Exploring the impact of intra-tumoural heterogeneity on liquid biopsy cell-free DNA methylation and copy number in head and neck squamous cell carcinoma.

Liquid biopsy profiling is gaining increasing promise towards biomarker-led identification and disease stratification of tumours, particularly for tumours displaying significant intra-tumoural heterogeneity (ITH). For head and neck squamous cell carcinoma (HNSCC), which display high levels of genetic ITH, identification of epigenetic modifications and methylation signatures has shown multiple uses in stratification of HNSCC for prognosis, treatment, and HPV status. In this study, we investigated the potential of liquid biopsy methylomics and genomic copy number to profile HNSCC.

Circulating tumour DNA detects somatic variants contributing to spatial and temporal intra-tumoural heterogeneity in head and neck squamous cell carcinoma.

Background: As circulating tumour DNA (ctDNA) liquid biopsy analysis is increasingly incorporated into modern oncological practice, establishing the impact of genomic intra-tumoural heterogeneity (ITH) upon data output is paramount. Despite advances in other cancer types the evidence base in head and neck squamous cell carcinoma (HNSCC) remains poor. We sought to investigate the utility of ctDNA to detect ITH in HNSCC.

A temporal in vivo catalog of chromatin accessibility and expression profiles in pineoblastoma reveals a prevalent role for repressor elements.

Pediatric pineoblastomas (PBs) are rare and aggressive tumors of grade IV histology. Although some oncogenic drivers are characterized, including germline mutations in RB1 and DICER1, the role of epigenetic deregulation and -regulatory regions in PB pathogenesis and progression is largely unknown. Here, we generated genome-wide gene expression, chromatin accessibility, and H3K27ac profiles covering key time points of PB initiation and progression from pineal tissues of a mouse model of -driven PB.

Computational pharmacogenomic screen identifies drugs that potentiate the anti-breast cancer activity of statins.

Statins, a family of FDA-approved cholesterol-lowering drugs that inhibit the rate-limiting enzyme of the mevalonate metabolic pathway, have demonstrated anticancer activity. Evidence shows that dipyridamole potentiates statin-induced cancer cell death by blocking a restorative feedback loop triggered by statin treatment. Leveraging this knowledge, we develop an integrative pharmacogenomics pipeline to identify compounds similar to dipyridamole at the level of drug structure, cell sensitivity and molecular perturbation.

Overview of Bioinformatics Software and Databases for Metabolic Engineering.

The explosion of the "omics" era has introduced a growing number of sets and tools that facilitate molecular interrogation of the metabolome. These include various bioinformatics and pharmacogenomics resources that can be utilized independently or collectively to facilitate metabolic engineering across disease, clinical oncology, and understanding of molecular changes across larger systems. This review provides starting points for accessing publicly available data and computational tools that support assessment of metabolic profiles and metabolic regulation, providing both a depth-and-breadth approach toward understanding the metabolome.

The anti-tumour activity of DNA methylation inhibitor 5-aza-2'-deoxycytidine is enhanced by the common analgesic paracetamol through induction of oxidative stress.

The DNA demethylating agent 5-aza-2'-deoxycytidine (DAC, decitabine) has anti-cancer therapeutic potential, but its clinical efficacy is hindered by DNA damage-related side effects and its use in solid tumours is debated. Here we describe how paracetamol augments the effects of DAC on cancer cell proliferation and differentiation, without enhancing DNA damage. Firstly, DAC specifically upregulates cyclooxygenase-2-prostaglandin E pathway, inadvertently providing cancer cells with survival potential, while the addition of paracetamol offsets this effect.

Modeling germline mutations in pineoblastoma uncovers lysosome disruption-based therapy.

Pineoblastoma is a rare pediatric cancer induced by germline mutations in the tumor suppressors RB1 or DICER1. Presence of leptomeningeal metastases is indicative of poor prognosis. Here we report that inactivation of Rb plus p53 via a WAP-Cre transgene, commonly used to target the mammary gland during pregnancy, induces metastatic pineoblastoma resembling the human disease with 100% penetrance.

Bioinformatics and computational approaches for analyzing patient-derived disease models in cancer research.

Patient-derived organoids (PDO) and patient-derived xenografts (PDX) continue to emerge as important preclinical platforms for investigations into the molecular landscape of cancer. While the advantages and disadvantage of these models have been described in detail, this review focuses in particular on the bioinformatics and state-of-the art techniques that accompany preclinical model development. We discuss the strength and limitations of currently used technologies, particularly 'omics profiling and bioinformatics analyses, in addressing the 'efficacy' of preclinical models, both for tumour characterization as well as their use in identifying potential therapeutics.

MetaGxData: Clinically Annotated Breast, Ovarian and Pancreatic Cancer Datasets and their Use in Generating a Multi-Cancer Gene Signature.

A wealth of transcriptomic and clinical data on solid tumours are under-utilized due to unharmonized data storage and format. We have developed the MetaGxData package compendium, which includes manually-curated and standardized clinical, pathological, survival, and treatment metadata across breast, ovarian, and pancreatic cancer data. MetaGxData is the largest compendium of curated transcriptomic data for these cancer types to date, spanning 86 datasets and encompassing 15,249 samples.

A subgroup of microRNAs defines PTEN-deficient, triple-negative breast cancer patients with poorest prognosis and alterations in RB1, MYC, and Wnt signaling.

