RESUMO
Estrogen receptor (ER) and progesterone receptor (PR) are two important members of steroid receptors family, an evolutionarily conserved family of transcription factors. Upon binding to their ligands, ER and PR enter cell nucleus to interact with specific DNA element in the context of chromatin to initiate the transcription of diverse target genes, which largely depends on the timely recruitment of a wide range of cofactors. Moreover, the interactions between steroid hormones and their respective receptors also trigger post-translational modifications on these receptors to fine-tune their transcriptional activities. Besides the well-known phosphorylation modifications on tyrosine and serine/threonine residues, recent studies have identified several other covalent modifications, such as ubiquitylation and sumoylation. These post-translational modifications of steroid receptors affect its stability, subcellular localization, and/or cofactor recruitment; eventually influence the duration and extent of transcriptional activation. This review is to focus on the recent research progress on the transcriptional activation of nuclear ER and PR as well as their physiological functions in early pregnancy, which may help us to better understand related female reproductive diseases.
Assuntos
Ativação Transcricional , Ligantes , Fosforilação , Receptores de Estrogênio , Receptores de Progesterona , SumoilaçãoRESUMO
Background: Postoperative recurrence impedes the curability of early-stage hepatocellular carcinoma (E-HCC). We aimed to establish a novel recurrence-related pathological prognosticator with artificial intelligence, and investigate the relationship between pathological features and the local immunological microenvironment. Methods: A total of 576 whole-slide images (WSIs) were collected from 547 patients with E-HCC in the Zhongshan cohort, which was randomly divided into a training cohort and a validation cohort. The external validation cohort comprised 147 Tumor Node Metastasis (TNM) stage I patients from The Cancer Genome Atlas (TCGA) database. Six types of HCC tissues were identified by a weakly supervised convolutional neural network. A recurrence-related histological score (HS) was constructed and validated. The correlation between immune microenvironment and HS was evaluated through extensive immunohistochemical data. Results: The overall classification accuracy of HCC tissues was 94.17%. The C-indexes of HS in the training, validation and TCGA cohorts were 0.804, 0.739 and 0.708, respectively. Multivariate analysis showed that the HS (HR= 4.05, 95% CI: 3.40-4.84) was an independent predictor for recurrence-free survival. Patients in HS high-risk group had elevated preoperative alpha-fetoprotein levels, poorer tumor differentiation and a higher proportion of microvascular invasion. The immunohistochemistry data linked the HS to local immune cell infiltration. HS was positively correlated with the expression level of peritumoral CD14+ cells (p= 0.013), and negatively with the intratumoral CD8+ cells (p< 0.001). Conclusions: The study established a novel histological score that predicted short-term and long-term recurrence for E-HCCs using deep learning, which could facilitate clinical decision making in recurrence prediction and management.