mRNA-based therapeutic strategies for cancer treatment.

In the rapidly evolving landscape of medical research, the emergence of RNA-based therapeutics is paradigm shifting. It is mainly driven by the molecular adaptability and capacity to provide precision in targeting. The coronavirus disease 2019 pandemic crisis underscored the effectiveness of the mRNA therapeutic development platform and brought it to the forefront of RNA-based interventions. These RNA-based therapeutic approaches can reshape gene expression, manipulate cellular functions, and correct the aberrant molecular processes underlying various diseases. The new technologies hold the potential to engineer and deliver tailored therapeutic agents to tackle genetic disorders, cancers, and infectious diseases in a highly personalized and precisely tuned manner. The review discusses the most recent advancements in the field of mRNA therapeutics for cancer treatment, with a focus on the features of the most utilized RNA-based therapeutic interventions, current pre-clinical and clinical developments, and the remaining challenges in delivery strategies, effectiveness, and safety considerations.

Convulsive Syncope as a Complication of Outpatient Procedures: A Case Series and Review of the Literature.

ABSTRACT: Sports medicine providers often perform various outpatient procedures to manage musculoskeletal and neuropathic conditions. Vasovagal syncope is a rare but a possible complication. Convulsive syncope is one subtype that involves brief extensor stiffening and nonsustained myoclonus and can be easily mistaken for seizures. We present a case series of convulsive syncope as a complication of common sports medicine outpatient procedures. We aim to describe how to identify this condition, and offer risk stratification and management strategies to mitigate the risks of this complication. Sports medicine providers who routinely practice outpatient procedures should be aware of this complication. Simple changes in approaching the procedure may mitigate these risks. High- and intermediate-risk features of the syncopal episode should prompt physicians to seek further evaluation by a specialist to rule out more serious conditions. In all instances, appropriate on-site support and equipment for emergent resuscitation and management should be prepared.

RNA deadenylation complexes in development and diseases.

RNA deadenylation, the process of shortening of the 3' poly(A) tail of an RNA molecule, is one of the key steps of post-transcriptional regulation of gene expression in eukaryotic cells. PAN2/3 and CCR4-NOT (CNOT) are the two dominant RNA deadenylation complexes, which play central roles in mediating mRNA decay and translation. While degradation is the final fate of virtually all RNAs in their life cycles, selection of RNA targets as well as control of the rate and timing of RNA decay, in coordination with other molecular pathways, including translation, can be modulated in certain contexts. Such regulation influences cell growth, proliferation, and differentiation at the cellular level; and contributes to establish polarity and regulate signaling at the tissue level. Dysregulation of deadenylation processes have also been implicated in human diseases ranging from cardiac diseases and neurodevelopmental disorders to cancers. In this review, we will discuss mechanisms of gene expression control mediated by the RNA deadenylation complexes and highlight relevant evidence supporting the emerging roles of RNA deadenylation and its regulatory proteins during development and in diseases. A systemic understanding of these mechanisms will be a critical foundation for development of effective strategies to therapeutically target them.

Non-contrast computed tomography features predict intraventricular hemorrhage growth.

OBJECTIVES: Non-contrast computed tomography (NCCT) markers are robust predictors of parenchymal hematoma expansion in intracerebral hemorrhage (ICH). We investigated whether NCCT features can also identify ICH patients at risk of intraventricular hemorrhage (IVH) growth. METHODS: Patients with acute spontaneous ICH admitted at four tertiary centers in Germany and Italy were retrospectively included from January 2017 to June 2020. NCCT markers were rated by two investigators for heterogeneous density, hypodensity, black hole sign, swirl sign, blend sign, fluid level, island sign, satellite sign, and irregular shape. ICH and IVH volumes were semi-manually segmented. IVH growth was defined as IVH expansion > 1 mL (eIVH) or any delayed IVH (dIVH) on follow-up imaging. Predictors of eIVH and dIVH were explored with multivariable logistic regression. Hypothesized moderators and mediators were independently assessed in PROCESS macro models. RESULTS: A total of 731 patients were included, of whom 185 (25.31%) suffered from IVH growth, 130 (17.78%) had eIVH, and 55 (7.52%) had dIVH. Irregular shape was significantly associated with IVH growth (OR 1.68; 95%CI [1.16-2.44]; p = 0.006). In the subgroup analysis stratified by the IVH growth type, hypodensities were significantly associated with eIVH (OR 2.06; 95%CI [1.48-2.64]; p = 0.015), whereas irregular shape (OR 2.72; 95%CI [1.91-3.53]; p = 0.016) in dIVH. The association between NCCT markers and IVH growth was not mediated by parenchymal hematoma expansion. CONCLUSIONS: NCCT features identified ICH patients at a high risk of IVH growth. Our findings suggest the possibility to stratify the risk of IVH growth with baseline NCCT and might inform ongoing and future studies. CLINICAL RELEVANCE STATEMENT: Non-contrast CT features identified ICH patients at a high risk of intraventricular hemorrhage growth with subtype-specific differences. Our findings may assist in the risk stratification of intraventricular hemorrhage growth with baseline CT and might inform ongoing and future clinical studies. KEY POINTS: • NCCT features identified ICH patients at a high risk of IVH growth with subtype-specific differences. • The effect of NCCT features was not moderated by time and location or indirectly mediated by hematoma expansion. • Our findings may assist in the risk stratification of IVH growth with baseline NCCT and might inform ongoing and future studies.

