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- Tumour summary:
- Tumour content is determined based on copy number and allelic ratios from whole genome sequencing data. If relevant to the tumour type, 'Subtype' indicates the likely tumour subtype based on RNA and/or DNA data. Microbial Species lists any species for which sequence reads suggest presence in the tumour sample, with more details in the 'Microbial' section. T Cell Score is determined based on expression of immune genes, with more details in the 'Immune' section. Mutation Signature indicates if there are any specific mutation patterns of potential clinical relevance, with more details in the 'Mutation Signatures' section. Mutation Burden reflects the prevalence of small mutations in the genome and is reported in mutations per megabase. SV Burden gives the count of structural variants determined from DNA, and the percentile in comparison to other sequenced samples. MSI Status gives the predicted MSI state based on sequence data, with more details in the Mutation Burden section.
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- Key genomic and transcriptomic alterations:
- The subset of alterations which have a previously described or inferred effect on genes of clinical or biological significance are summarized, with details of significance provided in the Knowledgebase Matches section, and details of the exact alteration provided in the section of the report corresponding to that mutation type. Additional alterations that do not have an inferred oncogenic or clinically relevant functional effect are variants of uncertain significance (VUS), and are only listed in the subsequent sections of the report. Alterations in genes that are not associated with cancer, cancer pathways, or therapeutics, may not be included in the genomic report but are available upon request.
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- Analyst comments:
- Text summary of the genomic and transcriptomic analysis for the case, based on manual case review, written by the genome analyst. This section contains interpretation of the genomic findings including references to relevant published literature and clinical trials.
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- Pathway analysis:
- Visual summary of the key genomic and expression alterations, placed in a pathway context. Genes and pathways shown are dependent on the cancer type and the alterations specific to the individual tumour.
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- Potential therapeutic targets:
- Tumour alterations are reviewed and those representing the most likely potential therapeutic targets are highlighted, with details on the associated therapy or general drug class, level of evidence, and any relevant clinical trials. Levels of evidence are based on professional guidelines and describe whether the therapy is approved for the biomarker in the same or another tumour type, or has clinical or preclinical evidence. Potential caveats are also specified. Alterations associated with potential resistance to relevant therapies are also documented.
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- Knowledgebase matches:
- Tumour alterations with specific therapeutic, prognostic, diagnostic or biological associations are identified using the expert curated knowledgebase GraphKB, which integrates information from sources including cancer databases, drug databases, clinical tests, and the literature. Associations are listed by the level of evidence for the use of that drug in the context of the observed alteration, including those that are approved in this or other cancer types, and those that have early clinical or preclinical evidence.
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- Microbial content:
- Sequences are compared to databases of viral, bacterial and fungal sequences in addition to the human genome. The microbial species is reported if observed levels are suggestive of microbial presence in the tumour sample. Specific viral integration sites are reported if identified in genomic DNA sequence.
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- Expression correlation:
- Transcriptome sequencing data from the tumour is compared to transcriptome data from a variety of tumour types using a correlation approach. In addition, the tumour is compared to tumours previously sequenced at Canada's Michael Smith Genome Sciences Centre to identify the most similar individual samples.
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- Mutation signatures:
- The pattern of specific base changes and base context of single and double nucleotide variants, small insertions and deletions in the tumour, referred to as the mutation signature, is computed and compared to patterns previously observed in a wide variety of tumour types. Signatures that suggest a particular mutation etiology, such as exposure to a specific mutagen, are noted.
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- Mutation burden and microsatellite instability:
- Tumour mutation burden is reported in mutations per megabase in the genome. Additionally, the number of protein coding alterations of each type are totaled and compared to other tumours of a similar type. When a suitable tumour-specific cohort is not available for comparison, these may be compared to an “average” cohort that is not tumour type specific but rather composed of all tumour types. Microsatellite instability is measured as the percentage of microsatellites across the whole genome that show evidence of instability. MSI status (MSI or MSS) is inferred based on this percentage.
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- Immune:
- Evidence for immune cells in the tumour sample, potentially representing tumour-infiltrating lymphocytes, are predicted based on analysis of transcriptome sequencing data. The total T cell score (T.cell.infiltration) represents the total of all scores attributed to T cells excluding regulatory T cells. The major histocompatibility complex class I HLA alleles found in sequenced samples are predicted based on alignment of DNA and RNA to databases of known HLA sequences.
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- Germline - Pharmacogenomic:
- Germline (normal) DNA is queried for specific variants associated with increased risk of drug toxicity. Identified variants are displayed with details of drug associations.
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- Somatic:
- Details of small mutations (single nucleotide variants and small insertions and deletions), copy number alterations, and structural variants are provided in the respective sections.
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- Expression:
- The most appropriate normal tissue and tumour types are chosen for expression comparisons based on the patient’s diagnosis and observed correlation with tissue data sets. If no appropriate tissue comparator is available, for instance for rare tumours, an average across all tissues may be used. Expression is calculated as percentile and kIQR (number of interquartile ranges) relative to comparator expression distributions. Outlier expression refers to genes with high or low expression compared to what is observed in other cancers of that type, and also compared to relevant normal tissue.
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- Additional analysis:
- Bespoke analysis for individual samples, including comparison among multiple samples from the same tumour, cancer-specific subtyping, and non-standard analysis approaches, may also be performed. Relevant results will be included in 'Additional Information' and 'Analyst Comments'.
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