Community assessment of methods to deconvolve cellular composition from bulk gene expression.

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery.

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.

De novo genome assembly and analysis unveil biosynthetic and metabolic potentials of Pseudomonas fragi A13BB.

OBJECTIVES: The role of rhizosphere microbiome in supporting plant growth under biotic stress is well documented. Rhizobacteria ward off phytopathogens through various mechanisms including antibiosis. We sought to recover novel antibiotic-producing bacterial strains from soil samples collected from the rhizosphere. Pseudomonas fragi A13BB was recovered as part of this effort, and the whole genome was sequenced to facilitate mining for potential antibiotic-encoding biosynthetic gene clusters. DATA DESCRIPTION: Here, we report the complete genome sequence of P. fragi A13BB obtained from de novo assembly of Illumina MiSeq and GridION reads. The 4.94 Mb genome consists of a single chromosome with a GC content of 59.40%. Genomic features include 4410 CDSs, 102 RNAs, 3 CRISPR arrays, 3 prophage regions, and 37 predicted genomic islands. Two ß-lactone biosynthetic gene clusters were identified; besides, metabolic products of these are known to show antibiotic and/or anticancer properties. A siderophore biosynthetic gene cluster was also identified even though P. fragi is considered a non-siderophore producing pseudomonad. Other gene clusters of broad interest identified include those associated with bioremediation, biocontrol, plant growth promotion, or environmental adaptation. This dataset unveils various un-/underexplored metabolic or biosynthetic potential of P. fragi and provides insight into molecular mechanisms underpinning these attributes.

PBRM1 Deficiency Confers Synthetic Lethality to DNA Repair Inhibitors in Cancer.

Inactivation of Polybromo 1 (PBRM1), a specific subunit of the PBAF chromatin remodeling complex, occurs frequently in cancer, including 40% of clear cell renal cell carcinomas (ccRCC). To identify novel therapeutic approaches to targeting PBRM1-defective cancers, we used a series of orthogonal functional genomic screens that identified PARP and ATR inhibitors as being synthetic lethal with PBRM1 deficiency. The PBRM1/PARP inhibitor synthetic lethality was recapitulated using several clinical PARP inhibitors in a series of in vitro model systems and in vivo in a xenograft model of ccRCC. In the absence of exogenous DNA damage, PBRM1-defective cells exhibited elevated levels of replication stress, micronuclei, and R-loops. PARP inhibitor exposure exacerbated these phenotypes. Quantitative mass spectrometry revealed that multiple R-loop processing factors were downregulated in PBRM1-defective tumor cells. Exogenous expression of the R-loop resolution enzyme RNase H1 reversed the sensitivity of PBRM1-deficient cells to PARP inhibitors, suggesting that excessive levels of R-loops could be a cause of this synthetic lethality. PARP and ATR inhibitors also induced cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS/STING) innate immune signaling in PBRM1-defective tumor cells. Overall, these findings provide the preclinical basis for using PARP inhibitors in PBRM1-defective cancers. SIGNIFICANCE: This study demonstrates that PARP and ATR inhibitors are synthetic lethal with the loss of PBRM1, a PBAF-specific subunit, thus providing the rationale for assessing these inhibitors in patients with PBRM1-defective cancer. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/11/2888/F1.large.jpg.

CRI iAtlas: an interactive portal for immuno-oncology research.

The Cancer Research Institute (CRI) iAtlas is an interactive web platform for data exploration and discovery in the context of tumors and their interactions with the immune microenvironment. iAtlas allows researchers to study immune response characterizations and patterns for individual tumor types, tumor subtypes, and immune subtypes. iAtlas supports computation and visualization of correlations and statistics among features related to the tumor microenvironment, cell composition, immune expression signatures, tumor mutation burden, cancer driver mutations, adaptive cell clonality, patient survival, expression of key immunomodulators, and tumor infiltrating lymphocyte (TIL) spatial maps. iAtlas was launched to accompany the release of the TCGA PanCancer Atlas and has since been expanded to include new capabilities such as (1) user-defined loading of sample cohorts, (2) a tool for classifying expression data into immune subtypes, and (3) integration of TIL mapping from digital pathology images. We expect that the CRI iAtlas will accelerate discovery and improve patient outcomes by providing researchers access to standardized immunogenomics data to better understand the tumor immune microenvironment and its impact on patient responses to immunotherapy.

