The transcriptional co-repressor Runx1t1 is essential for MYCN-driven neuroblastoma tumorigenesis.

MYCN oncogene amplification is frequently observed in aggressive childhood neuroblastoma. Using an unbiased large-scale mutagenesis screen in neuroblastoma-prone transgenic mice, we identify a single germline point mutation in the transcriptional corepressor Runx1t1, which abolishes MYCN-driven tumorigenesis. This loss-of-function mutation disrupts a highly conserved zinc finger domain within Runx1t1. Deletion of one Runx1t1 allele in an independent Runx1t1 knockout mouse model is also sufficient to prevent MYCN-driven neuroblastoma development, and reverse ganglia hyperplasia, a known pre-requisite for tumorigenesis. Silencing RUNX1T1 in human neuroblastoma cells decreases colony formation in vitro, and inhibits tumor growth in vivo. Moreover, RUNX1T1 knockdown inhibits the viability of PAX3-FOXO1 fusion-driven rhabdomyosarcoma and MYC-driven small cell lung cancer cells. Despite the role of Runx1t1 in MYCN-driven tumorigenesis neither gene directly regulates the other. We show RUNX1T1 forms part of a transcriptional LSD1-CoREST3-HDAC repressive complex recruited by HAND2 to enhancer regions to regulate chromatin accessibility and cell-fate pathway genes.

ZMIZ1 enhances ERα-dependent expression of E2F2 in breast cancer.

The estrogen receptor-α (ER) drives 75% of breast cancers. On activation, the ER recruits and assembles a 1-2 MDa transcriptionally active complex. These complexes can modulate tumour growth, and understanding the roles of individual proteins within these complexes can help identify new therapeutic targets. Here, we present the discovery of ER and ZMIZ1 within the same multi-protein assembly by quantitative proteomics, and validated by proximity ligation assay. We characterise ZMIZ1 function by demonstrating a significant decrease in the proliferation of ER-positive cancer cell lines. To establish a role for the ER-ZMIZ1 interaction, we measured the transcriptional changes in the estrogen response post-ZMIZ1 knockdown using an RNA-seq time-course over 24 h. Gene set enrichment analysis of the ZMIZ1-knockdown data identified a specific delay in the response of estradiol-induced cell cycle genes. Integration of ENCODE data with our RNA-seq results identified that ER and ZMIZ1 both bind the promoter of E2F2. We therefore propose that ER and ZMIZ1 interact to enable the efficient estrogenic response at subset of cell cycle genes via a novel ZMIZ1-ER-E2F2 signalling axis. Finally, we show that high ZMIZ1 expression is predictive of worse patient outcome, ER and ZMIZ1 are co-expressed in breast cancer patients in TCGA and METABRIC, and the proteins are co-localised within the nuclei of tumour cell in patient biopsies. In conclusion, we establish that ZMIZ1 is a regulator of the estrogenic cell cycle response and provide evidence of the biological importance of the ER-ZMIZ1 interaction in ER-positive patient tumours, supporting potential clinical relevance.

Smoking-associated gene expression alterations in nasal epithelium reveal immune impairment linked to lung cancer risk.

BACKGROUND: Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to modifiable lifestyle risk in the form of tobacco smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, 40% of which occur more than 15 years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk remain unclear. We thus set out to examine whether risk stratification in the clinic and in the general population can be improved upon by the addition of genetic data and to explore the mechanisms of the persisting risk in former smokers. METHODS: We analysed transcriptomic data from accessible airway tissues of 487 subjects, including healthy volunteers and clinic patients of different smoking statuses. We developed a computational model to assess smoking-associated gene expression changes and their reversibility after smoking is stopped, comparing healthy subjects to clinic patients with and without lung cancer. RESULTS: We find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune- and interferon-related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. CONCLUSIONS: Our results provide initial evidence for germline-mediated personalized smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

Copper chelation suppresses epithelial-mesenchymal transition by inhibition of canonical and non-canonical TGF-ß signaling pathways in cancer.

