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Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors
BACKGROUND: An increase in naturally-occurring porphyrins has been described in the blood of subjects bearing different kinds of tumors, including colorectal, and this is probably related to a systemic alteration of heme metabolism induced by tumor cells. The aim of our study was to develop an artif...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6106935/ https://www.ncbi.nlm.nih.gov/pubmed/30134852 http://dx.doi.org/10.1186/s12885-018-4754-2 |
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author | Lualdi, Manuela Cavalleri, Adalberto Battaglia, Luigi Colombo, Ambrogio Garrone, Giulia Morelli, Daniele Pignoli, Emanuele Sottotetti, Elisa Leo, Ermanno |
author_facet | Lualdi, Manuela Cavalleri, Adalberto Battaglia, Luigi Colombo, Ambrogio Garrone, Giulia Morelli, Daniele Pignoli, Emanuele Sottotetti, Elisa Leo, Ermanno |
author_sort | Lualdi, Manuela |
collection | PubMed |
description | BACKGROUND: An increase in naturally-occurring porphyrins has been described in the blood of subjects bearing different kinds of tumors, including colorectal, and this is probably related to a systemic alteration of heme metabolism induced by tumor cells. The aim of our study was to develop an artificial neural network (ANN) classifier for early detection of colorectal adenocarcinoma based on plasma porphyrin accumulation and risk factors. METHODS: We measured the endogenous fluorescence of blood plasma in 100 colorectal adenocarcinoma patients and 112 controls using a conventional spectrofluorometer. Height, weight, personal and family medical history, use of alcohol, red meat, vegetables and tobacco were all recorded. An ANN model was built up from demographic data and from the integral of the fluorescence emission peak in the range 610–650 nm. We used the Receiver Operating Characteristic (ROC) curve to assess performance in distinguishing colorectal adenocarcinoma patients and controls. A liquid chromatography-high resolution mass spectrometry (LC-HRMS) analytical method was employed to identify the agents responsible for native fluorescence. RESULTS: The fluorescence analysis indicated that the integral of the fluorescence emission peak in the range 610–650 nm was significantly higher in colorectal adenocarcinoma patients than controls (p < 0.0001) and was weakly correlated with the TNM staging (Spearman’s rho = 0.224, p = 0.011). LC-HRMS measurements showed that the agents responsible for the fluorescence emission were mainly protoporphyrin-IX (PpIX) and coproporphyrin-I (CpI). The overall accuracy of our ANN model was 88% (87% sensitivity and 90% specificity) with an area under the ROC curve of 0.83. CONCLUSIONS: These results confirm that tumor cells accumulate a diagnostic level of endogenous porphyrin compounds and suggest that plasma porphyrin concentrations, indirectly measured through fluorescence analysis, may be useful, together with risk factors, as a clinical decision support tool for the early detection of colorectal adenocarcinoma. Our future efforts will be aimed at examining how plasma porphyrin accumulation correlates with survival and response to therapy. |
format | Online Article Text |
id | pubmed-6106935 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61069352018-08-29 Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors Lualdi, Manuela Cavalleri, Adalberto Battaglia, Luigi Colombo, Ambrogio Garrone, Giulia Morelli, Daniele Pignoli, Emanuele Sottotetti, Elisa Leo, Ermanno BMC Cancer Research Article BACKGROUND: An increase in naturally-occurring porphyrins has been described in the blood of subjects bearing different kinds of tumors, including colorectal, and this is probably related to a systemic alteration of heme metabolism induced by tumor cells. The aim of our study was to develop an artificial neural network (ANN) classifier for early detection of colorectal adenocarcinoma based on plasma porphyrin accumulation and risk factors. METHODS: We measured the endogenous fluorescence of blood plasma in 100 colorectal adenocarcinoma patients and 112 controls using a conventional spectrofluorometer. Height, weight, personal and family medical history, use of alcohol, red meat, vegetables and tobacco were all recorded. An ANN model was built up from demographic data and from the integral of the fluorescence emission peak in the range 610–650 nm. We used the Receiver Operating Characteristic (ROC) curve to assess performance in distinguishing colorectal adenocarcinoma patients and controls. A liquid chromatography-high resolution mass spectrometry (LC-HRMS) analytical method was employed to identify the agents responsible for native fluorescence. RESULTS: The fluorescence analysis indicated that the integral of the fluorescence emission peak in the range 610–650 nm was significantly higher in colorectal adenocarcinoma patients than controls (p < 0.0001) and was weakly correlated with the TNM staging (Spearman’s rho = 0.224, p = 0.011). LC-HRMS measurements showed that the agents responsible for the fluorescence emission were mainly protoporphyrin-IX (PpIX) and coproporphyrin-I (CpI). The overall accuracy of our ANN model was 88% (87% sensitivity and 90% specificity) with an area under the ROC curve of 0.83. CONCLUSIONS: These results confirm that tumor cells accumulate a diagnostic level of endogenous porphyrin compounds and suggest that plasma porphyrin concentrations, indirectly measured through fluorescence analysis, may be useful, together with risk factors, as a clinical decision support tool for the early detection of colorectal adenocarcinoma. Our future efforts will be aimed at examining how plasma porphyrin accumulation correlates with survival and response to therapy. BioMed Central 2018-08-22 /pmc/articles/PMC6106935/ /pubmed/30134852 http://dx.doi.org/10.1186/s12885-018-4754-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Lualdi, Manuela Cavalleri, Adalberto Battaglia, Luigi Colombo, Ambrogio Garrone, Giulia Morelli, Daniele Pignoli, Emanuele Sottotetti, Elisa Leo, Ermanno Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
title | Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
title_full | Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
title_fullStr | Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
title_full_unstemmed | Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
title_short | Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
title_sort | early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6106935/ https://www.ncbi.nlm.nih.gov/pubmed/30134852 http://dx.doi.org/10.1186/s12885-018-4754-2 |
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