Assessing Biomarker Testing Results to Inform Treatment

Summary: This resource outlines the framework used by molecular tumor boards to evaluate the potential benefit of targeted therapies based on biomarker testing results. 

By JAX Clinical Education | May 2026  

Biomarker testing may identify one or more alterations that predict response to targeted therapy. These targeted therapies may be FDA-approved for the patient’s cancer type, FDA-approved for a different cancer type (off-label) or primarily available through clinical trials. It can be challenging to know which, if any, of these therapies is most likely to benefit a patient since the evidence evolves over time.  

Molecular tumor boards (MTBs) play an important role in weighing the available evidence and helping providers prioritize the treatment options. For each biomarker under consideration, MTBs typically explore a series of connected questions. These questions are rarely answered in isolation and often require revisiting as new information emerges. The framework and tools below describe the general steps taken to assess the evidence supporting treatment options. 

What Is the Biological Role of the Gene? 

Knowing the role of the gene in the biological pathway targeted by the therapy can be helpful in assessing the likelihood of response. Some test reports list targeted therapies for variants that are a few steps removed from the biologic pathway that is targeted by the therapy. Although many pathogenic variants affect shared downstream pathways, proximity to the target pathway alone is not sufficient to support therapy selection. 

MTB members often ask: 

• Is this gene a known driver of tumor behavior?
• Where does the gene sit within the relevant biological pathway?
• Is the gene a direct target of therapy or an upstream/downstream component?

What Is the Functional Impact of the Specific Variant? 

Not all variants in the same gene behave similarly. MTBs pay close attention to variant-level effects rather than relying solely on gene-level associations. 

Variants may: 

• Activate gene function (gain of function)
• Inactivate gene function (loss of function)
• Have no functional effect (benign)
• Have an unknown or unclear effect (variant of uncertain significance)

Both activating and inactivating events can disrupt normal regulation of cell growth, proliferation, or death, but their therapeutic implications may differ dramatically. 

MTB discussions often focus on: 

• Whether functional data exist for this specific variant
• Whether the variant’s predicted effect aligns with reported drug sensitivity or resistance
• The degree of confidence in functional interpretation 

How Does the Therapy Work? 

Understanding a therapy’s mechanism of action helps experts anticipate whether it is likely to be effective in the presence of a given alteration. Targeted therapies act on biological pathways that drive cancer behavior, including sustained cell growth, resistance to cell death, and angiogenesis. For example, tyrosine kinase inhibitors (e.g., erlotinib) block pro-growth signaling pathways while PARP inhibitors (e.g., niraparib) induce cancer cell death. 

MTBs ask: 

• What pathway or process does the therapy target?
• Does it directly target the altered gene, exploit a downstream effect, or act independently of the variant?
• At what biological level does the therapy exert its effect?

Is the Variant’s Functional Consequence Compatible with the Therapy? 

Some reports identify treatment options that have been associated at the gene level but not necessarily at the variant level. Because variants can have different impacts on gene function, it is important to determine whether the therapy is compatible with the impact of the variant. 

For example: 

• A pathway-inhibiting therapy is more likely to be effective when a variant causes pathway activation
• The same therapy may be ineffective or redundant if the variant already inactivates that pathway

MTBs also evaluate: 

• Whether the variant is known to confer resistance
• Whether secondary or co-occurring alterations could blunt the therapy’s effect
• Whether the association is based on gene-level data without variant-specific support

Are There Co‑Occurring Alterations That Modify Response? 

Tumors rarely rely on a single alteration. The presence of additional variants can enhance, diminish, or negate the expected benefit of a targeted therapy. 

Expert discussions often include: 

• Known resistance-associated alterations (primary or acquired)
• Changes in parallel or downstream pathways
• Whether the tumor appears biologically dependent on the alteration

This step frequently explains why an apparently “actionable” alteration may not be prioritized. 

What Is the Strength and Relevance of the Evidence? 

MTBs weigh evidence across multiple dimensions, recognizing that not all evidence is equal and that relevance is context-dependent. 

Evidence may come from: 

• Preclinical studies
• Early-phase or late-phase clinical trials
• Tumor-agnostic approvals
• Retrospective analyses or real-world data
• Institutional or registry-based experience

Experts consider: 

• Whether evidence applies to this specific variant
• Whether it applies to this specific cancer type
• How similar the studied population is to the patient under review

While clinical data generally carry greater weight, lower-level evidence may still inform discussion, particularly for rare variants or understudied cancers. 

Integrating Evidence Into Clinical Decision-Making 

After evaluating each potentially relevant finding, MTBs integrate additional clinical context to prioritize options. Key considerations include: 

• Prior treatments and treatment response
• Current disease status and comorbidities
• Expected toxicity and treatment burden
• Patient goals, preferences, and logistics
• Clinical trial eligibility and feasibility

MTBs also assess timing—whether a therapy is best considered now, reserved for later lines, or pursued only in a research setting. 

Learn More

Exploring Cancer Biomarker Testing (CME | CNE). Learn about benefits, limitations, and challenges of using cancer biomarker testing.

Choosing the Best Genomic Tumor Test (CME | CNE). Learn about the benefits and limitations of different genomic tumor test options for patients with cancer and how to determine the best test for each patient.

Interpreting Cancer Biomarker Testing – When is Additional Testing Needed? (JAX). Learn when additional cancer biomarker testing is indicated for further evaluation of genome-informed therapy.

Interpreting Cancer Biomarker Testing for Genetic Counselors (JAX). Practice evaluating biomarker test reports to determine when genetic testing for hereditary cancer risk is indicated for a patient

How to Maximize the Molecular Tumor Board Experience (JAX). Suggests ways for you to make the most of the genomic tumor board experience.

References

Chakravarty D, Gao J, Phillips SM, et al. OncoKB: A Precision Oncology Knowledge Base. JCO Precis Oncol. 2017;2017:PO.17.00011.

Dumbrava EI, Meric-Bernstam F. Personalized cancer therapy-leveraging a knowledge base for clinical decision-making. Cold Spring Harb Mol Case Stud. 2018;4(2).

Li MM, Datto M, Duncavage EJ, et al. Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J Mol Diagn. 2017;19(1):4-23.

Meric-Bernstam F, Johnson A, Holla V, et al. A decision support framework for genomically informed investigational cancer therapy. J Natl Cancer Inst. 2015;107(7).

Disclaimer 
All information in this resource is provided for educational purposes only.