Molecular Biomarkers of Response to Cancer Immunotherapy
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- Title: Molecular Biomarkers of Response to Cancer Immunotherapy
- Author: Lauren L. Ritterhouse MD, PhD and Tasos Gogakos MD, PhD
- Publication: Clinics in Laboratory Medicine
- Publisher: Elsevier Inc
- Year: 2022
- Language: English
- Pages: 16
- Format: PDF
- File size: 336 KB
- DOI: https://doi.org/10.1016/j.cll.2022.05.004
- CBID: CBR254
Harnessing the immune system to advance cancer therapy has offered a new weapon in the quiver of clinical oncology. The lack of uniform, robust, or durable responses in many patients has necessitated the development of approaches for the accurate prediction of subgroups that are most likely to benefit from immunotherapy. This has led to the development and regulatory approval of predictive biomarkers, as well as associated companion diagnostics. Despite these strides, there still exists great heterogeneity in the choice of biomarkers, the laboratory assays that generate them, and their overall clinical utility. This article surveys broadly the predictive biomarkers of response to cancer immunotherapy, focusing on the biomarkers with current Food and Drug Administration (FDA) approval, and raising awareness of issues that may affect their broad applicability.
Key points
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The lack of uniform responses to immunotherapy has necessitated the development of biomarkers predictive of response to immune checkpoint inhibitors.
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Three Food and Drug Administration (FDA)-approved biomarkers have shown important, yet heterogenous, utility in clinical practice.
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The development of predictive biomarkers has created a shift in clinical practice, with drug approvals based on biomarker status alone and not tumor type or site.
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Currently, there is no ideal biomarker that can accurately predict the response of every patient to ICIs.
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Development of novel and combination of multiple biomarkers may benefit more patients in the future.
Introduction
Harnessing the immune system to advance cancer therapy has offered a new weapon in the quiver of clinical oncology. The lack of uniform, robust, or durable responses in many patients has necessitated the development of approaches for accurate prediction of subgroups that are most likely to benefit from immunotherapy. This has led to the development and regulatory approval of predictive biomarkers, as well as associated companion diagnostics. Despite these strides, there still exists great heterogeneity in the choice of biomarkers, the laboratory assays that generate them, and their overall clinical utility. This article surveys broadly the predictive biomarkers of response to cancer immunotherapy, focusing on the biomarkers with current FDA approval, and raising awareness of issues that may affect their broad applicability.
Immune Checkpoint Inhibitors
Immune checkpoints inhibitors (ICIs) have evolved to maintain homeostasis and protect against autoimmunity. They are established by the interaction of surface proteins on immune cells (T cells) with antigen-presenting or antigen-expressing cells. Productive binding between these members of these 2 classes of proteins results in immunosuppressive signaling that attenuates the activation of T cells, keeping them in an “off” state.
The discovery of such immunosuppressive mechanisms provided a possible path to the activation of the immune system against tumor cells that, owing to their underlying mutational processes, express neoantigens. In order for such therapies to be effective, the immune system has to be able to recognize the tumor as antigenically different from self. In principle, the more antigenic the tumor, the more potent the effect of such therapies. The demonstration that inhibitory antibodies against such molecules can elicit an antitumor response ushered in a new era in clinical oncology.
Immunotherapy has essentially resulted in a paradigm shift in cancer treatment. Instead of targeting tumor vulnerabilities by direct cytotoxic or targeted therapies, ICIs use the host’s immune system for the elimination of cancer cells. Since the approval of the first ICI targeting CLTA-4 inhibition for the treatment of melanoma, several other agents have become available, either as single or combination therapies, in at least 15 different tumor types. Available ICIs in clinical practice include monoclonal antibodies against the programmed cell death protein (PD-1), its ligand (PD-L1), and the cytotoxic T-lymphocyte antigen 4 (CTLA-4).
Additional immune checkpoints are also being investigated in clinical trials. Lymphocyte activating gene 3 (LAG-3) negatively regulates the lymphocytic response by inhibiting several ligands, acting synergistically with PD-1, , making it a promising target for overcoming resistance to PD-1-based immunotherapy , As of this writing, 69 clinical trials on LAG-3 are currently active or recruiting ( http://www.clinicaltrials.gov/ ). T-cell immunoglobulin and mucin domain 3 (TIM-3) is expressed on multiple immune cell types as well as leukemic stem cells, and marks terminally exhausted CD8-positive T cells. Expression of TIM-3 in tumor-infiltrating immune cells may correlate with worse prognosis or more advanced metastasis in multiple cancers. Concurrent blockade of TIM-3 and PD-1 has shown promising results in preclinical trials in solid and hematologic malignancies.
Even though ICIs have taken center stage in immunotherapy, and are the main focus of this article, it should be noted that there exist multiple other modalities of exploiting the immune system against cancer. These include T-cell transfer therapy of tumor-infiltrating lymphocytes (TILs), chimeric antigen receptor T-cell (CAR-T) cell therapies, tumor-specific monoclonal antibodies, cancer vaccines, and immune modulators, such as cytokine therapy. , In the context of this blooming field, it is essential that the development of accurate biomarkers keep up with the pace of treatment advances, to ensure maximal benefit for patients.
Food and Drug Administration-approved biomarkers
Despite impressive rates of durable clinical response in multiple patients with advanced cancer, not all patients benefit from ICI treatment. The range of response rates varies widely with approximately 20% response rates across all indications. In addition, patients can experience serious adverse events. The variability of response rates among patients suggests the presence of biomarkers that could more accurately predict clinical responses in specific patient subgroups. Taken together the lack of uniform response and the associated toxicity of ICI therapy necessitate the deployment of predictive biomarkers. The next section will focus on the 3 predictive biomarkers that are currently approved by the US Food and Drug Administration (FDA): PD-L1 expression, mismatch repair deficiency/microsatellite instability (dMMR/MSI), and tumor mutational burden (TMB).
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