Produção e caracterização de uma célula com múltiplas fluorescências

A resistência de células tumorais à terapia consiste na principal causa de falha terapêutica no tratamento de câncer e está diretamente relacionada à heterogeneidade tumoral. Estudos populacionais falham em demonstrar as particularidades de cada célula em uma massa tumoral e, com isso, técnicas de análises de células únicas emergiram para o auxílio da compreensão da biologia tumoral. Entretanto, essas análises são ainda muito incipientes e dependem de pessoas altamente capacitadas e equipamentos e reagente de alto valor monetário e baixa disponibilidade nos centros de pesquisa. Tendo isso em vista, foi construída uma célula com marcação genômica de fluorescência de processos celulares importantes (quebra de fita duplas no DNA, apoptose e autofagia) para o estudo de células individuais vivas. Estas marcações foram, respectivamente: 53BP1 (vermelho), IMS simulando DIABLO (vermelho) e LC3B (ciano). Também foi desenvolvida uma ferramenta personalizada para análise automatizada de foci de dano ao DNA. Apesar de algumas alterações nas marcações celulares serem necessárias, foi possível mostrar que o sistema de tripla marcação é eficiente para o estudo de células únicas e não interfere o funcionamento celular de maneira a atrapalhar análises posteriores.Therapy resistance is one of the main causes of therapeutic failures in cancer treatment and it is directly related to tumoral heterogeneity. Populational studies fail in demonstrate the particularities of single cells in a tumor, and so single cell analysis techniques emerged to assist in the tumoral biology comprehension. However, these analyses are still incipient and demand highly skilled persons and high cost of reagent and equipment, not always available in all research centers. Thereby a cell transduced with three sensors for important processes in cancer biology (DNA damage, autophagy and apoptosis) was constructed for single-cell studies. We also developed a personalized tool for automated analysis of DNA damage foci. Despite the need of some changes in the chosen vectors, it was possible to show that a triple staining system is efficient for single-cell studies and it does not interfere in the cell function

Expression of key unfolded protein response genes predicts patient survival and an immunosuppressive microenvironment in glioblastoma

Abstract Background Dysregulation of cellular processes related to protein folding and trafficking leads to the accumulation of misfolded proteins in the endoplasmic reticulum (ER), triggering ER stress. Cells cope with ER stress by activating the unfolded protein response (UPR), a signaling pathway that has been implicated in a variety of diseases, including cancer. However, the role of the UPR in cancer initiation and progression is still unclear. Methods Here we used bulk and single cell RNA sequencing data to investigate ER stress-related gene expression in glioblastoma, as well as the impact key UPR genes have on patient survival. Results ER stress-related genes are highly expressed in both cancer cells and tumor-associated macrophages, with evidence of high intra- and inter-tumor heterogeneity. High expression of the UPR-related genes HSPA5, P4HB, and PDIA4 was identified as risk factors while high MAPK8 (JNK1) expression was identified as a protective factor in glioblastoma patients, indicating UPR genes have prognostic potential in this cancer type. Finally, expression of XBP1 and MAPK8, two key downstream targets of the ER sentinel IRE1α, correlates with the presence of immune cell types associated with immunosuppression and a worse patient outcome. This suggests that the expression of these genes is associated with an immunosuppressive tumor microenvironment and uncover a potential link between stress response pathways, tumor microenvironment and glioblastoma patient survival. Conclusions We performed a comprehensive transcriptional characterization of the unfolded protein response in glioblastoma patients and identified UPR-related genes associated with glioblastoma patient survival, providing potential prognostic and predictive biomarkers as well as promising targets for developing new therapeutic interventions in glioblastoma treatment

Additional file 1 of Expression of key unfolded protein response genes predicts patient survival and an immunosuppressive microenvironment in glioblastoma

Additional file 1

Additional file 1 of CD73 mitigates ZEB1 expression in papillary thyroid carcinoma

Additional file 1: Figure S1. NT5E expression across PTC samples and definition of patient groups based on EMT profile. (A) NT5E expression across PTC samples from follicular, classical, and tall cell subtypes. (B) NT5E expression in wild type and BRAF mutated PTC samples. (C) Pearson correlation between the expressions of a mesenchymal and an epithelial signature. The dotted lines represent the cut-off points that divide the patients into 4 groups based on their expressions: one in the correlation line and a second perpendicular to that line. Pearson’s correlation coefficient (r) and p-value (p) are indicated. (D) Expression of a partial-EMT (hybrid state) signature across the defined groups was used to validate the patient separation. * = p ≤ 0.05; **** = p ≤ 0.0001