Questions Arise about TMB as a Predictive Biomarker for Immune Checkpoint Inhibitor Therapy

Artist rendition of immune cells attacking a cancer cells. Immune checkpoint inhbitor therapy is a relatively new therapy for certain cancers.

Immune checkpoint inhibitor (ICI), or immune checkpoint blockade, therapies are a revolutionary, and relatively new, approach to treating cancer. These therapies work by blocking immune checkpoint proteins that act to negatively regulate the immune system through the PD-1 pathway. Some tumors express immune checkpoints to prevent the immune system from producing a strong enough immune response to kill the cancer cells. When these checkpoint proteins are blocked by an ICI, the body’s T-cells can recognize and kill the cancer cells. ICI therapies show tremendous promise. Unfortunately, not all tumors express immune checkpoint proteins, and so, not all tumors will be effectively treated with ICI therapies. The challenge is differentiating between the tumors that will respond and tumors that won’t.

DNA Mismatch Repair Deficiency Status as Detected by Microsatellite Instability or Immunohisotchemistry are Important Biomarkers for ICI

Biomarkers are measurable indicators of a clinical condition that can be found in tissue, blood, or other fluids. Predictive biomarkers for ICIs can help determine if these therapies are a suitable choice for treatment. Some tumors have deficiencies in their DNA mismatch repair mechanisms. Mismatch repair deficiency (dMMR) leads to the accumulation of mutations across the genome, particularly in microsatellites, which over time can result in higher levels of neoantigen production, rendering the tumors susceptible to the ICI therapy (1–5).

In 2017, Le et al. demonstrated that dMMR status reliably predicted response to an ICI therapy targeting the PD-1 checkpoint protein (6). Following this discovery, ICI based on dMMR  determined using either microsatellite instbility (MSI) or immunohistochemistry (IHC), gained clearance from the US Food and Drug Administation (FDA) for microsatellite instability-high (MSI-H) or dMMR by IHC solid tumors. This was the first time a cancer treatment was cleared based on a biomarker regardless of cancer origin (1,7).  Since then, MSI-H and dMMR, have become some of the most recognized tissue agnostic biomarkers for improved survival following ICI therapy of solid tumors (6,8,9).

Tumor Mutational Burden

In 2020, an FDA-cleared test for tumor mutational burden high (TMB-H) was added as a tumor agnostic predictive biomarker for one ICI therapy (10,11). TMB measures the number of somatic mutations present per megabase of analyzed genomic sequence. A higher mutational burden is expected to correspond to a higher level of neoantigens and tumor infiltrating lymphocytes. For ICI therapies, tumors with a TMB value of at least 10 mutations per megabase have been considered TMB-H and good candidates to respond to treatment. However, there is growing concern in the clinical community that TMB might not be a reliable predictive biomarker for ICI therapy success in all tissue types, given that the indication was based on a relatively small single-arm study (9,12,13).

New Studies Cast Doubt on TMB-high Usefulness as a Biomarker for ICI Therapies with All Solid Tumor Types

Recent studies evaluating TMB as a predictor for ICI threapies have concluded that TMB may not be reliable across all tumor types (9,14,15). One retrospective study that included 1678 patients and 16 different cancer types found that tumors with a TMB of 10 mutations per megabase or more generally had a higher response rate to ICI therapy, but the response was variable across cancer types and the association with survival outcomes was unclear. The authors suggest that TMB may need to be combined with other biomarkers to improve stratification of responders versus non-responders, and conclude that investigation should continue with the goal of better defining cancer-specific TMB cutoffs. (15).

Another study from Memorial Sloan Kettering and Johns Hopkins assesed the impact of a stratification strategy upon 137 patients with advanced colorectal cancer who were treated with ICI. This study found that the the difference in overall survival among patients with TMB-H and TMB low disappeared when MMR proficient tumors were assessed, suggesting that TMB-H was not able to predict response to ICI in tumors with a working MMR system.  The authors further extended their analysis to 1,661 patients with various tumor types and found that TMB-H accurately predicted an increased response to ICI therapies for only 3 cancer types (non-small-cell lung cancer, melanoma, and head and neck). Poorer response in TMB-H tumors was associated with both MMR proficiency and lack of POLD1 mutations, further suggesting that the association between TMB and response to ICI might not be consistent across all tumors and is dependent on MMR status and other mutations (9).

dMMR by MSI or IHC Remains the Reliable Biomarker as the Future Applications of TMB are Further Tested and Refined

Cancer is not one disease—it is hundreds, if not thousands, of different diseases. The power of ICI therapies is that they are tissue agnostic. However, not all cancers are susceptiable to these therapies, making the ability to reliably predict if a tumor will or won’t respond vitally important. There are a multitude of genetic aberrations in cancer that lead to neoantigen formation and sensitivity to ICI therapies. MSI-H and other biomarkers have been shown to predict response to these therapies. However, ICI therapies are still relatively new, and so is our understanding of the value of some predictive biomarkers in different subsets of cancers based on their mutational profiles. As our wealth of knowledge grows, it may lead to a refined recommendation for applying more broad genetic signatures, such as TMB-H, for predicting response to ICI. In the interim,  dMMR by MSI or IHC, remains an established and well supported testing strategy for predicting response to ICI across solid tumors, in addition to expression of immune checkpoint proteins.

To learn more about the value of MSI testing, visit the Microsatellite Instability Resources Center.


  1. Marcus, L. et al. (2019) FDA approval summary: pembrolizumab for the treatment of microsatellite instability-high solid tumors. Clin. Cancer Res., 25, 3753–8.
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  3. Ratti M, Lampis A, Hahne JC, Passalacqua R, Valeri N: Microsatellite instability in gastric cancer: molecular bases, clinical perspectives, and new treatment approaches. Cell Mol Life Sci 2018, 75(22):4151-4162.
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  5. Lizardo, D.Y. et al. (2020) Immunotherapy efficacy on mismatch repair-deficient colorectal cancer: From bench to bedside. Biochim Biophys Acta Rev Cancer 1874, 188447.
  6. Le, D.T. et al. (2015) PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. New Engl. J. Med. 372, 2509–20.
  7. Twomey, J.D., Zhang, B. (2021) Cancer Immunotherapy Update: FDA-Approved Checkpoint Inhibitors and Companion Diagnostics. AAPS J., 23,39.
  8. Shen, H et al. (2019)  Predictive biomarkers for immune checkpoint blockade and opportunities for combination therapies. Genes and Disease 6, 232–46.
  9. Rousseau, B. et al. (2021) The Spectrum of Benefit from Checkpoint Blockade in Hypermutated Tumors. N Engl J Med. 384, 1168–70.
  10. Sha, D. et al. (2020) Tumor mutational burden as a predictive biomarker in solid tumors. Cancer Disc., 10, 1808–25.
  11. Marabelle, A. et al. (2020) Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol., 21, 1353–65.
  12. Subbiah, V., et al. (2020) The FDA approval of pembrolizumab for adult and pediatric patients with tumor mutational burden (TMB) ≥10: a decision centered on empowering patients and their physicians. Ann Oncol. 31, 1115–8. doi:10.1016/j.annonc.2020.07.002
  13. Prasad, V. and Addeo, A. (2020) The FDA approval of pembrolizumab for patients with TMB >10 mut/Mb: was it a wise decision? No. Ann Oncol. 31, 1112–4. doi:10.1016/j.annonc.2020.07.001
  14. McGrail, D.J. et al. (2021) High tumor mutation burden fails to predict immune checkpoint blockeade resoibse acriss all cancer types. J. Ann. Oncol. 32, 661–72.
  15. Valero, C. et al. (2021) Response Rates to Anti–PD-1 Immunotherapy in Microsatellite-Stable Solid Tumors With 10 or More Mutations per Megabase. JAMA Oncol. 7, 739–43.

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Kelly Grooms

Kelly Grooms

Scientific Communications Specialist at Promega Corporation
Kelly earned her B.S. in Genetics from Iowa State University in Ames, IA. Prior to coming to Promega, she worked for biotech companies in San Diego and Madison. Kelly lives just outside Madison with her husband, son and daughter. Kelly collects hobbies including jewelry artistry, reading, writing and knitting. A black belt, she enjoys practicing karate with her daughter as well as hiking, biking and camping.

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