Matrin3 (MATR3) is an RNA binding protein involved in many roles in the nucleus, such as chromatin architecture and gene expression regulation, modulating transcriptional and post-transcriptional processes as RNA splicing and mRNA stabilization. Nevertheless, some functions of MATR3 within the cells are not entirely clear. MATR3 has been associated with Amyotrophic Lateral Sclerosis (ALS), a neurodegenerative disease that damages motor neuron (MN) cells and leads to progressive muscle paralysis and respiratory failure. A better understanding of MATR3 activity within cell physiology could represent an essential breakthrough for studying MATR3-associated pathologies. Using MATR3-silenced human pluripotent stem cell (hiPSC) line model, we collected data on the MATR3 role in the pluripotency and in the neural induction and differentiation. We found that the downregulation of MATR3 alters the expression level of crucial self-renewal factors such as OCT4, NANOG, KLF4, and LIN28A. We observed MATR3 acts at multiple levels of the gene expression, i.e. regulating YTHDF1 expression, and in RNA metabolism, having a role in mRNA stabilization and translation. The reduction of stemness potential caused by MATR3 downregulation creates a defect during the neurodifferentiation process, which does not arrest motor neurons formation but induces selective alterations that may affect motor neurons functionality. Indeed, several morphological and molecular abnormalities were observed during the neuronal differentiation, such as the alterations of the formation of neuroepithelial rosettes that arise in a reduction of neurite lengths and arborization in neuronal cells. On this basis, we investigated neuronal differentiation in the brain organoids grown from iPSCs derived from ALS patients fibroblasts. We show, for the first time, that MATR3 is a critical factor in orchestrating the stemness network through transcriptional, post-transcriptional, and translational regulation, therefore affecting the differentiation of mature neurons.

INTRODUÇÃO: O carcinoma de pulmão de pequenas células (CPPC) e o carcinoma neuroendócrino (CNE) extra-pulmonar apresentam características histopatológicas e tratamentos similares, porém os desfechos encontrados nos dois grupos podem ser diferentes. Avaliamos a expressão de alguns biomarcadores e a associação destes com taxa de resposta (TR) à quimioterapia baseada em platina e sobrevida global (SG) nos dois grupos. METODOS: Realizamos estudo retrospectivo de pacientes com CPPC e CNE extra-pulmonares tratados com quimioterapia baseada em platina. Todas as amostras tumorais foram revisadas pelo mesmo patologista (R.S.S.M.) e analisadas quanto a expressão imunoistoquímica de Ki-67, ERCC1, Bcl-2 e Lin28a, a qual foi determinada através do H-escore (calculado multiplicando o produto da intensidade da coloração - 0 a 3 - com a porcentagem de células positivas - 0 a 100 -, podendo variar de 0 a 300 - positivo quando >= 200). Os biomarcadores foram analisados tanto como variáveis contínuas quanto categóricas e a TR foi determinada por RECIST 1.1. A associação entre a expressão de cada biomarcador e a TR foi avaliada através do teste de qui-quadrado ou teste exato de Fisher para variáveis categóricas e regressão logística simples para variáveis contínuas. Sobrevida global foi estimada por Kaplan-Meier e as curvas foram comparadas por log-rank. O modelo de regressão de cox foi utilizado para avaliar associação entre SG e a expressão de biomarcadores como variável contínua. RESULTADOS: Entre Julho de 2006 e Julho de 2014, 142 pacientes foram identificados: N=82 (57,7%) com CPPC e N=60 (42,3%) com CNE extra-pulmonar. As características clínicas eram semelhantes em ambos os grupos. Mediana de ki67 foi de 60% (7-100) no CPPC e de 50% (20-95%) no segundo grupo (p=0,858). Com uma mediana de 5 ciclos por paciente (N=123 elegíveis para análise de TR), a TR foi de 86,8% no CPPC, enquanto nos com CNE extra-pulmonar, foi de 44,6% (p < 0.001). A mediana de SG (N=132 elegíveis para análise da SG) foi similar entre os grupos (10,3 meses em CPPC e 11,1 