Cited by 1,192Cancer Immunotherapy and BiomarkersImmunotherapy and Immune ResponsesCancer Genomics and Diagnostics

The DOI matches its Crossref record; 149 of the 151 references it cites were found in a registry or an index.

The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker

Open access

Jardim, Denis L., Goodman, Aaron, de Melo Gagliato, Debora, Kurzrock, Razelle·2021·Cancer Cell

DOI 10.1016/j.ccell.2020.10.001PMC PMC7878292

Open this paper in CoChat — free account Open PDF

Abstract

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1016/j.ccell.2020.10.001

Cites

149 of 149 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay‐Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,320
Improved Survival with Ipilimumab in Patients with Metastatic Melanoma
Hodi, F. S., O'Day, S. J., McDermott, D. F., Weber, R. W., Sosman, J. A., Haanen, J. B., Gonzalez, R., Robert, C., Schadendorf, D., Hassel, J. C., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1003466 · Cited by 15,155
Signatures of mutational processes in human cancer
Initiative, A. P. C. G., Alexandrov, L. B., ICGC Breast Cancer Consortium, ICGC MMML-Seq Consortium, PedBrain, I., Nik-Zainal, S., Wedge, D. C., Aparicio, S. A. J. R., Behjati, S., Biankin, A. V., et al. (2013) · Nature · doi:10.1038/nature12477 · Cited by 9,660
Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer
Borghaei, H., Paz-Ares, L., Horn, L., Spigel, D. R., Steins, M., Ready, N. E., Chow, L. Q., Vokes, E. E., Felip, E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1507643 · Cited by 9,335
Nivolumab versus Docetaxel in Advanced Squamous-Cell Non–Small-Cell Lung Cancer
Brahmer, J., Reckamp, K. L., Baas, P., Crinò, L., Eberhardt, W. E. E., Poddubskaya, E., Antonia, S., Pluzanski, A., Vokes, E. E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1504627 · Cited by 8,447
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade
Le, D. T., Durham, J. N., Smith, K. N., Wang, H., Bartlett, B. R., Aulakh, L. K., Lu, S., Kemberling, H., Wilt, C., Luber, B. S., et al. (2017) · Science · doi:10.1126/science.aan6733 · Cited by 6,645
Nivolumab in Previously Untreated Melanoma without BRAF Mutation
Robert, C., Long, G. V., Brady, B., Dutriaux, C., Maio, M., Mortier, L., Hassel, J. C., Rutkowski, P., McNeil, C., Kalinka-Warzocha, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1412082 · Cited by 5,519
Immune-Related Adverse Events Associated with Immune Checkpoint Blockade
Postow, M. A., Sidlow, R., & Hellmann, M. D. (2018) · New England Journal of Medicine · doi:10.1056/nejmra1703481 · Cited by 4,849

Show all 151 references

Research works printed but not linked: 1

Galsky, 2017, Impact of tumormutation burden on nivolumab efficacy in secondline urothelial carcinoma patients: exploratory analysis of the phase II checkmate 275 study, Ann. Oncol., 28, v295, 10.1093/annonc/mdx371.003 · DOI

