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FINDING CURES TOGETHER<sup>SM</sup>

Summary of AACR Project GENIE Data

Figure 1Total sample counts by tumor type. The contribution of samples for each tumor type is shown across the AACR GENIE database.

Figure 2Total sample counts by tumor type and contributing center. The contribution of samples for each tumor type across the institutions shown within each bar of the lower stacked bar plot.

Figure 3The degree of overlap at the gene level across the contributing centers' genomic heme assays.  The degree of overlap at the gene level across the contributing centers' genomic heme assays are shown. A core set of 37 genes is represented across all genomic assays in the GENIE dataset.

Figure 4The degree of overlap at the gene level across the contributing centers' genomic small gene assays.  The degree of overlap at the gene level across the contributing centers' genomic small gene panel assays (assays with less than 100 genes) are shown. A core set of 4 genes is represented across all genomic assays in the GENIE dataset.

Figure 5The degree of overlap at the gene level across the contributing centers' genomic large gene assays.  The degree of overlap at the gene level across the contributing centers' genomic large gene panel assays (assays with 100 genes or greater) are shown. A core set of 15 genes is represented across all genomic assays in the GENIE dataset.

Figure 6 – Distribution of race across the contributing centers.  The distribution of race across the 19 contributing GENIE centers.  The patient attributes race is described in five categories in the AACR GENIE registry – Native American, Asian, Black, White, and Other.  Some GENIE sites do not report race as a patient attribute.

Figure 7 – Distribution of ethnicity across the contributing centers.  The distribution of ethnicity across the 19 contributing GENIE centers.  The patient attribute ethnicity is described in two categories in the AACR GENIE registry – Spanish Hispanic and Non-Spanish Hispanic.  Some GENIE sites do not report ethnicity as a patient attribute.

Figure 8 – Distribution of sex across the contributing centers.  The distribution sex across the 19 contributing GENIE centers.  The patient attribute sex is described in two categories in the AACR GENIE registry – male and female.

Figure 9 - Potential clinical actionability. Tumor types are shown by decreasing overall frequency of actionability.  To communicate the clinical utility of individual mutant alleles consistently, actionability was defined using a classification system using variants from OncoKB Precision Oncology Knowledge Base developed originally by Chakravarty et. al (JCO Precis Oncol. 2017) that takes into account the site of tumor origin by recognizing that the effects of targeted inhibitors vary by tumor lineage, even in cancers that share the same mutant allele.  Potentially actionable alterations in a specific cancer type are assigned to one of four levels that are based on the strength of evidence that the mutation is a predictive biomarker of drug sensitivity to FDA-approved or investigational agents for a specific indication.  Individual mutational events are annotated by the level of evidence that supports the use of a certain drug in an indication that harbors that mutation. Standard therapeutic implications include Food and Drug Administration (FDA)–recognized biomarkers that are predictive of response to an FDA-approved drug in a specific indication (level 1) and standard care biomarkers that are predictive of response to an FDA-approved drug in a specific indication (level 2A). Investigational therapeutic implications include FDA-approved biomarkers predictive of response to an FDA-approved drug detected in an off-label indication (level 2B), FDA- or non–FDA-recognized biomarkers that are predictive of response to novel targeted agents that have shown promising results in clinical trials (level 3A), and non–FDA-recognized biomarkers that are predictive of response to novel targeted agents on the basis of compelling biologic data (level 4). VUS (a variant of uncertain significance) corresponds to a variant or biomarker that is not known to be oncogenic or confers sensitivity to a drug. "Oncogenic, no level" corresponds to variants were curated as oncogenic in OncoKB but not known to be a biomarker conferring sensitivity to a drug.  For each tumor sample, the highest level of actionability of any variant was considered. Only tumor types with 100 or more samples were included in this analysis.



Date Updated: 7/8/2019