BACKGROUND: Metastatic cancer cells exploit Epithelial-mesenchymal-transition (EMT) to enhance their migration, invasion, and resistance to treatments. Recent studies highlight that elevated levels of copper are implicated in cancer progression and metastasis. Clinical trials using copper chelators are associated with improved patient survival; however, the molecular mechanisms by which copper depletion inhibits tumor progression and metastasis are poorly understood. This remains a major hurdle to the clinical translation of copper chelators. Here, we propose that copper chelation inhibits metastasis by reducing TGF-ß levels and EMT signaling. Given that many drugs targeting TGF-ß have failed in clinical trials, partly because of severe side effects arising in patients, we hypothesized that copper chelation therapy might be a less toxic alternative to target the TGF-ß/EMT axis. RESULTS: Our cytokine array and RNA-seq data suggested a link between copper homeostasis, TGF-ß and EMT process. To validate this hypothesis, we performed single-cell imaging, protein assays, and in vivo studies. Here, we used the copper chelating agent TEPA to block copper trafficking. Our in vivo study showed a reduction of TGF-ß levels and metastasis to the lung in the TNBC mouse model. Mechanistically, TEPA significantly downregulated canonical (TGF-ß/SMAD2&3) and non-canonical (TGF-ß/PI3K/AKT, TGF-ß/RAS/RAF/MEK/ERK, and TGF-ß/WNT/ß-catenin) TGF-ß signaling pathways. Additionally, EMT markers of MMP-9, MMP-14, Vimentin, ß-catenin, ZEB1, and p-SMAD2 were downregulated, and EMT transcription factors of SNAI1, ZEB1, and p-SMAD2 accumulated in the cytoplasm after treatment. CONCLUSIONS: Our study suggests that copper chelation therapy represents a potentially effective therapeutic approach for targeting TGF-ß and inhibiting EMT in a diverse range of cancers.

Single-Cell Sequencing Identifies Master Regulators Affected by Panobinostat in Neuroblastoma Cells.

The molecular mechanisms and gene regulatory networks sustaining cell proliferation in neuroblastoma (NBL) cells are still not fully understood. In this tumor context, it has been proposed that anti-proliferative drugs, such as the pan-HDAC inhibitor panobinostat, could be tested to mitigate tumor progression. Here, we set out to investigate the effects of panobinostat treatment at the unprecedented resolution offered by single-cell sequencing. We identified a global senescence signature paired with reduction in proliferation in treated Kelly cells and more isolated transcriptional responses compatible with early neuronal differentiation. Using master regulator analysis, we identified BAZ1A, HCFC1, MAZ, and ZNF146 as the transcriptional regulators most significantly repressed by panobinostat. Experimental silencing of these transcription factors (TFs) confirmed their role in sustaining NBL cell proliferation in vitro.

Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data.

Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as 'signaling hubs'. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called 'SURFACER'. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.

Escalated (Dependent) Oxycodone Self-Administration Is Associated with Cognitive Impairment and Transcriptional Evidence of Neurodegeneration in Human Immunodeficiency Virus (HIV) Transgenic Rats.

Substance use disorder is associated with accelerated disease progression in people with human immunodeficiency virus (HIV; PWH). Problem opioid use, including high-dose opioid therapy, prescription drug misuse, and opioid abuse, is high and increasing in the PWH population. Oxycodone is a broadly prescribed opioid in both the general population and PWH. Here, we allowed HIV transgenic (Tg) rats and wildtype (WT) littermates to intravenously self-administer oxycodone under short-access (ShA) conditions, which led to moderate, stable, "recreational"-like levels of drug intake, or under long-access (LgA) conditions, which led to escalated (dependent) drug intake. HIV Tg rats with histories of oxycodone self-administration under LgA conditions exhibited significant impairment in memory performance in the novel object recognition (NOR) paradigm. RNA-sequencing expression profiling of the medial prefrontal cortex (mPFC) in HIV Tg rats that self-administered oxycodone under ShA conditions exhibited greater transcriptional evidence of inflammation than WT rats that self-administered oxycodone under the same conditions. HIV Tg rats that self-administered oxycodone under LgA conditions exhibited transcriptional evidence of an increase in neuronal injury and neurodegeneration compared with WT rats under the same conditions. Gene expression analysis indicated that glucocorticoid-dependent adaptations contributed to the gene expression effects of oxycodone self-administration. Overall, the present results indicate that a history of opioid intake promotes neuroinflammation and glucocorticoid dysregulation, and excessive opioid intake is associated with neurotoxicity and cognitive impairment in HIV Tg rats.