Sorted by citations

Items 701–800 of 1,000

The Role of Human Endogenous Retroviruses in Cancer Immunotherapy of the Post-COVID-19 World
Logotheti, S., Stiewe, T., & Georgakilas, A. G. (2023) · Cancers · doi:10.3390/cancers15225321 · Cited by 4
Immunotherapy as a promising treatment strategy for dmmr colorectal cancer with brain metastasis: a case report
Cheng, X., He, W., Zhong, W., Tong, C., & Wu, G. S. (2023) · Journal of Cancer Metastasis and Treatment · doi:10.20517/2394-4722.2023.85 · Cited by 3
Pan-analysis reveals CACYBP to be a novel prognostic and predictive marker for multiple cancers
Mo, B. (2024) · American Journal of Translational Research · doi:10.62347/owvw7440 · Cited by 3
BRAFV600E Metastatic Melanoma Journey: A Perspective from a Patient and his Oncologist
Finke, C., & Mohr, P. (2024) · Advances in Therapy · doi:10.1007/s12325-024-02883-0 · Cited by 3
“Genetic biomarkers will most likely also play an increased role in deciding which patients need prophylactic tumour therapy [42, 43].”
Background
Neoadjuvant Immunotherapy in Non-melanoma Skin Cancers of the Head and Neck
Ezzibdeh, R. M., Diop, M., & Divi, V. (2024) · Current Treatment Options in Oncology · doi:10.1007/s11864-024-01197-1 · Cited by 3
Comprehensive pan-cancer analysis reveals CDC6 as a potential immunomodulatory agent and promising therapeutic target in pancreatic cancer
Pu, D., Xu, Y., Yu, H., Yang, T., Tang, L., Tan, W., Zhang, W., & Liu, S. (2024) · Translational Cancer Research · doi:10.21037/tcr-24-505 · Cited by 3
“TMB quantifies the number of gene mutations within a specific tumor tissue, defined as mutations per megabase of the coding sequence in the genome of tumor samples (36,37).”
Mutational Landscape of Gastric Adenocarcinoma of the Fundic Gland Type Revealed by Whole Genome Sequencing
Hu, W., Chen, Z. M., Xue, X. F., Li, X., Yang, G. H., Zhai, Z. Y., Huang, Z. Y., Zhou, P., Bao, C. J., You, L. J., et al. (2024) · Cancer Medicine · doi:10.1002/cam4.70290 · Cited by 3
Integration of bulk and single-cell RNA-seq reveals prognostic gene signatures in patients with bladder cancer treated with immune checkpoint inhibitors
Cho, M., Chang, H. K., & Kim, J. H. (2024) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-024-03839-7 · Cited by 3
“TMB is widely used as an immunotherapeutic marker of antitumor activities [36].”
An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer
Das, S. K., Patel, V., Chakravarty, S., Ghosh, A., Mukhopadhyay, A., & Biswas, N. K. (2025) · BioData Mining · doi:10.1186/s13040-024-00420-x · Cited by 6
“Additionally, the relatively low mutation burden of HNSC makes it less responsive to traditional immunotherapy [43].”
Using Cancer-Associated Fibroblasts as a Shear-Wave Elastography Imaging Biomarker to Predict Anti-PD-1 Efficacy of Triple-Negative Breast Cancer
Zhang, Z., Liang, S.-Y., Zheng, D., Wang, S., Zhou, J., Wang, Z., Huang, Y., Chang, C., Wang, Y.-Y., Guo, Y., et al. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26083525 · Cited by 3
“At present, existing biomarkers used to predict immunotherapy response rely on invasive methods such as programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) expression [6,7].”
A comprehensive analysis of deubiquitinase USP20 on prognosis and immunity in pan‐cancer
Wang, T., Bai, Y., Dong, Y., Qin, J., Zhou, X., Wang, A., Liu, D., Li, X., Ma, Z., & Hu, Y. (2025) · The FASEB Journal · doi:10.1096/fj.202402603r · Cited by 3
“46,47 The HRD status is highly correlated with sensitivity to platinum-based chemotherapy and poly-ADP ribose polymerase (PARP) inhibitors, which serve as biomarkers for treatment options and prognosis in various tumors.”
Lung Immune Prognostic Index-Based Predictive Score in Advanced Non-Small Cell Lung Cancer with a Programmed Death Ligand-1 Tumor Proportion Score ≥ 50%
Raphael, A., Feldman, A. K., Lazarev, I., Kian, W., Peled, N., Hod, K., Shalata, W., & Dudnik, E. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14103543 · Cited by 3
“However, it remains impractical in routine care due to high costs, complex assays, and inconsistent prognostic data [3–5].”
ARID1A mutational status in non-small cell lung cancer: from molecular pathology to clinical implications with a focus on the relationships with EGFR
Lecce, C. D., Eccher, S., Simbolo, M., Cocomazzi, A., Piredda, M. L., Caliò, A., Cima, L., Munari, E., Veronese, N., Avancini, A., et al. (2025) · Lung Cancer · doi:10.1016/j.lungcan.2025.108594 · Cited by 3
Using Multiomics and Machine Learning: Insights into Improving the Outcomes of Clear Cell Renal Cell Carcinoma via the SRD5A3-AS1/hsa-let-7e-5p/RRM2 Axis
Sun, M., Yang, Z., Luo, Y., Qin, L., Peng, L., Pan, C., Yan, J., Qiu, T., & Zhang, Y. (2025) · ACS Omega · doi:10.1021/acsomega.5c01337 · Cited by 3