Background: Triple-negative breast cancer (TNBC) represents a heterogeneous group of ER- and HER2-negative tumors with poor clinical outcome. We recently reported that Pten-loss cooperates with low expression of microRNA-145 to induce aggressive TNBC-like lesions in mice. To systematically identify microRNAs that cooperate with PTEN-loss to induce aggressive human BC, we screened for miRNAs whose expression correlated with PTEN mRNA levels and determined the prognostic power of each PTEN-miRNA pair alone and in combination with other miRs.

Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis among solid malignancies and improved therapeutic strategies are needed to improve outcomes. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) serve as promising tools to identify new drugs with therapeutic potential in PDAC. For these preclinical disease models to be effective, they should both recapitulate the molecular heterogeneity of PDAC and validate patient-specific therapeutic sensitivities.

Consensus on Molecular Subtypes of High-Grade Serous Ovarian Carcinoma.

The majority of ovarian carcinomas are of high-grade serous histology, which is associated with poor prognosis. Surgery and chemotherapy are the mainstay of treatment, and molecular characterization is necessary to lead the way to targeted therapeutic options. To this end, various computational methods for gene expression-based subtyping of high-grade serous ovarian carcinoma (HGSOC) have been proposed, but their overlap and robustness remain unknown.

Administration of Hypoxia-Activated Prodrug Evofosfamide after Conventional Adjuvant Therapy Enhances Therapeutic Outcome and Targets Cancer-Initiating Cells in Preclinical Models of Colorectal Cancer.

Cancer-initiating cells (C-IC) have been described in multiple cancer types, including colorectal cancer. C-ICs are defined by their capacity to self-renew, thereby driving tumor growth. C-ICs were initially thought to be static entities; however, recent studies have determined these cells to be dynamic and influenced by microenvironmental cues such as hypoxia.

Integrative Cancer Pharmacogenomics to Infer Large-Scale Drug Taxonomy.

Identification of drug targets and mechanism of action (MoA) for new and uncharacterized anticancer drugs is important for optimization of treatment efficacy. Current MoA prediction largely relies on prior information including side effects, therapeutic indication, and chemoinformatics. Such information is not transferable or applicable for newly identified, previously uncharacterized small molecules.

Integrated (epi)-Genomic Analyses Identify Subgroup-Specific Therapeutic Targets in CNS Rhabdoid Tumors.

We recently reported that atypical teratoid rhabdoid tumors (ATRTs) comprise at least two transcriptional subtypes with different clinical outcomes; however, the mechanisms underlying therapeutic heterogeneity remained unclear. In this study, we analyzed 191 primary ATRTs and 10 ATRT cell lines to define the genomic and epigenomic landscape of ATRTs and identify subgroup-specific therapeutic targets. We found ATRTs segregated into three epigenetic subgroups with distinct genomic profiles, SMARCB1 genotypes, and chromatin landscape that correlated with differential cellular responses to a panel of signaling and epigenetic inhibitors.

MM2S: personalized diagnosis of medulloblastoma patients and model systems.

Background: Medulloblastoma (MB) is a highly malignant and heterogeneous brain tumour that is the most common cause of cancer-related deaths in children. Increasing availability of genomic data over the last decade had resulted in improvement of human subtype classification methods, and the parallel development of MB mouse models towards identification of subtype-specific disease origins and signaling pathways. Despite these advances, MB classification schemes remained inadequate for personalized prediction of MB subtypes for individual patient samples and across model systems.

PharmacoGx: an R package for analysis of large pharmacogenomic datasets.

Unlabelled: Pharmacogenomics holds great promise for the development of biomarkers of drug response and the design of new therapeutic options, which are key challenges in precision medicine. However, such data are scattered and lack standards for efficient access and analysis, consequently preventing the realization of the full potential of pharmacogenomics. To address these issues, we implemented PharmacoGx, an easy-to-use, open source package for integrative analysis of multiple pharmacogenomic datasets.

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.

Public data and open source tools for multi-assay genomic investigation of disease.

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition.

CD73 is associated with poor prognosis in high-grade serous ovarian cancer.

The cell surface nucleotidase CD73 is an immunosuppressive enzyme involved in tumor progression and metastasis. Although preclinical studies suggest that CD73 can be targeted for cancer treatment, the clinical impact of CD73 in ovarian cancer remains unclear. In this study, we investigated the prognostic value of CD73 in high-grade serous (HGS) ovarian cancer using gene and protein expression analyses.

Personalized diagnosis of medulloblastoma subtypes across patients and model systems.

Molecular subtyping is instrumental towards selection of model systems for fundamental research in tumor pathogenesis, and clinical patient assessment. Medulloblastoma (MB) is a highly heterogeneous, malignant brain tumor that is the most common cause of cancer-related deaths in children. Current MB classification schemes require large sample sizes, and standard reference samples, for subtype predictions.

Medulloblastoma subgroups remain stable across primary and metastatic compartments.

Medulloblastoma comprises four distinct molecular variants with distinct genetics, transcriptomes, and outcomes. Subgroup affiliation has been previously shown to remain stable at the time of recurrence, which likely reflects their distinct cells of origin. However, a therapeutically relevant question that remains unanswered is subgroup stability in the metastatic compartment.

The first small-molecule inhibitors of members of the ribonuclease E family.

The Escherichia coli endoribonuclease RNase E is central to the processing and degradation of all types of RNA and as such is a pleotropic regulator of gene expression. It is essential for growth and was one of the first examples of an endonuclease that can recognise the 5'-monophosphorylated ends of RNA thereby increasing the efficiency of many cleavages. Homologues of RNase E can be found in many bacterial families including important pathogens, but no homologues have been identified in humans or animals.