scholarly journals GISTs: From the History to the Tailored Therapy

10.5772/33925 ◽  
2012 ◽  
Author(s):  
Roberta Zappacosta ◽  
Barbara Zappacosta ◽  
Serena Capanna ◽  
Chiara DAngelo ◽  
Daniela Gatta ◽  
...  
Keyword(s):  



2020 ◽  
Vol 13 (5) ◽  
pp. e234490
Author(s):  
Evan C Chen ◽  
Jonathan A Stefely ◽  
Bimalangshu R Dey ◽  
Walter H Dzik

Haemophagocytic lymphohistiocytosis (HLH) can be a rapidly fatal disease. Current treatment in adults is extrapolated from the HLH-2004 protocol that specifies a regimen of etoposide, dexamethasone and cyclosporine. However, HLH presents as a spectrum of disease severity. A therapeutic challenge arises for milder cases where the harms of potent chemotherapy such as etoposide may outweigh its benefit. We present a case of an adult with HLH who developed significant pancytopenia but was otherwise not critically ill and who responded to treatment with a chemotherapy-sparing approach consisting of intravenous immunoglobulins and corticosteroids alone. The case illustrates that tailored therapy may allow effective treatment of the disorder while minimising therapy-related toxicities.



2021 ◽  
Vol 22 (15) ◽  
pp. 8051
Author(s):  
Rodrigo Teodoro ◽  
Daniel Gündel ◽  
Winnie Deuther-Conrad ◽  
Lea Ueberham ◽  
Magali Toussaint ◽  
...  

Cannabinoid receptors type 2 (CB2R) represent an attractive therapeutic target for neurodegenerative diseases and cancer. Aiming at the development of a positron emission tomography (PET) radiotracer to monitor receptor density and/or occupancy during a CB2R-tailored therapy, we herein describe the radiosynthesis of cis-[18F]1-(4-fluorobutyl-N-((1s,4s)-4-methylcyclohexyl)-2-oxo-1,2-dihydro-1,8-naphthyridine-3-carboxamide ([18F]LU14) starting from the corresponding mesylate precursor. The first biological evaluation revealed that [18F]LU14 is a highly affine CB2R radioligand with >80% intact tracer in the brain at 30 min p.i. Its further evaluation by PET in a well-established rat model of CB2R overexpression demonstrated its ability to selectively image the CB2R in the brain and its potential as a tracer to further investigate disease-related changes in CB2R expression.



Author(s):  
Andre Roncon DIAS ◽  
Beatriz Camargo AZEVEDO ◽  
Luciana Bastos Valente ALBAN ◽  
Osmar Kenji YAGI ◽  
Marcus Fernando Kodama Pertille RAMOS ◽  
...  

ABSTRACT Introduction: The frequency of gastric neuroendocrine tumors is increasing. Reasons are the popularization of endoscopy and its technical refinements. Despite this, they are still poorly understood and have complex management. Aim: Update the knowledge on gastric neuroendocrine tumor and expose the future perspectives on the diagnosis and treatment of this disease. Method: Literature review using the following databases: Medline/PubMed, Cochrane Library and SciELO. Search terms were: gastric carcinoid, gastric neuroendocrine tumor, treatment. From the selected articles, 38 were included in this review. Results: Gastric neuroendocrine tumors are classified in four clinical types. Correct identification of the clinical type and histological grade is fundamental, since treatment varies accordingly and defines survival. Conclusion: Gastric neuroendocrine tumors comprise different subtypes with distinct management and prognosis. Correct identification allows for a tailored therapy. Further studies will clarify the diseases biology and improve its treatment.



2018 ◽  
Vol 160 (12) ◽  
pp. 2387-2391 ◽  
Author(s):  
Quintino Giorgio D’Alessandris ◽  
Nicola Montano ◽  
Maurizio Martini ◽  
Tonia Cenci ◽  
Liverana Lauretti ◽  
...  


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248956
Author(s):  
Elizabeth R. Lusczek ◽  
Nicholas E. Ingraham ◽  
Basil S. Karam ◽  
Jennifer Proper ◽  
Lianne Siegel ◽  
...  

Purpose Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. Methods This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes. Results The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30-fold (HR:7.30, 95% CI:(3.11–17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10–6.00), p = 0.03) increases in hazard of death relative to phenotype III. Conclusion We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design.





Author(s):  
Jessica Lydiard ◽  
Charles B. Nemeroff
Keyword(s):  


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