RESUMO
Primary brain tumors remain among the deadliest of all cancers. Glioma grade IV (glioblastoma), the most common and malignant type of brain cancer, is associated with a 5-year survival rate of < 5%. Melatonin has been widely reported as an anticancer molecule, and we have recently demonstrated that the ability of gliomas to synthesize and accumulate this indolamine in the surrounding microenvironment negatively correlates with tumor malignancy. However, our understanding of the specific effects mediated through the activation of melatonin membrane receptors remains limited. Thus, here we investigated the specific roles of MT1 and MT2 in gliomas and medulloblastomas. Using the MT2 antagonist DH97, we showed that MT1 activation has a negative impact on the proliferation of human glioma and medulloblastoma cell lines, while MT2 activation has an opposite effect. Accordingly, gliomas have a decreased mRNA expression of MT1 (also known as MTNR1A) and an increased mRNA expression of MT2 (also known as MTNR1B) compared to the normal brain cortex. The MT1/MT2 expression ratio negatively correlates with the expression of cell cycle-related genes and is a positive prognostic factor in gliomas. Notably, we showed that functional selective drugs that simultaneously activate MT1 and inhibit MT2 exert robust anti-tumor effects in vitro and in vivo, downregulating the expression of cell cycle and energy metabolism genes in glioma stem-like cells. Overall, we provided the first evidence regarding the differential roles of MT1 and MT2 in brain tumor progression, highlighting their relevance as druggable targets. KEY MESSAGES: ⢠MT1 impairs while MT2 promotes the proliferation of glioma and medulloblastoma cell lines. ⢠Gliomas have a decreased expression of MT1 and an increased expression of MT2 compared to normal brain cortex. ⢠Tumors with a high MT1/MT2 expression ratio have significantly better survival rates. ⢠Functional selective drugs that simultaneously activate MT1 and inhibit MT2 downregulate the expression of cell cycle and energy metabolism genes in glioma stem-like cells and exert robust anti-tumor effects in vivo.
Assuntos
Neoplasias Encefálicas , Glioma , Receptor MT1 de Melatonina , Receptor MT2 de Melatonina , Animais , Encéfalo/metabolismo , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/mortalidade , Neoplasias Encefálicas/patologia , Linhagem Celular Tumoral , Proliferação de Células , Progressão da Doença , Feminino , Glioma/genética , Glioma/metabolismo , Glioma/mortalidade , Glioma/patologia , Humanos , Estimativa de Kaplan-Meier , Masculino , Camundongos Endogâmicos BALB C , Camundongos Nus , Receptor MT1 de Melatonina/genética , Receptor MT1 de Melatonina/metabolismo , Receptor MT2 de Melatonina/genética , Receptor MT2 de Melatonina/metabolismoRESUMO
OBJECTIVE: To identify, with the use of pretreatment clinical data, the children with idiopathic short stature responsive to treatment with growth hormone (GH). DESIGN: Open, prospective study in a university hospital. SUBJECTS: Patients admitted to the study met the following criteria: birth weight at least 2.5 kg, no sign of dysmorphic disease, stature less than the 3rd percentile for chronologic age (CA), linear growth velocity (GV) less than the 25th percentile for bone age (BA), no sign of puberty, maximal GH response to pharmacologic stimulation greater than 10 micrograms/L, no evidence of organic disease, treatment with daily subcutaneous administration of GH at a dose of 12 to 16 IU/m2 per week. MAIN OUTCOME MEASURES: Eight pretreatment growth variables and the increase of GV after 6 months of therapy were measured. Children with a change in GV that was greater than 2.5 cm/yr after 6 months of GH therapy were considered responders to GH. RESULTS: We studied 67 patients (44 boys). Forty patients (60%) were responders. With univariate analysis the variables found to have predictive value were GV (z score for gender and CA), bone age (z score for gender and CA), and percentage of ideal body weight. These variables were employed in a multivariate discriminant analysis. Growth velocity and BA showed the best independent discriminant analysis. Growth velocity and BA showed the best independent discriminant significance in predicting responsiveness to the initial 6 months of GH therapy. The obtained equation was as follows: Score = -0.40 + 0.92X1 - 0.87X2, where X1 is the GV z value for CA and X2 is the BA z value for CA). Using this scoring system, we obtained a specificity of 96.3% and a sensitivity of 92.5% in predicting responsiveness to GH (chi-square with Yates correction, 48.2; p < 0.001). CONCLUSIONS: Discriminant analysis may permit the pretreatment prediction of responsiveness to the initial 6 months of GH therapy in short children without GH deficiency.