IKAROS and AIOLOS directly regulate AP-1 transcriptional complexes and are essential for NK cell development.

Ikaros transcription factors are essential for adaptive lymphocyte function, yet their role in innate lymphopoiesis is unknown. Using conditional genetic inactivation, we show that Ikzf1/Ikaros is essential for normal natural killer (NK) cell lymphopoiesis and IKZF1 directly represses Cish, a negative regulator of interleukin-15 receptor resulting in impaired interleukin-15 receptor signaling. Both Bcl2l11 and BIM levels, and intrinsic apoptosis were increased in Ikzf1-null NK cells, which in part accounts for NK lymphopenia as both were restored to normal levels when Ikzf1 and Bcl2l11 were co-deleted. Ikzf1-null NK cells presented extensive transcriptional alterations with reduced AP-1 transcriptional complex expression and increased expression of Ikzf2/Helios and Ikzf3/Aiolos. IKZF1 and IKZF3 directly bound AP-1 family members and deletion of both Ikzf1 and Ikzf3 in NK cells resulted in further reductions in Jun/Fos expression and complete loss of peripheral NK cells. Collectively, we show that Ikaros family members are important regulators of apoptosis, cytokine responsiveness and AP-1 transcriptional activity.

Synthetic Epigenetic Reprogramming of Mesenchymal to Epithelial States Using the CRISPR/dCas9 Platform in Triple Negative Breast Cancer.

Epithelial-mesenchymal transition (EMT) is a reversible transcriptional program invoked by cancer cells to drive cancer progression. Transcription factor ZEB1 is a master regulator of EMT, driving disease recurrence in poor-outcome triple negative breast cancers (TNBCs). Here, this work silences ZEB1 in TNBC models by CRISPR/dCas9-mediated epigenetic editing, resulting in highly-specific and nearly complete suppression of ZEB1 in vivo, accompanied by long-lasting tumor inhibition. Integrated "omic" changes promoted by dCas9 linked to the KRAB domain (dCas9-KRAB) enabled the discovery of a ZEB1-dependent-signature of 26 genes differentially-expressed and -methylated, including the reactivation and enhanced chromatin accessibility in cell adhesion loci, outlining epigenetic reprogramming toward a more epithelial state. In the ZEB1 locus transcriptional silencing is associated with induction of locally-spread heterochromatin, significant changes in DNA methylation at specific CpGs, gain of H3K9me3, and a near complete erasure of H3K4me3 in the ZEB1 promoter. Epigenetic shifts induced by ZEB1-silencing are enriched in a subset of human breast tumors, illuminating a clinically-relevant hybrid-like state. Thus, the synthetic epi-silencing of ZEB1 induces stable "lock-in" epigenetic reprogramming of mesenchymal tumors associated with a distinct and stable epigenetic landscape. This work outlines epigenome-engineering approaches for reversing EMT and customizable precision molecular oncology approaches for targeting poor outcome breast cancers.

Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma.

BACKGROUND: Epigenetic silencing of tumor suppressor genes (TSGs) is a key feature of oncogenesis in hepatocellular carcinoma (HCC). Liver-targeted delivery of CRISPR-activation (CRISPRa) systems makes it possible to exploit chromatin plasticity, by reprogramming transcriptional dysregulation. RESULTS: Using The Cancer Genome Atlas HCC data, we identify 12 putative TSGs with negative associations between promoter DNA methylation and transcript abundance, with limited genetic alterations. All HCC samples harbor at least one silenced TSG, suggesting that combining a specific panel of genomic targets could maximize efficacy, and potentially improve outcomes as a personalized treatment strategy for HCC patients. Unlike epigenetic modifying drugs lacking locus selectivity, CRISPRa systems enable potent and precise reactivation of at least 4 TSGs tailored to representative HCC lines. Concerted reactivation of HHIP, MT1M, PZP, and TTC36 in Hep3B cells inhibits multiple facets of HCC pathogenesis, such as cell viability, proliferation, and migration. CONCLUSIONS: By combining multiple effector domains, we demonstrate the utility of a CRISPRa toolbox of epigenetic effectors and gRNAs for patient-specific treatment of aggressive HCC.

Removing unwanted variation from large-scale RNA sequencing data with PRPS.

Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq) data, especially when the data come from large and complex studies. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we examined several sources of unwanted variation and demonstrate here how these can significantly compromise various downstream analyses, including cancer subtype identification, association between gene expression and survival outcomes and gene co-expression analysis. We propose a strategy, called pseudo-replicates of pseudo-samples (PRPS), for deploying our recently developed normalization method, called removing unwanted variation III (RUV-III), to remove the variation caused by library size, tumor purity and batch effects in TCGA RNA-seq data. We illustrate the value of our approach by comparing it to the standard TCGA normalizations on several TCGA RNA-seq datasets. RUV-III with PRPS can be used to integrate and normalize other large transcriptomic datasets coming from multiple laboratories or platforms.

TGFß and CIS Inhibition Overcomes NK-cell Suppression to Restore Antitumor Immunity.

Antibodies targeting "immune checkpoints" have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8+ T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK-cell antitumor function is dependent on the cytokine IL15. Ablation of the IL15 signaling inhibitor CIS (Cish) enhances NK-cell antitumor immunity by increasing NK-cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK-cell fitness via the production of immunosuppressive transforming growth factor ß (TGFß), a suppression which occurs even in the presence of high IL15 signaling. Here, we identified an unexpected interaction between CIS and the TGFß signaling pathway in NK cells. Independently, Cish- and Tgfbr2-deficient NK cells are both hyperresponsive to IL15 and hyporesponsive to TGFß, with dramatically enhanced antitumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anticancer immunity.

Computational Screening of Anti-Cancer Drugs Identifies a New BRCA Independent Gene Expression Signature to Predict Breast Cancer Sensitivity to Cisplatin.

The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy. Here, we generated a series of predictive gene signatures to estimate the sensitivity of breast cancer samples to 90 drugs, comprising FDA-approved drugs or compounds in early development. To achieve this, we used a cell line-based drug screen with matched transcriptomic data to derive in silico models that we validated in large independent datasets obtained from cell lines and patient-derived xenograft (PDX) models. Robust computational signatures were obtained for 28 drugs and used to predict drug efficacy in a set of PDX models. We found that our signature for cisplatin can be used to identify tumors that are likely to respond to this drug, even in absence of the BRCA-1 mutation routinely used to select patients for platinum-based therapies. This clinically relevant observation was confirmed in multiple PDXs. Our study foreshadows an effective delivery approach for precision medicine.

Targeting WEE1/AKT Restores p53-Dependent Natural Killer-Cell Activation to Induce Immune Checkpoint Blockade Responses in "Cold" Melanoma.

Immunotherapy has revolutionized cancer treatment. Unfortunately, most tumor types do not respond to immunotherapy due to a lack of immune infiltration or "cold" tumor microenvironment (TME), a contributing factor in treatment failure. Activation of the p53 pathway can increase apoptosis of cancer cells, leading to enhanced antigen presentation, and can stimulate natural killer (NK) cells through expression of stress ligands. Therefore, modulation of the p53 pathway in cancer cells with wild-type TP53 has the potential to enhance tumor immunogenicity to NK cells, produce an inflammatory TME, and ultimately lead to tumor regression. In this study, we report simultaneous targeting of the AKT/WEE1 pathways is a novel and tolerable approach to synergistically induce p53 activation to inhibit tumor development. This approach reduced the growth of melanoma cells and induced plasma membrane surface localization of the ER-resident protein calreticulin, an indicator of immunogenic cell death (ICD). Increase in ICD led to enhanced expression of stress ligands recognized by the activating NK-cell receptor NKG2D, promoting tumor lysis. WEE1/AKT inhibition resulted in recruitment and activation of immune cells, including NK cells, in the TME, triggering an inflammatory cascade that transformed the "cold" TME of B16F10 melanoma into a "hot" TME that responded to anti-programmed cell death protein 1 (anti-PD-1), resulting in complete regression of established tumors. These results suggest that AKT/WEE1 pathway inhibition is a potential approach to broaden the utility of class-leading anti-PD-1 therapies by enhancing p53-mediated, NK cell-dependent tumor inflammation and supports the translation of this novel approach to further improve response rates for metastatic melanoma.

A new natural killer cell-specific gene signature predicting recurrence in colorectal cancer patients.

