Cargando…
Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies
Succinate dehydrogenase subunit B and D (SDHB and SDHD) mutations represent the most frequent cause of hereditary pheochromocytoma and paraganglioma (PPGL). Although truncation of the succinate dehydrogenase complex is thought to be the disease causing mechanism in both disorders, SDHB and SDHD pati...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091916/ https://www.ncbi.nlm.nih.gov/pubmed/30106970 http://dx.doi.org/10.1371/journal.pone.0201303 |
_version_ | 1783347445747417088 |
---|---|
author | Barbolosi, Dominique Crona, Joakim Serre, Raphaël Pacak, Karel Taieb, David |
author_facet | Barbolosi, Dominique Crona, Joakim Serre, Raphaël Pacak, Karel Taieb, David |
author_sort | Barbolosi, Dominique |
collection | PubMed |
description | Succinate dehydrogenase subunit B and D (SDHB and SDHD) mutations represent the most frequent cause of hereditary pheochromocytoma and paraganglioma (PPGL). Although truncation of the succinate dehydrogenase complex is thought to be the disease causing mechanism in both disorders, SDHB and SDHD patients exihibit different phenotypes. These phenotypic differences are currently unexplained by molecular genetics. The aim of this study is to compare disease dynamics in these two conditions via a Markov chain model based on 4 clinically-defined steady states. Our model corroborates at the population level phenotypic observations in SDHB and SDHD carriers and suggests potential explanations associated with the probabilities of disease maintenance and regression. In SDHB-related syndrome, PPGL maintenance seems to be reduced compared to SDHD (p = 0.04 vs 0.95) due to higher probability of tumor cell regression in SDHB vs SDHD (p = 0.87 vs 0.00). However, when SDHB-tumors give rise to metastases, metastatic cells are able to thrive with decreased probability of regression compared with SDHD counterparts (p = 0.17 vs 0.89). By constrast, almost all SDHD patients develop PGL (mainly head and neck) that persist throughout their lifetime. However, compared to SDHB, maintenance of metastatic lesions seems to be less effective for SDHD (p = 0.83 vs 0.11). These findings align with data suggesting that SDHD-related PPGL require less genetic events for tumor initiation and maintenance compared to those related to SDHB, but fail to initiate biology that promotes metastatic spread and metastatic cell survival in host tissues. By contrast, the higher number of genetic abnormalities required for tumor initiation and maintenance in SDHB PPGL result in a lower penetrance of PGL, but when cells give rise to metastases they are assumed to be better adapted to sustain survival. These proposed differences in disease progression dynamics between SDHB and SDHD diseases provide new cues for future exploration of SDHx PPGL behavior, offering considerations for future specific therapeutic and prevention strategies. |
format | Online Article Text |
id | pubmed-6091916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-60919162018-08-30 Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies Barbolosi, Dominique Crona, Joakim Serre, Raphaël Pacak, Karel Taieb, David PLoS One Research Article Succinate dehydrogenase subunit B and D (SDHB and SDHD) mutations represent the most frequent cause of hereditary pheochromocytoma and paraganglioma (PPGL). Although truncation of the succinate dehydrogenase complex is thought to be the disease causing mechanism in both disorders, SDHB and SDHD patients exihibit different phenotypes. These phenotypic differences are currently unexplained by molecular genetics. The aim of this study is to compare disease dynamics in these two conditions via a Markov chain model based on 4 clinically-defined steady states. Our model corroborates at the population level phenotypic observations in SDHB and SDHD carriers and suggests potential explanations associated with the probabilities of disease maintenance and regression. In SDHB-related syndrome, PPGL maintenance seems to be reduced compared to SDHD (p = 0.04 vs 0.95) due to higher probability of tumor cell regression in SDHB vs SDHD (p = 0.87 vs 0.00). However, when SDHB-tumors give rise to metastases, metastatic cells are able to thrive with decreased probability of regression compared with SDHD counterparts (p = 0.17 vs 0.89). By constrast, almost all SDHD patients develop PGL (mainly head and neck) that persist throughout their lifetime. However, compared to SDHB, maintenance of metastatic lesions seems to be less effective for SDHD (p = 0.83 vs 0.11). These findings align with data suggesting that SDHD-related PPGL require less genetic events for tumor initiation and maintenance compared to those related to SDHB, but fail to initiate biology that promotes metastatic spread and metastatic cell survival in host tissues. By contrast, the higher number of genetic abnormalities required for tumor initiation and maintenance in SDHB PPGL result in a lower penetrance of PGL, but when cells give rise to metastases they are assumed to be better adapted to sustain survival. These proposed differences in disease progression dynamics between SDHB and SDHD diseases provide new cues for future exploration of SDHx PPGL behavior, offering considerations for future specific therapeutic and prevention strategies. Public Library of Science 2018-08-14 /pmc/articles/PMC6091916/ /pubmed/30106970 http://dx.doi.org/10.1371/journal.pone.0201303 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Barbolosi, Dominique Crona, Joakim Serre, Raphaël Pacak, Karel Taieb, David Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies |
title | Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies |
title_full | Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies |
title_fullStr | Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies |
title_full_unstemmed | Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies |
title_short | Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies |
title_sort | mathematical modeling of disease dynamics in sdhb- and sdhd-related paraganglioma: further step in understanding hereditary tumor differences and future therapeutic strategies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091916/ https://www.ncbi.nlm.nih.gov/pubmed/30106970 http://dx.doi.org/10.1371/journal.pone.0201303 |
work_keys_str_mv | AT barbolosidominique mathematicalmodelingofdiseasedynamicsinsdhbandsdhdrelatedparagangliomafurtherstepinunderstandinghereditarytumordifferencesandfuturetherapeuticstrategies AT cronajoakim mathematicalmodelingofdiseasedynamicsinsdhbandsdhdrelatedparagangliomafurtherstepinunderstandinghereditarytumordifferencesandfuturetherapeuticstrategies AT serreraphael mathematicalmodelingofdiseasedynamicsinsdhbandsdhdrelatedparagangliomafurtherstepinunderstandinghereditarytumordifferencesandfuturetherapeuticstrategies AT pacakkarel mathematicalmodelingofdiseasedynamicsinsdhbandsdhdrelatedparagangliomafurtherstepinunderstandinghereditarytumordifferencesandfuturetherapeuticstrategies AT taiebdavid mathematicalmodelingofdiseasedynamicsinsdhbandsdhdrelatedparagangliomafurtherstepinunderstandinghereditarytumordifferencesandfuturetherapeuticstrategies |