metabolomic biomarkers in blood samples to identify cancers (cancer)

Last edited 01/2022 and last reviewed 07/2023

Metabolomics aims to comprehensively identify qualitatively and/or quantitatively detectable, endogenous metabolites in biological systems (1,2)

  • is the study of the complete biochemical phenotype of a cell, tissue, or whole organism mainly using analytical platforms such as:
    • nuclear magnetic resonance spectroscopy (NMR),
    • liquid chromatography-mass spectrometry (LC–MS) and
    • gas chromatography-mass spectrometry (GC-MS)

  • metabolomics interrogates biological systems since it is an unbiased, data-driven approach that may ultimately lead to hypotheses providing new biological knowledge (2)

  • term 'metabolomics' typically describing the state of an organisms' metabolism, was first coined by one its pioneers, Jeremy Nicholson, Chair in Biological Chemistry at Imperial College, London. United Kingdom
    • was concerned with measuring the metabolites in one sample and may be derived from only one cell type

  • biofluid metabolomics is a conceptually simple and inexpensive technique that relies upon the simultaneous determination of the levels of small-molecule constituents within a biological sample, which are analyzed to establish disease-specific patterns (3)
    • metabolomic profiles are produced by an analytical technique such as nuclearmagnetic resonance (NMR) spectroscopy or mass spectrometry
    • been demonstrated that able to identify different types of cancers using NMR metabolomics, including lung, colorectal,pancreatic, liver, breast, and bladder cancers

Larkin et al hypothesized that biomarkers within the blood metabolome could identify cancers within a mixed population of patients referred from primary care with nonspecific symptoms, the so-called “low-risk, but not no-risk” patient group, as well as distinguishing between those with and without metastatic disease.

Study design:

  • patients (n = 304 comprising modeling, n = 192, and test, n =92) were recruited from 2017 to 2018 from the Oxfordshire Suspected CANcer (SCAN) pathway, a multidisciplinary diagnostic center (MDC) referral pathway for patients with nonspecific signs and symptoms
    • blood was collected and analyzed by NMR metabolomics
    • orthogonal partial least squares discriminatory analysis (OPLS-DA) models separated patients, based upon diagnoses received from the MDC assessment, within 62 days of initial appointment

Study results:

  • area under the receiver operator characteristic (ROC) curve for identifying patients with solid tumors in the independent test set was 0.83 [95% confidence interval (CI): 0.72-0.95]
    • maximum sensitivity and specificity were 94% (95% CI: 73-99) and 82% (95% CI: 75-87), respectively
    • identified patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% and 88%, respectively

Study authors concluded that:

  • for a mixed group of patients referred from primary care with nonspecific signs and symptoms, NMR-based metabolomics can assist their diagnosis, and may differentiate both those with malignancies and those with and without metastatic disease
    • s sensitive, specific, and of low cost, requiring nothing more than a blood sample in the clinic and an inexpensive NMR analysis, and can identify patients with solid tumors when referred with nonspecific symptoms

Comparison of NMR-based metabolomics with analysis of circulating tumor DNA (ctDNA) (3)

  • an alternative technology is the analysis of circulating tumor DNA (ctDNA), which relies on the sequencing of DNA shed from tumors into the blood stream
    • the abundance of particular tumor-associated mutations in the isolated DNA gives an indication of tumor burden
    • owing to its genetic approach, ctDNA analysis has great potential for distinguishing tumor subtypes and for monitoring tumor evolution
    • for initial detection of tumors the case is less clear, as ctDNA is released only by tumor cells (3)
      • consequently, there is no indirect amplification of the signal as is seen with metabolomics
        • instead ctDNA analysis must detect the minute traces of DNA released directly by tumor cells which has intrinsic sensitivity limitations
    • a second factor is that all mutations must be known a priori, meaning that some mutations may be missed, even if they are being released by tumor cells (3)

Reference:

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