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Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms

PURPOSE: Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and dist...

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Autores principales: Larkin, James R., Anthony, Susan, Johanssen, Vanessa A., Yeo, Tianrong, Sealey, Megan, Yates, Abi G., Smith, Claire Friedemann, Claridge, Timothy D.W., Nicholson, Brian D., Moreland, Julie-Ann, Gleeson, Fergus, Sibson, Nicola R., Anthony, Daniel C., Probert, Fay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613224/
https://www.ncbi.nlm.nih.gov/pubmed/34983789
http://dx.doi.org/10.1158/1078-0432.CCR-21-2855
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author Larkin, James R.
Anthony, Susan
Johanssen, Vanessa A.
Yeo, Tianrong
Sealey, Megan
Yates, Abi G.
Smith, Claire Friedemann
Claridge, Timothy D.W.
Nicholson, Brian D.
Moreland, Julie-Ann
Gleeson, Fergus
Sibson, Nicola R.
Anthony, Daniel C.
Probert, Fay
author_facet Larkin, James R.
Anthony, Susan
Johanssen, Vanessa A.
Yeo, Tianrong
Sealey, Megan
Yates, Abi G.
Smith, Claire Friedemann
Claridge, Timothy D.W.
Nicholson, Brian D.
Moreland, Julie-Ann
Gleeson, Fergus
Sibson, Nicola R.
Anthony, Daniel C.
Probert, Fay
author_sort Larkin, James R.
collection PubMed
description PURPOSE: Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and distinguish between differing metastatic disease burdens. Here, we 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. EXPERIMENTAL 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. RESULTS: Area under the 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. We could also identify patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% (95% CI: 72–99) and 88% (95% CI: 53–98), respectively. CONCLUSIONS: 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. See related commentary by Van Tine and Lyssiotis, p. 1477
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spelling pubmed-76132242022-10-14 Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms Larkin, James R. Anthony, Susan Johanssen, Vanessa A. Yeo, Tianrong Sealey, Megan Yates, Abi G. Smith, Claire Friedemann Claridge, Timothy D.W. Nicholson, Brian D. Moreland, Julie-Ann Gleeson, Fergus Sibson, Nicola R. Anthony, Daniel C. Probert, Fay Clin Cancer Res Precision Medicine and Imaging PURPOSE: Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and distinguish between differing metastatic disease burdens. Here, we 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. EXPERIMENTAL 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. RESULTS: Area under the 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. We could also identify patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% (95% CI: 72–99) and 88% (95% CI: 53–98), respectively. CONCLUSIONS: 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. See related commentary by Van Tine and Lyssiotis, p. 1477 American Association for Cancer Research 2022-04-14 2022-01-04 /pmc/articles/PMC7613224/ /pubmed/34983789 http://dx.doi.org/10.1158/1078-0432.CCR-21-2855 Text en ©2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
spellingShingle Precision Medicine and Imaging
Larkin, James R.
Anthony, Susan
Johanssen, Vanessa A.
Yeo, Tianrong
Sealey, Megan
Yates, Abi G.
Smith, Claire Friedemann
Claridge, Timothy D.W.
Nicholson, Brian D.
Moreland, Julie-Ann
Gleeson, Fergus
Sibson, Nicola R.
Anthony, Daniel C.
Probert, Fay
Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms
title Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms
title_full Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms
title_fullStr Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms
title_full_unstemmed Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms
title_short Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms
title_sort metabolomic biomarkers in blood samples identify cancers in a mixed population of patients with nonspecific symptoms
topic Precision Medicine and Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613224/
https://www.ncbi.nlm.nih.gov/pubmed/34983789
http://dx.doi.org/10.1158/1078-0432.CCR-21-2855
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