Deficiency of metabolic regulator PKM2 activates the pentose phosphate pathway and generates TCF1+ progenitor CD8+ T cells to improve checkpoint blockade.

TCF1high progenitor CD8+ T cells mediate the efficacy of PD-1 blockade, however the mechanisms that govern their generation and maintenance are poorly understood. Here, we show that targeting glycolysis through deletion of pyruvate kinase muscle 2 (PKM2) results in elevated pentose phosphate pathway (PPP) activity, leading to enrichment of a TCF1high central memory-like phenotype and increased responsiveness to PD-1 blockade in vivo. PKM2KO CD8+ T cells showed reduced glycolytic flux, accumulation of glycolytic intermediates and PPP metabolites, and increased PPP cycling as determined by 1,2 13C glucose carbon tracing. Small molecule agonism of the PPP without acute glycolytic impairment skewed CD8+ T cells towards a TCF1high population, generated a unique transcriptional landscape, enhanced tumor control in mice in combination with PD-1 blockade, and promoted tumor killing in patient-derived tumor organoids. Our study demonstrates a new metabolic reprogramming that contributes to a progenitor-like T cell state amenable to checkpoint blockade.

Endothelial cell-leukemia interactions remodel drug responses, uncovering T-ALL vulnerabilities.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive and often incurable disease. To uncover therapeutic vulnerabilities, we first developed T-ALL patient-derived tumor xenografts (PDXs) and exposed PDX cells to a library of 433 clinical-stage compounds in vitro. We identified 39 broadly active drugs with antileukemia activity. Because endothelial cells (ECs) can alter drug responses in T-ALL, we developed an EC/T-ALL coculture system. We found that ECs provide protumorigenic signals and mitigate drug responses in T-ALL PDXs. Whereas ECs broadly rescued several compounds in most models, for some drugs the rescue was restricted to individual PDXs, suggesting unique crosstalk interactions and/or intrinsic tumor features. Mechanistically, cocultured T-ALL cells and ECs underwent bidirectional transcriptomic changes at the single-cell level, highlighting distinct "education signatures." These changes were linked to bidirectional regulation of multiple pathways in T-ALL cells as well as in ECs. Remarkably, in vitro EC-educated T-ALL cells transcriptionally mirrored ex vivo splenic T-ALL at single-cell resolution. Last, 5 effective drugs from the 2 drug screenings were tested in vivo and shown to effectively delay tumor growth and dissemination thus prolonging overall survival. In sum, we developed a T-ALL/EC platform that elucidated leukemia-microenvironment interactions and identified effective compounds and therapeutic vulnerabilities.

Assessing the involvement of the placental microbiome and virome in preeclampsia using non coding RNA sequencing.

OBJECTIVES: Preeclampsia is a dangerous pregnancy complication. The source of preeclampsia is unknown, though the placenta is believed to have a central role in its pathogenesis. An association between maternal infection and preeclampsia has been demonstrated, yet the involvement of the placental microbiome in the etiology of preeclampsia has not been determined. In this study, we examined whether preeclampsia is associated with an imbalanced microorganism composition in the placenta. METHODS: To this end, we developed a novel method for the identification of bacteria/viruses based on sequencing of small non-coding RNA, which increases the microorganism-to-host ratio, this being a major challenge in microbiome methods. We validated the method on various infected tissues and demonstrated its efficiency in detecting microorganisms in samples with extremely low bacterial/viral biomass. We then applied the method to placenta specimens from preeclamptic and healthy pregnancies. Since the placenta is a remarkably large and heterogeneous organ, we explored the bacterial and viral RNA at each of 15 distinct locations. RESULTS: Bacterial RNA was detected at all locations and was consistent with previous studies of the placental microbiome, though without significant differences between the preeclampsia and control groups. Nevertheless, the bacterial RNA composition differed significantly between various areas of the placenta. Viral RNA was detected in extremely low quantities, below the threshold of significance, thus viral abundance could not be determined. CONCLUSIONS: Our results suggest that the bacterial and viral abundance in the placenta may have only limited involvement in the pathogenesis of preeclampsia. The evidence of a heterogenic bacterial RNA composition in the various placental locations warrants further investigation to capture the true nature of the placental microbiome.

A Novel JAK1 Mutant Breast Implant-Associated Anaplastic Large Cell Lymphoma Patient-Derived Xenograft Fostering Pre-Clinical Discoveries.

Breast implant-associated lymphoma (BIA-ALCL) has recently been recognized as an independent peripheral T-cell lymphoma (PTCL) entity. In this study, we generated the first BIA-ALCL patient-derived tumor xenograft (PDTX) model (IL89) and a matching continuous cell line (IL89_CL#3488) to discover potential vulnerabilities and druggable targets. We characterized IL89 and IL89_CL#3488, both phenotypically and genotypically, and demonstrated that they closely resemble the matching human primary lymphoma. The tumor content underwent significant enrichment along passages, as confirmed by the increased variant allele frequency (VAF) of mutations. Known aberrations (JAK1 and KMT2C) were identified, together with novel hits, including PDGFB, PDGFRA, and SETBP1. A deep sequencing approach allowed the detection of mutations below the Whole Exome Sequencing (WES) sensitivity threshold, including JAK1G1097D, in the primary sample. RNA sequencing confirmed the expression of a signature of differentially expressed genes in BIA-ALCL. Next, we tested IL89's sensitivity to the JAK inhibitor ruxolitinib and observed a potent anti-tumor effect, both in vitro and in vivo. We also implemented a high-throughput drug screening approach to identify compounds associated with increased responses in the presence of ruxolitinib. In conclusion, these new IL89 BIA-ALCL models closely recapitulate the primary correspondent lymphoma and represent an informative platform for dissecting the molecular features of BIA-ALCL and performing pre-clinical drug discovery studies, fostering the development of new precision medicine approaches.

