Clinical outcome upon infection with SARS-CoV-2 ranges from silent infection to lethal COVID-19. We have found an enrichment in rare variants predicted to be loss-of-function (LOF) at the 13 human loci known to govern TLR3- and IRF7-dependent type I interferon (IFN) immunity to influenza virus, in 659 patients with life-threatening COVID-19 pneumonia, relative to 534 subjects with asymptomatic or benign infection. By testing these and other rare variants at these 13 loci, we experimentally define LOF variants in 23 patients (3.5%), aged 17 to 77 years, underlying autosomal recessive or dominant deficiencies. We show that human fibroblasts with mutations affecting this pathway are vulnerable to SARS-CoV-2. Inborn errors of TLR3- and IRF7-dependent type I IFN immunity can underlie life-threatening COVID-19 pneumonia in patients with no prior severe infection.

A large number of computational methods have been developed for analyzing differential gene expression in RNA-seq data. We describe a comprehensive evaluation of common methods using the SEQC benchmark dataset and ENCODE data. We consider a number of key features, including normalization, accuracy of differential expression detection and differential expression analysis when one condition has no detectable expression. We find significant differences among the methods, but note that array-based methods adapted to RNA-seq data perform comparably to methods designed for RNA-seq. Our results demonstrate that increasing the number of replicate samples significantly improves detection power over increased sequencing depth.

After allogeneic hematopoietic stem cell transplantation (allo-HSCT), intestinal bacteria modulate risks of infection and graft-versus-host disease (GVHD). Neutropenic fever is common and treated with a choice of clinically equivalent antibiotics that target obligately anaerobic bacteria (anaerobes) to varying degrees. We retrospectively examined 857 allo-HSCT recipients and found that treatment of neutropenic fever with imipenem-cilastatin and piperacillin-tazobactam was associated with increased GVHD-related mortality at 5 years (21.5% in imipenem-cilastatin-treated patients vs. 13.1% in untreated patients, p=0.025, and 19.8% in piperacillin-tazobactam-treated patients vs. 11.9% in untreated patients, p=0.007). However, two other antibiotics also used to treat neutropenic fever, aztreonam and cefepime, were not associated with GVHD-related mortality (p=0.78 and p=0.98, respectively). Analysis of stool microbiota composition showed that piperacillin-tazobactam administration was associated with increased compositional perturbation. Studies in mouse models demonstrated similar effects of these antibiotics, as well as aggravated GVHD mortality with imipenem-cilastatin or piperacillin-tazobactm compared to aztreonam (p<0.01 and p<0.05, respectively). We found pathological evidence for increased GVHD in the colon of imipenem-cilastatin-treated mice (p<0.05), but no differences in short-chain fatty acid concentrations or regulatory T cells numbers. Notably, imipenem-cilastatin treatment of mice with GVHD led to loss of the protective lining of mucus in the colon (p<0.01) and intestinal barrier function was compromised (p<0.05). Sequencing of mouse stool specimens showed expansion of Akkermansia muciniphila (p<0.001), a commensal bacterium with mucus-degrading capabilities, raising the possibility that mucus degradation can contribute to murine GVHD. We demonstrate an underappreciated risk for antibiotics with activity against anaerobes to exacerbate colonic GVHD after transplant.

Genetic heterogeneity contributes to clinical outcome and progression of most tumors. Yet, little is known regarding allelic diversity for epigenetic compartments and almost no data exists for acute myeloid leukemia (AML). Here we examined epigenetic heterogeneity as assessed by cytosine methylation within defined genomic loci with four CpGs (epigenetic alleles), somatic mutations and transcriptomes of AML patient samples at serial time points. We observe that epigenetic allele burden is linked to inferior outcome and varies considerably during disease progression. Epigenetic and genetic allelic burden and patterning follow different patterns and kinetics during disease progression. We observed a subset of AMLs with high epiallele and low somatic mutation burden at diagnosis, a subset with high somatic mutation and lower epiallele burdens at diagnosis, and a subset with a mixed profile, suggesting distinct modes of tumor heterogeneity. Genes linked to promoter-associated epiallele shifts during tumor progression display increased single-cell transcriptional variance and differential expression, suggesting functional impact on gene regulation. Thus, genetic and epigenetic heterogeneity can occur with distinct kinetics, each likely able to impact biological and clinical features of tumors.

Patients with myeloproliferative neoplasms (MPNs) are at significant, cumulative risk of leukemic transformation to acute myeloid leukemia (AML), which is associated with adverse clinical outcome and resistance to standard AML therapies. We performed genomic profiling of post-MPN AML samples; these studies demonstrate somatic tumor protein 53 (TP53) mutations are common in JAK2V617F-mutant, post-MPN AML but not in chronic-phase MPN and lead to clonal dominance of JAK2V617F/TP53-mutant leukemic cells. Consistent with these data, expression of JAK2V617F combined with Tp53 loss led to fully penetrant AML in vivo. JAK2V617F-mutant, Tp53-deficient AML was characterized by an expanded megakaryocyte erythroid progenitor population that was able to propagate the disease in secondary recipients. In vitro studies revealed that post-MPN AML cells were sensitive to decitabine, the JAK1/2 inhibitor ruxolitinib, or the heat shock protein 90 inhibitor 8-Treatment with ruxolitinib or PU-H71 improved survival of mice engrafted with JAK2V617F-mutant, Tp53-deficient AML, demonstrating therapeutic efficacy for these targeted therapies and providing a rationale for testing these therapies in post-MPN AML. (1). Mutations in JAK2 have been identified in the majority of patients with PV, ET, and PMF (2-6), underscoring the importance of activated JAK-STAT signaling to the pathogenesis of chronicphase MPN. Despite the increasing use of empiric and targeted therapies, a subset of MPN patients transform to secondary acute myeloid leukemia (AML). Leukemic transformation occurs in 1%, 4%, and 20% of patients over a 10-y period in ET, PV, and PMF, respectively (7). MPN patients who develop leukemic transformation have a dismal outcome, with a median survival of less than 6 mo (8). Advanced age (>60 y) and exposure to chemotherapy increase the risk of leukemic transformation; however, the mechanisms and pathways that contribute to transformation from MPN to AML have not been well delineated. Importantly, the use of standard AML therapies, including induction chemotherapy, has not been shown to improve outcome for patients with post-MPN AML (8, 9). These data indicate a need for new models and improved therapeutic approaches to improve outcomes for patients who have transformed from MPN to AML and to identify genetic lesions associated with leukemic transformation.Genetic studies of paired samples before and after leukemic transformation have suggested there are at least two distinct routes for leukemic transformation. Some patients who present with a JAK2/MPL-positive MPN progress to JAK2/MPL-positive AML that is associated with the acquisition of additional genetic alterations (10-13). A second, more complex route to AML from MPN has been described in which a JAK2/MPL-positive MPN is followed by JAK2/MPL-negative AML (14, 15). Clonality studies using X-chromosome inactivation in informative females demonstrated that JAK2/MPL-positive MPN and JAK2/MPL-negative AML are clonally related, consistent with transformation of an antecedent, preJAK2...

Metastasis remains the most common cause of death in most cancers, with limited therapies for combating disseminated disease. While the primary tumor microenvironment is an important regulator of cancer progression, it is less well understood how different tissue environments influence metastasis. We analyzed tumor-stroma interactions that modulate organ tropism of brain, bone and lung metastasis in xenograft models. We identified a number of potential modulators of site-specific metastasis, including cathepsin S as a regulator of breast-to-brain metastasis. High cathepsin S expression at the primary site correlated with decreased brain metastasis-free survival in breast cancer patients. Both macrophages and tumor cells produce cathepsin S, and only the combined depletion significantly reduced brain metastasis in vivo. Cathepsin S specifically mediates blood-brain barrier transmigration via proteolytic processing of the junctional adhesion molecule (JAM)-B. Pharmacological inhibition of cathepsin S significantly reduced experimental brain metastasis, supporting its consideration as a therapeutic target for this disease.

Summary Specific combinations of Acute Myeloid Leukemia (AML) disease alleles, including FLT3 and TET2 mutations, confer distinct biologic features and adverse outcome. We generated mice with mutations in Tet2 and Flt3, which resulted in fully penetrant, lethal AML. Multipotent Tet2−/−;Flt3ITD progenitors (LSK CD48+CD150−) propagate disease in secondary recipients and were refractory to standard AML chemotherapy and FLT3-targeted therapy. Flt3ITD mutations and Tet2 loss cooperatively remodeled DNA methylation and gene expression to an extent not seen with either mutant allele alone, including at the Gata2 locus. Re-expression of Gata2 induced differentiation in AML stem cells and attenuated leukemogenesis. TET2 and FLT3 mutations cooperatively induce AML, with a defined leukemia stem cell population characterized by site-specific changes in DNA methylation and gene expression.

Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation.