A TREM2-activating antibody with a blood-brain barrier transport vehicle enhances microglial metabolism in Alzheimer's disease models.

Loss-of-function variants of TREM2 are associated with increased risk of Alzheimer's disease (AD), suggesting that activation of this innate immune receptor may be a useful therapeutic strategy. Here we describe a high-affinity human TREM2-activating antibody engineered with a monovalent transferrin receptor (TfR) binding site, termed antibody transport vehicle (ATV), to facilitate blood-brain barrier transcytosis. Upon peripheral delivery in mice, ATV:TREM2 showed improved brain biodistribution and enhanced signaling compared to a standard anti-TREM2 antibody.

The Immunoglobulin Superfamily Receptome Defines Cancer-Relevant Networks Associated with Clinical Outcome.

Cell surface receptors and their interactions play a central role in physiological and pathological signaling. Despite its clinical relevance, the immunoglobulin superfamily (IgSF) remains uncharacterized and underrepresented in databases. Here, we present a systematic extracellular protein map, the IgSF interactome.

Brain delivery and activity of a lysosomal enzyme using a blood-brain barrier transport vehicle in mice.

Most lysosomal storage diseases (LSDs) involve progressive central nervous system (CNS) impairment, resulting from deficiency of a lysosomal enzyme. Treatment of neuronopathic LSDs remains a considerable challenge, as approved intravenously administered enzyme therapies are ineffective in modifying CNS disease because they do not effectively cross the blood-brain barrier (BBB). We describe a therapeutic platform for increasing the brain exposure of enzyme replacement therapies.

TREM2 Regulates Microglial Cholesterol Metabolism upon Chronic Phagocytic Challenge.

Loss-of-function (LOF) variants of TREM2, an immune receptor expressed in microglia, increase Alzheimer's disease risk. TREM2 senses lipids and mediates myelin phagocytosis, but its role in microglial lipid metabolism is unknown. Combining chronic demyelination paradigms and cell sorting with RNA sequencing and lipidomics, we find that wild-type microglia acquire a disease-associated transcriptional state, while TREM2-deficient microglia remain largely homeostatic, leading to neuronal damage.

Transposable element expression in tumors is associated with immune infiltration and increased antigenicity.

Profound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data.

Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration.

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy.

Testosterone is an endogenous regulator of BAFF and splenic B cell number.

Testosterone deficiency in men is associated with increased risk for autoimmunity and increased B cell numbers through unknown mechanisms. Here we show that testosterone regulates the cytokine BAFF, an essential survival factor for B cells. Male mice lacking the androgen receptor have increased splenic B cell numbers, serum BAFF levels and splenic Baff mRNA.

Tumor suppressor BAP1 is essential for thymic development and proliferative responses of T lymphocytes.

Loss of function of the nuclear deubiquitinating enzyme BRCA1-associated protein-1 (BAP1) is associated with a wide spectrum of cancers. We report that tamoxifen-induced BAP1 deletion in adult mice resulted in severe thymic atrophy. BAP1 was critical for T cell development at several stages.

TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies.

Tumour and host cell PD-L1 is required to mediate suppression of anti-tumour immunity in mice.

Expression of PD-L1, the ligand for T-cell inhibitory receptor PD-1, is one key immunosuppressive mechanism by which cancer avoids eradication by the immune system. Therapeutic use of blocking antibodies to PD-L1 or its receptor PD-1 has produced unparalleled, durable clinical responses, with highest likelihood of response seen in patients whose tumour or immune cells express PD-L1 before therapy. The significance of PD-L1 expression in each cell type has emerged as a central and controversial unknown in the clinical development of immunotherapeutics.

Reproducible pharmacogenomic profiling of cancer cell line panels.

The use of large-scale genomic and drug response screening of cancer cell lines depends crucially on the reproducibility of results. Here we consider two previously published screens, plus a later critique of these studies. Using independent data, we show that consistency is achievable, and provide a systematic description of the best laboratory and analysis practices for future studies.

Musashi-2 controls cell fate, lineage bias, and TGF-β signaling in HSCs.

Hematopoietic stem cells (HSCs) are maintained through the regulation of symmetric and asymmetric cell division. We report that conditional ablation of the RNA-binding protein Msi2 results in a failure of HSC maintenance and engraftment caused by a loss of quiescence and increased commitment divisions. Contrary to previous studies, we found that these phenotypes were independent of Numb.

Ubiquitously transcribed genes use alternative polyadenylation to achieve tissue-specific expression.

More than half of human genes use alternative cleavage and polyadenylation (ApA) to generate mRNA transcripts that differ in the lengths of their 3' untranslated regions (UTRs), thus altering the post-transcriptional fate of the message and likely the protein output. The extent of 3' UTR variation across tissues and the functional role of ApA remain poorly understood. We developed a sequencing method called 3'-seq to quantitatively map the 3' ends of the transcriptome of diverse human tissues and isogenic transformation systems.

Genome-wide identification of miRNA targets by PAR-CLIP.

miRNAs are short (20-23 nt) RNAs that are loaded into proteins of the Argonaute (AGO) family and guide them to partially complementary target sites on mRNAs, resulting in mRNA destabilization and/or translational repression. It is estimated that about 60% of the mammalian genes are potentially regulated by miRNAs, and therefore methods for experimental miRNA target determination have become valuable tools for the characterization of posttranscriptional gene regulation. Here we present a step-by-step protocol and guidelines for the computational analysis for the large-scale identification of miRNA target sites in cultured cells by photoactivatable ribonucleoside enhanced crosslinking and immunoprecipitation (PAR-CLIP) of AGO proteins.

A predictive model of the oxygen and heme regulatory network in yeast.

Deciphering gene regulatory mechanisms through the analysis of high-throughput expression data is a challenging computational problem. Previous computational studies have used large expression datasets in order to resolve fine patterns of coexpression, producing clusters or modules of potentially coregulated genes. These methods typically examine promoter sequence information, such as DNA motifs or transcription factor occupancy data, in a separate step after clustering.

Learning regulatory programs that accurately predict differential expression with MEDUSA.

Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology. In this paper, we describe a predictive modeling approach for studying regulatory networks, based on a machine learning algorithm called MEDUSA. MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes.