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Due to an advanced understanding of cancer biology and the rapid development of genomic technologies, cancer has shifted from 200 diseases based on pathology (i.e., what a tumor looks like under the microscope) to thousands of diseases based on molecular tumor profiles (i.e., what a tumor looks like when its altered genome is interrogated). Most cancers arise from alterations to the genome, including changes in the number or structure of chromosomes and variations in a single building block of the genetic code.
Uveal melanoma is a rare melanoma originating in the eye's uvea, with 50% of patients experiencing metastasis predominantly in the liver. In contrast to cutaneous melanoma, there is only a limited effectiveness of combined immune checkpoint therapies, and half of patients with uveal melanoma metastases succumb to disease within 2 years.
Chronic obstructive pulmonary disease (COPD) results from gene-environment interactions over the lifetime. These interactions are captured by epigenetic changes, such as DNA methylation.
RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early.
Genomic information is increasingly used to inform medical treatments and manage future disease risks. However, any personal and societal gains must be carefully balanced against the risk to individuals contributing their genomic data. Expanding our understanding of actionable genomic insights requires researchers to access large global datasets to capture the complexity of genomic contribution to diseases.
Type-2 diabetes is a systemic condition with rising global prevalence, disproportionately affecting Indigenous communities worldwide. Recent advances in epigenomics methods, particularly in DNA methylation detection, have enabled the discovery of associations between epigenetic changes and Type-2 diabetes. In this review, we summarise DNA methylation profiling methods, and discuss how these technologies can facilitate the discovery of epigenomic biomarkers for Type-2 diabetes.
Whole genome sequencing offers significant potential to improve the diagnosis and treatment of rare diseases by enabling the identification of thousands of rare, potentially pathogenic variants. Existing variant prioritisation tools can be complemented by approaches that incorporate phenotype specificity and provide contextual biological information, such as tissue or cell-type specificity.
Current differentiation protocols have not been successful in reproducibly generating fully functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single-cell RNA sequencing with spatial transcriptomics at multiple developmental time points and revealed distinct temporal-spatial gene cascades.
Head, Epigenetics
Honorary Research Associate