meses em CNE extra-pulmonar; p=0,069). Não houve diferença no padrão de expressão do ERCC1 (p=0,277) e do Lin28a (p=0,051) entre os grupos. Bcl2 foi expresso em 38 pacientes (46,3%) com CPPC e em 17 pacientes (28,3%) com CNE extra-pulmonar (p=0,030). Apenas no grupo com CNE extra-pulmonar, a alta expressão do Bcl2 foi associada com pior prognóstico (8,0 meses vs 14,7 meses; p=0,025). A expressão dos demais marcadores em CNE extra-pulmonar e dos quatro em CPPC não apresentou influência sobre a SG, não havendo também associação entre estes e a taxa de resposta à quimioterapia. Dentre os pacientes com CNE extra-pulmonar, não houve diferença na SG ou na TR entre os pacientes com carcinoma bem diferenciado (N=13;) e com carcinoma pouco diferenciado (N=47). CONCLUSÃO: Apesar do CPPC e do CNE extra-pulmonar serem tratados de forma semelhante, nesta coorte a taxa de resposta entre os grupos foi significativamente diferente. Quando comparado com CPPC, os pacientes com CNE extra-pulmonar apresentam uma menor responsividade à quimioterapia baseada em platina, mas com tendência a maior SG. Dentre os CNE extra-pulmonares, a alta expressão de Bcl-2 foi associada a pior prognóstico. Os demais biomarcadores não apresentaram papel preditor de resposta ou prognóstico / INTRODUCTION: Small cell lung cancer (SCLC) and high-grade extrapulmonary neuroendocrine carcinomas (EPNEC) share similar histopathological features and treatment, but outcomes may differ. We evaluated the expression of biomarkers and their association with response rate (RR) to platin-based chemotherapy and overall survival (OS) in these entities. METHODS: We conducted a retrospective analysis of patients with advanced EPNEC and SCLC treated with platinum-based chemotherapy. A single pathologist (R.S.S.M.) revised all samples. Paraffin-embedded tumor samples were tested for Ki-67, ERCC1, Bcl-2 and Lin28a expression by immunohistochemistry (IHC). Final IHC score (H-score) was calculated multiplying the intensity of staining by grading (0-300, with >= 200 considered positive). Biomarkers were analyzed as both categorical and continuous variables. RR was determined by RECIST 1.1. Associations between each biomarkers expression and RR were assessed using Chi-square or Fisher\'s exact test for categorical variables and univariate logistic regression for continuous variables. OS was estimated by the Kaplan-Meier method and curves were compared by log-rank. Cox regression analysis was used to evaluate any association between biomarkers expression (continuous variables) and OS. RESULTS: From July 2006 to July 2014, 142 patients were identified: N=82 (57,7%) with SCLC and N=60 (42,3%) with EPNEC. Baseline clinical characteristics were similar. Median Ki67 was 60% (7-100) among SCLC patients and 50% (20-95%) in EPNEC (p=0,858). With a median of 5 cycles per patient in both groups (N=123 evaluable patients), the RR was significantly higher in the SCLC group (86,8% vs 44.6%; p < 0.001). Median OS (N=132 evaluable patients) was similar between the groups (10.3 months in SCLC and 11.1 months in EPNEC; p=0,069). In the EPNEC group, there wasn\'t any difference in OS or RR between the patients with welldifferentiated (N=13) and poorly differentiated carcinoma (N=47). ERCC1 (p=0.277) and Lin28a (p=0.051) were similarly expressed between the groups. Bcl2 was expressed in 38 SCLC patients (46.3%) and in 17 EPNEC patients (28.3%; p=0.030). Only in the EPNEC group, Bcl2 high expression was associated with worse survival (8.0 months vs 14.7 months; p = 0.025). RR to chemotherapy was not influenced by the expression of the ERCC1, Lin28a, Bcl-2, Ki-67 in either EPNEC or SCLC groups. CONCLUSION: Even though SCLC and EPNEC are treated similarly, in this cohort, the rate response differed significantly. When compared with SCLC, patients with EPNEC apparently had tumors less responsive to platin-based chemotherapy, but tended to live longer. In EPNEC treated with platin, high expression of Bcl2 was associated with poor prognosis. We could not identify additional predictive or prognostic biomarkers