Molecular characteristics by race and ethnicity of patients with high tumor mutational burden, high microsatellite instability, and mismatch repair deficiency: Real-world data from the multi-institutional Endometrial cancer Molecularly Targeted Therapy Consortium (ECMT2)
Lee, S. S., Secord, A. A., Friedman, S., Hade, E. M., Smitherman, C., Bisht, N., Borden, L., Jackson, A. L., Backes, F. J., Thaker, P. H., et al. (2025) · Gynecologic Oncology · doi:10.1016/j.ygyno.2025.07.006 · Cited by 3
Biomarkers of immunotherapy response in neuro-oncology
Landry, A., Ellenbogen, Y., Ajisebutu, A. A., Gui, C., Gao, A. F., Nassiri, F., & Zadeh, G. M. (2025) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdaf104 · Cited by 3
Pan-cancer multi-omics profiling reveals ubiquitin D as a novel biomarker for diagnosis, immune microenvironment remodeling and prognostic prediction
Su, Y., Wang, Y., Liu, F., & Chen, Q. (2025) · Discover Oncology · doi:10.1007/s12672-025-03545-5 · Cited by 3
“Several studies have shown that TMB, MSI, and NEO are very attractive related biomarkers to guide tumor immunotherapy [67, 68].”
Construction and verification of a prognostic risk model based on immunogenomic landscape analysis of bladder caner
Zhang, Y., Xie, Y., Feng, Y., Wang, Y., Xu, X., Zhu, S., Xu, F., & Feng, N. (2021) · Gene · doi:10.1016/j.gene.2021.145966 · Cited by 3
Bioinformatics Analysis Based on TCGA: MUC16 Mutation Correlates with Clinical Outcome in Gastric Cancer
Huang, L., Zheng, S., Fu, J., Zhang, M., Ge, X., & Mu, N. (2022) · Disease Markers · doi:10.1155/2022/6734105 · Cited by 3
The prognostic value of tumor mutational burden related 6-gene-based Risk Score in laryngeal cancer patients
Dong, Y., Liu, J., Liu, N., Yin, C., Zhang, H., & Xu, J. (2022) · BMC Oral Health · doi:10.1186/s12903-022-02534-2 · Cited by 3
“These mutations are processed into neoantigens, then they are presented to T cells, so higher TMB level may incline to harbor more neoantigens as targets for activated immune cells, which thereby increases the chances for T cell recognition and enhances anti-tumor effects [12].”
Background
Pancancer Analysis of the Prognostic and Immunotherapeutic Value of Progestin and AdipoQ Receptor 4
Yang, Z., Zhu, Y., Li, Z., Pu, Z., Lin, Y. N., Deng, Y., Li, N., & Peng, F. (2022) · Computational and Mathematical Methods in Medicine · doi:10.1155/2022/2528164 · Cited by 3
“TMB is an indicator of the efficacy of anti-PD1/PDL1 therapy in tumors, and persistently high TMB improves efficacy of immune checkpoint blockade therapy [29, 47].”
Background
Gene S-phase kinase associated protein 2 is a novel prognostic marker in human neoplasms
Li, G., Huang, T., & Zhou, H. (2023) · BMC Medical Genomics · doi:10.1186/s12920-023-01561-4 · Cited by 3
“SKP2 expression with immunity Elevated MSI and TMB tend to increase immune neoantigen levels [28, 29]; thus, the relationship between immune neoantigen count and SKP2 expression was investigated.”
Background
The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation
Li, S., Wang, X., Liu, Y., Xiao, J., & Yi, J. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1170640 · Cited by 4
“It is generally believed that in malignant patients with high TMB, more antigens are induced that could enhance tumor immunogenicity, by which ICI response are more prevalent, leading to a better prognosis (Jardim et al., 2021).”
Background
Next generation immuno-oncology biomarkers in gastrointestinal cancer: what does the future hold?
Abushukair, H. M., Ababneh, O. E., Al-Bzour, A. N., Şahin, İ. H., & Saeed, A. (2023) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2023.2252739 · Cited by 3
“The two commonly used approaches include whole exome sequencing (WES) and targeted gene panels [58].”
BackgroundMethod
Pan-cancer analysis and experimental validation identify ndc1 as a potential immunological, prognostic and therapeutic biomarker in pancreatic cancer
Shen, Q., Li, J., Zhang, C., Pan, X., Li, Y., Zhang, X., En, G., & Pang, B. (2023) · Aging · doi:10.18632/aging.205048 · Cited by 3
Multiple instance learning to predict immune checkpoint blockade efficacy using neoantigen candidates
Lang, F., Sorn, P., Schrörs, B., Weber, D., Krämer, S., Şahin, U., & Löwer, M. (2023) · iScience · doi:10.1016/j.isci.2023.108014 · Cited by 3
“These observations support previous ﬁndings by other studies 27–29 that the SNV or SNV-derived neoantigen candidate load alone is an imperfect predictor of the response to ICB.”
Result
RPTOR mutation: a novel predictor of efficacious immunotherapy in melanoma
Jiang, Y., Hu, X., Wang, Z., Zhang, Q., Chen, D., & Zhao, P. (2023) · Investigational New Drugs · doi:10.1007/s10637-023-01413-z · Cited by 4
“Moreover, the lack of a standardized TMB cut-off value limits its clinical application [34].”