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patients with breast cancer, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed 'SURFACER'. METHODS: Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA versus normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2 and Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity. RESULTS: Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of five BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms. CONCLUSIONS: BRCA patients can be stratified into five surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.

Dual targeting of the epigenome via FACT complex and histone deacetylase is a potent treatment strategy for DIPG.

Diffuse intrinsic pontine glioma (DIPG) is an aggressive and incurable childhood brain tumor for which new treatments are needed. CBL0137 is an anti-cancer compound developed from quinacrine that targets facilitates chromatin transcription (FACT), a chromatin remodeling complex involved in transcription, replication, and DNA repair. We show that CBL0137 displays profound cytotoxic activity against a panel of patient-derived DIPG cultures by restoring tumor suppressor TP53 and Rb activity. Moreover, in an orthotopic model of DIPG, treatment with CBL0137 significantly extends animal survival. The FACT subunit SPT16 is found to directly interact with H3.3K27M, and treatment with CBL0137 restores both histone H3 acetylation and trimethylation. Combined treatment of CBL0137 with the histone deacetylase inhibitor panobinostat leads to inhibition of the Rb/E2F1 pathway and induction of apoptosis. The combination of CBL0137 and panobinostat significantly prolongs the survival of mice bearing DIPG orthografts, suggesting a potential treatment strategy for DIPG.

Copper: An Intracellular Achilles' Heel Allowing the Targeting of Epigenetics, Kinase Pathways, and Cell Metabolism in Cancer Therapeutics.

Copper is an essential transition metal frequently increased in cancer known to strongly influence essential cellular processes. Targeted therapy protocols utilizing both novel and repurposed drug agents initially demonstrate strong efficacy, before failing in advanced cancers as drug resistance develops and relapse occurs. Overcoming this limitation involves the development of strategies and protocols aimed at a wider targeting of the underlying molecular changes. Receptor Tyrosine Kinase signaling pathways, epigenetic mechanisms and cell metabolism are among the most common therapeutic targets, with molecular investigations increasingly demonstrating the strong influence each mechanism exerts on the others. Interestingly, all these mechanisms can be influenced by intracellular copper. We propose that copper chelating agents, already in clinical trial for multiple cancers, may simultaneously target these mechanisms across a wide variety of cancers, serving as an excellent candidate for targeted combination therapy. This review summarizes the known links between these mechanisms, copper, and copper chelation therapy.

A G316A Polymorphism in the Ornithine Decarboxylase Gene Promoter Modulates MYCN-Driven Childhood Neuroblastoma.

Ornithine decarboxylase (ODC1), a critical regulatory enzyme in polyamine biosynthesis, is a direct transcriptional target of MYCN, amplification of which is a powerful marker of aggressive neuroblastoma. A single nucleotide polymorphism (SNP), G316A, within the first intron of ODC1, results in genotypes wildtype GG, and variants AG/AA. CRISPR-cas9 technology was used to investigate the effects of AG clones from wildtype MYCN-amplified SK-N-BE(2)-C cells and the effect of the SNP on MYCN binding, and promoter activity was investigated using EMSA and luciferase assays. AG clones exhibited decreased ODC1 expression, growth rates, and histone acetylation and increased sensitivity to ODC1 inhibition. MYCN was a stronger transcriptional regulator of the ODC1 promoter containing the G allele, and preferentially bound the G allele over the A. Two neuroblastoma cohorts were used to investigate the clinical impact of the SNP. In the study cohort, the minor AA genotype was associated with improved survival, while poor prognosis was associated with the GG genotype and AG/GG genotypes in MYCN-amplified and non-amplified patients, respectively. These effects were lost in the GWAS cohort. We have demonstrated that the ODC1 G316A polymorphism has functional significance in neuroblastoma and is subject to allele-specific regulation by the MYCN oncoprotein.

A modular master regulator landscape controls cancer transcriptional identity.

Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.

Oncoprotein-specific molecular interaction maps (SigMaps) for cancer network analyses.

Tumor-specific elucidation of physical and functional oncoprotein interactions could improve tumorigenic mechanism characterization and therapeutic response prediction. Current interaction models and pathways, however, lack context specificity and are not oncoprotein specific. We introduce SigMaps as context-specific networks, comprising modulators, effectors and cognate binding-partners of a specific oncoprotein. SigMaps are reconstructed de novo by integrating diverse evidence sources-including protein structure, gene expression and mutational profiles-via the OncoSig machine learning framework. We first generated a KRAS-specific SigMap for lung adenocarcinoma, which recapitulated published KRAS biology, identified novel synthetic lethal proteins that were experimentally validated in three-dimensional spheroid models and established uncharacterized crosstalk with RAB/RHO. To show that OncoSig is generalizable, we first inferred SigMaps for the ten most mutated human oncoproteins and then for the full repertoire of 715 proteins in the COSMIC Cancer Gene Census. Taken together, these SigMaps show that the cell's regulatory and signaling architecture is highly tissue specific.

svpluscnv: analysis and visualization of complex structural variation data.

MOTIVATION: Despite widespread prevalence of somatic structural variations (SVs) across most tumor types, understanding of their molecular implications often remains poor. SVs are extremely heterogeneous in size and complexity, hindering the interpretation of their pathogenic role. Tools integrating large SV datasets across platforms are required to fully characterize the cancer's somatic landscape. RESULTS: svpluscnv R package is a swiss army knife for the integration and interpretation of orthogonal datasets including copy number variant segmentation profiles and sequencing-based structural variant calls. The package implements analysis and visualization tools to evaluate chromosomal instability and ploidy, identify genes harboring recurrent SVs and detects complex rearrangements such as chromothripsis and chromoplexia. Further, it allows systematic identification of hot-spot shattered genomic regions, showing reproducibility across alternative detection methods and datasets. AVAILABILITY AND IMPLEMENTATION: https://github.com/ccbiolab/svpluscnv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Intratumoral Copper Modulates PD-L1 Expression and Influences Tumor Immune Evasion.

Therapeutic checkpoint antibodies blocking programmed death receptor 1/programmed death ligand 1 (PD-L1) signaling have radically improved clinical outcomes in cancer. However, the regulation of PD-L1 expression on tumor cells is still poorly understood. Here we show that intratumoral copper levels influence PD-L1 expression in cancer cells. Deep analysis of the The Cancer Genome Atlas database and tissue microarrays showed strong correlation between the major copper influx transporter copper transporter 1 (CTR-1) and PD-L1 expression across many cancers but not in corresponding normal tissues. Copper supplementation enhanced PD-L1 expression at mRNA and protein levels in cancer cells and RNA sequencing revealed that copper regulates key signaling pathways mediating PD-L1-driven cancer immune evasion. Conversely, copper chelators inhibited phosphorylation of STAT3 and EGFR and promoted ubiquitin-mediated degradation of PD-L1. Copper-chelating drugs also significantly increased the number of tumor-infiltrating CD8+ T and natural killer cells, slowed tumor growth, and improved mouse survival. Overall, this study reveals an important role for copper in regulating PD-L1 and suggests that anticancer immunotherapy might be enhanced by pharmacologically reducing intratumor copper levels. SIGNIFICANCE: These findings characterize the role of copper in modulating PD-L1 expression and contributing to cancer immune evasion, highlighting the potential for repurposing copper chelators as enhancers of antitumor immunity. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/19/4129/F1.large.jpg.

Transcriptional network inference and master regulator analysis of the response to ribosome-inactivating proteins in leukemia cells.

Gene-regulatory networks reconstruction has become a very popular approach in applied biology to infer and dissect functional interactions of Transcription Factors (TFs) driving a defined phenotypic state, termed as Master Regulators (MRs). In the present work, cutting-edge bioinformatic methods were applied to re-analyze experimental data on leukemia cells (human myelogenous leukemia cell line THP-1 and acute myeloid leukemia MOLM-13 cells) treated for 6 h with two different Ribosome-Inactivating Proteins (RIPs), namely Shiga toxin type 1 (400 ng/mL) produced by Escherichia coli strains and the plant toxin stenodactylin (60 ng/mL), purified from the caudex of Adenia stenodactyla Harms. This analysis allowed us to identify the common early transcriptional response to 28S rRNA damage based on gene-regulatory network inference and Master Regulator Analysis (MRA). Both toxins induce a common response at 6 h which involves inflammatory mediators triggered by AP-1 family transcriptional factors and ATF3 in leukemia cells. We describe for the first time the involvement of MAFF, KLF2 and KLF6 in regulating RIP-induced apoptotic cell death, while receptor-mediated downstream signaling through ANXA1 and TLR4 is suggested for both toxins.