The protective role of Natural Killer (NK) cell tumour immunosurveillance has long been recognised in colorectal cancer (CRC). However, as most patients show limited intra-tumoral NK cell infiltration, improving our ability to identify those with high NK cell activity might aid in dissecting the molecular features which underlie NK cell sensitivity. Here, a novel CRC-specific NK cell gene signature that infers NK cell load in primary tissue samples was derived and validated in multiple patient CRC cohorts. In contrast with other NK cell gene signatures that have several overlapping genes across different immune cell types, our NK cell signature has been extensively refined to be specific for CRC-infiltrating NK cells. The specificity of the signature is substantiated in tumour-infiltrating NK cells from primary CRC tumours at the single cell level, and the signature includes genes representative of NK cells of different maturation states, activation status and anatomical origin. Our signature also accurately discriminates murine NK cells, demonstrating the applicability of this geneset when mining datasets generated from preclinical studies. Differential gene expression analysis revealed tumour-intrinsic features associated with NK cell inclusion versus exclusion in CRC patients, with those tumours with predicted high NK activity showing strong evidence of enhanced chemotactic and cytotoxic transcriptional programs. Furthermore, survival modelling indicated that NK signature expression is associated with improved survival outcomes in CRC patients. Thus, scoring CRC samples with this refined NK cell signature might aid in identifying patients with high NK cell activity who could be prime candidates for NK cell directed immunotherapies.

The Ratio of Exhausted to Resident Infiltrating Lymphocytes Is Prognostic for Colorectal Cancer Patient Outcome.

Immunotherapy success in colorectal cancer is mainly limited to patients whose tumors exhibit high microsatellite instability (MSI). However, there is variability in treatment outcomes within this group, which is in part driven by the frequency and characteristics of tumor-infiltrating immune cells. Indeed, the presence of specific infiltrating immune-cell subsets has been shown to correlate with immunotherapy response and is in many cases prognostic of treatment outcome. Tumor-infiltrating lymphocytes (TIL) can undergo distinct differentiation programs, acquiring features of tissue-residency or exhaustion, a process during which T cells upregulate inhibitory receptors, such as PD-1, and lose functionality. Although residency and exhaustion programs of CD8+ T cells are relatively well studied, these programs have only recently been appreciated in CD4+ T cells and remain largely unknown in tumor-infiltrating natural killer (NK) cells. In this study, we used single-cell RNA sequencing (RNA-seq) data to identify signatures of residency and exhaustion in colorectal cancer-infiltrating lymphocytes, including CD8+, CD4+, and NK cells. We then tested these signatures in independent single-cell data from tumor and normal tissue-infiltrating immune cells. Furthermore, we used versions of these signatures designed for bulk RNA-seq data to explore tumor-intrinsic mutations associated with residency and exhaustion from TCGA data. Finally, using two independent transcriptomic datasets from patients with colon adenocarcinoma, we showed that combinations of these signatures, in particular combinations of NK-cell activity signatures, together with tumor-associated signatures, such as TGFß signaling, were associated with distinct survival outcomes in patients with colon adenocarcinoma.

CSK-homologous kinase (CHK/MATK) is a potential colorectal cancer tumour suppressor gene epigenetically silenced by promoter methylation.

Hyperactivation of SRC-family protein kinases (SFKs) contributes to the initiation and progression of human colorectal cancer (CRC). Since oncogenic mutations of SFK genes are rare in human CRC, we investigated if SFK hyperactivation is linked to dysregulation of their upstream inhibitors, C-terminal SRC kinase (CSK) and its homolog CSK-homologous kinase (CHK/MATK). We demonstrate that expression of CHK/MATK but not CSK was significantly downregulated in CRC cell lines and primary tumours compared to normal colonic tissue. Investigation of the mechanism by which CHK/MATK expression is down-regulated in CRC cells uncovered hypermethylation of the CHK/MATK promoter in CRC cell lines and primary tumours. Promoter methylation of CHK/MATK was also observed in several other tumour types. Consistent with epigenetic silencing of CHK/MATK, genetic deletion or pharmacological inhibition of DNA methyltransferases increased CHK/MATK mRNA expression in CHK/MATK-methylated colon cancer cell lines. SFKs were hyperactivated in CHK/MATK-methylated CRC cells despite expressing enzymatically active CSK, suggesting loss of CHK/MATK contributes to SFK hyperactivation. Re-expression of CHK/MATK in CRC cell lines led to reduction in SFK activity via a non-catalytic mechanism, a reduction in anchorage-independent growth, cell proliferation and migration in vitro, and a reduction in tumour growth and metastasis in a zebrafish embryo xenotransplantation model in vivo, collectively identifying CHK/MATK as a novel putative tumour suppressor gene in CRC. Furthermore, our discovery that CHK/MATK hypermethylation occurs in the majority of tumours warrants its further investigation as a diagnostic marker of CRC.

