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Table 2 An example of an actionability hierarchy for identified genomic variants

From: Integrating cancer genomic data into electronic health records

Hierarchical levela

Example scenariob

1. Variant known to confer sensitivity to an FDA-approved agent for the cancer subtype

1. BRAF p.V600E mutation

2. Vemurafenib

3. Melanoma

2. Variant predicted to confer sensitivity to an FDA-approved agent for the cancer subtype

1. BRAF p.V600K mutation

2. Vemurafenib

3. Melanoma

3. Variant known to confer sensitivity to an FDA-approved agent for another cancer subtype

1. BRAF p.V600E mutation

2. Vemurafenib

3. Hairy cell leukemia

4. Variant predicted to confer sensitivity to an FDA-approved agent for another cancer subtype

1. BRAF p.V600K mutation

2. Vemurafenib

3. Lung adenocarcinoma

5. Variant known to confer sensitivity to an experimental agent for the cancer subtype

1. BRAF p.V600E mutation

2. Binimetinib

3. Melanoma

6. Variant known to confer sensitivity to an experimental agent for another cancer subtype

1. BRAF p.V600E mutation

2. Binimetinib

3. Hairy cell leukemia

7. Variant predicted to confer sensitivity to an experimental agent for the cancer subtype

1. BRAF p.V600K mutation

2. Binimetinib

3. Melanoma

8. Variant with known prognostic significance for the cancer subtype

1. KMT2A rearrangement t(4;11)(q21;q23) as sole abnormality

2. B-cell ALL

3. Poor prognosis in adults

9. Variant with predicted prognostic significance for the cancer subtype

1. ABL1 p.M244V mutation

2. CML

3. Likely poor prognosis, faster progression to accelerated or blast phase

10. VUS

1. BRCA1 p.S645Y mutation

2. Triple-negative breast cancer

3. No known sensitivity or prognostic significance

  1. ALL acute lymphoblastic leukemia, CML chronic myeloid leukemia, FDA Food and Drug Administration, VUS variant of unknown significance
  2. aHierarchy of actionability of identified genomic variants, ranging from the situation with the strongest evidence base relating cause and effect (for example, treatment of the given condition with a given drug will result in an expected response) (1) to the weakest (10). For each hierarchical level, an example is provided that meets three criteria: 1) genomic variant, 2) pharmacologic agent, and 3) disease context. For simplicity, we do not further delineate disease context by status (for example, untreated, relapsed/refractory), although pharmaceutical agents are increasingly FDA-approved only for a given disease context and status
  3. bThe examples use predicted sensitivity but predicted resistance has the equivalent hierarchy
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Genome Medicine

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