RESUMO
In this study, the antioxidant components in co-culture of Chlorella pyrenoidosa and Yarrowia lipolytica (3:1 ratio) were confirmed as trypsin-hydrolyzed peptides (EHPs). The EHPs were composed of 836 different peptides with molecular weights ranging from 639 to 3531 Da and were mainly composed of hydrophobic amino acids (48.1%). These peptides showed remarkable protective effects against oxidative stress in HepG2, which may be attributed to their structures. Furthermore, the mRNA and protein levels of nuclear factor erythroid 2-related factor 2 (Nrf2) were significantly lower in the peptide-treated group than in the control group, suggesting that the antioxidant enzyme-coding genes were not activated. The EC50 value of three peptides in the EHPs were in the order of AGYSPIGFVR (0.04 ± 0.002 mg/mL) > VLDELTLAR (0.09 ± 0.001 mg/mL) > LFDPVYLFDQG (0.41 ± 0.03 mg/mL); these results agreed with the prediction of the model (R2 > 0.9, Q2 > 0.5). Thus, EHPs show potential as potent new antioxidant agents.
Assuntos
Antioxidantes/farmacologia , Chlorella/química , Peptídeos/farmacologia , Yarrowia/química , Aminoácidos/química , Antioxidantes/química , Antioxidantes/isolamento & purificação , Técnicas de Cocultura , Células Hep G2 , Humanos , Hidrólise , Estresse Oxidativo/efeitos dos fármacos , Peptídeos/química , Peptídeos/isolamento & purificação , Relação Quantitativa Estrutura-Atividade , Tripsina/metabolismoRESUMO
BACKGROUND: One of the most usual gynecological state of tumor is ovarian cancer and is a major reason of gynecological tumor-related global mortality rate. There have been multiple risk elements related to ovarian cancer like the background of past cases associated with breast cancer or ovarian cancer, or excessive body weight issues, case history of smoking, and untimely menstruation or menopause. Because of unclear expressions, more than 70% of the ovarian cancer patient cases are determined during the early stage. Material and Methods. GSE38666, GSE40595, and GSE66957 were the three microarray datasets which were analyzed using GEO2R for screening the differentially expressed genes. GO, Kyoto Encyclopedia of Genes, and protein expression studies were performed for analysis of hub genes. Then, survival analysis was performed for all the hub genes. RESULTS: From the dataset, a total of 199 differentially expressed genes (DEGs) were identified. Through the KEGG pathway study, it was noted that the DEGs are mainly linked with the AGE-RAGE signaling pathway, central carbon metabolism, and human papillomavirus infection. The survival analysis showed 4 highly expressed hub genes COL4A1, SDC1, CDKN2A, and TOP2A which correlated with overall survival in ovarian cancer patients. Moreover, the expression of the 4 hub genes was validated by the GEPIA database and the Human Protein Atlas. CONCLUSION: The results have shown that all 4 hub genes were found to be upregulated in ovarian cancer tissues which predict poor prognosis in patients with ovarian cancer.
Assuntos
Biomarcadores Tumorais/genética , Redes Reguladoras de Genes , Neoplasias Ovarianas/genética , Biomarcadores Tumorais/metabolismo , Colágeno Tipo IV/genética , Colágeno Tipo IV/metabolismo , Biologia Computacional , Inibidor p16 de Quinase Dependente de Ciclina/genética , Inibidor p16 de Quinase Dependente de Ciclina/metabolismo , DNA Topoisomerases Tipo II/genética , DNA Topoisomerases Tipo II/metabolismo , Bases de Dados Genéticas , Feminino , Regulação Neoplásica da Expressão Gênica , Humanos , Estimativa de Kaplan-Meier , Neoplasias Ovarianas/metabolismo , Proteínas de Ligação a Poli-ADP-Ribose/genética , Proteínas de Ligação a Poli-ADP-Ribose/metabolismo , Prognóstico , Mapas de Interação de Proteínas/genética , Sindecana-1/genética , Sindecana-1/metabolismo , Regulação para CimaRESUMO
Purpose: Cancer development and immune escape involve DNA methylation, copy number variation, and other molecular events. However, there are remarkably few studies integrating multiomics genetic profiles into endometrial cancer (EC). This study aimed to develop a multiomics signature for the prognosis and immunotherapy response of endometrial carcinoma. Methods: The gene expression, somatic mutation, copy number alteration, and DNA methylation data of EC were analyzed from the UCSC Xena database. Then, a multiomics signature was constructed by a machine learning model, with the ROC curve comparing its prognostic power with traditional clinical features. Two computational strategies were utilized to estimate the signature's performance in predicting immunotherapy response in EC. Further validation focused on the most frequently mutant molecule, ARID1A, in the signature. The association of ARID1A with survival, MSI (Microsatellite-instability), immune checkpoints, TIL (tumor-infiltrating lymphocyte), and downstream immune pathways was explored. Results: The signature consisted of 22 multiomics molecules, showing excellent prognostic performance in predicting the overall survival of patients with EC (AUC = 0.788). After stratifying patients into a high and low-risk group according to the signature's median value, low-risk patients displayed a greater possibility of respond to immunotherapy. Further validation on ARID1A suggested it could induce immune checkpoints upregulation, promote interferon response pathway, and interact with Treg (regulatory T cell) to facilitate immune activation in EC. Conclusion: A novel multiomics prognostic signature of EC was identified and validated in this study, which could guide clinical management of EC and benefit personalized immunotherapy.