INTRODUÇÃO: O carcinoma de pulmão de pequenas células (CPPC) e o carcinoma neuroendócrino (CNE) extra-pulmonar apresentam características histopatológicas e tratamentos similares, porém os desfechos encontrados nos dois grupos podem ser diferentes. Avaliamos a expressão de alguns biomarcadores e a associação destes com taxa de resposta (TR) à quimioterapia baseada em platina e sobrevida global (SG) nos dois grupos. METODOS: Realizamos estudo retrospectivo de pacientes com CPPC e CNE extra-pulmonares tratados com quimioterapia baseada em platina. Todas as amostras tumorais foram revisadas pelo mesmo patologista (R.S.S.M.) e analisadas quanto a expressão imunoistoquímica de Ki-67, ERCC1, Bcl-2 e Lin28a, a qual foi determinada através do H-escore (calculado multiplicando o produto da intensidade da coloração - 0 a 3 - com a porcentagem de células positivas - 0 a 100 -, podendo variar de 0 a 300 - positivo quando >= 200). Os biomarcadores foram analisados tanto como variáveis contínuas quanto categóricas e a TR foi determinada por RECIST 1.1. A associação entre a expressão de cada biomarcador e a TR foi avaliada através do teste de qui-quadrado ou teste exato de Fisher para variáveis categóricas e regressão logística simples para variáveis contínuas. Sobrevida global foi estimada por Kaplan-Meier e as curvas foram comparadas por log-rank. O modelo de regressão de cox foi utilizado para avaliar associação entre SG e a expressão de biomarcadores como variável contínua. RESULTADOS: Entre Julho de 2006 e Julho de 2014, 142 pacientes foram identificados: N=82 (57,7%) com CPPC e N=60 (42,3%) com CNE extra-pulmonar. As características clínicas eram semelhantes em ambos os grupos. Mediana de ki67 foi de 60% (7-100) no CPPC e de 50% (20-95%) no segundo grupo (p=0,858). Com uma mediana de 5 ciclos por paciente (N=123 elegíveis para análise de TR), a TR foi de 86,8% no CPPC, enquanto nos com CNE extra-pulmonar, foi de 44,6% (p < 0.001). A mediana de SG (N=132 elegíveis para análise da SG) foi similar entre os grupos (10,3 meses em CPPC e 11,1 meses em CNE extra-pulmonar; p=0,069). Não houve diferença no padrão de expressão do ERCC1 (p=0,277) e do Lin28a (p=0,051) entre os grupos. Bcl2 foi expresso em 38 pacientes (46,3%) com CPPC e em 17 pacientes (28,3%) com CNE extra-pulmonar (p=0,030). Apenas no grupo com CNE extra-pulmonar, a alta expressão do Bcl2 foi associada com pior prognóstico (8,0 meses vs 14,7 meses; p=0,025). A expressão dos demais marcadores em CNE extra-pulmonar e dos quatro em CPPC não apresentou influência sobre a SG, não havendo também associação entre estes e a taxa de resposta à quimioterapia. Dentre os pacientes com CNE extra-pulmonar, não houve diferença na SG ou na TR entre os pacientes com carcinoma bem diferenciado (N=13;) e com carcinoma pouco diferenciado (N=47). CONCLUSÃO: Apesar do CPPC e do CNE extra-pulmonar serem tratados de forma semelhante, nesta coorte a taxa de resposta entre os grupos foi significativamente diferente. Quando comparado com CPPC, os pacientes com CNE extra-pulmonar apresentam uma menor responsividade à quimioterapia baseada em platina, mas com tendência a maior SG. Dentre os CNE extra-pulmonares, a alta expressão de Bcl-2 foi associada a pior prognóstico. Os demais biomarcadores não apresentaram papel preditor de resposta ou prognóstico / INTRODUCTION: Small cell lung cancer (SCLC) and high-grade extrapulmonary neuroendocrine carcinomas (EPNEC) share similar histopathological features and treatment, but outcomes may differ. We evaluated the expression of biomarkers and their association with response rate (RR) to platin-based chemotherapy and overall survival (OS) in these entities. METHODS: We conducted a retrospective analysis of patients with advanced EPNEC and SCLC treated with platinum-based chemotherapy. A single pathologist (R.S.S.M.) revised all samples. Paraffin-embedded tumor samples were tested for Ki-67, ERCC1, Bcl-2 and Lin28a expression by immunohistochemistry (IHC). Final IHC score (H-score) was calculated multiplying the intensity of staining by grading (0-300, with >= 200 considered