Spathial: an R package for the evolutionary analysis of biological data.

SUMMARY: A primary problem in high-throughput genomics experiments is finding the most important genes involved in biological processes (e.g. tumor progression). In this applications note, we introduce spathial, an R package for navigating high-dimensional data spaces. spathial implements the Principal Path algorithm, which is a topological method for locally navigating on the data manifold. The package, together with the core algorithm, provides several high-level functions for interpreting the results. One of the analyses we propose is the extraction of the genes that are mainly involved in the progress from one state to another. We show a possible application in the context of tumor progression using RNA-Seq and single-cell datasets, and we compare our results with two commonly used algorithms, edgeR and monocle3, respectively. AVAILABILITY AND IMPLEMENTATION: The R package spathial is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/spathial/index.html) and on GitHub (https://github.com/erikagardini/spathial). It is distributed under the GNU General Public License (version 3). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Histone Deacetylases (HDACs): Evolution, Specificity, Role in Transcriptional Complexes, and Pharmacological Actionability.

Histone deacetylases (HDACs) are evolutionary conserved enzymes which operate by removing acetyl groups from histones and other protein regulatory factors, with functional consequences on chromatin remodeling and gene expression profiles. We provide here a review on the recent knowledge accrued on the zinc-dependent HDAC protein family across different species, tissues, and human pathologies, specifically focusing on the role of HDAC inhibitors as anti-cancer agents. We will investigate the chemical specificity of different HDACs and discuss their role in the human interactome as members of chromatin-binding and regulatory complexes.

corto: a lightweight R package for gene network inference and master regulator analysis.

MOTIVATION: Gene network inference and master regulator analysis (MRA) have been widely adopted to define specific transcriptional perturbations from gene expression signatures. Several tools exist to perform such analyses but most require a computer cluster or large amounts of RAM to be executed. RESULTS: We developed corto, a fast and lightweight R package to infer gene networks and perform MRA from gene expression data, with optional corrections for copy-number variations and able to run on signatures generated from RNA-Seq or ATAC-Seq data. We extensively benchmarked it to infer context-specific gene networks in 39 human tumor and 27 normal tissue datasets. AVAILABILITY AND IMPLEMENTATION: Cross-platform and multi-threaded R package on CRAN (stable version) https://cran.r-project.org/package=corto and Github (development release) https://github.com/federicogiorgi/corto. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DNA Repair Biomarker for Lung Cancer Risk and its Correlation With Airway Cells Gene Expression.

BACKGROUND: Improving lung cancer risk assessment is required because current early-detection screening criteria miss most cases. We therefore examined the utility for lung cancer risk assessment of a DNA Repair score obtained from OGG1, MPG, and APE1 blood tests. In addition, we examined the relationship between the level of DNA repair and global gene expression. METHODS: We conducted a blinded case-control study with 150 non-small cell lung cancer case patients and 143 control individuals. DNA Repair activity was measured in peripheral blood mononuclear cells, and the transcriptome of nasal and bronchial cells was determined by RNA sequencing. A combined DNA Repair score was formed using logistic regression, and its correlation with disease was assessed using cross-validation; correlation of expression to DNA Repair was analyzed using Gene Ontology enrichment. RESULTS: DNA Repair score was lower in case patients than in control individuals, regardless of the case's disease stage. Individuals at the lowest tertile of DNA Repair score had an increased risk of lung cancer compared to individuals at the highest tertile, with an odds ratio (OR) of 7.2 (95% confidence interval [CI] = 3.0 to 17.5; P < .001), and independent of smoking. Receiver operating characteristic analysis yielded an area under the curve of 0.89 (95% CI = 0.82 to 0.93). Remarkably, low DNA Repair score correlated with a broad upregulation of gene expression of immune pathways in patients but not in control individuals. CONCLUSIONS: The DNA Repair score, previously shown to be a lung cancer risk factor in the Israeli population, was validated in this independent study as a mechanism-based cancer risk biomarker and can substantially improve current lung cancer risk prediction, assisting prevention and early detection by computed tomography scanning.