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Leukocyte-associated Ig-like receptor 1 (LAIR1) is a collagen-binding inhibitory immune receptor that negatively regulates cellular activation. In this issue of the JCI, Tao et al. show that LAIR1-inhibitory signaling plays an important role in immunosuppressive M2-like tumor-associated macrophages (TAMs) in aggressive brain tumors. LAIR1 KO, antibody blockade, and an immunotherapy that incorporates a LAIR1-inhibitory module into a chimeric antigen receptor (CAR) all led to increased antitumor activity by CAR T cells, reduced M2-like TAMs, altered collagen networks, and increased survival rates in mouse tumor models. These findings demonstrate an innovative immunotherapeutic approach for cancer that leverages LAIR1 inhibition to combat multiple tumor immune evasion strategies.

Background Long non-coding RNAs (lncRNAs) exhibit remarkable cell-type specificity and disease association. LncRNA’s functional versatility includes epigenetic modification, nuclear domain organization, transcriptional control, regulation of RNA splicing and translation, and modulation of protein activity. However, most lncRNAs remain uncharacterized due to a shortage of predictive tools available to guide functional experiments. Results To address this gap for lymphoma-associated lncRNAs identified in our studies, we developed a new computational method, Predicting LncRNA Activity through Integrative Data-driven ‘Omics and Heuristics (PLAIDOH), which has several unique features not found in other methods. PLAIDOH integrates transcriptome, subcellular localization, enhancer landscape, genome architecture, chromatin interaction, and RNA-binding (eCLIP) data and generates statistically defined output scores. PLAIDOH’s approach identifies and ranks functional connections between individual lncRNA, coding gene, and protein pairs using enhancer, transcript cis -regulatory, and RNA-binding protein interactome scores that predict the relative likelihood of these different lncRNA functions. When applied to ‘omics datasets that we collected from lymphoma patients, or to publicly available cancer (TCGA) or ENCODE datasets, PLAIDOH identified and prioritized well-known lncRNA-target gene regulatory pairs (e.g., HOTAIR and HOX genes, PVT1 and MYC), validated hits in multiple lncRNA-targeted CRISPR screens, and lncRNA-protein binding partners (e.g., NEAT1 and NONO). Importantly, PLAIDOH also identified novel putative functional interactions, including one lymphoma-associated lncRNA based on analysis of data from our human lymphoma study. We validated PLAIDOH’s predictions for this lncRNA using knock-down and knock-out experiments in lymphoma cell models. Conclusions Our study demonstrates that we have developed a new method for the prediction and ranking of functional connections between individual lncRNA, coding gene, and protein pairs, which were validated by genetic experiments and comparison to published CRISPR screens. PLAIDOH expedites validation and follow-on mechanistic studies of lncRNAs in any biological system. It is available at https://github.com/sarahpyfrom/PLAIDOH .

The Mediator complex facilitates interactions between transcription factors and RNA polymerase II, a process that is required for host gene transcription, including in response to viral infections. Among the many subunits in the Mediator complex, the MED25 subunit has been shown to be a target for viral activators during infection. Here we provide the molecular basis for the interaction between human respiratory syncytial virus (hRSV) nonstructural 1 protein (NS1) and the activator interaction domain (ACID) of MED25. The X-ray crystal structure of the complex revealed that NS1 straddles and binds two faces of MED25 ACID. This interaction is distinct from previously known viral activators. Importantly, our data support the conformational flexibility of viral transcriptional regulators. Furthermore, ChIP-seq and RNA-seq analysis identified the ATF3 transcription factor and a role for NS1/Mediator/ATF3 interaction in host gene regulation in hRSV infections. Our findings provide a molecular basis for hRSV NS1-based regulation of host gene transcription and reveal how viruses exploit the conformational heterogeneity at fuzzy transcription activator interfaces. This study provides the structural and biochemical characterization of the RSV NS1/MED25 ACID complex, revealing how RSV exploits fuzzy interfaces between coactivators and transcription factors, including ATF3, to modulate host gene transcription.

Human T-cell leukemia virus type 1 (HTLV-1) is a retrovirus that causes an aggressive T-cell malignancy and a variety of inflammatory conditions. The integrated provirus includes a single binding site for the epigenomic insulator, CCCTC-binding protein (CTCF), but its function remains unclear. In the current study, a mutant virus was examined that eliminates the CTCF-binding site. The mutation did not disrupt the kinetics and levels of virus gene expression, or establishment of or reactivation from latency. However, the mutation disrupted the epigenetic barrier function, resulting in enhanced DNA CpG methylation downstream of the CTCF binding site on both strands of the integrated provirus and H3K4Me3, H3K36Me3, and H3K27Me3 chromatin modifications both up- and downstream of the site. A majority of clonal cell lines infected with wild type HTLV-1 exhibited increased plus strand gene expression with CTCF knockdown, while expression in mutant HTLV-1 clonal lines was unaffected. These findings indicate that CTCF binding regulates HTLV-1 gene expression, DNA and histone methylation in an integration site dependent fashion.

The surface receptor CD8α is present on 20%-80% of human (but not mouse) NK cells, yet its function on NK cells remains poorly understood. CD8α expression on donor NK cells was associated with a lack of therapeutic responses in patients with leukemia in prior studies, thus, we hypothesized that CD8α may affect critical NK cell functions. Here, we discovered that CD8α- NK cells had improved control of leukemia in xenograft models compared with CD8α+ NK cells, likely due to an enhanced capacity for proliferation. Unexpectedly, we found that CD8α expression was induced on approximately 30% of previously CD8α- NK cells following IL-15 stimulation. These induced CD8α+ (iCD8α+) NK cells had the greatest proliferation, responses to IL-15 signaling, and metabolic activity compared with those that sustained existing CD8α expression (sustained CD8α+) or those that remained CD8α- (persistent CD8α-). These iCD8α+ cells originated from an IL-15Rβhi NK cell population, with CD8α expression dependent on the transcription factor RUNX3. Moreover, CD8A CRISPR/Cas9 deletion resulted in enhanced responses through the activating receptor NKp30, possibly by modulating KIR inhibitory function. Thus, CD8α status identified human NK cell capacity for IL-15-induced proliferation and metabolism in a time-dependent fashion, and its presence had a suppressive effect on NK cell-activating receptors.

Antiapoptotic BCL2 family members have been implicated in the pathogenesis of acute myelogenous leukemia (AML), but the functional significance and relative importance of individual proteins (e.g., BCL2, BCL-XL, and myeloid cell leukemia 1 [MCL1]) remain poorly understood. Here, we examined the expression of BCL2, BCL-XL, and MCL1 in primary human hematopoietic subsets and leukemic blasts from AML patients and found that MCL1 transcripts were consistently expressed at high levels in all samples tested. Consistent with this, Mcl1 protein was also highly expressed in myeloid leukemic blasts in a mouse Myc-induced model of AML. We used this model to test the hypothesis that Mcl1 facilitates AML development by allowing myeloid progenitor cells to evade Myc-induced cell death. Indeed, activation of Myc for 7 days in vivo substantially increased myeloid lineage cell numbers, whereas hematopoietic stem, progenitor, and B-lineage cells were depleted. Furthermore, Mcl1 haploinsufficiency abrogated AML development. In addition, deletion of a single allele of Mcl1 from fully transformed AML cells substantially prolonged the survival of transplanted mice. Conversely, the rapid lethality of disease was restored by coexpression of Bcl2 and Myc in Mcl1-haploinsufficient cells. Together, these data demonstrate a critical and dose-dependent role for Mcl1 in AML pathogenesis in mice and suggest that MCL1 may be a promising therapeutic target in patients with de novo AML.

Macrophages produce genotoxic agents, such as reactive oxygen and nitrogen species, that kill invading pathogens. Here we show that these agents activate the DNA damage response (DDR) kinases ATM and DNA-PKcs through the generation of double stranded breaks (DSBs) in murine macrophage genomic DNA. In contrast to other cell types, initiation of this DDR depends on signaling from the type I interferon receptor. Once activated, ATM and DNA-PKcs regulate a genetic program with diverse immune functions and promote inflammasome activation and the production of IL-1β and IL-18. Indeed, following infection with Listeria monocytogenes, DNA-PKcs-deficient murine macrophages produce reduced levels of IL-18 and are unable to optimally stimulate IFN-γ production by NK cells. Thus, genomic DNA DSBs act as signaling intermediates in murine macrophages, regulating innate immune responses through the initiation of a type I IFN-dependent DDR.

Acute promyelocytic leukemia (APL) is characterized by the t(15;17) chromosomal translocation, which results in fusion of the retinoic acid receptor alpha (RARA) gene to another gene, most commonly promyelocytic leukemia (PML). The resulting fusion protein, PML-RARA, initiates APL, which is a subtype (M3) of acute myeloid leukemia (AML). In this report, we identify a gene expression signature that is specific to M3 samples; it was not found in other AML subtypes and did not simply represent the normal gene expression pattern of primary promyelocytes. To validate this signature for a large number of genes, we tested a recently developed high throughput digital technology (NanoString nCounter). Nearly all of the genes tested demonstrated highly significant concordance with our microarray data (P < 0.05). The validated gene signature reliably identified M3 samples in 2 other AML datasets, and the validated genes were substantially enriched in our mouse model of APL, but not in a cell line that inducibly expressed PML-RARA. These results demonstrate that nCounter is a highly reproducible, customizable system for mRNA quantification using limited amounts of clinical material, which provides a valuable tool for biomarker measurement in low-abundance patient samples.

DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Many studies have mapped DNA methylation changes associated with embryogenesis, cell differentiation, and cancer at a genome-wide scale. Our understanding of genome-wide DNA methylation changes in a developmental or disease-related context has been steadily growing. However, the investigation of which CpGs are variably methylated in different normal cell or tissue types is still limited. Here, we present an in-depth analysis of 54 single-CpG-resolution DNA methylomes of normal human cell types by integrating high-throughput sequencing-based methylation data. We found that the ratio of methylated to unmethylated CpGs is relatively constant regardless of cell type. However, which CpGs made up the unmethylated complement was cell-type specific. We categorized the 26,000,000 human autosomal CpGs based on their methylation levels across multiple cell types to identify variably methylated CpGs and found that 22.6% exhibited variable DNA methylation. These variably methylated CpGs formed 660,000 variably methylated regions (VMRs), encompassing 11% of the genome. By integrating a multitude of genomic data, we found that VMRs enrich for histone modifications indicative of enhancers, suggesting their role as regulatory elements marking cell type specificity. VMRs enriched for transcription factor binding sites in a tissue-dependent manner. Importantly, they enriched for GWAS variants, suggesting that VMRs could potentially be implicated in disease and complex traits. Taken together, our results highlight the link between CpG methylation variation, genetic variation, and disease risk for many human cell types.

Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF) is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance) among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF) and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) for CSF biomarker discovery by (1) identifying reparable sources of technical variability, (2) assessing subject variance and residual technical variability for numerous CSF proteins, and (3) testing its ability to segregate samples on the basis of desired biomarker characteristics. Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i) incomplete MAF and keratins; ii) globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii) oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5%) whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and individual samples. Quantitative label-free LC-MS/MS can measure scores of CSF proteins with low technical variability and can segregate samples according to desired criteria. Thus, this technique shows potential for biomarker discovery for neurological diseases.