Therapeutic Spp1 silencing in TREM2+ cardiac macrophages suppresses atrial fibrillation.

Atrial fibrillation (AFib) and the risk of its lethal complications are propelled by fibrosis, which induces electrical heterogeneity and gives rise to reentry circuits. Atrial TREM2+ macrophages secrete osteopontin (encoded by Spp1), a matricellular signaling protein that engenders fibrosis and AFib. Here we show that silencing Spp1 in TREM2+ cardiac macrophages with an antibody-siRNA conjugate reduces atrial fibrosis and suppresses AFib in mice, thus offering a new immunotherapy for the most common arrhythmia.

A deep profile of gene expression across 18 human cancers.

Clinically and biologically valuable information may reside untapped in large cancer gene expression data sets. Deep unsupervised learning has the potential to extract this information with unprecedented efficacy but has thus far been hampered by a lack of biological interpretability and robustness. Here, we present DeepProfile, a comprehensive framework that addresses current challenges in applying unsupervised deep learning to gene expression profiles. We use DeepProfile to learn low-dimensional latent spaces for 18 human cancers from 50,211 transcriptomes. DeepProfile outperforms existing dimensionality reduction methods with respect to biological interpretability. Using DeepProfile interpretability methods, we show that genes that are universally important in defining the latent spaces across all cancer types control immune cell activation, while cancer type-specific genes and pathways define molecular disease subtypes. By linking DeepProfile latent variables to secondary tumor characteristics, we discover that tumor mutation burden is closely associated with the expression of cell cycle-related genes. DNA mismatch repair and MHC class II antigen presentation pathway expression, on the other hand, are consistently associated with patient survival. We validate these results through Kaplan-Meier analyses and nominate tumor-associated macrophages as an important source of survival-correlated MHC class II transcripts. Our results illustrate the power of unsupervised deep learning for discovery of novel cancer biology from existing gene expression data.

Chromosome evolution screens recapitulate tissue-specific tumor aneuploidy patterns.

Whole chromosome and arm-level copy number alterations occur at high frequencies in tumors, but their selective advantages, if any, are poorly understood. Here, utilizing unbiased whole chromosome genetic screens combined with in vitro evolution to generate arm- and subarm-level events, we iteratively selected the fittest karyotypes from aneuploidized human renal and mammary epithelial cells. Proliferation-based karyotype selection in these epithelial lines modeled tissue-specific tumor aneuploidy patterns in patient cohorts in the absence of driver mutations. Hi-C-based translocation mapping revealed that arm-level events usually emerged in multiples of two via centromeric translocations and occurred more frequently in tetraploids than diploids, contributing to the increased diversity in evolving tetraploid populations. Isogenic clonal lineages enabled elucidation of pro-tumorigenic mechanisms associated with common copy number alterations, revealing Notch signaling potentiation as a driver of 1q gain in breast cancer. We propose that intrinsic, tissue-specific proliferative effects underlie tumor copy number patterns in cancer.

Germline mutations and developmental mosaicism underlying EGFR-mutant lung cancer.

While the development of multiple primary tumors in smokers with lung cancer can be attributed to carcinogen-induced field cancerization, the occurrence of multiple primary tumors in individuals with EGFR-mutant lung cancer who lack known environmental exposures remains unexplained. We identified ten patients with early-stage, resectable non-small cell lung cancer who presented with multiple anatomically distinct EGFR-mutant tumors. We analyzed the phylogenetic relationships among multiple tumors from each patient using whole exome sequencing (WES) and hypermutable poly-guanine (poly-G) repeat genotyping, as orthogonal methods for lineage tracing. In two patients, we identified germline EGFR variants, which confer moderately enhanced signaling when modeled in vitro. In four other patients, developmental mosaicism is supported by the poly-G lineage tracing and WES, indicating a common non-germline cell-of-origin. Thus, developmental mosaicism and germline variants define two distinct mechanisms of genetic predisposition to multiple EGFR-mutant primary tumors, with implications for understanding their etiology and clinical management.

Recruited macrophages elicit atrial fibrillation.

Atrial fibrillation disrupts contraction of the atria, leading to stroke and heart failure. We deciphered how immune and stromal cells contribute to atrial fibrillation. Single-cell transcriptomes from human atria documented inflammatory monocyte and SPP1+ macrophage expansion in atrial fibrillation. Combining hypertension, obesity, and mitral valve regurgitation (HOMER) in mice elicited enlarged, fibrosed, and fibrillation-prone atria. Single-cell transcriptomes from HOMER mouse atria recapitulated cell composition and transcriptome changes observed in patients. Inhibiting monocyte migration reduced arrhythmia in Ccr2-∕- HOMER mice. Cell-cell interaction analysis identified SPP1 as a pleiotropic signal that promotes atrial fibrillation through cross-talk with local immune and stromal cells. Deleting Spp1 reduced atrial fibrillation in HOMER mice. These results identify SPP1+ macrophages as targets for immunotherapy in atrial fibrillation.

Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models.

Machine learning may aid the choice of optimal combinations of anticancer drugs by explaining the molecular basis of their synergy. By combining accurate models with interpretable insights, explainable machine learning promises to accelerate data-driven cancer pharmacology. However, owing to the highly correlated and high-dimensional nature of transcriptomic data, naively applying current explainable machine-learning strategies to large transcriptomic datasets leads to suboptimal outcomes. Here by using feature attribution methods, we show that the quality of the explanations can be increased by leveraging ensembles of explainable machine-learning models. We applied the approach to a dataset of 133 combinations of 46 anticancer drugs tested in ex vivo tumour samples from 285 patients with acute myeloid leukaemia and uncovered a haematopoietic-differentiation signature underlying drug combinations with therapeutic synergy. Ensembles of machine-learning models trained to predict drug combination synergies on the basis of gene-expression data may improve the feature attribution quality of complex machine-learning models.

Lymphatic Invasion of Plakoglobin-Dependent Tumor Cell Clusters Drives Formation of Polyclonal Lung Metastases in Colon Cancer.

BACKGROUND & AIMS: Patients with colon cancer with liver metastases may be cured with surgery, but the presence of additional lung metastases often precludes curative treatment. Little is known about the processes driving lung metastasis. This study aimed to elucidate the mechanisms governing lung vs liver metastasis formation. METHODS: Patient-derived organoid (PDO) cultures were established from colon tumors with distinct patterns of metastasis. Mouse models recapitulating metastatic organotropism were created by implanting PDOs into the cecum wall. Optical barcoding was applied to trace the origin and clonal composition of liver and lung metastases. RNA sequencing and immunohistochemistry were used to identify candidate determinants of metastatic organotropism. Genetic, pharmacologic, in vitro, and in vivo modeling strategies identified essential steps in lung metastasis formation. Validation was performed by analyzing patient-derived tissues. RESULTS: Cecum transplantation of 3 distinct PDOs yielded models with distinct metastatic organotropism: liver only, lung only, and liver and lung. Liver metastases were seeded by single cells derived from select clones. Lung metastases were seeded by polyclonal clusters of tumor cells entering the lymphatic vasculature with very limited clonal selection. Lung-specific metastasis was associated with high expression of desmosome markers, including plakoglobin. Plakoglobin deletion abrogated tumor cell cluster formation, lymphatic invasion, and lung metastasis formation. Pharmacologic inhibition of lymphangiogenesis attenuated lung metastasis formation. Primary human colon, rectum, esophagus, and stomach tumors with lung metastases had a higher N-stage and more plakoglobin-expressing intra-lymphatic tumor cell clusters than those without lung metastases. CONCLUSIONS: Lung and liver metastasis formation are fundamentally distinct processes with different evolutionary bottlenecks, seeding entities, and anatomic routing. Polyclonal lung metastases originate from plakoglobin-dependent tumor cell clusters entering the lymphatic vasculature at the primary tumor site.

Losartan controls immune checkpoint blocker-induced edema and improves survival in glioblastoma mouse models.

Immune checkpoint blockers (ICBs) have failed in all phase III glioblastoma trials. Here, we found that ICBs induce cerebral edema in some patients and mice with glioblastoma. Through single-cell RNA sequencing, intravital imaging, and CD8+ T cell blocking studies in mice, we demonstrated that this edema results from an inflammatory response following antiprogrammed death 1 (PD1) antibody treatment that disrupts the blood-tumor barrier. Used in lieu of immunosuppressive corticosteroids, the angiotensin receptor blocker losartan prevented this ICB-induced edema and reprogrammed the tumor microenvironment, curing 20% of mice which increased to 40% in combination with standard of care treatment. Using a bihemispheric tumor model, we identified a "hot" tumor immune signature prior to losartan+anti-PD1 therapy that predicted long-term survival. Our findings provide the rationale and associated biomarkers to test losartan with ICBs in glioblastoma patients.

Bone marrow adipocytes fuel emergency hematopoiesis after myocardial infarction.

After myocardial infarction (MI), emergency hematopoiesis produces inflammatory myeloid cells that accelerate atherosclerosis and promote heart failure. Since the balance between glycolysis and mitochondrial metabolism regulates hematopoietic stem cell homeostasis, metabolic cues may influence emergency myelopoiesis. Here, we show in humans and female mice that hematopoietic progenitor cells increase fatty acid metabolism after MI. Blockade of fatty acid oxidation by deleting carnitine palmitoyltransferase (Cpt1A) in hematopoietic cells of Vav1Cre/+Cpt1Afl/fl mice limited hematopoietic progenitor proliferation and myeloid cell expansion after MI. We also observed reduced bone marrow adiposity in humans, pigs and mice following MI. Inhibiting lipolysis in adipocytes using AdipoqCreERT2Atglfl/fl mice or local depletion of bone marrow adipocytes in AdipoqCreERT2iDTR mice also curbed emergency hematopoiesis. Furthermore, systemic and regional sympathectomy prevented bone marrow adipocyte shrinkage after MI. These data establish a critical role for fatty acid metabolism in post-MI emergency hematopoiesis.

Sleep exerts lasting effects on hematopoietic stem cell function and diversity.

A sleepless night may feel awful in its aftermath, but sleep's revitalizing powers are substantial, perpetuating the idea that convalescent sleep is a consequence-free physiological reset. Although recent studies have shown that catch-up sleep insufficiently neutralizes the negative effects of sleep debt, the mechanisms that control prolonged effects of sleep disruption are not understood. Here, we show that sleep interruption restructures the epigenome of hematopoietic stem and progenitor cells (HSPCs) and increases their proliferation, thus reducing hematopoietic clonal diversity through accelerated genetic drift. Sleep fragmentation exerts a lasting influence on the HSPC epigenome, skewing commitment toward a myeloid fate and priming cells for exaggerated inflammatory bursts. Combining hematopoietic clonal tracking with mathematical modeling, we infer that sleep preserves clonal diversity by limiting neutral drift. In humans, sleep restriction alters the HSPC epigenome and activates hematopoiesis. These findings show that sleep slows decay of the hematopoietic system by calibrating the hematopoietic epigenome, constraining inflammatory output, and maintaining clonal diversity.

Bone marrow endothelial dysfunction promotes myeloid cell expansion in cardiovascular disease.

Abnormal hematopoiesis advances cardiovascular disease by generating excess inflammatory leukocytes that attack the arteries and the heart. The bone marrow niche regulates hematopoietic stem cell proliferation and hence the systemic leukocyte pool, but whether cardiovascular disease affects the hematopoietic organ's microvasculature is unknown. Here we show that hypertension, atherosclerosis and myocardial infarction (MI) instigate endothelial dysfunction, leakage, vascular fibrosis and angiogenesis in the bone marrow, altogether leading to overproduction of inflammatory myeloid cells and systemic leukocytosis. Limiting angiogenesis with endothelial deletion of Vegfr2 (encoding vascular endothelial growth factor (VEGF) receptor 2) curbed emergency hematopoiesis after MI. We noted that bone marrow endothelial cells assumed inflammatory transcriptional phenotypes in all examined stages of cardiovascular disease. Endothelial deletion of Il6 or Vcan (encoding versican), genes shown to be highly expressed in mice with atherosclerosis or MI, reduced hematopoiesis and systemic myeloid cell numbers in these conditions. Our findings establish that cardiovascular disease remodels the vascular bone marrow niche, stimulating hematopoiesis and production of inflammatory leukocytes.

Mapping the long road to cancer.

Every cell in our body accumulates mutations throughout life, and sometimes an unfortunate combination of mutations drives the initiation of cancer. A new study infers extraordinarily detailed timelines of pre-cancerous evolution by sequencing single-cell genomes in patients with blood malignancies-finding that key mutations can arrive decades before diagnosis.

B lymphocyte-derived acetylcholine limits steady-state and emergency hematopoiesis.

Autonomic nerves control organ function through the sympathetic and parasympathetic branches, which have opposite effects. In the bone marrow, sympathetic (adrenergic) nerves promote hematopoiesis; however, how parasympathetic (cholinergic) signals modulate hematopoiesis is unclear. Here, we show that B lymphocytes are an important source of acetylcholine, a neurotransmitter of the parasympathetic nervous system, which reduced hematopoiesis. Single-cell RNA sequencing identified nine clusters of cells that expressed the cholinergic α7 nicotinic receptor (Chrna7) in the bone marrow stem cell niche, including endothelial and mesenchymal stromal cells (MSCs). Deletion of B cell-derived acetylcholine resulted in the differential expression of various genes, including Cxcl12 in leptin receptor+ (LepR+) stromal cells. Pharmacologic inhibition of acetylcholine signaling increased the systemic supply of inflammatory myeloid cells in mice and humans with cardiovascular disease.

Molecular mechanisms of cancer metastasis via the lymphatic versus the blood vessels.

Cancer metastasis is the process by which primary cancer cells invade through the lymphatic or blood vessels to distant sites. The molecular mechanisms by which cancer cells spread either through the lymphatic versus blood vessels or both are not well established. Two major developments have helped us to understand the process more clearly. First, the development of the sentinel lymph node (SLN) concept which is well established in melanoma and breast cancer. The SLN is the first lymph node in the draining nodal basin to receive cancer cells. Patients with a negative SLN biopsy show a significantly lower incidence of distant metastasis, suggesting that the SLN may be the major gateway for cancer metastasis in these cancer types. Second, the discovery and characterization of several biomarkers including VEGF-C, LYVE-1, Podoplanin and Prox-1 have opened new vistas in the understanding of the induction of lymphangiogenesis by cancer cells. Cancer cells must complete multiple steps to invade the lymphatic system, some of which may be enabled by the evolution of new traits during cancer progression. Thus, cancer cells may spread initially through the main gateway of the SLN, from which evolving cancer clones can invade the blood vessels to distant sites. Cancer cells may also enter the blood vessels directly, bypassing the SLN to establish distant metastases. Future studies need to pinpoint the molecules that are used by cancer cells at different stages of metastasis via different routes so that specific therapies can be targeted against these molecules, with the goal of stopping or preventing cancer metastasis.

Integrated loss- and gain-of-function screens define a core network governing human embryonic stem cell behavior.

Understanding the genetic control of human embryonic stem cell function is foundational for developmental biology and regenerative medicine. Here we describe an integrated genome-scale loss- and gain-of-function screening approach to identify genetic networks governing embryonic stem cell proliferation and differentiation into the three germ layers. We identified a deep link between pluripotency maintenance and survival by showing that genetic alterations that cause pluripotency dissolution simultaneously increase apoptosis resistance. We discovered that the chromatin-modifying complex SAGA and in particular its subunit TADA2B are central regulators of pluripotency, survival, growth, and lineage specification. Joint analysis of all screens revealed that genetic alterations that broadly inhibit differentiation across multiple germ layers drive proliferation and survival under pluripotency-maintaining conditions and coincide with known cancer drivers. Our results show the power of integrated multilayer genetic screening for the robust mapping of complex genetic networks.

PolyG-DS: An ultrasensitive polyguanine tract-profiling method to detect clonal expansions and trace cell lineage.

Polyguanine tracts (PolyGs) are short guanine homopolymer repeats that are prone to accumulating mutations when cells divide. This feature makes them especially suitable for cell lineage tracing, which has been exploited to detect and characterize precancerous and cancerous somatic evolution. PolyG genotyping, however, is challenging because of the inherent biochemical difficulties in amplifying and sequencing repetitive regions. To overcome this limitation, we developed PolyG-DS, a next-generation sequencing (NGS) method that combines the error-correction capabilities of duplex sequencing (DS) with enrichment of PolyG loci using CRISPR-Cas9-targeted genomic fragmentation. PolyG-DS markedly reduces technical artifacts by comparing the sequences derived from the complementary strands of each original DNA molecule. We demonstrate that PolyG-DS genotyping is accurate, reproducible, and highly sensitive, enabling the detection of low-frequency alleles (<0.01) in spike-in samples using a panel of only 19 PolyG markers. PolyG-DS replicated prior results based on PolyG fragment length analysis by capillary electrophoresis, and exhibited higher sensitivity for identifying clonal expansions in the nondysplastic colon of patients with ulcerative colitis. We illustrate the utility of this method for resolving the phylogenetic relationship among precancerous lesions in ulcerative colitis and for tracing the metastatic dissemination of ovarian cancer. PolyG-DS enables the study of tumor evolution without prior knowledge of tumor driver mutations and provides a tool to perform cost-effective and easily scalable ultra-accurate NGS-based PolyG genotyping for multiple applications in biology, genetics, and cancer research.