Cargando…

Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses

Linear-no-threshold (LNT) risk extrapolation has long been applied to estimate risks posed by low-level environmental carcinogen exposures, based on the 60-year-old multistage somatic mutation/clonal expansion (MSM) cancer theory. Recent evidence supports an alternative theory: Malignant tumors aris...

Descripción completa

Detalles Bibliográficos
Autor principal: Bogen, Kenneth T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537503/
https://www.ncbi.nlm.nih.gov/pubmed/31205456
http://dx.doi.org/10.1177/1559325819847834
_version_ 1783422026580492288
author Bogen, Kenneth T.
author_facet Bogen, Kenneth T.
author_sort Bogen, Kenneth T.
collection PubMed
description Linear-no-threshold (LNT) risk extrapolation has long been applied to estimate risks posed by low-level environmental carcinogen exposures, based on the 60-year-old multistage somatic mutation/clonal expansion (MSM) cancer theory. Recent evidence supports an alternative theory: Malignant tumors arise most efficiently from a stem cell that incurs requisite mutations and also is activated by inflammation to an epigenetically mediated and maintained state of adaptive hyperplasia (AH). This new inflammation-MSM (ISM) theory posits that inflammation-activated stem cells normally restricted to sites of injury-induced inflammation and tissue repair become uniquely susceptible to efficient carcinogenesis if normal post-inflammation AH termination is blocked by mutation. This theory posits that inflammation generally thus co-initiates cancer and transiently amplifies activated stem cells, implying that MSM theory (eg, the 2-stage stochastic “Moolgavkar, Venzon, Knudson [MVK]” model) is incomplete. Because inflammation dose–response typically is not LNT, the ISM theory predicts this is also true for most (perhaps all) carcinogens. The ISM (but not the MVK) model is shown to be consistent with recent data showing ∼100% carcinoma incidence (but not DNA adducts) in livers of rats exposed to aflatoxin B(1) and was eliminated when that dose was co-administered with a highly potent anti-inflammatory agent. Experimental approaches to test ISM theory more robustly are discussed.
format Online
Article
Text
id pubmed-6537503
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher SAGE Publications
record_format MEDLINE/PubMed
spelling pubmed-65375032019-06-14 Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses Bogen, Kenneth T. Dose Response Original Article Linear-no-threshold (LNT) risk extrapolation has long been applied to estimate risks posed by low-level environmental carcinogen exposures, based on the 60-year-old multistage somatic mutation/clonal expansion (MSM) cancer theory. Recent evidence supports an alternative theory: Malignant tumors arise most efficiently from a stem cell that incurs requisite mutations and also is activated by inflammation to an epigenetically mediated and maintained state of adaptive hyperplasia (AH). This new inflammation-MSM (ISM) theory posits that inflammation-activated stem cells normally restricted to sites of injury-induced inflammation and tissue repair become uniquely susceptible to efficient carcinogenesis if normal post-inflammation AH termination is blocked by mutation. This theory posits that inflammation generally thus co-initiates cancer and transiently amplifies activated stem cells, implying that MSM theory (eg, the 2-stage stochastic “Moolgavkar, Venzon, Knudson [MVK]” model) is incomplete. Because inflammation dose–response typically is not LNT, the ISM theory predicts this is also true for most (perhaps all) carcinogens. The ISM (but not the MVK) model is shown to be consistent with recent data showing ∼100% carcinoma incidence (but not DNA adducts) in livers of rats exposed to aflatoxin B(1) and was eliminated when that dose was co-administered with a highly potent anti-inflammatory agent. Experimental approaches to test ISM theory more robustly are discussed. SAGE Publications 2019-05-16 /pmc/articles/PMC6537503/ /pubmed/31205456 http://dx.doi.org/10.1177/1559325819847834 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Article
Bogen, Kenneth T.
Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses
title Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses
title_full Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses
title_fullStr Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses
title_full_unstemmed Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses
title_short Inflammation as a Cancer Co-Initiator: New Mechanistic Model Predicts Low/Negligible Risk at Noninflammatory Carcinogen Doses
title_sort inflammation as a cancer co-initiator: new mechanistic model predicts low/negligible risk at noninflammatory carcinogen doses
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537503/
https://www.ncbi.nlm.nih.gov/pubmed/31205456
http://dx.doi.org/10.1177/1559325819847834
work_keys_str_mv AT bogenkennetht inflammationasacancercoinitiatornewmechanisticmodelpredictslownegligibleriskatnoninflammatorycarcinogendoses