research directions, include addressing cell heterogeneity, advancing single-cell analysis, and exploring extracellular vesicles for cancer diagnosis.

• Emerging technologies like low-field NMR spectroscopy and breath analysis for VOCs show promise for point-of-care diagnostics, offering an alternative perspective to specific metabolite analysis.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.