Literature DB >> 34983789

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

James R Larkin1, Susan Anthony2, Vanessa A Johanssen1, Tianrong Yeo3,4,5, Megan Sealey3, Abi G Yates3, Claire Friedemann Smith6, Timothy D W Claridge7, Brian D Nicholson6, Julie-Ann Moreland2, Fergus Gleeson1,2, Nicola R Sibson1, Daniel C Anthony3, Fay Probert3,7.   

Abstract

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. ©2022 The Authors; Published by the American Association for Cancer Research.

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Year:  2022        PMID: 34983789      PMCID: PMC7613224          DOI: 10.1158/1078-0432.CCR-21-2855

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   13.801


  44 in total

1.  Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses.

Authors:  Etienne A Thévenot; Aurélie Roux; Ying Xu; Eric Ezan; Christophe Junot
Journal:  J Proteome Res       Date:  2015-07-02       Impact factor: 4.466

2.  Cancer survival data emphasise importance of early diagnosis.

Authors:  Nigel Hawkes
Journal:  BMJ       Date:  2019-01-25

Review 3.  Lactate and cancer: a "lactatic" perspective on spinal tumor metabolism (part 1).

Authors:  Matthew L Goodwin; Zach Pennington; Erick M Westbroek; Ethan Cottrill; A Karim Ahmed; Daniel M Sciubba
Journal:  Ann Transl Med       Date:  2019-05

4.  Diagnosis of pancreatic cancer via1H NMR metabolomics of human plasma.

Authors:  Lenka Michálková; Štěpán Horník; Jan Sýkora; Lucie Habartová; Vladimír Setnička
Journal:  Analyst       Date:  2018-12-03       Impact factor: 4.616

5.  Isotope tracing in adult zebrafish reveals alanine cycling between melanoma and liver.

Authors:  Fuad J Naser; Madelyn M Jackstadt; Ronald Fowle-Grider; Jonathan L Spalding; Kevin Cho; Ethan Stancliffe; Steven R Doonan; Eva T Kramer; Lijun Yao; Bradley Krasnick; Li Ding; Ryan C Fields; Charles K Kaufman; Leah P Shriver; Stephen L Johnson; Gary J Patti
Journal:  Cell Metab       Date:  2021-05-13       Impact factor: 31.373

6.  Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort.

Authors:  Anne Fages; Talita Duarte-Salles; Magdalena Stepien; Pietro Ferrari; Veronika Fedirko; Clément Pontoizeau; Antonia Trichopoulou; Krasimira Aleksandrova; Anne Tjønneland; Anja Olsen; Françoise Clavel-Chapelon; Marie-Christine Boutron-Ruault; Gianluca Severi; Rudolf Kaaks; Tilman Kuhn; Anna Floegel; Heiner Boeing; Pagona Lagiou; Christina Bamia; Dimitrios Trichopoulos; Domenico Palli; Valeria Pala; Salvatore Panico; Rosario Tumino; Paolo Vineis; H Bas Bueno-de-Mesquita; Petra H Peeters; Elisabete Weiderpass; Antonio Agudo; Esther Molina-Montes; José María Huerta; Eva Ardanaz; Miren Dorronsoro; Klas Sjöberg; Bodil Ohlsson; Kay-Tee Khaw; Nick Wareham; Ruth C Travis; Julie A Schmidt; Amanda Cross; Marc Gunter; Elio Riboli; Augustin Scalbert; Isabelle Romieu; Benedicte Elena-Herrmann; Mazda Jenab
Journal:  BMC Med       Date:  2015-09-23       Impact factor: 8.775

7.  Serum proton NMR metabolomics analysis of human lung cancer following microwave ablation.

Authors:  Jian-Ming Hu; Huang-Tao Sun
Journal:  Radiat Oncol       Date:  2018-03-12       Impact factor: 3.481

8.  Metabolomics Analysis in Serum from Patients with Colorectal Polyp and Colorectal Cancer by 1H-NMR Spectrometry.

Authors:  Jinping Gu; Yaqing Xiao; Dan Shu; Xianrui Liang; Xiaomin Hu; Yuanyuan Xie; Donghai Lin; Hua Li
Journal:  Dis Markers       Date:  2019-04-07       Impact factor: 3.434

9.  Integrative metabolic and transcriptomic profiling of prostate cancer tissue containing reactive stroma.

Authors:  Maria K Andersen; Kjersti Rise; Guro F Giskeødegård; Elin Richardsen; Helena Bertilsson; Øystein Størkersen; Tone F Bathen; Morten Rye; May-Britt Tessem
Journal:  Sci Rep       Date:  2018-09-24       Impact factor: 4.379

10.  Metabolomics of Non-muscle Invasive Bladder Cancer: Biomarkers for Early Detection of Bladder Cancer.

Authors:  Xiangming Cheng; Xiaoyan Liu; Xiang Liu; Zhengguang Guo; Haidan Sun; Mingxin Zhang; Zhigang Ji; Wei Sun
Journal:  Front Oncol       Date:  2018-11-02       Impact factor: 6.244

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