positive). Biomarkers were analyzed as both categorical and continuous variables. RR was determined by RECIST 1.1. Associations between each biomarkers expression and RR were assessed using Chi-square or Fisher\'s exact test for categorical variables and univariate logistic regression for continuous variables. OS was estimated by the Kaplan-Meier method and curves were compared by log-rank. Cox regression analysis was used to evaluate any association between biomarkers expression (continuous variables) and OS. RESULTS: From July 2006 to July 2014, 142 patients were identified: N=82 (57,7%) with SCLC and N=60 (42,3%) with EPNEC. Baseline clinical characteristics were similar. Median Ki67 was 60% (7-100) among SCLC patients and 50% (20-95%) in EPNEC (p=0,858). With a median of 5 cycles per patient in both groups (N=123 evaluable patients), the RR was significantly higher in the SCLC group (86,8% vs 44.6%; p < 0.001). Median OS (N=132 evaluable patients) was similar between the groups (10.3 months in SCLC and 11.1 months in EPNEC; p=0,069). In the EPNEC group, there wasn\'t any difference in OS or RR between the patients with welldifferentiated (N=13) and poorly differentiated carcinoma (N=47). ERCC1 (p=0.277) and Lin28a (p=0.051) were similarly expressed between the groups. Bcl2 was expressed in 38 SCLC patients (46.3%) and in 17 EPNEC patients (28.3%; p=0.030). Only in the EPNEC group, Bcl2 high expression was associated with worse survival (8.0 months vs 14.7 months; p = 0.025). RR to chemotherapy was not influenced by the expression of the ERCC1, Lin28a, Bcl-2, Ki-67 in either EPNEC or SCLC groups. CONCLUSION: Even though SCLC and EPNEC are treated similarly, in this cohort, the rate response differed significantly. When compared with SCLC, patients with EPNEC apparently had tumors less responsive to platin-based chemotherapy, but tended to live longer. In EPNEC treated with platin, high expression of Bcl2 was associated with poor prognosis. We could not identify additional predictive or prognostic biomarkers

The genes that regulate pubertal timing in the general population are not well understood. Recently, genome-wide association studies have demonstrated that genetic variants near LIN28B associate with variation in pubertal timing in humans. To investigate where within the hypothalamic-pituitary-ovarian (HPO) axis Lin28b, and its homologue Lin28a, regulate pubertal timing, expression of these genes was assessed across the pubertal transition. The finding that Lin28a/b expression decreases only in the ovary suggests that the Lin28 pathway may exert its regulatory effects with respect to puberty in the ovary. Another aim of this thesis was to examine the effect of estrogen on Lin28b expression in immortalized GnRH neuronal cells, but the data remains equivocal and detailed future studies are needed to make definitive conclusions. The ovarian expression data lay the foundation for further studies using conditional knockout mice to verify the importance of the tissue and age specific developmental pattern that was identified.

The genes that regulate pubertal timing in the general population are not well understood. Recently, genome-wide association studies have demonstrated that genetic variants near LIN28B associate with variation in pubertal timing in humans. To investigate where within the hypothalamic-pituitary-ovarian (HPO) axis Lin28b, and its homologue Lin28a, regulate pubertal timing, expression of these genes was assessed across the pubertal transition. The finding that Lin28a/b expression decreases only in the ovary suggests that the Lin28 pathway may exert its regulatory effects with respect to puberty in the ovary. Another aim of this thesis was to examine the effect of estrogen on Lin28b expression in immortalized GnRH neuronal cells, but the data remains equivocal and detailed future studies are needed to make definitive conclusions. The ovarian expression data lay the foundation for further studies using conditional knockout mice to verify the importance of the tissue and age specific developmental pattern that was identified.