Ion Reporter™ Software Oncomine™ Workflows
Discovering the drivers of cancer
Cancer can be characterized by numerous somatic mutations, although only a subset may contribute to tumor progression. Distinguishing these “driver” mutations from neutral “passenger” mutations can help explain the phenotypic diversity in cancer and provide increased understanding of tumor initiation, maintenance, progression, and metastasis.
Ion Torrent™ systems provide an end-to-end solution that simplifies your sequencing and analysis for detecting and characterizing cancer mutations as drivers or passengers. Using the Ion Reporter™ Oncomine™ workflow with Ion AmpliSeq™ gene panels, such as the Ion AmpliSeq™ Cancer Hotspot v2 and Comprehensive Cancer Panels, enables researchers to move from sample to sequence to driver mutations in a single day. The Oncomine™ workflow is integrated into Ion Reporter™ Software to automate file transfer, data analysis, and display of annotated mutations in a consolidated workflow.
Rapid and simple driver mutation identification workflow
- Sequence your sample using one of the Ion AmpliSeq™ gene panels or the Ion TargetSeq™ exome kit.
- Analyze with Ion Reporter™ single-sample workflows to identify mutations relative to a reference genome, or use the integrated Tumor-Normal workflow to identify somatic mutations from paired samples.
- Annotate mutations by gene name, COSMIC classifications, and other public or private content.
- Leverage the Oncomine™ Knowledge Base to find driver mutations.
- Filter your set of variants to identify biologically relevant SNPs, indels, and CNVs in your sample.
- Document your results in an interpretive report with supporting information.
Next-generation sequencing of cancer samples identifies many potentially important variants, particularly if matched germline DNA is not sequenced in parallel. The addition of Oncomine™ annotations to Ion Reporter™ Software provides the best way to prioritize those mutations that are likely cancer drivers, based on well-curated supporting evidence across cancer types.
Scott Tomlins, MD, PhD
Assistant Professor, Department of
Pathology, University of Michigan
Leverage the Oncomine™ Knowledge Base to find driver mutations
The Oncomine™ Knowledge Base within Ion Reporter™ Software provides access to curated data from 30,000 samples, including next-generation sequencing data from 5,000 matched tumor and normal pairs, and is designed to assist with interpreting variants from data obtained on Ion Torrent™ semiconductor sequencing platforms. The consistent application of robust analysis methods across the compendium of Oncomine™ mutation data provides a powerful set of analytical functions to help identify driver mutations in individual samples. A well-tested algorithm classifies gain-of-function or loss-of-function driver mutations based on mutation significance, frequency, and reoccurrence across 15 cancer types, which can increase understanding of mutations in your sample. Separation of impactful mutations from background variants is especially helpful in larger panel studies.
Figure 1. Identify deleterious and driver mutations by leveraging genomic data from thousands of samples across many different types of cancer, using the Oncomine™ platform’s Mutation Profile. This view shows specific mutation types that are associated with specific cancers.
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