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The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker
Open accessAbstract
Tumor mutational burden (TMB) reflects cancer mutation quantity. Mutations are processed to neo-antigens and presented by major histocompatibility complex (MHC) proteins to T cells. To evade immune eradication, cancers exploit checkpoints that dampen T cell reactivity. Immune checkpoint inhibitors (ICIs) have transformed cancer treatment by enabling T cell reactivation; however, response biomarkers are required, as most patients do not benefit. Higher TMB results in more neo-antigens, increasing chances for T cell recognition, and clinically correlates with better ICI outcomes. Nevertheless, TMB is an imperfect response biomarker. A composite predictor that also includes critical variables, such as MHC and T cell receptor repertoire, is needed.
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“In certain tumour types, the number of neoantigens in a tumour (or tumour mutational burden (TMB)) is correlated with responsiveness to ICIs67,68.”
From Adjuvant and neoadjuvant immunotherapies in hepatocellular carcinoma (2024) · cites this paper as [67]
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“5 19 When tumor cells attempt to escape such immune responses, they may simultaneously regulate PD-L1 expression and TMB.”
Aberrant SUMOylation Restricts the Targetable Cancer Immunopeptidome
Demel, U. M., Meurer, A., Zaghla, B. K. Q., Atay, B., Steiert, D., Hummel, L. V., Isaakidis, K., Zang, C., Korenkov, M., Schielin, M., et al. (2026) · Advanced Science · doi:10.1002/advs.202511449 · Cited by 1
“Remarkably, high TMB is associated with increased expression of tumor-specific neoantigens, overall potentiating the patient’s therapeutic response to ICB [ 8 ].”
Zhu, S., Li, W., Zhang, H., Lin, Y. E., & Chen, Z. (2026) · Biomarkers in Medicine · doi:10.1080/17520363.2026.2625220 · Cited by 2
Zhu, J., Luo, M., Yuan, L., He, J., Wang, Z., Deng, Q., Wang, J., Jin, M., Liu, G., Liang, H., et al. (2026) · Cell & Bioscience · doi:10.1186/s13578-026-01538-7 · Cited by 1
“5D) [32].”
Kim, H., Lee, H., Lee, S., Lee, Y., Hyung, J., Moon, M., Shin, J., Park, Y. S., & Ryu, M. (2026) · Journal of the Korean Gastric Cancer Association · doi:10.5230/jgc.2026.26.e14 · Cited by 1
“Mechanistically, Indels frequently cause frameshift mutations, which generate more immunogenic neoantigens than SNVs [14,19,20].”
Overcoming Immunotherapy Resistance in Small-Cell Lung Cancer
Canale, M., Suzzi, F., Verlicchi, A., Citarella, F., Delmonte, A., & Ulivi, P. (2026) · Biology · doi:10.3390/biology15040356 · Cited by 1
“The influence of finding an optimal cut-off and the variability of different genomic tests limit the potential of TMB as a reliable predictor of immunotherapy benefit [9].”
Kuroda, S., Tazawa, H., Hashimoto, M., Kanaya, N., Kakiuchi, Y., Kagawa, S., Urata, Y., & Fujiwara, T. (2026) · International Journal of Clinical Oncology · doi:10.1007/s10147-026-02991-7 · Cited by 1
“Furthermore, the intrinsically low tumor mutation burden (TMB) and downregulation of major histocompatibility complex (MHC) molecules reduce the immunogenicity of pancreatic cancer, allowing tumors to evade immune surveillance [34].”
Tumor Mutational Burden Shapes Success and Resistance in Cancer Immunotherapy
Aguadé‐Gorgorió, G. (2026) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2026.112421 · Cited by 1
Li, X.-N., Wei, L. L., Wang, S.-Y., Yu, Y.-K., Hazaisihan, Y., Gao, X., Huang, L.-J., Meng, Q.-H., Zheng, Y.-Q., & Jia, W. (2026) · Scientific Reports · doi:10.1038/s41598-026-42628-3 · Cited by 1
Biomarker-guided immunotherapy in gastric cancer: current insights and future perspectives
Mulet, M. T., Rodríguez, J. V., Terán, E., Piñol, M., Vilardell, F., Iglesias, M., Hierro, C., Calvo, M., Matías‐Guiu, X., Salud, A., et al. (2026) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2026.103124 · Cited by 1
Bauer, A., Arndt, A., Reichenbach, L. B., Gebauer, N., Müller, M. M., Neumann, C., Schulz, C., Steinestel, K., Heller, R. A., Chteinberg, E., et al. (2026) · Cancers · doi:10.3390/cancers18071087 · Cited by 1
“…immune escape in brain metastases may be dominated by microenvironmental and metabolic suppression programs that can operate independently of neoantigen burden, consistent with current perspectives questioning the predictive value of TMB in immunologically constrained metastatic niches [35,36].”
Swiecicki, P. L., Othus, M. K. D., Patel, S. P., Chae, Y. K., & Kurzrock, R. (2026) · Cancer · doi:10.1002/cncr.70374 · Cited by 1
“19,20 Imaging is a tool that is broadly used and thus is amenable to analysis in relation to outcome.”
Self-citationYang, H., Zhu, Z., Zhu, H., Li, N., Zheng, S., Hu, L., Wu, Z., & Shi, Y. (2026) · Cancers · doi:10.3390/cancers18071144 · Cited by 1
“Previous studies have demonstrated that elevated TMB leads to the generation of more neoantigens, which are processed and presented by major histocompatibility complex (MHC) molecules to T cells, thereby eliciting an anti-tumor immune response [37].”
Immunotherapy in Thyroid Cancer: Current Strategies and Challenges
Zhang, Q. P., Wang, F., Ma, W., Liu, N., Lu, Y., & Zhang, P. X. (2026) · Cancer Medicine · doi:10.1002/cam4.71742 · Cited by 1
“A low TMB implies fewer neoantigens produced by the tumor, and the absence of tumor-specific antigens may hinder the effective activation of immune responses by anti- PD-1/PD-L1 therapy [82, 83].”
Calabrò, C., Palma, G. D., Gheit, T., Iacovelli, S., Mastrandrea, G., Rizzo, A., & Palermo, L. (2026) · Expert Review of Clinical Pharmacology · doi:10.1080/17512433.2026.2665455 · Cited by 1
“To escape immune elimination, cancers exploit checkpoints that suppress T-cell activity [32].”
He, L., Zhao, M., Hu, Y., Chen, L., & Zheng, B. (2026) · International Immunopharmacology · doi:10.1016/j.intimp.2026.116797 · Cited by 1
Konečný, T., Zadirako, N., Grigoryan, A., Tamazyan, M., Mnatsakanyan, S., Stepanyan, L., Loeffler‐Wirth, H., Bourdelais, S., Mednick, G., Delepine, C., et al. (2026) · Oncogene · doi:10.1038/s41388-026-03861-2 · Cited by 1
“These fi ndings support the hypothesis that tumor heterogeneity is shaped by both the developmental state of epithelial tumor cells and their dynamic interactions with the TME and its varying composition, although the ATRX loss, CIMP status, and copy-number changes were inferred from…”
Microbiome–Driven Carcinogenesis and Circulating Microbial Signals in Genitourinary Cancers
Kawashima, A., Jingushi, K., Saito, T., Uemura, T., Yamamoto, A., Sassi, N., Horitani, H., Inoguchi, S., Horibe, Y., Ishizuya, Y., et al. (2026) · Cancer Science · doi:10.1111/cas.70448 · Cited by 1
“Tumor-intrinsic markers such as PD-L1 expression, tumor mutational burden, and related gene-expression features can be informative, but they do not fully explain the heterogeneity of clinical benefit observed across patients [59, 60].”
Radiotherapy-Associated Systemic Antitumor Responses Beyond the Classical Abscopal Paradigm
Dotsu, Y., Akagi, K., Honda, N., Matsuo, M., Taniguchi, H., Takemoto, S., & Mukae, H. (2026) · Cancers · doi:10.3390/cancers18132098 · Cited by 1
“Similarly, ctDNA kinetics and TCR repertoire changes are promising tools for monitoring tumor burden and adaptive immune activation, but their role in confirming radiation-associated systemic immune responses remains to be explored [73,74].”
Umar, S., Shahid, Z., O’Cathail, M., & Sivanandan, A. (2026) · Journal of Skin Cancer · doi:10.1155/jskc/8993856 · Cited by 1
Xiang, M., Liu, S., Xiao, D., & Tao, Y. (2026) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-026-02810-5 · Cited by 1
“188 TMB quanti fi es the mutation load in tumors and is a predictive biomarker for response to immunotherapy.”
Dong, D., Wang, W., Wang, H., Chen, L., & Liu, T. (2022) · Journal of Oncology · doi:10.1155/2022/5722599 · Cited by 1
Li, F., Dong, K., Zhang, C., Wang, J., Tang, Y., Xue, K., Zheng, X., Song, K., Zhang, X., Li, M., et al. (2023) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-023-03414-6 · Cited by 1
Chen, M., Li, P., Yao, H., Liu, F., Fu, L., Wang, Y., Zhu, J., Xu, Q., Liang, H., Zhou, Y., et al. (2023) · Translational Andrology and Urology · doi:10.21037/tau-23-21 · Cited by 1
“And nonsynonymous gene mutation results in more neo-antigens, thus increasing chances for T cell recognition, and indicating better ICI outcomes (17).”
Evolution of Biomarkers and Treatment Outcomes of Immunotherapy in Lung Cancer
Kaler, A. K., Maskomani, S., Ritambhara, Kavyashree, K., Vadera, V., Choudhary, V., Shaikh, I. N., Goyle, S., & Mistry, R. (2023) · Current Tissue Microenvironment Reports · doi:10.1007/s43152-023-00047-w · Cited by 1
“However, the combination of both factors would enhance the predictive power significantly [51, 52].”
Wu, W.-S., Chang, F., Zhang, J., Tang, S., Lv, Z., & Chen, F. (2023) · Scientific Reports · doi:10.1038/s41598-023-43065-2 · Cited by 1
Stroma-associated FSTL3 is a factor of calcium channel-derived tumor fibrosis
Li, J.-P., Liu, Y., Yin, Y. H., Li, R., Huang, W., & Zou, X. (2023) · Scientific Reports · doi:10.1038/s41598-023-48574-8 · Cited by 1
“Further calculations showed that FSTL3 was independent of MSI but inversely associated with TMB (r = − 0.244, P 0.001, Fig.”
MethodInfluentialLi, W., Han, C., Cai, C., Wu, J., Chen, J., & Su, C. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26974 · Cited by 1
Prognostic value and immune landscapes of anoikis-associated lncRNAs in lung adenocarcinoma
Wu, B. C., Zhang, X., Feng, N., Guo, Z., Gao, L., Wan, Z., & Zhang, W. (2024) · Aging · doi:10.18632/aging.205481 · Cited by 1
“Furthermore, TMB is usually employed as a predictive indicator for immunotherapy in urothelial, lung and head and neck squamous cell cancers [31].”
Background
Metadata
- Authors
- Jardim, D. L., Goodman, A., de Melo Gagliato, D., & Kurzrock, R.
- Affiliations
- Hospital Sírio-Libanês (BR)
- University of California San Diego (US)
- Corresponding author
- Kurzrock, Razelle
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 39
- Issue
- 2
- Pages
- 154-173
- ISSN
- 1535-6108 (ISSN-L)
- PMC
- PMC7878292
- OpenAlex
- W3097803258
- Cited by
- 1,192
- References
- 151
- Citations by year
- 2026: 134 · 2025: 263 · 2024: 294 · 2023: 276 · 2022: 171 · 2021: 53
- FWCI
- 13.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 372 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cancer Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Astellas Pharma US
- National Cancer Institute (P30 CA023100)
- Janssen Pharmaceuticals
- AstraZeneca
- Bristol-Myers Squibb
- Genentech
- Roche
- EMD Serono
- Pfizer
- Meso Scale Diagnostics
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- tumor mutational burden, immunotherapy biomarkers, immune checkpoint inhibitors, neoantigens, MHC class I antigen presentation, T cell receptor repertoire, cancer immunotherapy response prediction
- MeSH terms
- Immune Checkpoint Inhibitors, Humans, Immunotherapy, Major Histocompatibility Complex, Mutation, Neoplasms, T-Lymphocytes, Biomarkers, Tumor
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