Prognostic Significance of Tumor Mutation Burden among Patients with Non-small Cell Lung Cancer Who Received Platinum-based Adjuvant Chemotherapy: An Exploratory Study
Shen, W.-X., Li, G.-H., Li, Y.-J., Zhang, P.-F., Yu, J., Shang, D., & Wang, Q. (2023) · Journal of Cancer Prevention · doi:10.15430/jcp.2023.28.4.175 · Cited by 3
“The standard method for TMB testing is scanty, and it is unclear whether the detection of mutations is whole exome sequencing (WES) [18].”
Method
Lamin B1: a novel biomarker in adult and pediatric adrenocortical carcinoma
Chen, Y., Chen, J.-H., Shi, Y., Ling, X., Fang, S., Zhong, C., Liu, F., Zhong, W., Bi, X., Dong, Z., et al. (2024) · Endocrine Related Cancer · doi:10.1530/erc-23-0178 · Cited by 3
Pharmacogenomics and Precision Therapy in Prostate Cancer: Challenges and Perspectives
STEFANOVIĆ, N. Z. (2024) · Springer eBooks · doi:10.1007/978-3-031-51712-9_17 · Cited by 3
RNF43 in cancer: Molecular understanding and clinical significance in immunotherapy
Huo, X., Han, W., Yang, Z., Lu, Y., Liu, N., & Hou, H. (2024) · The Journal of Gene Medicine · doi:10.1002/jgm.3729 · Cited by 3
“50 Specific gene mutations in SMAD2, MTOR, KEAP1, NFE2L2, RB1, TERT and RASA1 may attenuate the anti-tumor immune response of TMB-H, while 16 other genes (CDC73, CTNNA1, ERBB4, EZH2, JAK2, MAP 2 K1, MAP 2 K4, PIK3R1, POLE, PPP2R1A, PPP2R2A, PTPN11, RAF1, RUNX1, STAG2 and XPO1) may be associated…”
Exploring Unique Extracellular Vesicles Associated Signatures: Prognostic Insights, Immune Microenvironment Dynamics, and Therapeutic Responses in Pancreatic Adenocarcinoma
Nan, K., Zhang, M., Geng, Z., Zhang, Y., Liu, L., Yang, Z., & Xu, P. (2024) · Mediators of Inflammation · doi:10.1155/2024/2825971 · Cited by 3
“Tumor mutational burden (TMB) constitutes a pivotal factor in tumor onset and progression, thus offering predictive value regarding the ef ﬁ cacy of immune checkpoint inhibitors (ICIs) [16].”
Background
Bridging the Gap: Immune Checkpoint Inhibitor as an Option in the Management of Advanced and Recurrent Cervical Cancer in Sub-Saharan Africa
Okpalanwaka, I. F., Anazodo, F. I., Chike-Aliozor, Z. L., Ekweozor, C. A., Ochie, K. M., Oboh, O. F., Okonkwo, F. C., & Njoku, M. F. (2024) · Cureus · doi:10.7759/cureus.69136 · Cited by 3
“High mutational burden correlates positively with high microsatellite instability (MSI-H) [92].”
Pyroptosis-associated genes and tumor immune response in endometrial cancer
Gong, X., Wang, Z., You, J., Gao, J., Chen, K., Chu, J., Sui, X., Dang, J., & Liu, X. (2024) · Discover Oncology · doi:10.1007/s12672-024-01315-3 · Cited by 3
“Furthermore, apart from PD-L1, tumor mutation burden (TMB) serves as a valuable biomarker for predicting the efficacy of ICIS treatment, as confirmed by previous investigations in the field of immunotherapy for melanoma and lung cancer [44].”
Background
Unveiling the Enigmatic Role of SLC35F3 in Lung Adenocarcinoma
Ye, Y., Long, F., Yue, W., Wei, Z., Yang, J., & Xie, Y. (2024) · The Clinical Respiratory Journal · doi:10.1111/crj.70023 · Cited by 3
Somatic mutational landscape reveals mutational signatures and significantly mutated genes of cancer immunotherapeutic outcome and sex disparities
Li, Y., Wang, Q., Gao, X., Zheng, J., Zhang, W., Ren, Y., Shen, W., Su, W. C., & Lü, P. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1423796 · Cited by 3
Clinical Bioinformatician Body of Knowledge—Molecular Diagnostics Core
Leon, A., Castro‐Echeverry, E., Fussell, A. M., Jordan, D., Kip, N. S., Roy, A., Suarez, C. J., Temple‐Smolkin, R., & Coleman, J. F. (2025) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2025.03.006 · Cited by 3
Cavity macrophages stop anti-tumor T cells
Rodrı́guez, P. C., & Ruffell, B. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.06.007 · Cited by 3
Identification of Novel Immunologic Checkpoint Gene Prognostic Markers for Ovarian Cancer
Huo, X., Zhang, X., Li, S., Wang, S., Sun, H., & Yang, M. (2022) · Journal of Oncology · doi:10.1155/2022/8570882 · Cited by 3
Pan-Cancer Analysis of Pentraxin 3: A Potential Biomarker of COVID-19
Zhou, Z., Zhou, X., Yang, Y., Wang, L., & Wu, Z. (2022) · Cancers · doi:10.3390/cancers14184438 · Cited by 3
“Emerging evidence has confirmed that ICI blockade therapy is more effective when there is a high TMB and NEO, since higher TMB and NEO expose more tumor neoantigens [38,39].”
Background
Machine learning-based identification of a novel prognosis-related long noncoding RNA signature for gastric cancer
Zhao, L., Teng, Q., Liu, Y., Chen, H., Chong, W., Du, F., Xiao, K., Sang, Y., Ma, C., Cui, J., et al. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.1017767 · Cited by 3
“Recent studies have demonstrated that the TMB is emerging as a predictive biomarker for the response to immune checkpoint blockade (Chan et al., 2019; Jardim et al., 2021).”
Imprints of tumor mutation burden on chromosomes and relation to cancer risk in humans: A pan-cancer analysisPreprint
Li, X., & Thirumalai, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.20.050989 · Cited by 3
Emerging Targets and Therapeutics in Immuno-Oncology Landscape: Insights from Natural Language Processing AnalysisPreprint
Iyer, K. A., Ivanov, J. M., Tenchov, R., Ralhan, K., Rodríguez, Y., Sasso, J. M., Scott, S. A., & Zhou, Q. A. (2023) · ChemRxiv · doi:10.26434/chemrxiv-2023-bpvfq · Cited by 3
Immune Monitoring during Cancer Immunotherapy
Shehata, H. M., Dogra, P., & Sanjabi, S. (2024) · Wiley eBooks · doi:10.1002/9781683674023.ch105 · Cited by 3
Dual inhibition of the nonsense mediated mRNA decay enhances tumour immunogenicity, drives immunoediting, and potentiates checkpoint blockadePreprint
Zadra, I., Orsolic, D., Kounis, D., Mateos, M. A., Márquez, G. P., Abad, E., Ortet, L., Benito, A., Kharraz, Y., Martínez, C. M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.04.692418 · Cited by 2
Research trends on anti-PD-1/PD-L1 immunotherapy for esophageal cancer: A bibliometric analysis
Yang, Y., & Wang, F. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.983892 · Cited by 2
Identification and Biological Validation of a Chemokine/Chemokine Receptor-Based Risk Model for Predicting Immunotherapeutic Response and Prognosis in Head and Neck Squamous Cell Carcinoma
Wang, Y., Wang, S., Wang, H., Yang, J., & Zhou, H. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24043317 · Cited by 2
“It is reported that diverse factors might contribute to the low response rate of immunotherapy, including a complex mutation landscape [6,7], heterogeneity of the tumor microenvironment (TME) [8], etc.”
Background
Cancer Biomarkers V: Update on B-Cell Lymphoma Biomarkers
Crane, G. M. (2023) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2023-0056-ra · Cited by 2
A pan-cancer analysis of the core pre-mRNA 3′ end processing factors, and their association with prognosis, tumor microenvironment, and potential targets
Li, X., Che, Y., Wang, X., & Zhu, Y. (2024) · Scientific Reports · doi:10.1038/s41598-024-57402-6 · Cited by 2
“Tumor Mutational Burden (TMB) scores in various cancer cells have been shown to enhance immune recognition and are strongly correlated with the efficacy of immunotherapy 25–27 .”
Background
Association of lower tumor mutation burden with rapid local progression in patients with brain metastases
Shukla, P. D., Nguyen, M. P., Lui, A., Catalan, T., Young, J. S., Berger, M. S., Theodosopoulos, P. V., Hervey‐Jumper, S. L., Huppert, L. A., Aghi, M. K., et al. (2025) · Journal of neurosurgery · doi:10.3171/2024.9.jns241391 · Cited by 2
Biologics for novel driver altered non-small cell lung cancer: potential and pitfalls
Russo, G., Scimone, C., Palumbo, L., Roscigno, G., Sarracino, C., Tomaiuolo, I., Pisapia, P., Pepe, F., Rocco, D., Gridelli, C., et al. (2025) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2025.104748 · Cited by 2
Integrated Single-Cell and Bulk RNA Sequencing Analysis Identifies a Regulated Cell Death-Related Gene Signature for Predicting Prognosis and Therapeutic Responses in Cutaneous Melanoma
Tang, J., Zhu, S., & Zhu, L. (2025) · Journal of Immunotherapy · doi:10.1097/cji.0000000000000564 · Cited by 2
Current knowledge about immunotherapy response after liver transplantation of patients with liver cancer
Shivega, W. G., Wang, X. W., & Behrens, S. (2025) · Journal of Liver Transplantation · doi:10.1016/j.liver.2025.100285 · Cited by 4
Integrating mitophagy-associated lncRNAs to predict prognosis and therapeutic response in clear cell renal cell carcinoma
Hu, G., Zhong, S., Lin, H., & He, J. (2025) · International Urology and Nephrology · doi:10.1007/s11255-025-04626-8 · Cited by 2
“Although high TMB may enhance response to ICI) [35, 36], coexisting immunosuppressive states may compromise therapeutic efficacy, highlighting the need for integrated evaluation of TMB and immune context.”
CPLX1 is a novel prognostic biomarker in CRC correlating with immunotherapy resistance and ferroptosis
Liu, C., Liu, Q., Lv, Y., Chang, T., Song, S., Ding, Y., Zhong, J., & Liu, Y. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1589423 · Cited by 2
Explore the role of CBS in stomach adenocarcinoma based on the sulfur-containing amino acid metabolism network
Zhang, P., Liu, Y., Lu, Y., Deng, A., Cao, J., Huang, H., Wu, C., Du, J., Li, Y., & Xia, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-12460-2 · Cited by 2
Predicting response and survival of lung adenocarcinoma under anti-programmed death-1 therapy using biological deep learning
Wang, Y., Zhang, L., Xie, H., Wang, L., Wang, Y., Li, S., He, J., Wang, M., Zhang, X., Wang, H., et al. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf479 · Cited by 2
