Comprehensive molecular portraits of human breast tumours

This Article from the Cancer Genome Atlas consortium describes a multifaceted analysis of primary breast cancers in 825 people. Exome sequencing, copy number variation, DNA methylation, messenger RNA arrays, microRNA sequencing and proteomic analyses were performed and integrated to shed light on breast-cancer heterogeneity. Just three genes — TP53, PIK3CA and GATA3 — are mutated at greater than 10% frequency across all breast cancers. Many subtype-associated and novel mutations were identified, as well as two breast-cancer subgroups with specific signalling-pathway signatures. The analyses also suggest that much of the clinically observable plasticity and heterogeneity occurs within, and not across, the major subtypes of breast cancer

Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data

Programmed cell death (PCD), or cell suicide, encompasses multiple pathways including apoptosis and autophagy and is essential for development, cellular homeostasis, and prevention of cancer cell growth. I describe here the development and use of bioinformatic methods to identify and analyze genes involved in PCD, both in the model organism Drosophila melanogaster and in human cancer, by analysis of large-scale gene expression data. An approach was developed to correctly identify genes from serial analysis of gene expression (SAGE) data, distinguish the set of genes not accessible to the SAGE method, and determine the optimal set of enzymes for Drosophila, C. elegans, and human SAGE library construction. In Drosophila metamorphosis the salivary gland undergoes autophagic PCD, whereby cellular components are engulfed and degraded by cytoplasmic vacuoles, with additional hallmarks of apoptosis. This is an excellent model in which to study the genes involved in PCD. Transcriptional profiling of this tissue by expressed sequence tags (ESTs) and serial analysis of gene expression (SAGE) identified many genes differentially regulated prior to cell death, including genes known to be death regulators, genes in related pathways, genes of no known function, and potentially novel unannotated genes. The PCD-associated genes found in this analysis were then used to identify similar genes in the human genome that are differentially expressed in cancer, which have the potential to be involved in PCD and in oncogenesis. The pattern of genes expressed suggests a role for autophagy-associated processes in cancer progression. To examine this further, expression of the autophagy gene LC3 was examined in multiple cancer types, subtypes, and stages. LC3 expression is decreased significantly in several cancer types and also during cancer progression, suggesting a tissue- and stage-specific role for autophagy in regulating oncogenesis.Medicine, Faculty ofMedical Genetics, Department ofGraduat

Assessment of SAGE in Transcript Identification

An essential step in Serial Analysis of Gene Expression (SAGE) is tag mapping, which refers to the unambiguous determination of the gene represented by a SAGE tag. Current resources for tag mapping are incomplete, and thus do not allow assessment of the efficacy of SAGE in transcript identification. A method of tag mapping is described here and applied to the Drosophila melanogaster and Caenorhabditis elegans genomes, which permits detailed SAGE assessment and provides tag-mapping resources that were unavailable previously for these organisms. In our method, a conceptual transcriptome is constructed using genomic sequence and annotation by extending predicted coding regions to include UTRs on the basis of EST and cDNA alignments, UTR length distributions, and polyadenylation signals. Analysis of extracted tags suggests that, using the standard SAGE procedure, expression of 8% of D. melanogaster and 15% of C. elegans genes cannot be detected unambiguously by SAGE due to shared sequence or lack of NlaIII-anchoring enzyme sites. Both increasing tag length by 2–3 bp and using Sau3A instead of NlaIII as the anchoring enzyme increases potential for transcript detection. This work identifies and quantifies genes not amenable to SAGE analysis, in addition to providing tag-to-gene mappings for two model organisms

TMBur : a distributable tumor mutation burden approach for whole genome sequencing

