Radioprotective effectiveness of a novel delta-tocotrienol prodrug on mouse hematopoietic system against 60Co gamma-ray irradiation through inducing granulocyte-colony stimulating factor production.

Considering the increasing risk of nuclear attacks worldwide, the development of develop potent and safe radioprotective agents for nuclear emergencies is urgently needed. γ-tocotrienol (GT3) and δ-tocotrienol (DT3) have demonstrated a potent radioprotective effect by inducing the production of granulocyte-colony stimulating factor (G-CSF) in vivo. However, their application is limited because of their low bioavailability. The utilization of ester prodrugs can be an effective strategy for modifying the pharmacokinetic properties of drug molecules. In this study, we initially confirmed that DT3 exhibited the most significant potential for inducing G-CSF effects among eight natural vitamin E homologs. Consequently, we designed and synthesized a series of DT3 ester and ether derivatives, leading to improved radioprotective effects. The metabolic study conducted in vitro and in vivo has identified DT3 succinate 5b as a prodrug of DT3 with an approximately seven-fold higher bioavailability compared to DT3 alone. And DT3 ether derivative 8a were relatively stable and approximately 4 times more bioavailable than DT3 prototype. Furthermore, 5b exhibited superior ability to mitigate radiation-induced pancytopenia, enhance the recovery of bone marrow hematopoietic stem and progenitor cells, and promote splenic extramedullary hematopoiesis in sublethal irradiated mice. Similarly, 8a shown potential radiation protection, but its radiation protection is less than DT3. Based on these findings, we identified 5b as a DT3 prodrug, and providing an attractive candidate for further drug development.

Sequential administration of delta-tocotrienol ameliorates radiation-induced myelosuppression in mice and non-human primates through inducing G-CSF production.

To date only four recombinant growth factors, including Filgrastim (rhG-CSF), have been approved by FDA as radiomitigators to ameliorate hematopoietic acute radiation syndrome (H-ARS). These approved agents are not stable under room-temperature, needing to be stored at 2-8 °C, and would not be feasible in a mass casualty scenario where rapid and cost-effective intervention is crucial. Delta-tocotrienol (δ-T3H), the most potent G-CSF-inducing agent among vitamin E isoforms, exhibited efficiency and selectivity on G-CSF production in comparison with TLR and STING agonists in mice. Five-dose δ-T3H was utilized as the optimal therapeutic regimen due to long-term G-CSF production and the best peripheral blood (PB) recovery of irradiated mice. Comparable with rhG-CSF, sequential administration of δ-T3H post-irradiation improved hematologic recovery and accelerated the regeneration of hematopoietic stem cells (HSCs) and hematopoietic progenitor cells (HPCs) in the bone marrow (BM) and spleen of 6.5Gy irradiated mice; and consistently enhanced repopulation of BM-HSCs. In 4.0Gy irradiated nonhuman primates, δ-T3H exhibited comparable efficacy as rhG-CSF to promote PB recovery and colony-formation of BM-HPCs. Altogether, we demonstrated that sequential administration of delta-tocotrienol ameliorates radiation-induced myelosuppression in mice and non-human primates through inducing G-CSF production, indicated δ-T3H as a promising radiomitigator for the management of H-ARS, particularly in a mass casualty scenario.

Comprehensive Characterizations of Immune Receptor Repertoire in Tumors and Cancer Immunotherapy Studies.

We applied our computational algorithm TRUST4 to assemble immune receptor (T-cell receptor/B-cell receptor) repertoires from approximately 12,000 RNA sequencing samples from The Cancer Genome Atlas and seven immunotherapy studies. From over 35 million assembled complete complementary-determining region 3 sequences, we observed that the expression of CCL5 and MZB1 is the most positively correlated genes with T-cell clonal expansion and B-cell clonal expansion, respectively. We analyzed amino acid evolution during B-cell receptor somatic hypermutation and identified tyrosine as the preferred residue. We found that IgG1+IgG3 antibodies together with FcRn were associated with complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity or phagocytosis. In addition to B-cell infiltration, we discovered that B-cell clonal expansion and IgG1+IgG3 antibodies are also correlated with better patient outcomes. Finally, we created a website, VisualizIRR, for users to interactively explore and visualize the immune repertoires in this study. See related Spotlight by Liu and Han, p. 786.

TRUST4: immune repertoire reconstruction from bulk and single-cell RNA-seq data.

We introduce the TRUST4 open-source algorithm for reconstruction of immune receptor repertoires in αß/γδ T cells and B cells from RNA-sequencing (RNA-seq) data. Compared with competing methods, TRUST4 supports both FASTQ and BAM format and is faster and more sensitive in assembling longer-even full-length-receptor repertoires. TRUST4 can also call repertoire sequences from single-cell RNA-seq (scRNA-seq) data without V(D)J enrichment, and is compatible with both SMART-seq and 5' 10x Genomics platforms.

Clonal tracing reveals diverse patterns of response to immune checkpoint blockade.

BACKGROUND: Immune checkpoint blockade (ICB) therapy has improved patient survival in a variety of cancers, but only a minority of cancer patients respond. Multiple studies have sought to identify general biomarkers of ICB response, but elucidating the molecular and cellular drivers of resistance for individual tumors remains challenging. We sought to determine whether a tumor with defined genetic background exhibits a stereotypic or heterogeneous response to ICB treatment. RESULTS: We establish a unique mouse system that utilizes clonal tracing and mathematical modeling to monitor the growth of each cancer clone, as well as the bulk tumor, in response to ICB. We find that tumors derived from the same clonal populations showed heterogeneous ICB response and diverse response patterns. Primary response is associated with higher immune infiltration and leads to enrichment of pre-existing ICB-resistant cancer clones. We further identify several cancer cell-intrinsic gene expression signatures associated with ICB resistance, including increased interferon response genes and glucocorticoid response genes. These findings are supported by clinical data from ICB treatment cohorts. CONCLUSIONS: Our study demonstrates diverse response patterns from the same ancestor cancer cells in response to ICB. This suggests the value of monitoring clonal constitution and tumor microenvironment over time to optimize ICB response and to design new combination therapies. Furthermore, as ICB response may enrich for cancer cell-intrinsic resistance signatures, this can affect interpretations of tumor RNA-seq data for response-signature association studies.

Oocyte competence is maintained by m6A methyltransferase KIAA1429-mediated RNA metabolism during mouse follicular development.

KIAA1429 (also known as vir-like m6A methyltransferase-associated protein (VIRMA)), a newly identified component of the RNA m6A methyltransferase complex, plays critical roles in guiding region-selective m6A deposition. However, in mammals, whether KIAA1429 mediates RNA m6A regulatory pathway functions in vivo remains unknown. Here, we show that the Kiaa1429-specific deficiency in oocytes resulted in female infertility with defective follicular development and fully grown germinal vesicle (GV) oocytes failing to undergo germinal vesicle breakdown (GVBD) and consequently losing the ability to resume meiosis. The oocyte growth is accompanied by the accumulation of abundant RNAs and posttranscriptional regulation. We found that the loss of Kiaa1429 could also lead to abnormal RNA metabolism in GV oocytes. RNA-seq profiling revealed that Kiaa1429 deletion altered the expression pattern of the oocyte-derived factors essential for follicular development. In addition, our data show that the conditional depletion of Kiaa1429 decreased the m6A levels in oocytes and mainly affected the alternative splicing of genes associated with oogenesis. In summary, the m6A methyltransferase KIAA1429-mediated RNA metabolism plays critical roles in folliculogenesis and the maintenance of oocyte competence.

Immune receptor repertoires in pediatric and adult acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML), caused by the abnormal proliferation of immature myeloid cells in the blood or bone marrow, is one of the most common hematologic malignancies. Currently, the interactions between malignant myeloid cells and the immune microenvironment, especially T cells and B cells, remain poorly characterized. METHODS: In this study, we systematically analyzed the T cell receptor and B cell receptor (TCR and BCR) repertoires from the RNA-seq data of 145 pediatric and 151 adult AML samples as well as 73 non-tumor peripheral blood samples. RESULTS: We inferred over 225,000 complementarity-determining region 3 (CDR3) sequences in TCR α, ß, γ, and δ chains and 1,210,000 CDR3 sequences in B cell immunoglobulin (Ig) heavy and light chains. We found higher clonal expansion of both T cells and B cells in the AML microenvironment and observed many differences between pediatric and adult AML. Most notably, adult AML samples have significantly higher level of B cell activation and more secondary Ig class switch events than pediatric AML or non-tumor samples. Furthermore, adult AML with highly expanded IgA2 B cells, which might represent an immunosuppressive microenvironment, are associated with regulatory T cells and worse overall survival. CONCLUSIONS: Our comprehensive characterization of the AML immune receptor repertoires improved our understanding of T cell and B cell immunity in AML, which may provide insights into immunotherapies in hematological malignancies.

LIVE: a manually curated encyclopedia of experimentally validated interactions of lncRNAs.

Advances in studies of long noncoding RNAs (lncRNAs) have provided data regarding the regulatory roles of lncRNAs, which perform functional roles through interactions with other functional elements. To track the underlying relationships among lncRNAs, various databases have been developed as repositories for lncRNA data. However, the ability to comprehensively explore the diverse interactions between lncRNAs and other functional elements is limited. To this end, we developed LIVE (LncRNA Interaction Validated Encyclopaedia), an interactive resource to integrate the diverse interactions of functional elements with lncRNAs. LIVE is a manually curated database of experimentally validated interactions of lncRNAs with genes, proteins and other various functional elements. By mining publications, we constructed LIVE with the following three interaction networks: a binding interaction network, a regulation network and a disease network; then, we combined them to form a comprehensive lncRNA interaction network. The current release of LIVE contains the validated interactions of 572 lncRNAs in humans and mice with 103 proteins, 209 genes, 56 transcription factors and 194 diseases. LIVE provides an interactive interface with charts and figures to aid users in searching and browsing interactions with lncRNAs. LIVE will greatly facilitate further investigation into the regulatory roles of lncRNAs and is freely available.

The landscape of the A-to-I RNA editome from 462 human genomes.

A-to-I editing, as a post-transcriptional modification process mediated by ADAR, plays a crucial role in many biological processes in metazoans. However, how and to what extent A-to-I editing diversifies and shapes population diversity at the RNA level are largely unknown. Here, we used 462 mRNA-sequencing samples from five populations of the Geuvadis Project and identified 16,518 A-to-I editing sites, with false detection rate of 1.03%. These sites form the landscape of the RNA editome of the human genome. By exploring RNA editing within and between populations, we revealed the geographic restriction of rare editing sites and population-specific patterns of edQTL editing sites. Moreover, we showed that RNA editing can be used to characterize the subtle but substantial diversity between different populations, especially those from different continents. Taken together, our results demonstrated that the nature and structure of populations at the RNA level are illustrated well by RNA editing, which provides insights into the process of how A-to-I editing shapes population diversity at the transcriptomic level. Our work will facilitate the understanding of the landscape of the RNA editome at the population scale and will be helpful for interpreting differences in the distribution and prevalence of disease among individuals and across populations.

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

Lnc2Catlas: an atlas of long noncoding RNAs associated with risk of cancers.

Lnc2Catlas ( http://lnc2catlas.bioinfotech.org/ ) is an atlas of long noncoding RNAs (lncRNAs) associated with cancer risk. LncRNAs are a class of functional noncoding RNAs with lengths over 200 nt and play a vital role in diverse biological processes. Increasing evidence shows that lncRNA dysfunction is associated with many human cancers/diseases. It is therefore important to understand the underlying relationship between lncRNAs and cancers. To this end, we developed Lnc2Catlas to compile quantitative associations between lncRNAs and cancers using three computational methods, assessing secondary structure disruption, lncRNA-protein interactions, and co-expression networks. Lnc2Catlas was constructed based on 27,670 well-annotated lncRNAs, 31,749,216 SNPs, 1,473 cancer-associated proteins, and 10,539 expression profiles of 33 cancers from The Cancer Genome Atlas (TCGA). Lnc2Catlas contains 247,124 lncRNA-SNP pairs, over two millions lncRNA-protein interactions, and 6,902 co-expression clusters. We deposited Lnc2Catlas on Alibaba Cloud and developed interactive, mobile device-compatible, user-friendly interfaces to help users search and browse Lnc2Catlas with ultra-low latency. Lnc2Catlas can aid in the investigation of associations between lncRNAs and cancers and can provide candidate lncRNAs for further experimental validation. Lnc2Catlas will facilitate an understanding of the associations between lncRNAs and cancer and will help reveal the critical role of lncRNAs in cancer.

Functional annotation of structural ncRNAs within enhancer RNAs in the human genome: implications for human disease.

Enhancer RNAs (eRNAs) are a novel class of non-coding RNA (ncRNA) molecules transcribed from the DNA sequences of enhancer regions. Despite extensive efforts devoted to revealing the potential functions and underlying mechanisms of eRNAs, it remains an open question whether eRNAs are mere transcriptional noise or relevant biologically functional species. Here, we identified a catalogue of eRNAs in a broad range of human cell/tissue types and extended our understanding of eRNAs by demonstrating their multi-omic signatures. Gene Ontology (GO) analysis revealed that eRNAs play key roles in human cell identity. Furthermore, we detected numerous known and novel functional RNA structures within eRNA regions. To better characterize the cis-regulatory effects of non-coding variation in these structural ncRNAs, we performed a comprehensive analysis of the genetic variants of structural ncRNAs in eRNA regions that are associated with inflammatory autoimmune diseases. Disease-associated variants of the structural ncRNAs were disproportionately enriched in immune-specific cell types. We also identified riboSNitches in lymphoid eRNAs and investigated the potential pathogenic mechanisms by which eRNAs might function in autoimmune diseases. Collectively, our findings offer valuable insights into the function of eRNAs and suggest that eRNAs might be effective diagnostic and therapeutic targets for human diseases.

BiRen: predicting enhancers with a deep-learning-based model using the DNA sequence alone.

MOTIVATION: Enhancer elements are noncoding stretches of DNA that play key roles in controlling gene expression programmes. Despite major efforts to develop accurate enhancer prediction methods, identifying enhancer sequences continues to be a challenge in the annotation of mammalian genomes. One of the major issues is the lack of large, sufficiently comprehensive and experimentally validated enhancers for humans or other species. Thus, the development of computational methods based on limited experimentally validated enhancers and deciphering the transcriptional regulatory code encoded in the enhancer sequences is urgent. RESULTS: We present a deep-learning-based hybrid architecture, BiRen, which predicts enhancers using the DNA sequence alone. Our results demonstrate that BiRen can learn common enhancer patterns directly from the DNA sequence and exhibits superior accuracy, robustness and generalizability in enhancer prediction relative to other state-of-the-art enhancer predictors based on sequence characteristics. Our BiRen will enable researchers to acquire a deeper understanding of the regulatory code of enhancer sequences. AVAILABILITY AND IMPLEMENTATION: Our BiRen method can be freely accessed at https://github.com/wenjiegroup/BiRen . CONTACT: shuwj@bmi.ac.cn or boxc@bmi.ac.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

iFORM: Incorporating Find Occurrence of Regulatory Motifs.

Accurately identifying the binding sites of transcription factors (TFs) is crucial to understanding the mechanisms of transcriptional regulation and human disease. We present incorporating Find Occurrence of Regulatory Motifs (iFORM), an easy-to-use and efficient tool for scanning DNA sequences with TF motifs described as position weight matrices (PWMs). Both performance assessment with a receiver operating characteristic (ROC) curve and a correlation-based approach demonstrated that iFORM achieves higher accuracy and sensitivity by integrating five classical motif discovery programs using Fisher's combined probability test. We have used iFORM to provide accurate results on a variety of data in the ENCODE Project and the NIH Roadmap Epigenomics Project, and the tool has demonstrated its utility in further elucidating individual roles of functional elements. Both the source and binary codes for iFORM can be freely accessed at https://github.com/wenjiegroup/iFORM. The identified TF binding sites across human cell and tissue types using iFORM have been deposited in the Gene Expression Omnibus under the accession ID GSE53962.