Using singscore to predict mutation status in acute myeloid leukemia from transcriptomic signatures.

Advances in RNA sequencing (RNA-seq) technologies that measure the transcriptome of biological samples have revolutionised our ability to understand transcriptional regulatory programs that underpin diseases such as cancer. We recently published singscore - a single sample, rank-based gene set scoring method which quantifies how concordant the transcriptional profile of individual samples are relative to specific gene sets of interest. Here we demonstrate the application of singscore to investigate transcriptional profiles associated with specific mutations or genetic lesions in acute myeloid leukemia. Using matched genomic and transcriptomic data available through the TCGA we show that scoring of appropriate signatures can distinguish samples with corresponding mutations, reflecting the ability of these mutations to drive aberrant transcriptional programs involved in leukemogenesis. We believe the singscore method is particularly useful for studying heterogeneity within a specific subsets of cancers, and as demonstrated, we show the ability of singscore to identify where alternative mutations appear to drive similar transcriptional programs.

A Gene Signature Predicting Natural Killer Cell Infiltration and Improved Survival in Melanoma Patients.

Natural killer (NK) cell activity is essential for initiating antitumor responses and may be linked to immunotherapy success. NK cells and other innate immune components could be exploitable for cancer treatment, which drives the need for tools and methods that identify therapeutic avenues. Here, we extend our gene-set scoring method singscore to investigate NK cell infiltration by applying RNA-seq analysis to samples from bulk tumors. Computational methods have been developed for the deconvolution of immune cell types within solid tumors. We have taken the NK cell gene signatures from several such tools, then curated the gene list using a comparative analysis of tumors and immune cell types. Using a gene-set scoring method to investigate RNA-seq data from The Cancer Genome Atlas (TCGA), we show that patients with metastatic cutaneous melanoma have an improved survival rate if their tumor shows evidence of NK cell infiltration. Furthermore, these survival effects are enhanced in tumors that show higher expression of genes that encode NK cell stimuli such as the cytokine IL15 Using this signature, we then examine transcriptomic data to identify tumor and stromal components that may influence the penetrance of NK cells into solid tumors. Our results provide evidence that NK cells play a role in the regulation of human tumors and highlight potential survival effects associated with increased NK cell activity. Our computational analysis identifies putative gene targets that may be of therapeutic value for boosting NK cell antitumor immunity.

Single sample scoring of molecular phenotypes.

BACKGROUND: Gene set scoring provides a useful approach for quantifying concordance between sample transcriptomes and selected molecular signatures. Most methods use information from all samples to score an individual sample, leading to unstable scores in small data sets and introducing biases from sample composition (e.g. varying numbers of samples for different cancer subtypes). To address these issues, we have developed a truly single sample scoring method, and associated R/Bioconductor package singscore ( https://bioconductor.org/packages/singscore ). RESULTS: We use multiple cancer data sets to compare singscore against widely-used methods, including GSVA, z-score, PLAGE, and ssGSEA. Our approach does not depend upon background samples and scores are thus stable regardless of the composition and number of samples being scored. In contrast, scores obtained by GSVA, z-score, PLAGE and ssGSEA can be unstable when less data are available (NS < 25). The singscore method performs as well as the best performing methods in terms of power, recall, false positive rate and computational time, and provides consistently high and balanced performance across all these criteria. To enhance the impact and utility of our method, we have also included a set of functions implementing visual analysis and diagnostics to support the exploration of molecular phenotypes in single samples and across populations of data. CONCLUSIONS: The singscore method described here functions independent of sample composition in gene expression data and thus it provides stable scores, which are particularly useful for small data sets or data integration. Singscore performs well across all performance criteria, and includes a suite of powerful visualization functions to assist in the interpretation of results. This method performs as well as or better than other scoring approaches in terms of its power to distinguish samples with distinct biology and its ability to call true differential gene sets between two conditions. These scores can be used for dimensional reduction of transcriptomic data and the phenotypic landscapes obtained by scoring samples against multiple molecular signatures may provide insights for sample stratification.

Combinatorial Targeting by MicroRNAs Co-ordinates Post-transcriptional Control of EMT.

