Trisenox Disrupts MDM2-DAXX-HAUSP Complex and Induces Apoptosis in a Mouse Model of Acute Leukemia

Trappc1 deficiency impairs thymic epithelial cell development by breaking endoplasmic reticulum homeostasis

Thymic epithelial cells (TECs) are important for T cell development and immune tolerance establishment. Although comprehensive molecular regulation of TEC development has been studied, the role of transport protein particle complexes (Trappcs) in TECs is not clear. Using TEC-specific homozygous or heterozygous Trappc1 deleted mice model, we found that Trappc1 deficiency caused severe thymus atrophy with decreased cell number and blocked maturation of TECs. Mice with a TEC-specific Trappc1 deletion show poor thymic T cell output and have a greater percentage of activated/memory T cells, suffered from spontaneous autoimmune disorders. Our RNA-seq and molecular studies indicated that the decreased endoplasmic reticulum (ER) and Golgi apparatus, enhanced unfolded protein response (UPR) and subsequent Atf4-CHOP-mediated apoptosis, and reactive oxygen species (ROS)-mediated ferroptosis coordinately contributed to the reduction of Trappc1-deleted TECs. Additionally, reduced Aire⁺ mTECs accompanied by the decreased expression of Irf4, Irf8, and Tbx21 in Trappc1 deficiency mTECs, may further coordinately block the tissue-restricted antigen expression. In this study, we reveal that Trappc1 plays an indispensable role in TEC development and maturation and provide evidence for the importance of inter-organelle traffic and ER homeostasis in TEC development. This article is protected by copyright. All rights reserved.

Identification of the integrated prognostic signature associated with immuno-relevant genes and long non-coding RNAs in acute myeloid leukemia

BACKGROUND

Like other cancers, considerable effort has been made in acute myeloid leukemia (AML) to identify prognostic genes and long non-coding RNAs (lncRNAs) with their potential clinical applications. However, to date, no integrated prognostic model has been developed that combines both gene expression and lncRNAs as a singular approach in AML.

METHOD

Comprehensive bioinformatic approaches (Weighted gene co-expression network analysis, Univariate Cox regression analyses, Pearson correlation, LASSO-Cox regression, Wilcoxon test) were used to construct the signature and to define high- and low-risk groups in AML datasets. ESTIMATE and CIBERSORT algorithms were applied to investigate the potential impact of infiltrating immune cells based on the obtained signature in tumor microenvironment. In addition, gene ontology (GO) and KEGG enrichment were applied to explore the potential function of the signature.

RESULTS

Herein, we focused on immune-related genes (IRGs) and immune-related long non-coding RNAs (IRlncRNAs) and constructed an integrated prognostic immunorelevant signature in AML. The obtained signature exhibit five IRGs (DAXX, PSMB8, CSRP1, RAC2 and PTPN6) and one IRlncRNA (AC080037.2), and is strictly associated with age and FAB (French-American-British classification). Importantly, the high-risk AML group (defined by the signature) correlated positively with three types of scores (immune score, stroma score, and ESTIMATE score). We also identified a few immune cells (resting mast cells and monocytes) potentially involved in the correlation between signature and survival of AML patients. The prognostic ability of the obtained signature was tested in the training cohort and then validated in both test and total cohorts. The pathway enrichment analysis confirmed the possible immune- related role of the signature.

CONCLUSION

We constructed an integrated prognostic signature comprising five immune-related protein-coding genes (IRPCG) (DAXX, PSMB8, CSRP1, RAC2, and PTPN6) and one immune-related lncRNA (AC080037.2) that may serve as potential biomarkers for predicting survival and further stratifying AML patients.