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

Correction to: RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking.

Following publication of the original article [1], the authors provided an updated accession number in the "Availability of data and materials" section of the declarations.

Whole blood RNA sequencing reveals a unique transcriptomic profile in patients with ARDS following hematopoietic stem cell transplantation.

BACKGROUND: The acute respiratory distress syndrome (ARDS) is characterized by the acute onset of hypoxemia and bilateral lung infiltrates in response to an inciting event, and is associated with high morbidity and mortality. Patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are at increased risk for ARDS. We hypothesized that HSCT patients with ARDS would have a unique transcriptomic profile identifiable in peripheral blood compared to those that did not undergo HSCT. METHODS: We isolated RNA from banked peripheral blood samples from a biorepository of critically ill ICU patients. RNA-Seq was performed on 11 patients with ARDS (5 that had undergone HSCT and 6 that had not) and 12 patients with sepsis without ARDS (5 that that had undergone HCST and 7 that had not). RESULTS: We identified 687 differentially expressed genes between ARDS and ARDS-HSCT (adjusted p-value < 0.01), including IFI44L, OAS3, LY6E, and SPATS2L that had increased expression in ARDS vs. ARDS-HSCT; these genes were not differentially expressed in sepsis vs sepsis-HSCT. Gene ontology enrichment analysis revealed that many differentially expressed genes were related to response to type I interferon. CONCLUSIONS: Our findings reveal significant differences in whole blood transcriptomic profiles of patients with non-HSCT ARDS compared to ARDS-HSCT patients and point toward different immune responses underlying ARDS and ARDS-HSCT that contribute to lung injury.

PARP inhibition enhances tumor cell-intrinsic immunity in ERCC1-deficient non-small cell lung cancer.

The cyclic GMP-AMP synthase/stimulator of IFN genes (cGAS/STING) pathway detects cytosolic DNA to activate innate immune responses. Poly(ADP-ribose) polymerase inhibitors (PARPi) selectively target cancer cells with DNA repair deficiencies such as those caused by BRCA1 mutations or ERCC1 defects. Using isogenic cell lines and patient-derived samples, we showed that ERCC1-defective non-small cell lung cancer (NSCLC) cells exhibit an enhanced type I IFN transcriptomic signature and that low ERCC1 expression correlates with increased lymphocytic infiltration. We demonstrated that clinical PARPi, including olaparib and rucaparib, have cell-autonomous immunomodulatory properties in ERCC1-defective NSCLC and BRCA1-defective triple-negative breast cancer (TNBC) cells. Mechanistically, PARPi generated cytoplasmic chromatin fragments with characteristics of micronuclei; these were found to activate cGAS/STING, downstream type I IFN signaling, and CCL5 secretion. Importantly, these effects were suppressed in PARP1-null TNBC cells, suggesting that this phenotype resulted from an on-target effect of PARPi on PARP1. PARPi also potentiated IFN-γ-induced PD-L1 expression in NSCLC cell lines and in fresh patient tumor cells; this effect was enhanced in ERCC1-deficient contexts. Our data provide a preclinical rationale for using PARPi as immunomodulatory agents in appropriately molecularly selected populations.

Integrative Genomics Analysis Identifies ACVR1B as a Candidate Causal Gene of Emphysema Distribution.

Genome-wide association studies (GWAS) have identified multiple associations with emphysema apicobasal distribution (EABD), but the biological functions of these variants are unknown. To characterize the functions of EABD-associated variants, we integrated GWAS results with 1) expression quantitative trait loci (eQTL) from the Genotype Tissue Expression (GTEx) project and subjects in the COPDGene (Genetic Epidemiology of COPD) study and 2) cell type epigenomic marks from the Roadmap Epigenomics project. On the basis of these analyses, we selected a variant near ACVR1B (activin A receptor type 1B) for functional validation. SNPs from 168 loci with P values less than 5 × 10-5 in the largest GWAS meta-analysis of EABD were analyzed. Eighty-four loci overlapped eQTL, with 12 of these loci showing greater than 80% likelihood of harboring a single, shared GWAS and eQTL causal variant. Seventeen cell types were enriched for overlap between EABD loci and Roadmap Epigenomics marks (permutation P < 0.05), with the strongest enrichment observed in CD4+, CD8+, and regulatory T cells. We selected a putative causal variant, rs7962469, associated with ACVR1B expression in lung tissue for additional functional investigation, and reporter assays confirmed allele-specific regulatory activity for this variant in human bronchial epithelial and Jurkat immune cell lines. ACVR1B expression levels exhibit a nominally significant association with emphysema distribution. EABD-associated loci are preferentially enriched in regulatory elements of multiple cell types, most notably T-cell subsets. Multiple EABD loci colocalize to regulatory elements that are active across multiple tissues and cell types, and functional analyses confirm the presence of an EABD-associated functional variant that regulates ACVR1B expression, indicating that transforming growth factor-ß signaling plays a role in the EABD phenotype. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