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression, functioning in part by facilitating the degradation of target mRNAs. They have an established role in controlling epithelial-mesenchymal transition (EMT), a reversible phenotypic program underlying normal and pathological processes. Many studies demonstrate the role of individual miRNAs using overexpression at levels greatly exceeding physiological abundance. This can influence transcripts with relatively poor targeting and may in part explain why over 130 different miRNAs are directly implicated as EMT regulators. Analyzing a human mammary cell model of EMT we found evidence that a set of miRNAs, including the miR-200 and miR-182/183 family members, co-operate in post-transcriptional regulation, both reinforcing and buffering transcriptional output. Investigating this, we demonstrate that combinatorial treatment altered cellular phenotype with miRNA concentrations much closer to endogenous levels and with less off-target effects. This suggests that co-operative targeting by miRNAs is important for their physiological function and future work classifying miRNAs should consider such combinatorial effects.

A Transcriptional Program for Detecting TGFß-Induced EMT in Cancer.

Most cancer deaths are due to metastasis, and epithelial-to-mesenchymal transition (EMT) plays a central role in driving cancer cell metastasis. EMT is induced by different stimuli, leading to different signaling patterns and therapeutic responses. TGFß is one of the best-studied drivers of EMT, and many drugs are available to target this signaling pathway. A comprehensive bioinformatics approach was employed to derive a signature for TGFß-induced EMT which can be used to score TGFß-driven EMT in cells and clinical specimens. Considering this signature in pan-cancer cell and tumor datasets, a number of cell lines (including basal B breast cancer and cancers of the central nervous system) show evidence for TGFß-driven EMT and carry a low mutational burden across the TGFß signaling pathway. Furthermore, significant variation is observed in the response of high scoring cell lines to some common cancer drugs. Finally, this signature was applied to pan-cancer data from The Cancer Genome Atlas to identify tumor types with evidence of TGFß-induced EMT. Tumor types with high scores showed significantly lower survival rates than those with low scores and also carry a lower mutational burden in the TGFß pathway. The current transcriptomic signature demonstrates reproducible results across independent cell line and cancer datasets and identifies samples with strong mesenchymal phenotypes likely to be driven by TGFß.Implications: The TGFß-induced EMT signature may be useful to identify patients with mesenchymal-like tumors who could benefit from targeted therapeutics to inhibit promesenchymal TGFß signaling and disrupt the metastatic cascade. Mol Cancer Res; 15(5); 619-31. ©2017 AACR.

Stimulus-dependent differences in signalling regulate epithelial-mesenchymal plasticity and change the effects of drugs in breast cancer cell lines.

INTRODUCTION: The normal process of epithelial mesenchymal transition (EMT) is subverted by carcinoma cells to facilitate metastatic spread. Cancer cells rarely undergo a full conversion to the mesenchymal phenotype, and instead adopt positions along the epithelial-mesenchymal axis, a propensity we refer to as epithelial mesenchymal plasticity (EMP). EMP is associated with increased risk of metastasis in breast cancer and consequent poor prognosis. Drivers towards the mesenchymal state in malignant cells include growth factor stimulation or exposure to hypoxic conditions. METHODS: We have examined EMP in two cell line models of breast cancer: the PMC42 system (PMC42-ET and PMC42-LA sublines) and MDA-MB-468 cells. Transition to a mesenchymal phenotype was induced across all three cell lines using epidermal growth factor (EGF) stimulation, and in MDA-MB-468 cells by hypoxia. We used RNA sequencing to identify gene expression changes that occur as cells transition to a more-mesenchymal phenotype, and identified the cell signalling pathways regulated across these experimental systems. We then used inhibitors to modulate signalling through these pathways, verifying the conclusions of our transcriptomic analysis. RESULTS: We found that EGF and hypoxia both drive MDA-MB-468 cells to phenotypically similar mesenchymal states. Comparing the transcriptional response to EGF and hypoxia, we have identified differences in the cellular signalling pathways that mediate, and are influenced by, EMT. Significant differences were observed for a number of important cellular signalling components previously implicated in EMT, such as HBEGF and VEGFA. We have shown that EGF- and hypoxia-induced transitions respond differently to treatment with chemical inhibitors (presented individually and in combinations) in these breast cancer cells. Unexpectedly, MDA-MB-468 cells grown under hypoxic growth conditions became even more mesenchymal following exposure to certain kinase inhibitors that prevent growth-factor induced EMT, including the mTOR inhibitor everolimus and the AKT1/2/3 inhibitor AZD5363. CONCLUSIONS: While resulting in a common phenotype, EGF and hypoxia induced subtly different signalling systems in breast cancer cells. Our findings have important implications for the use of kinase inhibitor-based therapeutic interventions in breast cancers, where these heterogeneous signalling landscapes will influence the therapeutic response.