scholarly journals miRNA-Based Therapeutics in the Era of Immune-Checkpoint Inhibitors

2021 ◽  
Vol 14 (2) ◽  
pp. 89
Author(s):  
Florian Huemer ◽  
Michael Leisch ◽  
Roland Geisberger ◽  
Nadja Zaborsky ◽  
Richard Greil

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to complementary target regions on gene transcripts. Thus, miRNAs fine-tune gene expression profiles in a cell-type-specific manner and thereby regulate important cellular functions, such as cell growth, proliferation and cell death. MiRNAs are frequently dysregulated in cancer cells by several mechanisms, which significantly affect the course of the disease. In this review, we summarize the current knowledge on how dysregulated miRNAs contribute to cancer and how miRNAs can be exploited as predictive factors and therapeutic targets, particularly in regard to immune-checkpoint inhibitor therapies.

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2671-2671
Author(s):  
Yan Cheng ◽  
Fumou Sun ◽  
Huojun Cao ◽  
Dongzheng Gai ◽  
Bailu Peng ◽  
...  

Abstract Introduction The development of new treatments for high-risk multiple myeloma (HRMM) are needed. The PD-1/PD-L1 axis is one of the chief inhibitory immune checkpoints in antitumor immunity. Despite the success of PD-1 (PDCD1) / PD-L1 (CD274) blockade in some neoplasms, use of it as a monotherapy has failed to improve outcome in RRMM. We have previously demonstrated that the cell-cycle-regulated serine-threonine kinase, NEK2 is elevated in HRMM and that inhibition of NEK2 can overcome drug-resistance and prolong survival of xenografted MM cells. Here, we aimed to investigate the possible role of NEK2 in regulating the immune checkpoint response in MM and development of possible anti-PD1/PDL1 combination therapies. Methods Gene expression profiles and pathway enrichment analyses were conducted on oligonucleotide microarray gene expression profiles from over 1000 primary MM samples to evaluate the correlation of NEK2 and immune checkpoint expression levels. To elucidate the underlying mechanism, we used Nek2 -/- mice crossed with EμMyc mice to generate B cell tumor mouse model with NEK2 deficiency. RNA-sequencing analyses of premalignant B cells was compared between EμMyc/Nek2 WT and EμMyc/Nek2 -/- mice. The hub molecular regulators in the NEK2 correlated pathways were further determined by western blot using NEK2 overexpressing and knockdown cell lines and then verified by co-immunoprecipitation with a NEK2 antibody. Lastly, to establish its clinic significance, the efficacy of INH1 (small compound NEK2 inhibitor), (D)-PPA 1 (peptide-based PD-1/PD-L1 interaction inhibitor) or a PD-L1 (monoclonal antibody) was tested in bone marrow BM mononuclear cells from primary MM patients in-vitro as well as in MM xenografts. Tumor burden and T cell immune responses were monitored by M-spike and mass cytometry. Results Gene expression profiles demonstrated that CD274 expression was significantly higher in the non-proliferative hyperdiploid (HY) subtype of MM, representing between 25-35% of all MM. NEK2 was negatively correlated with CD274 gene expression across all 7 MM subtypes. Gene set enrichment analysis showed that the IFN-γ signaling pathway, which can induce CD274 expression, was significantly enriched in the HY subtype as well as premalignant B cells from EμMyc/Nek2 -/- mice. Elevated expression of EZH2, a histone methyltransferase gene, is also highly correlated wirth NEK2 levels in primary MM. We found that NEK2 inhibition increases CD274 expression as well as reduced EZH2 expression and H3K27me3 levels in MM cell lines. In contrarst, myeloma cells overexpressing NEK2 showed increased expression and activity of EZH2 and H3K27me3 levels. Thus, NEK2 appears to regulate CD274/PD-L1 expression through EZH2-mediated histone methylation. Next we demonstrated that NEK2 and EZH2 directly interact and that overexpression of NEK2 leads to increased methylation of the CD274/PD-L1 gene. We treated BM mononuclear cells from primary MM with PD-1/PD-L1 inhibitor with and without a NEK2 inhibitor. The combination was most effective at eliminating CD138 + myeloma cells while having no effects on T, B and myeloid cell populations. Conclusion Our study showed that expression of CD274/PD-L1 is suppressed in primary HRMM and that CD274/PD-L1 expression is negatively regulated by NEK2 via EZH2-mediated methylation. Inhibition of NEK2 sensitizes myeloma cells to PD-1/PD-L1 blockade, showing either a synergistic or an additive effect in MM cell cytotoxicity. Disclosures No relevant conflicts of interest to declare.


2013 ◽  
Vol 14 (1) ◽  
pp. 89 ◽  
Author(s):  
Yi Zhong ◽  
Ying-Wooi Wan ◽  
Kaifang Pang ◽  
Lionel ML Chow ◽  
Zhandong Liu

2010 ◽  
Vol 155 (2) ◽  
pp. 881-891 ◽  
Author(s):  
Takayuki Ohnishi ◽  
Hideki Takanashi ◽  
Mirai Mogi ◽  
Hirokazu Takahashi ◽  
Shunsuke Kikuchi ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2436
Author(s):  
Yiming Huang ◽  
Wendy Smith ◽  
Colin Harwood ◽  
Anil Wipat ◽  
Jaume Bacardit

A goal of the biotechnology industry is to be able to recognise detrimental cellular states that may lead to suboptimal or anomalous growth in a bacterial population. Our current knowledge of how different environmental treatments modulate gene regulation and bring about physiology adaptations is limited, and hence it is difficult to determine the mechanisms that lead to their effects. Patterns of gene expression, revealed using technologies such as microarrays or RNA-seq, can provide useful biomarkers of different gene regulatory states indicative of a bacterium’s physiological status. It is desirable to have only a few key genes as the biomarkers to reduce the costs of determining the transcriptional state by opening the way for methods such as quantitative RT-PCR and amplicon panels. In this paper, we used unsupervised machine learning to construct a transcriptional landscape model from condition-dependent transcriptome data, from which we have identified 10 clusters of samples with differentiated gene expression profiles and linked to different cellular growth states. Using an iterative feature elimination strategy, we identified a minimal panel of 10 biomarker genes that achieved 100% cross-validation accuracy in predicting the cluster assignment. Moreover, we designed and evaluated a variety of data processing strategies to ensure our methods were able to generate meaningful transcriptional landscape models, capturing relevant biological processes. Overall, the computational strategies introduced in this study facilitate the identification of a detailed set of relevant cellular growth states, and how to sense them using a reduced biomarker panel.


2020 ◽  
Vol 49 (D1) ◽  
pp. D1413-D1419 ◽  
Author(s):  
Tianyi Zhao ◽  
Shuxuan Lyu ◽  
Guilin Lu ◽  
Liran Juan ◽  
Xi Zeng ◽  
...  

Abstract SC2disease (http://easybioai.com/sc2disease/) is a manually curated database that aims to provide a comprehensive and accurate resource of gene expression profiles in various cell types for different diseases. With the development of single-cell RNA sequencing (scRNA-seq) technologies, uncovering cellular heterogeneity of different tissues for different diseases has become feasible by profiling transcriptomes across cell types at the cellular level. In particular, comparing gene expression profiles between different cell types and identifying cell-type-specific genes in various diseases offers new possibilities to address biological and medical questions. However, systematic, hierarchical and vast databases of gene expression profiles in human diseases at the cellular level are lacking. Thus, we reviewed the literature prior to March 2020 for studies which used scRNA-seq to study diseases with human samples, and developed the SC2disease database to summarize all the data by different diseases, tissues and cell types. SC2disease documents 946 481 entries, corresponding to 341 cell types, 29 tissues and 25 diseases. Each entry in the SC2disease database contains comparisons of differentially expressed genes between different cell types, tissues and disease-related health status. Furthermore, we reanalyzed gene expression matrix by unified pipeline to improve the comparability between different studies. For each disease, we also compare cell-type-specific genes with the corresponding genes of lead single nucleotide polymorphisms (SNPs) identified in genome-wide association studies (GWAS) to implicate cell type specificity of the traits.