The Immune Landscape of Cancer.

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-ß dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.

RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking.

BACKGROUND: Cigarette smoking is the leading modifiable risk factor for disease and death worldwide. Previous studies quantifying gene-level expression have documented the effect of smoking on mRNA levels. Using RNA sequencing, it is possible to analyze the impact of smoking on complex regulatory phenomena (e.g. alternative splicing, differential isoform usage) leading to a more detailed understanding of the biology underlying smoking-related disease. METHODS: We used whole-blood RNA sequencing to describe gene and exon-level expression differences between 229 current and 286 former smokers in the COPDGene study. We performed differential gene expression and differential exon usage analyses using the voom/limma and DEXseq R packages. Samples from current and former smokers were compared while controlling for age, gender, race, lifetime smoke exposure, cell counts, and technical covariates. RESULTS: At an adjusted p-value <0.05, 171 genes were differentially expressed between current and former smokers. Differentially expressed genes included 7 long non-coding RNAs that have not been previously associated with smoking: LINC00599, LINC01362, LINC00824, LINC01624, RP11-563D10.1, RP11-98G13.1, AC004791.2. Secondary analysis of acute smoking (having smoked within 2-h) revealed 5 of the 171 smoking genes demonstrated an acute response above the baseline effect of chronic smoking. Exon-level analyses identified 9 exons from 8 genes with significant differential usage by smoking status, suggesting smoking-induced changes in isoform expression. CONCLUSIONS: Transcriptomic changes at the gene and exon levels from whole blood can refine our understanding of the molecular mechanisms underlying the response to smoking.

Novel function of a dynein light chain in actin assembly during clathrin-mediated endocytosis.

Clathrin- and actin-mediated endocytosis is essential in eukaryotic cells. In this study, we demonstrate that Tda2 is a novel protein of the endocytic machinery necessary for normal internalization of native cargo in yeast. Tda2 has not been classified in any protein family. Unexpectedly, solving the crystal structure of Tda2 revealed it belongs to the dynein light chain family. However, Tda2 works independently of the dynein motor complex and microtubules. Tda2 forms a tight complex with the polyproline motif-rich protein Aim21, which interacts physically with the SH3 domain of the Arp2/3 complex regulator Bbc1. The Tda2-Aim21 complex localizes to endocytic sites in a Bbc1- and filamentous actin-dependent manner. Importantly, the Tda2-Aim21 complex interacts directly with and facilitates the recruitment of actin-capping protein, revealing barbed-end filament capping at endocytic sites to be a regulated event. Thus, we have uncovered a new layer of regulation of the actin cytoskeleton by a member of a conserved protein family that has not been previously associated with a function in endocytosis.

An analysis of the operative experience of plastic surgery trainees in the United Kingdom using eLogbook.

INTRODUCTION: We performed a comprehensive analysis of the operative experience of UK Plastic Surgery Trainees using the web-based eLogbook. METHODS: An analysis of data recorded prospectively by Plastic Surgery Registrars 2010-2014 in eLogbook. RESULTS: The eLogbook data of 336 Specialty Registrars entered from 2010 to 2014 was analysed. Over the six-year training programme, trainees participated in a mean of 2117 procedures and performed a mean of 1571 procedures with or without supervision. We also determined the mean number of procedures for 14 indicative operative domains performed during training and compared these to current (2012) indicative numbers required prior to the award of a Certificate of Completion of Training (CCT). CONCLUSION: The eLogbook contains valuable data to determine the operative experience of UK Plastic Surgery trainees. This new data will be reflected in the updated indicative numbers required for CCT. Both trainees and trainers may use the data to monitor the acquisition of operative experience over time and target training where necessary.