Histone-binding of DPF2 mediates its repressive role in myeloid differentiation.

Double plant homeodomain finger 2 (DPF2) is a highly evolutionarily conserved member of the d4 protein family that is ubiquitously expressed in human tissues and was recently shown to inhibit the myeloid differentiation of hematopoietic stem/progenitor and acute myelogenous leukemia cells. Here, we present the crystal structure of the tandem plant homeodomain finger domain of human DPF2 at 1.6-Å resolution. We show that DPF2 interacts with the acetylated tails of both histones 3 and 4 via bipartite binding pockets on the DPF2 surface. Blocking these interactions through targeted mutagenesis of DPF2 abolishes its recruitment to target chromatin regions as well as its ability to prevent myeloid differentiation in vivo. Our findings suggest that the histone binding of DPF2 plays an important regulatory role in the transcriptional program that drives myeloid differentiation.

The relationship between population growth and precipitation change in some regions across Vietnam: implications for urbanization effect.

According to a review of numerous publications and scientific reports, the effects of urbanization on urban climate are of greatest concern. This study aims to evaluate the impact of urbanization focusing on population growth on precipitation trends in 11 provinces across Vietnam during the period 2008-2018 by identifying the relationship between population growth and precipitation change. Regression analysis is used to determine the trends of precipitation and population growth. Precipitation maps and graphs show the overall precipitation trends, changes, and patterns in past decades. Overall, population growth tends to correlate with precipitation change trends. Furthermore, the type of region groups (countryside region, small city, or medium city) also plays a crucial role in determining the magnitude of the change in precipitation trends for each region. This further lends credibility to the notion that urbanization contributes to changes in precipitation trends.

Translation efficiency driven by CNOT3 subunit of the CCR4-NOT complex promotes leukemogenesis.

Protein synthesis is frequently deregulated during tumorigenesis. However, the precise contexts of selective translational control and the regulators of such mechanisms in cancer is poorly understood. Here, we uncovered CNOT3, a subunit of the CCR4-NOT complex, as an essential modulator of translation in myeloid leukemia. Elevated CNOT3 expression correlates with unfavorable outcomes in patients with acute myeloid leukemia (AML). CNOT3 depletion induces differentiation and apoptosis and delayed leukemogenesis. Transcriptomic and proteomic profiling uncovers c-MYC as a critical downstream target which is translationally regulated by CNOT3. Global analysis of mRNA features demonstrates that CNOT3 selectively influences expression of target genes in a codon usage dependent manner. Furthermore, CNOT3 associates with the protein network largely consisting of ribosomal proteins and translation elongation factors in leukemia cells. Overall, our work elicits the direct requirement for translation efficiency in tumorigenesis and propose targeting the post-transcriptional circuitry via CNOT3 as a therapeutic vulnerability in AML.

Affinity-based proteomics reveal cancer-specific networks coordinated by Hsp90.

Most cancers are characterized by multiple molecular alterations, but identification of the key proteins involved in these signaling pathways is currently beyond reach. We show that the inhibitor PU-H71 preferentially targets tumor-enriched Hsp90 complexes and affinity captures Hsp90-dependent oncogenic client proteins. We have used PU-H71 affinity capture to design a proteomic approach that, when combined with bioinformatic pathway analysis, identifies dysregulated signaling networks and key oncoproteins in chronic myeloid leukemia. The identified interactome overlaps with the well-characterized altered proteome in this cancer, indicating that this method can provide global insights into the biology of individual tumors, including primary patient specimens. In addition, we show that this approach can be used to identify previously uncharacterized oncoproteins and mechanisms, potentially leading to new targeted therapies. We further show that the abundance of the PU-H71-enriched Hsp90 species, which is not dictated by Hsp90 expression alone, is predictive of the cell's sensitivity to Hsp90 inhibition.

