Revealing treatment options with category variants



When time isn’t on anyone’s side, how can clinicians and patients make the most educated decision for their treatment? Implementation of next-generation sequencing to uncover the genomic landscape of a patient’s tumor is essential to precision oncology. It opens the door to new therapeutic opportunities for patients and provides oncologists an additional tool to make well-informed clinical decisions. JAX-CKBTM takes the data a step further and enables users to navigate variant relationships and identify the highest level of evidence or relevant clinical trial(s), saving valuable time. Here’s how you can use CKB to navigate tumor category variants.


Imagine the genomic results of a patient’s tumor are being discussed in a molecular tumor board. The patient in question has a gastrointestinal stromal tumor and has failed standard of care therapy. A variant in KIT, which has not been specifically described in the literature, was identified in the tumor. So, how does one determine whether the patient might be eligible for alternative therapies based on a variant that has not been previously described? 

Let’s take a quick step back from our example tumor board. For our discussion, we’ll consider a genomic alteration as a modification that could be used to predict therapeutic response. The key to identifying potential targeted therapies is determining which of the genomic alterations found in the tumor are actionable, and herein often lies the challenge. In some cases, the biomarkers associated with the US Food and Drug Administration (FDA)-approved drugs or professional guidelines are straightforward. For example, BRAF V600E in melanoma patients is included in the FDA approval for Vemurafenib, while EGFR T790M in patients with non-small cell lung cancer is included in the NCCN guidelines for the drug Osimertinib. In these cases, one could easily regard either of these genomic alterations as actionable if identified in a patient’s tumor.

However, there are “non-specific” biomarkers, or higher-level categories of biomarkers, that are frequently included in FDA approvals, professional guidelines, recruiting clinical trials, and even published studies in peer-reviewed journals, which are sometimes the highest level of evidence for a given variant. One example of the use of a non-specific biomarker is in the FDA-drug approval for Avapritinib, which is approved for patients with gastrointestinal stromal tumors harboring a PDGFRA exon 18 mutation. In another instance, the Phase II clinical trial, MATCH, is recruiting patients with KIT exon 11 mutations for treatment with Sunitinib. While these non-specific genomic alterations are considered actionable, how does one quickly and accurately match their patient to a potential therapy if the patient’s identified variant has not been previously described? We know time is of the essence when it comes to identifying a relevant therapy or clinical trial, as there are a number of other factors to consider as well, including insurance coverage and additional eligibility criteria.

The JAX Clinical Knowledgebase (JAX-CKBTM), a database designed for genomic variant interpretation and identification of potential treatment approaches through evidence-based literature, takes the curated data one step further and offers a solution to this problem. The subscription, web-based version of JAX-CKBTM, CKB BOOST, includes content related to more than 1500 genes, and now features category variant relationships. Through category variants, users can navigate variant relationships and identify the highest level of evidence or relevant clinical trial(s) for a given variant. Category variants can be based on protein functional effect, including gain-of-function or loss-of-function. For these instances, the category variant would be described “act mut” (activating mutation), such as EGFR act mut or “inact mut” (inactivating mutation), such as BRCA inact mut.

Additionally, CKB BOOST includes category variants that are based on position, in either the codon or exon. Subsequently, variants within CKB BOOST can then be assigned as a member of a category variant centered on position and/or function. Variant relationships within CKB BOOST can be observed through multiple visuals, which are linked to tables of efficacy evidence annotations. Efficacy evidence annotations in JAX-CKBTM briefly describe the results of a clinical or preclinical study, linking a genomic alteration(s) to a therapy and tumor type. Consequently, the list of efficacy evidence annotations for a variant and the category variant(s) to which the variant belongs allows the user to identify the most appropriate therapy or therapies based on evidence level and variant tier coding. CKB BOOST users also have the ability to search for potentially relevant clinical trials via category variant relationships.

Let’s go back to our scenario of the gastrointestinal stromal tumor patient being discussed at the molecular tumor board. Suppose the variant, KIT W557_K558delinsE, was identified and is reported to potentially result in a gain of protein function. However, there is no direct evidence to support the use of a potential therapy for this variant. Figure 1 provides a preview of how CKB BOOST can identify possible therapies and clinical trials for this patient through category variant relationships.

Gene Variant Detail

KIT W557_K558delinsE results in the deletion of 2 amino acids in the juxtamebrane domain (exon 11) of the Kit protein from amino acids 557 to 558, combined with the insertion of a glutamic acid (E) at the same site (PMID: 16226710). W557_K558delinsE has not been characterized, but is predicted to activate Kit based on the effects of similar Kit exon 11 mutations (PMID: 9438854, PMID: 15365079).

Use Category Variant Paths to Identify Relevant Efficacy Evidence and Clinical Trials

Efficacy Evidence linked to KIT act mut

Molecular Profile Tumor Type Approval Status Evidence Type Efficacy Evidence Evidence Level Inferred Tier
KIT act mut GIST Guideline Diagnostic KIT activating mutations aid the diagnosis of gastrointestinal stromal tumor ( A I
KIT act mut Melanoma Guideline Actionable Gleevec (imatinib) is included in guidelines as second-line therapy for metastatic or unresectable cutaneous melanoma patients with KIT activating mutations ( A I

Clinical Trials linked to KIT exon 11 and KIT mutant

Clinical Trial Phase Therapies Title Recruitment Status
(KIT exon 11)
Phase II Erdafitinib, Copanlisib, Trametinib, Crizotinib, Sunitinib, Sapanisertib, Nivolumab, AZD4547, Dasatinib, Pertuzumab + Trastuzumab, Binimetinib, Osimertinib,... Targeted Therapy Directed by Genetic Testing in Treating Patients With Advanced Refractory Solid Tumors, Lymphomas, or Multiple Myeloma (The MATCH Screening Trial) Recruiting
(KIT mutant)
Phase II Cobimetinib + Vemurafenib, Regorafenib, Ipilimumab + Nivolumab, Palbociclib, Afatinib, Talazoparib, Pembrolizumab, Sunitinib, Olaparib,... TAPUR: Testing the Use of Food and Drug Administration (FDA) Approved Drugs That Target a Specific Abnormality in a Tumor Gene in People with Advanced Stage Cancer Recruiting


As the precision oncology field continues to evolve, the need to have access to a reliable and up-to-date resource for genomic variant interpretation will get stronger. The JAX-CKBTM BOOST application serves as that powerful resource and its innovative feature of category variant relationships further ensures the best-informed clinical decision is made for a patient.

To learn more about JAX-CKBTM and CKB BOOST, visit the CKB home page.


Recommended Resources

CKB Home Page

 Introducing: The Clinical Knowledgebase (CKB), Powered by The Jackson Laboratory

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