Biomarkers /
KRAS Q61E
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Overview
KRAS Q61E is present in 0.00% of AACR GENIE cases, with lung adenocarcinoma having the greatest prevalence [4].
Biomarker-Directed Therapies
KRAS Q61E is a predictive biomarker for use of afatinib, dacomitinib, erlotinib, gefitinib, osimertinib, cetuximab, and panitumumab in patients.
Of the therapies with KRAS Q61E as a predictive biomarker, 2 are FDA-approved and 7 have NCCN guidelines in at least one clinical setting.
Non-small cell lung carcinoma and colorectal carcinoma have the most therapies targeted against KRAS Q61E or its related pathways [5].
Afatinib +
Non-Small Cell Lung Carcinoma -
|
Biomarker Criteria:
Sample must match one or more of the following:
|
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
|
Biomarker Criteria:
Sample must match all of the following:
Sample must match one or more of the following: Sample must match one or more of the following: |
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
Cetuximab +
Dacomitinib +
Non-Small Cell Lung Carcinoma -
|
Biomarker Criteria:
Sample must match one or more of the following:
|
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
|
Biomarker Criteria:
Sample must match all of the following:
Sample must match one or more of the following: Sample must match one or more of the following: |
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
Erlotinib +
Non-Small Cell Lung Carcinoma -
|
Biomarker Criteria:
Sample must match one or more of the following:
|
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
|
Biomarker Criteria:
Sample must match all of the following:
Sample must match one or more of the following: Sample must match one or more of the following: |
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
Gefitinib +
Non-Small Cell Lung Carcinoma -
|
Biomarker Criteria:
Sample must match one or more of the following:
|
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
|
Biomarker Criteria:
Sample must match all of the following:
Sample must match one or more of the following: Sample must match one or more of the following: |
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
Osimertinib +
Non-Small Cell Lung Carcinoma -
|
Biomarker Criteria:
Sample must match one or more of the following:
|
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
|
Biomarker Criteria:
Sample must match all of the following:
Sample must match one or more of the following: Sample must match one or more of the following: |
Predicted Response: Primary Resistance |
| Clinical Setting(s): Metastatic (NCCN) | |
| Note: According to NCCN, mutations in KRAS have been associated with reduced responsiveness to EGFR TKI therapy. |
References
1. Hart R and Prlic A. Universal Transcript Archive Repository. Version uta_20180821. San Francisco CA: Github;2015. https://github.com/biocommons/uta
2. The UniProt Consortium. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Research. 2019;47:D506-D515.
3. Liu X, Wu C, Li C, and Boerwinkle E. dbNSFP v3.0: A one-stop database of functional predictions and annotations for human nonsynonymous and splice site SNVs. Human Mutation. 2015;37:235-241.
Liu X, Jian X, and Boerwinkle E. dbNSFP: A lightweight database of human nonsynonymous SNPs and their functional predictions. Human Mutation. 2011;32:894-899.
4. The AACR Project GENIE Consortium. AACR Project GENIE: powering precision medicine through an international consortium. Cancer Discovery. 2017;7(8):818-831. Dataset Version 8. This dataset does not represent the totality of the genetic landscape; see paper for more information.
5. All assertions and clinical trial landscape data are curated from primary sources. You can read more about the curation process here.
