Biomarkers for Predicting Response to Immunotherapy in Cancer

Immunotherapy has transformed cancer treatment by leveraging the body's immune system to fight tumors. However, patients respond variably to these therapies. Biomarkers, measurable biological indicators, offer a promising approach to identify patients most likely to benefit from immunotherapy. This article explores key biomarkers used to predict response to immunotherapy.

Current Predictive Biomarkers:

  • PD-L1 Expression: Programmed death-ligand 1 (PD-L1) is a protein involved in the immune checkpoint pathway, which tumors can exploit to evade immune attack. High PD-L1 expression on tumor cells often correlates with a positive response to immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 pathway. However, PD-L1 expression can vary within tumors and is influenced by the tumor microenvironment. Additionally, some patients with low PD-L1 expression still respond to immunotherapy.
  • Microsatellite Instability (MSI) and Deficient Mismatch Repair (dMMR): MSI is a hypermutable state caused by defects in the DNA repair system. Tumors with high MSI (MSI-H) and dMMR often have a high number of mutations, making them more recognizable and targeted by the immune system. MSI-H/dMMR status is a strong predictor of response to ICIs across various cancers, including colorectal and endometrial cancers.
  • Tumor Mutational Burden (TMB): TMB refers to the number of mutations per unit of DNA in a tumor genome. Tumors with high TMB are thought to express more neoantigens (mutated proteins unique to the tumor) that can be recognized by the immune system. Emerging evidence suggests that TMB may be a pan-cancer predictor of response to immunotherapy, showing promise across diverse cancer types.

Currently validated and evolving predictive biomarkers for response to immune checkpoint inhibitors (ICIs) in patients with TNBC. Abbreviations. PD-L1: programmed death-ligand protein 1; PD-1: programmed death-1.

Emerging Biomarker Research:

The field of immunotherapy biomarkers is rapidly advancing. Researchers are exploring other promising avenues, including:

  • Tumor-infiltrating Lymphocytes (TILs): The presence and composition of TILs, particularly CD8+ T cells, within the tumor microenvironment can indicate the extent of the anti-tumor immune response.
  • Immune Gene Signatures: Analyzing the expression profile of specific immune-related genes within the tumor or blood may provide insights into a patient's immune response and predict response to immunotherapy.

Key biomarkers tested in advanced gastroesophageal adenocarcinomas. Biomarkers are assessed via immunohistochemistry (IHC) in gastric cancer tissue for HER2 testing, PD-L1 CPS testing, and MMR evaluation. MSI and TMB are measured using polymerase chain reaction (PCR) or DNA-based assays such as comprehensive genomic profiling (CGP). CLDN18.2 and FGFR2b are novel biomarkers that utilize the IHC platform. CGP tests can detect various types of genomic alterations, including mutations, copy number variations, and structural rearrangements. They can be performed on different types of samples, including blood and tumor tissues, and analyzed using next-generation sequencing (NGS). Bang, Y.J. et al. 2010 [43], Shitara, K. et al. 2020 [52], Janjigian, Y.Y. et al. 2021 [63], Shitara, K et al. 2022 [76], Cancer Genome Atlas Research Network. 2014 [11], Pietrantonio, F. et al. 2021 [101], Marabelle, A. et al. 2020 [106], Shitara, K. et al. 2021 [107], Su, X. et al. 2014 [117], Wainberg, Z.A. et al. 2022 [122], Ahn, S. et al. 2016 [120], Wainberg, Z.A. et al. 2022 [122], Pellino, A. et al. 2021 [128], Shitara, K. et al. 2023 [131]. Abbreviations: amp, amplification; CPS, combined positive score; EGFR, epidermal growth factor receptor; ERBB2, Erb-B2 Receptor Tyrosine Kinase; FGFR2b, fibroblast growth factor receptor 2b; HER2, human epidermal growth factor receptor 2; ICI, immune checkpoint inhibitor; IHC, immunohistochemistry; MET, MET proto-oncogene, receptor tyrosine kinase; MMR, mismatch repair; MSI, microsatellite instability; NTRK, neurotrophic receptor tyrosine kinase; PD-L1, programmed death-ligand 1; TMB, tumor mutation burden.

Challenges and Future Directions:

Despite the progress made, challenges remain in using biomarkers for immunotherapy selection. These include:

  • Standardization of Assays: Variations in methods for assessing biomarkers like PD-L1 expression can lead to inconsistent results. Standardized assays are crucial for reliable clinical use.
  • Multifactorial Response: Response to immunotherapy is likely influenced by a complex interplay of factors beyond a single biomarker. Combining multiple biomarkers and integrating clinical data may provide a more comprehensive picture.

Conclusion:

Biomarkers hold significant potential for personalized medicine in immunotherapy. Established markers like PD-L1, MSI/dMMR, and TMB offer valuable tools, but further research is needed to refine their use, identify novel biomarkers, and develop comprehensive assessment strategies. Overcoming these challenges will allow us to tailor immunotherapy to each patient, maximizing therapeutic benefit and minimizing unnecessary treatment burden. Companies like Maxanim are continuously developing and refining tools for accurate biomarker assessment, which is vital for advancing this field.


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Biomarkers for Predicting Response to Immunotherapy in Cancer
Gen store June 14, 2024
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