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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.
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.
Genomic sequencing in congenital heart disease (CHD) patients often discovers novel genetic variants, which are classified as variants of uncertain significance (VUS). Functional analysis of each VUS is required in specialised laboratories, to determine whether the VUS is disease causative or not, leading to lengthy diagnostic delays.
The Australian Genomics Cardiovascular Disorders Flagship was a national multidisciplinary collaboration. It aimed to investigate the feasibility of genome sequencing and functional genomics to resolve variants of uncertain significance in the clinical management of patients and families with cardiomyopathies, primary arrhythmias, and congenital heart disease.
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.
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.
To define clinical common data elements (CDEs) and a mandatory minimum data set (MDS) for genomic studies of cerebral palsy (CP). Method: Candidate data elements were collated following a review of the literature and existing CDEs.
The goal of this study was to understand individuals with cerebral palsy (CP) and their family's attitudes and preferences to genomic research, including international data sharing and biobanking.
Mitochondrial energy metabolism plays an important role in the pathophysiology of insulin resistance. Recently, a missense N437S variant was identified in the MRPP3 gene, which encodes a mitochondrial RNA processing enzyme within the RNase P complex, with predicted impact on metabolism. We used CRISPR-Cas9 genome editing to introduce this variant into the mouse Mrpp3 gene and show that the variant causes insulin resistance on a high-fat diet.
Head, Epigenetics