Abstract
BackgroundIncreasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient’s genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly.ResultsHere, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data.ConclusionsOur CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.
Highlights
Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology
Deep sequencing is about to become a part of clinical tests, but the probabilistic and complex nature of the results makes it vastly different from conventional clinical tests that are deterministic and simple to use without sophisticated informatics analysis
We provide Galaxy workflow files for Whole Exome Sequencing (WES) and Whole Transcriptome Sequencing (WTS) data processing in Additional files 3 and 4 respectively so that those files can be imported into another Galaxy server
Summary
Variant annotation and Druggability The variant calling process using the WES Galaxy pipeline produces VCF (variant calling format containing details of variants) and BAM (binary alignment map for aligned reads) files, which are imported to the variant annotation and prioritization module of CGIS. We further provide filtering utility to select genes of known importance in cancer as well as variants based on patient frequency and functional impact (Fig. 2a). Users may select the cancer drug targets in clinical practice (26 genes) that were curated by MD Anderson personalized cancer medicine Knowledgebase [13] Our variant annotation and prioritization scheme based on knowledge of cancer genes and targeted drugs provides an efficient way of scrutinizing clinical relevance of somatic variants in a given cancer type. We use Mutex program [18] to identify mutually exclusive set of genes with a common downstream effect on the signaling network and implemented survival analysis for altered vs unaltered patient groups. Even in patient samples where those acquired resistance emerges, alterations often converge on specific gene modules or pathways, suggesting that even these scenarios could
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