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Summary: Although aberrant activation of the KRAS and PI3K pathway alongside TP53 mutations account for frequent aberrations in human gastric cancers, neither the sequence nor the individual contributions of these mutations have been clarified. Here, we establish an allelic series of mice to afford conditional expression in the glandular epithelium of KrasG12D;Pik3caH1047R or Trp53R172H and/or ablation of Pten or Trp53. We find that KrasG12D;Pik3caH1047R is sufficient to induce adenomas and that lesions progress to carcinoma when also harboring Pten deletions. An additional challenge with either Trp53 loss- or gain-of-function alleles further accelerated tumor progression and triggered metastatic disease. While tumor-intrinsic STAT3 signaling in response to gp130 family cytokines remained as a gatekeeper for all stages of tumor development, metastatic progression required a mutant Trp53-induced interleukin (IL)-11 to IL-6 dependency switch. Consistent with the poorer survival of patients with high IL-6 expression, we identify IL-6/STAT3 signaling as a therapeutic vulnerability for TP53-mutant gastric cancer.

Abstract Although gastric cancer is a leading cause of cancer-related deaths, systemic treatment strategies remain scarce. Here, we report the pro-tumorigenic properties of the crosstalk between intestinal tuft cells and type 2 innate lymphoid cells (ILC2) that is evolutionarily optimized for epithelial remodeling in response to helminth infection. We demonstrate that tuft cell-derived interleukin 25 (IL25) drives ILC2 activation, inducing the release of IL13 and promoting epithelial tuft cell hyperplasia. While the resulting tuft cell - ILC2 feed-forward circuit promotes gastric metaplasia and tumor formation, genetic depletion of tuft cells or ILC2s, or therapeutic targeting of IL13 or IL25 alleviates these pathologies in mice. In gastric cancer patients, tuft cell and ILC2 gene signatures predict worsening survival in intestinal-type gastric cancer where ~40% of the corresponding cancers show enriched co-existence of tuft cells and ILC2s. Our findings suggest a role for ILC2 and tuft cells, along with their associated cytokine IL13 and IL25 as gatekeepers and enablers of metaplastic transformation and gastric tumorigenesis, thereby providing an opportunity to therapeutically inhibit early-stage gastric cancer through repurposing antibody-mediated therapies.

Summary: Cancer immunotherapies have demonstrated remarkable success; however, the majority of patients do not respond or develop resistance. Here, we conduct epigenetic gene-targeted CRISPR-Cas9 screens to identify epigenomic factors that limit CD8+ T cell-mediated anti-tumor immunity. We identify that PRMT1 suppresses interferon gamma (Ifnγ)-induced MHC-I expression, thus dampening CD8+ T cell-mediated killing. Indeed, PRMT1 knockout or pharmacological targeting of type I PRMT with the clinical inhibitor GSK3368715 enhances Ifnγ-induced MHC-I expression through elevated STAT1 expression and activation, while re-introduction of PRMT1 in PRMT1-deficient cells reverses this effect. Importantly, loss of PRMT1 enhances the efficacy of anti-PD-1 immunotherapy, and The Cancer Genome Atlas analysis reveals that PRMT1 expression in human melanoma is inversely correlated with expression of human leukocyte antigen molecules, infiltration of CD8+ T cells, and overall survival. Taken together, we identify PRMT1 as a negative regulator of anti-tumor immunity, unveiling clinical type I PRMT inhibitors as immunotherapeutic agents or as adjuncts to existing immunotherapies.

Abstract Background RNA sequencing is currently the method of choice for genome-wide profiling of gene expression. A popular approach to quantify expression levels of genes from RNA-seq data is to map reads to a reference genome and then count mapped reads to each gene. Gene annotation data, which include chromosomal coordinates of exons for tens of thousands of genes, are required for this quantification process. There are several major sources of gene annotations that can be used for quantification, such as Ensembl and RefSeq databases. However, there is very little understanding of the effect that the choice of annotation has on the accuracy of gene expression quantification in an RNA-seq analysis. Results In this paper, we present results from our comparison of Ensembl and RefSeq human annotations on their impact on gene expression quantification using a benchmark RNA-seq dataset generated by the SEQC consortium. We show that the use of RefSeq gene annotation models led to better quantification accuracy, based on the correlation with ground truths including expression data from >800 real-time PCR validated genes, known titration ratios of gene expression and microarray expression data. We also found that the recent expansion of the RefSeq annotation has led to a decrease in its annotation accuracy. Finally, we demonstrated that the RNA-seq quantification differences observed between different annotations were not affected by the use of different normalization methods. Conclusion In conclusion, our study found that the use of the conservative RefSeq gene annotation yields better RNA-seq quantification results than the more comprehensive Ensembl annotation. We also found that, surprisingly, the recent expansion of the RefSeq database, which was primarily driven by the incorporation of sequencing data into the gene annotation process, resulted in a reduction in the accuracy of RNA-seq quantification.