RNA modifications in hematological malignancies.

RNA modifications play an important role in various cancers including blood cancers by controlling gene expression programs critical for survival, proliferation and differentiation of cancer cells. While hundreds of RNA modifications have been identified, many have not been functionally characterized. With development of enabling technologies to identify and map RNA modifications, tremendous advancement has been made in our understanding of the biological functions of these molecular markers in diverse cellular contexts. In the last 5 years, N6-methyladenosine (m6A), the most prevalent internal mRNA modification, has been extensively implicated in many facets of leukemogenesis. Other types of RNA modifications are also involved in the regulation of cell fate decisions and tumorigenesis. Here, we summarize existing knowledge and recent discoveries regarding the role of RNA modifications in leukemia. We choose to highlight cutting-edge techniques to characterize and profile RNA modifications while discussing critical functions of key modifiers and regulatory mechanisms in the pathogenesis of hematological malignancies and touch on therapeutic strategies targeting RNA modifications. These important advancements in the field will continue to foster a strong foundation for the development of innovative treatments for hematological malignancies.

Deep Generative Learning Models for Cloud Intrusion Detection Systems.

Intrusion detection (ID) on the cloud environment has received paramount interest over the last few years. Among the latest approaches, machine learning-based ID methods allow us to discover unknown attacks. However, due to the lack of malicious samples and the rapid evolution of diverse attacks, constructing a cloud ID system (IDS) that is robust to a wide range of unknown attacks remains challenging. In this article, we propose a novel solution to enable robust cloud IDSs using deep neural networks. Specifically, we develop two deep generative models to synthesize malicious samples on the cloud systems. The first model, conditional denoising adversarial autoencoder (CDAAE), is used to generate specific types of malicious samples. The second model (CDAEE-KNN) is a hybrid of CDAAE and the K -nearest neighbor algorithm to generate malicious borderline samples that further improve the accuracy of a cloud IDS. The synthesized samples are merged with the original samples to form the augmented datasets. Three machine learning algorithms are trained on the augmented datasets and their effectiveness is analyzed. The experiments conducted on four popular IDS datasets show that our proposed techniques significantly improve the accuracy of the cloud IDSs compared with the baseline technique and the state-of-the-art approaches. Moreover, our models also enhance the accuracy of machine learning algorithms in detecting some currently challenging distributed denial of service (DDoS) attacks, including low-rate DDoS attacks and application layer DDoS attacks.

miR-148a-3p and DDX6 functional link promotes survival of myeloid leukemia cells.

Regulation of gene expression at the RNA level is an important regulatory mechanism in cancer. However, posttranscriptional molecular pathways underlying tumorigenesis remain largely unexplored. In this study, we uncovered a functional axis consisting of microRNA (miR)-148a-3p, RNA helicase DDX6, and its downstream target thioredoxin-interacting protein (TXNIP) in acute myeloid leukemia (AML). Using a DROSHA-knockout cell system to evaluate miR-mediated gene expression control, we comprehensively profiled putative transcripts regulated by miR-148a-3p and identified DDX6 as a direct target of miR-148a-3p in AML cells. DDX6 depletion induced cell cycle arrest, apoptosis, and differentiation, although delaying leukemia development in vivo. Genome-wide assessment of DDX6-binding transcripts and gene expression profiling of DDX6-depleted cells revealed TXNIP, a tumor suppressor, as the functional downstream target of DDX6. Overall, our study identified DDX6 as a posttranscriptional regulator that is required for AML survival. We proposed the regulatory link between miR-148a-3p and DDX6 as a potential therapeutic target in leukemia.

Multilesion Segmentations in Patients with Intracerebral Hemorrhage: Reliability of ICH, IVH and PHE Masks.

Background and Purpose: Fully automated methods for segmentation and volume quantification of intraparenchymal hemorrhage (ICH), intraventricular hemorrhage extension (IVH), and perihematomal edema (PHE) are gaining increasing interest. Yet, reliabilities demonstrate considerable variances amongst each other. Our aim was therefore to evaluate both the intra- and interrater reliability of ICH, IVH and PHE on ground-truth segmentation masks. Methods: Patients with primary spontaneous ICH were retrospectively included from a German tertiary stroke center (Charité Berlin; January 2016−June 2020). Baseline and follow-up non-contrast Computed Tomography (NCCT) scans were analyzed for ICH, IVH, and PHE volume quantification by two radiology residents. Raters were blinded to all demographic and outcome data. Inter- and intrarater agreements were determined by calculating the Intraclass Correlation Coefficient (ICC) for a randomly selected set of patients with ICH, IVH, and PHE. Results: 100 out of 670 patients were included in the analysis. Interrater agreements ranged from an ICC of 0.998 for ICH (95% CI [0.993; 0.997]), to an ICC of 0.979 for IVH (95% CI [0.984; 0.993]), and an ICC of 0.886 for PHE (95% CI [0.760; 0.938]), all p-values < 0.001. Intrarater agreements ranged from an ICC of 0.997 for ICH (95% CI [0.996; 0.998]), to an ICC of 0.995 for IVH (95% CI [0.992; 0.996]), and an ICC of 0.980 for PHE (95% CI [0.971; 0.987]), all p-values < 0.001. Conclusion Manual segmentations of ICH, IVH, and PHE demonstrate good-to-excellent inter- and intrarater reliabilities, with the highest agreement for ICH and IVH and lowest for PHE. Therefore, the degree of variances reported in fully automated quantification methods might be related amongst others to variances in ground-truth masks.

A target discovery pipeline identified ILT3 as a target for immunotherapy of multiple myeloma.

Multiple myeloma (MM) is an incurable malignancy of plasma cells. To identify targets for MM immunotherapy, we develop an integrated pipeline based on mass spectrometry analysis of seven MM cell lines and RNA sequencing (RNA-seq) from 900+ patients. Starting from 4,000+ candidates, we identify the most highly expressed cell surface proteins. We annotate candidate protein expression in many healthy tissues and validate the expression of promising targets in 30+ patient samples with relapsed/refractory MM, as well as in primary healthy hematopoietic stem cells and T cells by flow cytometry. Six candidates (ILT3, SEMA4A, CCR1, LRRC8D, FCRL3, IL12RB1) and B cell maturation antigen (BCMA) present the most favorable profile in malignant and healthy cells. We develop a bispecific T cell engager targeting ILT3 that shows potent killing effects in vitro and decreased tumor burden and prolonged mice survival in vivo, suggesting therapeutic relevance. Our study uncovers MM-associated antigens that hold great promise for immune-based therapies of MM.

RNA binding protein SYNCRIP maintains proteostasis and self-renewal of hematopoietic stem and progenitor cells.

Tissue homeostasis is maintained after stress by engaging and activating the hematopoietic stem and progenitor compartments in the blood. Hematopoietic stem cells (HSCs) are essential for long-term repopulation after secondary transplantation. Here, using a conditional knockout mouse model, we revealed that the RNA-binding protein SYNCRIP is required for maintenance of blood homeostasis especially after regenerative stress due to defects in HSCs and progenitors. Mechanistically, we find that SYNCRIP loss results in a failure to maintain proteome homeostasis that is essential for HSC maintenance. SYNCRIP depletion results in increased protein synthesis, a dysregulated epichaperome, an accumulation of misfolded proteins and induces endoplasmic reticulum stress. Additionally, we find that SYNCRIP is required for translation of CDC42 RHO-GTPase, and loss of SYNCRIP results in defects in polarity, asymmetric segregation, and dilution of unfolded proteins. Forced expression of CDC42 recovers polarity and in vitro replating activities of HSCs. Taken together, we uncovered a post-transcriptional regulatory program that safeguards HSC self-renewal capacity and blood homeostasis.

Learning Latent Representation for IoT Anomaly Detection.

Internet of Things (IoT) has emerged as a cutting-edge technology that is changing human life. The rapid and widespread applications of IoT, however, make cyberspace more vulnerable, especially to IoT-based attacks in which IoT devices are used to launch attack on cyber-physical systems. Given a massive number of IoT devices (in order of billions), detecting and preventing these IoT-based attacks are critical. However, this task is very challenging due to the limited energy and computing capabilities of IoT devices and the continuous and fast evolution of attackers. Among IoT-based attacks, unknown ones are far more devastating as these attacks could surpass most of the current security systems and it takes time to detect them and "cure" the systems. To effectively detect new/unknown attacks, in this article, we propose a novel representation learning method to better predictively "describe" unknown attacks, facilitating supervised learning-based anomaly detection methods. Specifically, we develop three regularized versions of autoencoders (AEs) to learn a latent representation from the input data. The bottleneck layers of these regularized AEs trained in a supervised manner using normal data and known IoT attacks will then be used as the new input features for classification algorithms. We carry out extensive experiments on nine recent IoT datasets to evaluate the performance of the proposed models. The experimental results demonstrate that the new latent representation can significantly enhance the performance of supervised learning methods in detecting unknown IoT attacks. We also conduct experiments to investigate the characteristics of the proposed models and the influence of hyperparameters on their performance. The running time of these models is about 1.3 ms that is pragmatic for most applications.

m6A RNA modifications: Key regulators of normal and malignant hematopoiesis.

Post-transcriptional RNA modifications determine RNA fate by influencing numerous processes such as translation, decay and localization. One of the most abundant RNA modifications is N6-methyladenoside (m6A), which has been shown to be important in healthy as well as malignant hematopoiesis. Several proteins representing key players in m6A RNA biology, such as m6A writers, erasers and readers, were recently reported to be essential for hematopoietic stem cell (HSC) function. In leukemia, expression of m6A regulators has been shown to be increased, opening up potential opportunities for therapeutic exploitation by targeting them in blood malignancies. These recent discoveries were the focus of the Fall 2021 International Society for Experimental Hematology New Investigators webinar. We review here the latest findings in the field of mRNA modifications in normal and malignant hematopoiesis and how this might open up novel therapeutic options.

Diagnostic Accuracy and Reliability of Noncontrast Computed Tomography Markers for Acute Hematoma Expansion among Radiologists.

BACKGROUND: Noncontrast Computed Tomography (NCCT) features are promising markers for acute hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH). It remains unclear whether accurate identification of these markers is also reliable in raters with different levels of experience. METHODS: Patients with acute spontaneous ICH admitted at four tertiary centers in Germany and Italy were retrospectively included from January 2017 to June 2020. In total, nine NCCT markers were rated by one radiology resident, one radiology fellow, and one neuroradiology fellow with different levels experience in ICH imaging. Interrater reliabilities of the resident and radiology fellow were evaluated by calculated Cohen's kappa (κ) statistics in reference to the neuroradiology fellow who was referred as the gold standard. Gold-standard ratings were evaluated by calculated interrater κ statistics. Global interrater reliabilities were evaluated by calculated Fleiss kappa statistics across all three readers. A comparison of receiver operating characteristics (ROCs) was used to evaluate differences in the diagnostic accuracy for predicting acute hematoma expansion (HE) among the raters. RESULTS: Substantial-to-almost-perfect interrater concordance was found for the resident with interrater Cohen's kappa from 0.70 (95% CI 0.65-0.81) to 0.96 (95% CI 0.94-0.98). The interrater Cohen's kappa for the radiology fellow was moderate to almost perfect and ranged from 0.58 (95% CI 0.52-0.65) to 94 (95% CI 92-0.97). The intrarater gold-standard Cohen's kappa was almost perfect and ranged from 0.79 (95% CI 0.78-0.90) to 0.98 (95% CI 0.78-0.90). The global interrater Fleiss kappa ranged from 0.62 (95%CI 0.57-0.66) to 0.93 (95%CI 0.89-0.97). The diagnostic accuracy for the prediction of acute hematoma expansion (HE) was different for the island sign and fluid sign, with p-values < 0.05. CONCLUSION: The NCCT markers had a substantial-to-almost-perfect interrater agreement among raters with different levels of experience. Differences in the diagnostic accuracy for the prediction of acute HE were found in two out of nine NCCT markers. The study highlights the promising utility of NCCT markers for acute HE prediction.

Transcriptional control of CBX5 by the RNA binding proteins RBMX and RBMXL1 maintains chromatin state in myeloid leukemia.

RNA binding proteins (RBPs) are key arbiters of post-transcriptional regulation and are found to be found dysregulated in hematological malignancies. Here, we identify the RBP RBMX and its retrogene RBMXL1 to be required for murine and human myeloid leukemogenesis. RBMX/L1 are overexpressed in acute myeloid leukemia (AML) primary patients compared to healthy individuals, and RBMX/L1 loss delayed leukemia development. RBMX/L1 loss lead to significant changes in chromatin accessibility, as well as chromosomal breaks and gaps. We found that RBMX/L1 directly bind to mRNAs, affect transcription of multiple loci, including CBX5 (HP1α), and control the nascent transcription of the CBX5 locus. Forced CBX5 expression rescued the RBMX/L1 depletion effects on cell growth and apoptosis. Overall, we determine that RBMX/L1 control leukemia cell survival by regulating chromatin state through their downstream target CBX5. These findings identify a mechanism for RBPs directly promoting transcription and suggest RBMX/L1, as well as CBX5, as potential therapeutic targets in myeloid malignancies.

Introductions to the Community: Early-Career Researchers in the Time of COVID-19.

COVID-19 has unfortunately halted lab work, conferences, and in-person networking, which is especially detrimental to researchers just starting their labs. Through social media and our reviewer networks, we met some early-career stem cell investigators impacted by the closures. Here, they introduce themselves and their research to our readers.