2008 ◽  
Vol 29 (5) ◽  
pp. 1363-1374 ◽  
Author(s):  
Takeshi Yoshizaki ◽  
Jill C. Milne ◽  
Takeshi Imamura ◽  
Simon Schenk ◽  
Noriyuki Sonoda ◽  
...  

ABSTRACT SIRT1 is a prominent member of a family of NAD+-dependent enzymes and affects a variety of cellular functions ranging from gene silencing, regulation of the cell cycle and apoptosis, to energy homeostasis. In mature adipocytes, SIRT1 triggers lipolysis and loss of fat content. However, the potential effects of SIRT1 on insulin signaling pathways are poorly understood. To assess this, we used RNA interference to knock down SIRT1 in 3T3-L1 adipocytes. SIRT1 depletion inhibited insulin-stimulated glucose uptake and GLUT4 translocation. This was accompanied by increased phosphorylation of JNK and serine phosphorylation of insulin receptor substrate 1 (IRS-1), along with inhibition of insulin signaling steps, such as tyrosine phosphorylation of IRS-1, and phosphorylation of Akt and ERK. In contrast, treatment of cells with specific small molecule SIRT1 activators led to an increase in glucose uptake and insulin signaling as well as a decrease in serine phosphorylation of IRS-1. Moreover, gene expression profiles showed that SIRT1 expression was inversely related to inflammatory gene expression. Finally, we show that treatment of 3T3-L1 adipocytes with a SIRT1 activator attenuated tumor necrosis factor alpha-induced insulin resistance. Taken together, these data indicate that SIRT1 is a positive regulator of insulin signaling at least partially through the anti-inflammatory actions in 3T3-L1 adipocytes.


Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Jia Wang

Abstract INTRODUCTION Different gene expression profiles are observed in intracranial aneurysm tissue. Understanding these genes and what regulates their expression will help us to understand intracranial aneurysm pathogenesis. We investigated whether there are differences in gene expression in intracranial aneurysms. METHODS A total of 16 intracranial aneurysm tissues were compared with 16 matched samples from the superficial temporal artery as controls. We detected the gene expression profiles in these samples with the Human U133 Plus 2.0 GeneChip. RESULTS A total of 2357 differentially expressed gene transcripts were detected based on the gene expression profile. Verification analysis showed that the VCAM1, MAGI2, PPP2R2B, PPP2R3A genes were associated with the occurrence and development of intracranial aneurysm. These genes mainly encode cell adhesion molecules (CAMs) and ERK/JNK signaling pathways. CONCLUSION Changes of genes expression involved in immune and inflammatory reactions, CAMs may be associated with the development of aneurysms.


Author(s):  
Yuki Fujita ◽  
Toshihide Yamashita

Microglia are resident immune cells in the central nervous system (CNS). Microglia exhibit diversity in their morphology, density, electrophysiological properties, and gene expression profiles, and play various roles in neural development and adulthood in both physiological and pathological conditions. Recent transcriptomic analysis using bulk and single-cell RNA-seq has revealed that microglia can shift their gene expression profiles in various contexts, such as developmental stages, aging, and disease progression in the CNS, suggesting that the heterogeneity of microglia may be associated with their distinct functions. Epigenetic changes, including histone modifications and DNA methylation, coordinate gene expression, thereby contributing to the regulation of cellular state. In this review, we summarize the current knowledge regarding the epigenetic mechanisms underlying spatiotemporal and functional diversity of microglia that are altered in response to developmental stages and disease conditions. We also discuss how this knowledge may lead to advances in therapeutic approaches for diseases.


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