Dietary extracellular vesicles (EVs) could potentially be absorbed by the intestinal tract of the host and exert multiple phenotypic changes. Here, the authors isolate and characterize EVs from raw and commercial bovine milk and show orally administered EVs to have a context specific role in promoting or suppressing primary tumor growth and metastasis in multiple mouse tumor models.

The transcription factor Bach2 is critical for T cell differentiation, but how it functions in Treg cells is unclear. Here the authors use a Treg-specific mouse model to show that Bach2 controls homeostasis and function of Treg cells by limiting DNA accessibility and activity of IRF4 in response to TCR signaling.

Abstract Exosomes are extracellular vesicles secreted by multiple cell types into the extracellular space. They contain cell-state specific cargos which often reflects the (patho)physiological condition of the cells/organism. Milk contains high amounts of exosomes and it is unclear whether their cargo is altered based on the lactation stage of the organism. Here, we isolated exosomes from bovine milk that were obtained at various stages of lactation and examined the content by quantitative proteomics. Exosomes were isolated by OptiPrep density gradient centrifugation from milk obtained from cow after 24, 48 and 72 h post calving. As control, exosomes were also isolated from cows during mid-lactation period which has been referred to as mature milk (MM). Biochemical and biophysical characterization of exosomes revealed the high abundance of exosomes in colostrum and MM samples. Quantitative proteomics analysis highlighted the change in the proteomic cargo of exosomes based on the lactation state of the cow. Functional enrichment analysis revealed that exosomes from colostrum are significantly enriched with proteins that can potentially regulate the immune response and growth. This study highlights the importance of exosomes in colostrum and hence opens up new avenues to exploit these vesicles in the regulation of the immune response and growth.

BackgroundThis study evaluated the feasibility of achieving high response rates in stage II or III breast cancer by tailoring neoadjuvant therapy using clinical and histopathological features and the Oncotype DX Breast Recurrence Score. Genomic determinants of response and resistance were also explored.Patients and outcome measuresFifty-one patients were enrolled. The primary cohort comprised 40 patients: 15 human epidermal growth factor receptor type 2 (HER2)-amplified; 15 triple-negative (TNBC); and ten hormone receptor (HR)-positive, HER2-non-amplified tumours; with recurrence scores ≥25. Patients were treated with epirubicin and cyclophosphamide, followed by nab-paclitaxel, with the addition of trastuzumab if HER2-amplified. The primary endpoint was pathological complete response (pCR) in the breast. Pre- and post-treatment tumour samples underwent variant burden, gene and gene pathway, mutational signature profile and clonal evolution analyses.ResultsThe pCR rates were: overall 55% (n = 22), HER2-amplified 80% (n = 12), triple-negative 46% (n = 7) and HR-positive, HER2-non-amplified 30% (n = 3). Grade 3 or 4 adverse events included febrile neutropenia (8%), neutropenia (18%), sensory neuropathy (5%), deranged transaminases (5%), fatigue (2%), diarrhoea (2%), and pneumothorax (2%). Molecular analyses demonstrated strong similarities between residual disease and matched primary tumour. ATM signalling pathway alterations and the presence of a COSMIC Signature 3 implied the majority of tumours contained some form of homologous repair deficiency. ATM pathway alterations were identified in the subset of TNBC patients who did not achieve pCR; Signature 3 was present in both pCR and non-pCR subgroups. Clonal evolution analyses demonstrated both persistence and emergence of chemoresistant clones.ConclusionsThis treatment regime resulted in a high rate of pCR, demonstrating that tailored neoadjuvant therapy using a genomic recurrence score is feasible and warrants further investigation. Molecular analysis revealed few commonalities between patients. For TNBC future clinical gains will require precision medicine, potentially using DNA sequencing to identify specific targets for individuals with resistant disease.Trial registrationClinicaltrials.gov NCT01830244.

Bioinformatics tools are imperative for the in depth analysis of heterogeneous high-throughput data. Most of the software tools are developed by specific laboratories or groups or companies wherein they are designed to perform the required analysis for the group. However, such software tools may fail to capture “what the community needs in a tool”. Here, we describe a novel community-driven approach to build a comprehensive functional enrichment analysis tool. Using the existing FunRich tool as a template, we invited researchers to request additional features and/or changes. Remarkably, with the enthusiastic participation of the community, we were able to implement 90% of the requested features. FunRich enables plugin for extracellular vesicles wherein users can download and analyse data from Vesiclepedia database. By involving researchers early through community needs software development, we believe that comprehensive analysis tools can be developed in various scientific disciplines.