Early diagnosis of gestational diabetes mellitus using circulating microRNAs.

DESIGN: Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and its prevalence is constantly rising worldwide. Diagnosis is commonly in the late second or early third trimester of pregnancy, though the development of GDM starts early; hence, first-trimester diagnosis is feasible. OBJECTIVE: Our objective was to identify microRNAs that best distinguish GDM samples from those of healthy pregnant women and to evaluate the predictive value of microRNAs for GDM detection in the first trimester. METHODS: We investigated the abundance of circulating microRNAs in the plasma of pregnant women in their first trimester. Two populations were included in the study to enable population-specific as well as cross-population inspection of expression profiles. Each microRNA was tested for differential expression in GDM vs control samples, and their efficiency for GDM detection was evaluated using machine-learning models. RESULTS: Two upregulated microRNAs (miR-223 and miR-23a) were identified in GDM vs the control set, and validated on a new cohort of women. Using both microRNAs in a logistic-regression model, we achieved an AUC value of 0.91. We further demonstrated the overall predictive value of microRNAs using several types of multivariable machine-learning models that included the entire set of expressed microRNAs. All models achieved high accuracy when applied on the dataset (mean AUC = 0.77). The significance of the classification results was established via permutation tests. CONCLUSIONS: Our findings suggest that circulating microRNAs are potential biomarkers for GDM in the first trimester. This warrants further examination and lays the foundation for producing a novel early non-invasive diagnostic tool for GDM.

Characterization of MicroRNA and Gene Expression Profiles Following Ricin Intoxication.

Ricin, derived from the castor bean plant, is a highly potent toxin, classified as a potential bioterror agent. Current methods for early detection of ricin poisoning are limited in selectivity. MicroRNAs (miRNAs), which are naturally occurring, negative gene expression regulators, are known for their tissue specific pattern of expression and their stability in tissues and blood. While various approaches for ricin detection have been investigated, miRNAs remain underexplored. We evaluated the effect of pulmonary exposure to ricin on miRNA expression profiles in mouse lungs and peripheral blood mononuclear cells (PBMCs). Significant changes in lung tissue miRNA expression levels were detected following ricin intoxication, specifically regarding miRNAs known to be involved in innate immunity pathways. Transcriptome analysis of the same lung tissues revealed activation of several immune regulation pathways and immune cell recruitment. Our work contributes to the understanding of the role of miRNAs and gene expression in ricin intoxication.

Early Detection of Preeclampsia Using Circulating Small non-coding RNA.

Preeclampsia is one of the most dangerous pregnancy complications, and the leading cause of maternal and perinatal mortality and morbidity. Although the clinical symptoms appear late, its origin is early, and hence detection is feasible already at the first trimester. In the current study, we investigated the abundance of circulating small non-coding RNAs in the plasma of pregnant women in their first trimester, seeking transcripts that best separate the preeclampsia samples from those of healthy pregnant women. To this end, we performed small non-coding RNAs sequencing of 75 preeclampsia and control samples, and identified 25 transcripts that were differentially expressed between preeclampsia and the control groups. Furthermore, we utilized those transcripts and created a pipeline for a supervised classification of preeclampsia. Our pipeline generates a logistic regression model using a 5-fold cross validation on numerous random partitions into training and blind test sets. Using this classification procedure, we achieved an average AUC value of 0.86. These findings suggest the predictive value of circulating small non-coding RNA in the first trimester, warranting further examination, and lay the foundation for producing a novel early non-invasive diagnostic tool for preeclampsia, which could reduce the life-threatening risk for both the mother and fetus.

Deep sequencing analysis of viral infection and evolution allows rapid and detailed characterization of viral mutant spectrum.

MOTIVATION: The study of RNA virus populations is a challenging task. Each population of RNA virus is composed of a collection of different, yet related genomes often referred to as mutant spectra or quasispecies. Virologists using deep sequencing technologies face major obstacles when studying virus population dynamics, both experimentally and in natural settings due to the relatively high error rates of these technologies and the lack of high performance pipelines. In order to overcome these hurdles we developed a computational pipeline, termed ViVan (Viral Variance Analysis). ViVan is a complete pipeline facilitating the identification, characterization and comparison of sequence variance in deep sequenced virus populations. RESULTS: Applying ViVan on deep sequenced data obtained from samples that were previously characterized by more classical approaches, we uncovered novel and potentially crucial aspects of virus populations. With our experimental work, we illustrate how ViVan can be used for studies ranging from the more practical, detection of resistant mutations and effects of antiviral treatments, to the more theoretical temporal characterization of the population in evolutionary studies. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.vivanbioinfo.org CONTACT: : nshomron@post.tau.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The possible involvement of microRNAs in preeclampsia and gestational diabetes mellitus.

Great obstetrical syndromes is a collective name for several complications of pregnancy that affect >15% of pregnancies. They may confer adverse pregnancy outcomes and maternal and fetal morbidity, and require close medical monitoring and treatment. The etiology, pathogenesis, and outcome of these syndromes are obscure in the majority of cases. All appear during mid-to-late pregnancy with no reliable biomarkers for early detection and possibly prevention at present. This article focuses on the quest for early reliable markers for preeclampsia and gestational diabetes mellitus (GDM) development, mainly on the involvement of microRNA in the pathogenesis and its possible role as an early biomarker for disease development.