“TMB,in contrast,measures the number of gene mutations in a tumor patient and has been approved by the FDA as a predictive biomarker for response to PD-1 inhibitors in all solid tumors, highlighting its potential clinical applications [21, 22].”
Intravenous iRGD‐Guided, RBC‐Membrane Camouflaged Lactococcus Lactis Remodels Cold NSCLC and Enhances PD‐1 Blockade
Chen, C., Junmeng, Liu, X., Shao, J., Chen, A., Mei, Y., Zhang, X., Chen, Q., Li, L., & Liu, B. (2025) · Advanced Science · doi:10.1002/advs.202509604 · Cited by 2
TMBclaw: tumor clone-aware graph learning improves immunotherapy response prediction across heterogeneous cohorts
Wang, Y., Zhu, T., Song, X., Chen, P., Zhu, X., Chang, Z., Wang, X., Lai, X., & Wang, J. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf578 · Cited by 2
“This multidimensional heterogeneity compromises clinical decision-making for ICIs [20] and makes naïve pooling of datasets ineffective.”
Identification and external validation of a prognostic signature based on MAPK-related genes to evaluate survival prognosis and treatment efficacy in lung adenocarcinoma
Hu, Z., Zhou, Y., Xie, L., Zhang, W., & Rao, H. (2025) · Clinical and Experimental Medicine · doi:10.1007/s10238-025-01925-3 · Cited by 2
“We employed Strawberry Perl to compute mutation frequencies per million bases in both the HRG and LRG. Mutation landscapes were illustrated through waterfall diagrams created using the "maftools" R package [22].”
Identification and validation of a diagnostic and prognostic model based on immune escape and cancer-associated fibroblast-related genes in lung adenocarcinoma
Ma, Y., Li, X., Wang, X., Song, B., Geng, R., Yuan, H., & Su, W. (2025) · Medicine · doi:10.1097/md.0000000000045756 · Cited by 2
A novel disulfidptosis-related lncRNA signature for development and evaluation of hepatocellular carcinoma prognosis
Bian, G., Zhu, P., & Wang, Q. (2025) · Medicine · doi:10.1097/md.0000000000045638 · Cited by 2
Menin inhibitors as targeted therapy in KMT2A-Rearranged acute leukemia: A comprehensive review of current advances and therapeutic implications
Ahmed, N., Ali, S., Asif, M. L., Aslam, F., Murtaza, M., Ahsan, M. F., Kamil, K. A., & Khaliq, A. (2025) · Medical Oncology · doi:10.1007/s12032-025-03124-2 · Cited by 2
Prognostic Value of Homologous Recombination Deficiency Identified by Comprehensive Genomic Profiling in Incurable Pancreatic Cancer
Kranjc, M., Cankar, U., & Novak, T. (2024) · Asian journal of Current Research in Clinical Cancer · doi:10.51847/mfl0ydhabz · Cited by 2
Paediatric Solid Tumour Vaccines: Current Processes, Prevailing Challenges and Future Perspectives
Liu, S., Yang, M., Xi, B., Wang, Y., Zhang, A., Liu, A., & Jin, H. (2026) · Immunology · doi:10.1111/imm.70105 · Cited by 2
“Tumours with higher malignancy typically exhibit an increased tumour mutation burden, leading to the generation of neoanti-gens with altered amino acid sequences and enhanced MHC-binding affinity [104].”
Development and validation of an interpretable machine learning model identify the lactylation-related protein SUSD3 as a prognostic and therapeutic biomarker for breast cancer
Tang, L. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1701978 · Cited by 2
“Moreover, TMB serves as a predictive marker for immunogenicity, with elevated TMB levels leading to the production of more neoantigens, which correlates with a more favorable response to immunotherapy (40, 41).”
PTGDS is a potential marker for lung adenocarcinoma identified in a pancancer analysis
Wang, R., Shao, F., liu, D., Chen, J., & Zhou, Q. (2026) · Scientific Reports · doi:10.1038/s41598-026-38688-0 · Cited by 2
“…immune infiltration status and tumor mutation burden, serving as pivotal immunotherapy biomarkers and prognostic indicators for patients 19,20 , underscoring the importance of investigating PTGDS within the tumor immune microenvironment, an area that remains largely unexplored to date 21,22 .”
T‐Cell Immunity and Lung Cancer
Yamada, K., & Togashi, Y. (2026) · Respirology · doi:10.1002/resp.70220 · Cited by 2
“This section sum-marises T cell–related biomarkers that more accurately capture determinants of ICI responsiveness in lung cancer [90, 91, 93].”
mRNA vaccines transform personalized lung cancer treatment
Wei, K., Wan, Z., Wen, M., Xin, S., Zhou, Y., Wei, J. C., Zhu, J., Tang, C., Xiong, Y., Jiang, T., et al. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1707654 · Cited by 2
Multi-omics analyses related to mitochondria and ageing in triple-negative breast cancer implicate PYCR1 potentiates tumor progression
Huang, J., Hu, J., Shi, C., Chu, C., & Hu, H. (2026) · Cancer Cell International · doi:10.1186/s12935-026-04235-0 · Cited by 2
A macrophage MHC-I axis links intratumoral heterogeneity to terminal CD8+ T cell exhaustion in lung adenocarcinoma