Background Tumor mutation burden (TMB) is a key characteristic used in a tumor-type agnostic context to inform the use of immune checkpoint inhibitors (ICI). Accurate and consistent measurement of TMB is crucial as it can significantly impact patient selection for therapy and clinical trials, with a threshold of 10 mutations/Mb commonly used as an inclusion criterion. Studies have shown that the most significant contributor to variability in mutation counts in whole genome sequence (WGS) data is differences in analysis methods, even more than differences in extraction or library construction methods. Therefore, tools for improving consistency in whole genome TMB estimation are of clinical importance. Methods We developed a distributable TMB analysis suite, TMBur, to address the need for genomic TMB estimate consistency in projects that span jurisdictions. TMBur is implemented in Nextflow and performs all analysis steps to generate TMB estimates directly from fastq files, incorporating somatic variant calling with Manta, Strelka2, and Mutect2, and microsatellite instability profiling with MSISensor. These tools are provided in a Singularity container downloaded by the workflow at runtime, allowing the entire workflow to be run identically on most computing platforms. To test the reproducibility of TMBur TMB estimates, we performed replicate runs on WGS data derived from the COLO829 and COLO829BL cell lines at multiple research centres. The clinical value of derived TMB estimates was then evaluated using a cohort of 90 patients with advanced, metastatic cancer that received ICIs following WGS analysis. Patients were split into groups based on a threshold of 10/Mb, and time to progression from initiation of ICIs was examined using Kaplan–Meier and cox-proportional hazards analyses. Results TMBur produced identical TMB estimates across replicates and at multiple analysis centres. The clinical utility of TMBur-derived TMB estimates were validated, with a genomic TMB ≥ 10/Mb demonstrating improved time to progression, even after correcting for differences in tumor type (HR = 0.39, p = 0.012). Conclusions TMBur, a shareable workflow, generates consistent whole genome derived TMB estimates predictive of response to ICIs across multiple analysis centres. Reproducible TMB estimates from this approach can improve collaboration and ensure equitable treatment and clinical trial access spanning jurisdictions.Medicine, Faculty ofNon UBCMedical Genetics, Department ofMedical Oncology, Division ofReviewedFacult

Identification and analysis of internal promoters in Caenorhabditis elegans operons

The current Caenorhabditis elegans genomic annotation has many genes organized in operons. Using directionally stitched promoter∷GFP methodology, we have conducted the largest survey to date on the regulatory regions of annotated C. elegans operons and identified 65, over 25% of those studied, with internal promoters. We have termed these operons “hybrid operons.” GFP expression patterns driven from internal promoters differ in tissue specificity from expression of operon promoters, and serial analysis of gene expression data reveals that there is a lack of expression correlation between genes in many hybrid operons. The average length of intergenic regions with putative promoter activity in hybrid operons is larger than previous estimates for operons as a whole. Genes with internal promoters are more commonly involved in gene duplications and have a significantly lower incidence of alternative splicing than genes without internal promoters, although we have observed almost all trans-splicing patterns in these two distinct groups. Finally, internal promoter constructs are able to rescue lethal knockout phenotypes, demonstrating their necessity in gene regulation and survival. Our work suggests that hybrid operons are common in the C. elegans genome and that internal promoters influence not only gene organization and expression but also operon evolution

Estimation of rearrangement phylogeny for cancer genomes

Cancer genomes are complex, carrying thousands of somatic mutations including base substitutions, insertions and deletions, rearrangements, and copy number changes that have been acquired over decades. Recently, technologies have been introduced that allow generation of high-resolution, comprehensive catalogs of somatic alterations in cancer genomes. However, analyses of these data sets generally do not indicate the order in which mutations have occurred, or the resulting karyotype. Here, we introduce a mathematical framework that begins to address this problem. By using samples with accurate data sets, we can reconstruct relatively complex temporal sequences of rearrangements and provide an assembly of genomic segments into digital karyotypes. For cancer genes mutated in rearranged regions, this information can provide a chronological examination of the selective events that have taken place

Exploration of Germline Correlates and Risk of Immune-Related Adverse Events in Advanced Cancer Patients Treated with Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICIs) are increasingly used in the treatment of many tumor types, and durable responses can be observed in select populations. However, patients may exhibit significant immune-related adverse events (irAEs) that may lead to morbidity. There is limited information on whether the presence of specific germline mutations may highlight those at elevated risk of irAEs. We evaluated 117 patients with metastatic solid tumors or hematologic malignancies who underwent genomic analysis through the ongoing Personalized OncoGenomics (POG) program at BC Cancer and received an ICI during their treatment history. Charts were reviewed for irAEs. Whole genome sequencing of a fresh biopsy and matched normal specimens (blood) was performed at the time of POG enrollment. Notably, we found that MHC class I alleles in the HLA-B27 family, which have been previously associated with autoimmune conditions, were associated with grade 3 hepatitis and pneumonitis (q = 0.007) in patients treated with combination PD-1/PD-L1 and CTLA-4 inhibitors, and PD-1 inhibitors in combination with IDO-1 inhibitors. These data highlight that some patients may have a genetic predisposition to developing irAEs.Medicine, Faculty ofNon UBCMedical Genetics, Department ofReviewedFacultyResearche