Epitope-engineered human hematopoietic stem cells are shielded from CD123-targeted immunotherapy.

Targeted eradication of transformed or otherwise dysregulated cells using monoclonal antibodies (mAb), antibody-drug conjugates (ADC), T cell engagers (TCE), or chimeric antigen receptor (CAR) cells is very effective for hematologic diseases. Unlike the breakthrough progress achieved for B cell malignancies, there is a pressing need to find suitable antigens for myeloid malignancies. CD123, the interleukin-3 (IL-3) receptor alpha-chain, is highly expressed in various hematological malignancies, including acute myeloid leukemia (AML). However, shared CD123 expression on healthy hematopoietic stem and progenitor cells (HSPCs) bears the risk for myelotoxicity. We demonstrate that epitope-engineered HSPCs were shielded from CD123-targeted immunotherapy but remained functional, while CD123-deficient HSPCs displayed a competitive disadvantage. Transplantation of genome-edited HSPCs could enable tumor-selective targeted immunotherapy while rebuilding a fully functional hematopoietic system. We envision that this approach is broadly applicable to other targets and cells, could render hitherto undruggable targets accessible to immunotherapy, and will allow continued posttransplant therapy, for instance, to treat minimal residual disease (MRD).

Inhibition of nonsense-mediated mRNA decay reduces the tumorigenicity of human fibrosarcoma cells.

Nonsense-mediated mRNA decay (NMD) is a eukaryotic RNA decay pathway with roles in cellular stress responses, differentiation, and viral defense. It functions in both quality control and post-transcriptional regulation of gene expression. NMD has also emerged as a modulator of cancer progression, although available evidence supports both a tumor suppressor and a pro-tumorigenic role, depending on the model. To further investigate the role of NMD in cancer, we knocked out the NMD factor SMG7 in the HT1080 human fibrosarcoma cell line, resulting in suppression of NMD function. We then compared the oncogenic properties of the parental cell line, the SMG7-knockout, and a rescue cell line in which we re-introduced both isoforms of SMG7. We also tested the effect of a drug inhibiting the NMD factor SMG1 to distinguish NMD-dependent effects from putative NMD-independent functions of SMG7. Using cell-based assays and a mouse xenograft tumor model, we showed that suppression of NMD function severely compromises the oncogenic phenotype. Molecular pathway analysis revealed that NMD suppression strongly reduces matrix metalloprotease 9 (MMP9) expression and that MMP9 re-expression partially rescues the oncogenic phenotype. Since MMP9 promotes cancer cell migration and invasion, metastasis and angiogenesis, its downregulation may contribute to the reduced tumorigenicity of NMD-suppressed cells. Collectively, our results highlight the potential value of NMD inhibition as a therapeutic approach.

Controlled Cycling and Quiescence Enables Efficient HDR in Engraftment-Enriched Adult Hematopoietic Stem and Progenitor Cells.

Genome editing often takes the form of either error-prone sequence disruption by non-homologous end joining (NHEJ) or sequence replacement by homology-directed repair (HDR). Although NHEJ is generally effective, HDR is often difficult in primary cells. Here, we use a combination of immunophenotyping, next-generation sequencing, and single-cell RNA sequencing to investigate and reprogram genome editing outcomes in subpopulations of adult hematopoietic stem and progenitor cells. We find that although quiescent stem-enriched cells mostly use NHEJ, non-quiescent cells with the same immunophenotype use both NHEJ and HDR. Inducing quiescence before editing results in a loss of HDR in all cell subtypes. We develop a strategy of controlled cycling and quiescence that yields a 6-fold increase in the HDR/NHEJ ratio in quiescent stem cells ex vivo and in vivo. Our results highlight the tension between editing and cellular physiology and suggest strategies to manipulate quiescent cells for research and therapeutic genome editing.

Integrated genomic analysis reveals mutated ELF3 as a potential gallbladder cancer vaccine candidate.

Gallbladder cancer (GBC) is an aggressive gastrointestinal malignancy with no approved targeted therapy. Here, we analyze exomes (n = 160), transcriptomes (n = 115), and low pass whole genomes (n = 146) from 167 gallbladder cancers (GBCs) from patients in Korea, India and Chile. In addition, we also sequence samples from 39 GBC high-risk patients and detect evidence of early cancer-related genomic lesions. Among the several significantly mutated genes not previously linked to GBC are ETS domain genes ELF3 and EHF, CTNNB1, APC, NSD1, KAT8, STK11 and NFE2L2. A majority of ELF3 alterations are frame-shift mutations that result in several cancer-specific neoantigens that activate T-cells indicating that they are cancer vaccine candidates. In addition, we identify recurrent alterations in KEAP1/NFE2L2 and WNT pathway in GBC. Taken together, these define multiple targetable therapeutic interventions opportunities for GBC treatment and management.

ATF4 Regulates MYB to Increase γ-Globin in Response to Loss of ß-Globin.

ß-Hemoglobinopathies can trigger rapid production of red blood cells in a process known as stress erythropoiesis. Cellular stress prompts differentiating erythroid precursors to express high levels of fetal γ-globin. However, the mechanisms underlying γ-globin production during cellular stress are still poorly defined. Here, we use CRISPR-Cas genome editing to model the stress caused by reduced levels of adult ß-globin. We find that decreased ß-globin is sufficient to induce robust re-expression of γ-globin, and RNA sequencing (RNA-seq) of differentiating isogenic erythroid precursors implicates ATF4 as a causal regulator of this response. ATF4 binds within the HBS1L-MYB intergenic enhancer and regulates expression of MYB, a known γ-globin regulator. Overall, the reduction of ATF4 upon ß-globin knockout decreases the levels of MYB and BCL11A. Identification of ATF4 as a key regulator of globin compensation adds mechanistic insight to the poorly understood phenomenon of stress-induced globin compensation and could inform strategies to treat hemoglobinopathies.

Effect of progesterone on Candida albicans biofilm formation under acidic conditions: A transcriptomic analysis.

Vulvovaginal candidiasis (VVC) caused by Candida albicans is a common disease worldwide. A very important C. albicans virulence factor is its ability to form biofilms on epithelium and/or on intrauterine devices promoting VVC. It has been shown that VVC has a hormonal dependency and that progesterone affects virulence traits of C. albicans cells. To understand how the acidic environment (pH 4) and progesterone (either alone and in combination) modulate C. albicans response during formation of biofilm, a transcriptomic analysis was performed together with characterization of the biofilm properties. Compared to planktonic cells, acidic biofilm-cells exhibited major changes in their transcriptome, including modifications in the expression of 286 genes that were not previously associated with biofilm formation in C. albicans. The vast majority of the genes up-regulated in the acidic biofilm cells (including those uniquely identified in our study) are known targets of Sfl1, and consistently, Sfl1 deletion is herein shown to impair the formation of acidic biofilms (pH 4). Under the acidic conditions used, the presence of progesterone reduced C. albicans biofilm biomass and structural cohesion. Transcriptomic analysis of biofilms developed in the presence of progesterone led to the identification of 65 down-regulated genes including, among others, the regulator Tec1 and several of its target genes, suggesting that the function of this transcription factor is inhibited by the presence of the hormone. Additionally, progesterone reduced the susceptibility of biofilm cells to fluconazole, consistent with an up-regulation of efflux pumps. Overall, the results of this study show that progesterone modulates C. albicans biofilm formation and genomic expression under acidic conditions, which may have implications for C. albicans pathogenicity in the vaginal environment.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies.

The CgHaa1-Regulon Mediates Response and Tolerance to Acetic Acid Stress in the Human Pathogen Candida glabrata.

To thrive in the acidic vaginal tract, Candida glabrata has to cope with high concentrations of acetic acid. The mechanisms underlying C. glabrata tolerance to acetic acid at low pH remain largely uncharacterized. In this work, the essential role of the CgHaa1 transcription factor (encoded by ORF CAGL0L09339g) in the response and tolerance of C. glabrata to acetic acid is demonstrated. Transcriptomic analysis showed that CgHaa1 regulates, directly or indirectly, the expression of about 75% of the genes activated under acetic acid stress. CgHaa1-activated targets are involved in multiple physiological functions including membrane transport, metabolism of carbohydrates and amino acids, regulation of the activity of the plasma membrane H+-ATPase, and adhesion. Under acetic acid stress, CgHaa1 increased the activity and the expression of the CgPma1 proton pump and contributed to increased colonization of vaginal epithelial cells by C. glabrata CgHAA1, and two identified CgHaa1-activated targets, CgTPO3 and CgHSP30, are herein demonstrated to be determinants of C. glabrata tolerance to acetic acid. The protective effect of CgTpo3 and of CgHaa1 was linked to a role of these proteins in reducing the accumulation of acetic acid inside C. glabrata cells. In response to acetic acid stress, marked differences were found in the regulons controlled by CgHaa1 and by its S. cerevisiae ScHaa1 ortholog, demonstrating a clear divergent evolution of the two regulatory networks. The results gathered in this study significantly advance the understanding of the molecular mechanisms underlying the success of C. glabrata as a vaginal colonizer.

Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer.

UNLABELLED: Breast cancer is one of the most frequent cancers among women. Extensive studies into the molecular heterogeneity of breast cancer have produced a plethora of molecular subtype classification and prognosis prediction algorithms, as well as numerous gene expression signatures. However, reimplementation of these algorithms is a tedious but important task to enable comparison of existing signatures and classification models between each other and with new models. Here, we present the genefu R/Bioconductor package, a multi-tiered compendium of bioinformatics algorithms and gene signatures for molecular subtyping and prognostication in breast cancer. AVAILABILITY AND IMPLEMENTATION: The genefu package is available from Bioconductor. http://www.bioconductor.org/packages/devel/bioc/html/genefu.html Source code is also available on Github https://github.com/bhklab/genefu CONTACT: bhaibeka@uhnresearch.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RamiGO: an R/Bioconductor package providing an AmiGO visualize interface.

SUMMARY: The R/Bioconductor package RamiGO is an R interface to AmiGO that enables visualization of Gene Ontology (GO) trees. Given a list of GO terms, RamiGO uses the AmiGO visualize API to import Graphviz-DOT format files into R, and export these either as images (SVG, PNG) or into Cytoscape for extended network analyses. RamiGO provides easy customization of annotation, highlighting of specific GO terms, colouring of terms by P-value or export of a simplified summary GO tree. We illustrate RamiGO functionalities in a genome-wide gene set analysis of prognostic genes in breast cancer. AVAILABILITY AND IMPLEMENTATION: RamiGO is provided in R/Bioconductor, is open source under the Artistic-2.0 License and is available with a user manual containing installation, operating instructions and tutorials. It requires R version 2.15.0 or higher. URL: http://bioconductor.org/packages/release/bioc/html/RamiGO.html

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures.

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a 'basket' feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org.

survcomp: an R/Bioconductor package for performance assessment and comparison of survival models.

SUMMARY: The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models; (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework; and (iii) statistically compare the performance of competitive models.