Yin, S., Gao, H., Li, Q., Wang, M., Zhang, P., Guo, Y., Nan, P., Kong, W., Shen, H., Wang, L., et al. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01446-6 · Cited by 2
The case for tumour-agnostic reimbursement of dual immunotherapy
Subbiah, V., & Kurzrock, R. (2026) · European Journal of Cancer · doi:10.1016/j.ejca.2026.116784 · Cited by 2
Self-citation
Simplified perioperative serplulimab and chemotherapy for resectable squamous NSCLC: a phase II trial with biomarker analysis
Fu, F., Wu, H., Deng, C., Chen, H., Huang, Q., Yuan, C., Ding, X., Ye, T., Zhou, Y., Chen, S., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-014437 · Cited by 3
Integrative single-cell and bulk transcriptomics analysis reveals cellular heterogeneity, immune microenvironment dynamics, and prognostic signatures in oral squamous cell carcinoma
Zhang, M., Wang, H., Zhang, D., & Xu, S. (2026) · SLAS TECHNOLOGY · doi:10.1016/j.slast.2026.100432 · Cited by 2
Predictive Biomarkers for Immune Checkpoint Inhibitor Efficacy: Challenges, Innovations, and a Pathway to Precision Medicine in the Era of Cancer Immunotherapy
Lee, M., SoRelle, J. A., Everest‐Dass, A., Gerber, D. E., & von Itzstein, M. S. (2026) · Clinical Chemistry · doi:10.1093/clinchem/hvag062 · Cited by 3
Identification of Immune-Related Subtypes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma
Qin, H., Wang, T., & Zhang, H. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.906113 · Cited by 2
“The Relationship Between the TMB, Immune Cell Infiltration Score, and Prognosis TMB has a relationship with TME and may be a predictor of immunotherapy response (Chan et al., 2019; Jardim et al., 2021; Strickler et al., 2021).”
Background
SARS-CoV-2-correlated ASGR1 is a novel potential marker for the treatment and identification of multiple human cancers.
Huang, T. (2022) · PubMed Central · Cited by 2
An enhanced genetic mutation-based model for predicting the efficacy of immune checkpoint inhibitors in patients with melanoma
Pan, C., Tang, H., Wang, W., Wu, D., Luo, H., Xu, L., & Lin, X.-J. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2022.1077477 · Cited by 2
[Advances of Immunotherapy Resistance and Coping Strategies in Non-small Cell Lung Cancer].
Jing, Y., Zeng, H., Cheng, R., Tian, P., & Li, Y. (2023) · PubMed Central · doi:10.3779/j.issn.1009-3419.2023.102.03 · Cited by 2
Development of a novel copper metabolism-related risk model to predict prognosis and tumor microenvironment of patients with stomach adenocarcinoma
Sun, D., Zhang, H., & Zhang, C. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1185418 · Cited by 2
“There has been evidence of a link between response to immunotherapy and genetic alterations (Jardim et al., 2021).”
Background
Construction and validation of a cuproptosis-related lncRNA prognosis signature in bladder carcinoma
Song, J., Sun, X., Wang, T., Li, Y., Su, P., & Yuan, L. (2023) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-023-05013-5 · Cited by 2
“Immune‐Related function and tumor mutation burden analysis Recently, more and more studies have discovered that TMB was closely related to OS after immunotherapy for multiple tumor types (Klempner et al. 2020; Jardim et al. 2021).”
Background
Prognostic characteristics of T-cell mediated cell killing-related genes in lung adenocarcinoma
Bi, L., Ai, C., Zhang, H., Chen, Z., Deng, Y., Xiong, J., & Lv, Z. (2023) · Autoimmunity · doi:10.1080/08916934.2023.2250097 · Cited by 2
Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes
Xu, H., Hu, Y., Peng, X., & Chen, E. (2023) · Immunopharmacology and Immunotoxicology · doi:10.1080/08923973.2023.2261146 · Cited by 2
“However, there is evidence indicating that ICB therapy can effectively control the disease progression in some individuals with low TMB [47].”
Background
Identification of immunogenic cell death‑related prognostic signatures in pancreatic cancer
Yu, W., Li, M., & Xia, J. (2023) · Oncology Letters · doi:10.3892/ol.2023.14061 · Cited by 2
“Furthermore, the utilization of ICIs was observed to bolster the activity of effector T cells, subsequently augmenting the anti‑tumor efficacy (20).”
Molecular pathology as basis for timely cancer diagnosis and therapy
Mackinnon, A. C., Chandrashekar, D. S., & Suster, D. I. (2023) · Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin · doi:10.1007/s00428-023-03707-2 · Cited by 2
“Debate surrounds the best method to measure and interpret TMB, as well as the optimal cutoff values for different cancer types and treatment settings [44, 45].”
Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma
Xiang, X., Gao, L., Zhang, Y., Zhu, Q., Zhao, S., Liu, W., Ye, Y., Tang, Y., & Zhang, W. (2023) · PeerJ · doi:10.7717/peerj.16618 · Cited by 2
An endoplasmic reticulum stress-related signature featuring ASNS for predicting prognosis and immune landscape in prostate cancer
