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1.
Front Endocrinol (Lausanne) ; 13: 903085, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36187102

RESUMEN

Composite pheochromocytoma (CP) is a very rare tumor originating from neural crest cells, predominantly composed of pheochromocytoma (PCC), a chromaffin cell tumor arising in adrenal medulla, and ganglioneuroma, a tumor derived from autonomic ganglion cells of the nervous system. Moreover, CP may be present in the hereditary syndromes of which pheochromocytoma is part. Literature offers scarce data on this subject, and particularly about its biological behavior, clinical evolution, and molecular profile. We report the phenotype and outcome of three cases of CP (PCC and ganglioneuroma components), followed up at the Endocrine Service of the Clementino Fraga Filho University Hospital, Federal University of Rio de Janeiro, UFRJ, Rio de Janeiro, Brazil. Two nonsyndromic patients (cases 1 and 2) were negative to germline mutations in genes VHL, SDHB, SDHC, SDHD, SDHAF2, TMEM127, and MAX, while the third case (case 3) had clinical diagnosis of neurofibromatosis syndrome. Cases 1, 2, and 3 were diagnosed at 29, 39, and 47 years old, respectively, and were followed up for 3, 17, and 9 years without no CP recurrence. All cases had apparent symptoms of catecholaminergic excess secreted by PCC. Ganglioneuroma, the neurogenic component present in all three cases, had a percentage representation ranging from 5% to 15%. Tumors were unilateral and large, measuring 7.0 cm × 6.0 cm × 6.0 cm, 6.0 cm × 4.0 cm × 3.2 cm, and 7.5 cm × 6.0 cm × 4.5 cm, respectively. All cases underwent adrenalectomy with no recurrence, metastasis, or development of contralateral tumor during follow-up. Genetic testing has been scarcely offered to CP cases. However, a similar frequency of genetic background is found when compared with classic PCC, mainly by the overrepresentation of NF1 cases in the CP subset. By literature review, we identified a notorious increase in cases reported with CP in the last decade, especially in the last 3 years, indicating a recent improvement in the diagnosis of this rare disorder in clinical practice.


Asunto(s)
Neoplasias de las Glándulas Suprarrenales , Ganglioneuroma , Paraganglioma , Feocromocitoma , Neoplasias de las Glándulas Suprarrenales/diagnóstico , Neoplasias de las Glándulas Suprarrenales/genética , Neoplasias de las Glándulas Suprarrenales/cirugía , Brasil , Ganglioneuroma/diagnóstico , Ganglioneuroma/genética , Ganglioneuroma/cirugía , Humanos , Paraganglioma/patología , Feocromocitoma/diagnóstico , Feocromocitoma/genética , Feocromocitoma/cirugía
2.
J Comput Biol ; 22(7): 649-65, 2015 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-25973723

RESUMEN

Cancer is characterized by the uncontrolled growth of cells with the ability of invading local organs and/or tissues and of spreading to other sites. Several kinds of mathematical models have been proposed in the literature, involving different levels of refinement, for the evolution of tumors and their interactions with chemotherapy drugs. In this article, we present the solution of a state estimation problem for tumor size evolution. A system of nonlinear ordinary differential equations is used as the state evolution model, which involves as state variables the numbers of tumor, normal and angiogenic cells, as well as the masses of the chemotherapy and anti-angiogenic drugs in the body. Measurements of the numbers of tumor and normal cells are considered available for the inverse analysis. Parameters appearing in the formulation of the state evolution model are treated as Gaussian random variables and their uncertainties are taken into account in the estimation of the state variables, by using an algorithm based on the auxiliary sampling importance resampling particle filter. Test cases are examined in the article dealing with a chemotherapy protocol for pancreatic cancer.


Asunto(s)
Neoplasias/patología , Algoritmos , Antimetabolitos Antineoplásicos/farmacocinética , Simulación por Computador , Desoxicitidina/análogos & derivados , Desoxicitidina/farmacocinética , Diagnóstico por Computador , Semivida , Humanos , Modelos Biológicos , Método de Montecarlo , Neoplasias/tratamiento farmacológico , Carga Tumoral , Gemcitabina
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