Wu, Z., Zhenquan, W., Zeng, J., Liu, Y., Wang, Y., Li, H., Xia, T., Liu, W., Lin, Z., & Xu, W. (2024) · Aging · doi:10.18632/aging.205280 · Cited by 2
“Since TMB reflects a mutagenesis process induced by environmental and intracellular factors, it has become a useful biomarker in certain cancer types to identify patients who will benefit from immunotherapy [38, 39].”
Background
Neoadjuvant Chemoradiotherapy Upregulates the Immunogenicity of Cold to Hot Tumors in Esophageal Cancer Patients
Nagaki, Y., Motoyama, S., Sato, Y., Wakita, A., Fujita, H., Kemuriyama, K., Sasamori, R., Nozaki, S., Nomura, K., & Minamiya, Y. (2024) · Annals of Surgery Open · doi:10.1097/as9.0000000000000385 · Cited by 2
Identification and Validation of Tumor Microenvironment-Associated Signature in Clear-Cell Renal Cell Carcinoma through Integration of DNA Methylation and Gene Expression
Ye, Z., Xu, J., Zhang, X., Zhang, Y., Ivanova, D., Lu, W., Zhang, J., Li, F., Chen, X., Wang, Y., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25126792 · Cited by 2
Construction and validation of a prognostic model for bladder cancer based on disulfidptosis-related lncRNAs
Yang, X., Zhang, Y., Liu, J., & Feng, Y. (2024) · Medicine · doi:10.1097/md.0000000000038750 · Cited by 2
“[58] High TMB tumors generally have more mutations, generating a greater array of neoantigens that can elicit an immune response.”
Background
Characterization of SUSD3 as a novel prognostic biomarker and therapeutic target for breast cancer
Dong, Y.-M., & Bao, G.-Q. (2024) · Clinical & Translational Oncology · doi:10.1007/s12094-024-03641-y · Cited by 2
Multi-omics pan-cancer analysis reveals the prognostic values and immunological functions of PPA2, with a spotlight on breast cancer
Zhang, J., Yang, B., Li, L., Xu, H., Wang, B., Yi, Z.-L., Zhou, X., & Liu, H. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1435502 · Cited by 2
“Inorganic pyrophosphatase 2(PPA2) is a pyrophosphatase that hydrolyzes inorganic pyrophosphate (PPi) from many nucleotide-dependent reactions into two orthophosphate molecules (9).”
Background
Enhanced precision in immunotherapy
Bergstrom, E. N., & Alexandrov, L. B. (2024) · Nature Cancer · doi:10.1038/s43018-024-00802-4 · Cited by 3
MEF2C is a Potential Prognostic Biomarker and is Correlated with Immune Infiltrates in Lung Adenocarcinoma
Liang, K., Xie, R., Xie, Z., Wan, W., Fu, X., Lai, X., Li, D., & Miao, H. (2024) · Current Medicinal Chemistry · doi:10.2174/0109298673317910241003101925 · Cited by 2
Bioinformatics analysis and experimental validation of the oncogenic role of COL11A1 in pan-cancer
Wan, X., Deng, Q., Chen, A., Zhang, X., & Yang, W. (2024) · 3 Biotech · doi:10.1007/s13205-024-04133-0 · Cited by 2
“It is a potential biomarker as a measure of the number of mutations in cancer cells (Jardim et al. 2021), and can predict the response of a cancer to immunotherapy (Yarchoan et al. 2017).”
Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer
Fang, Y., Fu, T., Zhang, Q., Xiong, Z., Yu, K., & Le, A. (2024) · Biology Direct · doi:10.1186/s13062-024-00564-0 · Cited by 2
Unveiling Varied Cell Death Patterns in Lung Adenocarcinoma Prognosis and Immunotherapy Based on Single‐Cell Analysis and Machine Learning
Song, Z., Zhang, W., Zhu, M., Wang, Y., Zhou, D., Cao, X., Geng, X., Zhou, S., Li, Z., Wei, K., et al. (2024) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.70218 · Cited by 2
“…TMB is of critical importance in the analysis of tumour bioinformatics, aiding in the establishment of molecular subtypes, prediction of immune therapy response and patient prognosis, as well as identification of tumour driver genes for precision medicine and targeted treatment guidance [46, 47].”
Mutational landscape of cancer and how latest technologies can help in simplifying the understanding
Deshmukh, S. S., Manoharan, A., Sabih, A. N., Dullea, A. D., & Mohammadi, S. M. K. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-15504-8.00005-3 · Cited by 2
An integrated machine learning framework for developing and validating a prognostic risk model of gastric cancer based on endoplasmic reticulum stress-associated genes
Wei, G., Wang, Y., Liu, R., & Liu, L. (2024) · Biochemistry and Biophysics Reports · doi:10.1016/j.bbrep.2024.101891 · Cited by 2
MMP9 in pan-cancer and computational study to screen for MMP9 inhibitors
Ai, X. (2024) · American Journal of Translational Research · doi:10.62347/nxmr6806 · Cited by 2

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
ORCID: Jardim, Denis L.
Goodman, Aaron
Kurzrock, Razelle
Venue: Cancer Cell
Publisher: Elsevier BV
Published: 2021-02
Volume: 39
Issue: 2
Pages: 154-173
ISSN: 1535-6108 (ISSN-L)
DOI: 10.1016/j.ccell.2020.10.001
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks