Optimal Cutoff Value of the Tumor Mutation Burden for Immune Checkpoint Inhibitors: A Lesson from 175 Pembrolizumab-Treated Cases Among 6403 Breast Cancer Patients
by
,
Hinano Nishikubo
1,†,
Kyoka Kawabata
1,†,
Dongheng Ma
1,
Tomoya Sano
1,
Daiki Imanishi
1,
Takashi Sakuma
1,
Koji Maruo
1,
Canfeng Fan
1,
Yurie Yamamoto
1 and
Masakazu Yashiro
1,2,* 1
Molecular Oncology and Therapeutics, Osaka Metropolitan University Graduate School of Medicine, Osaka 545-8585, Japan
2
Cancer Center for Translational Research, Osaka Metropolitan University Graduate School of Medicine, 1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Appl. Sci. 2025, 15(18), 10173; https://doi.org/10.3390/app151810173
Submission received: 23 August 2025
/
Revised: 11 September 2025
/
Accepted: 16 September 2025
/
Published: 18 September 2025
(This article belongs to the Special Issue Research on Computational Biology and Bioinformatics)
Abstract
Featured Application
The optimal cutoff value of the TMB for treating breast cancer with pembrolizumab might be ≥18.5 mut/Mb.
Abstract
The immune checkpoint inhibitor pembrolizumab is effective for the treatment of recurrent cancer with a tumor mutation burden-high (TMB-high) status. Globally, the cutoff value of TMB-high has been set as ≥10 mut/Mb, but the optimal cutoff value of TMB for treating breast cancer (BC) with pembrolizumab has not been identified. We re-evaluated the optimal cutoff value of TMB-high status in BC by using the clinical dataset from Japan’s Center for Cancer Genomics and Advanced Therapeutics (C-CAT) profiling database. We extracted 6403 BC cases that had been enrolled from the C-CAT database of 101,231 cases of various types of cancers. Of all 6403 BC cases, 683 (10.7%) showed TMB ≥ 10 mut/Mb as TMB-high. Of the 683 TMB-high cases, 175 were administered pembrolizumab. The receiver operating characteristic curve indicated that for treating BC with pembrolizumab, a TMB ≥ 18.5 mut/Mb was an adequate cutoff regarding sensitivity and specificity. The BC patients’ overall response rate was 21.4%. The disease control rate was 42.9%. The probability of time-to-treatment failure was significantly better in the BC cases with TMB ≥ 18.5 mut/Mb versus those with TMB < 18.5 mut/Mb (p = 0.007). These findings suggested that the optimal cutoff value of the TMB for treating breast cancer with pembrolizumab might be ≥18.5 mut/Mb.
1. Introduction
Breast cancers are classified into four types based on the expression of hormone receptors (HRs), including estrogen receptor (ER) and progesterone receptor (PR) and human epidermal growth factor receptor type 2 (HER2) [1]. HR-positive breast cancer is treated mainly with hormonal therapy, and HER2-positive breast cancer is treated with the monoclonal antibody herceptin (trastuzumab). The triple-negative breast cancer (TNBC) type with neither HR nor HER2 expression is treated mainly with chemotherapy [2,3]. Immune checkpoint inhibitors (ICIs) were developed relatively recently, and the ICI pembrolizumab has been approved for the treatment of inoperable or recurrent TNBC with programmed cell death ligand 1 (PD-L1) expression [4]. ICIs have also been approved for the treatment of solid tumors with a tumor mutational burden (TMB)-high status, which has been set by the U.S. Food and Drug Administration (FDA) as ≥10 mutations/mega base (mut/Mb). TMB-high cancer cells might produce tumor-specific antigens as neoantigens on the cell membrane and might also be a potentially useful biomarker for predicting the therapeutic effects of ICIs.
The reported response rate to ICIs for breast cancers is only 7.1%, indicating that the effects of ICIs against breast cancers are limited [5,6]. A potential reason for the lesser effectiveness of ICIs for breast cancer might be the inadequate cut-off value of TMB-high status as ≥10 mut/Mb as the indication for ICI treatment. In fact, our search of the relevant literature revealed no investigation of the optimal TMB value for the use of ICIs to treat breast cancer, and we also found no report indicating whether a TMB at 10 mut/Mb is the most accurate cutoff value for ICI treatment in breast cancer [7,8,9]. It is thus necessary to re-evaluate the TMB-high criteria for ICI indication in breast cancers. We conducted the present study to re-evaluate the cutoff value of TMB-high status in breast cancers by analyzing the effectiveness of pembrolizumab treatment for breast cancer. For this purpose, we used the data from Japan’s Center for Cancer Genomics and Advanced Therapeutics (C-CAT), which has accumulated genomic and clinical information data from over 100,000 patients who underwent multi-comprehensive genomic profiling (multi-CGP) tests in Japan since June 2019 [10,11]. C-CAT has published their information in order to promote innovative research. As of June 2025, approx. 6403 breast cancer cases had accumulated in the C-CAT database.
2. Materials and Methods
2.1. Patients and C-CAT Database
We extracted a total of 7940 breast cancer cases from the C-CAT database, which contained 101,231 cases of various types of cancer deposited in the database during the 6 year period from June 2019 through to June 2025. Due to a lack of TMB data, we excluded 1537 breast cancer cases and analyzed the remaining 6403 cases, which had been classified into four subtypes based on their HR (i.e., ER and PR) and HER2 expression status. The 6403 breast cancer cases included HR+/HER2− cases (n = 3580), HR+/HER2+ cases (n = 339), HR−/HER2+ cases (n = 211), TNBC cases (n = 1597), and unclassifiable breast cancer cases (n = 676). The C-CAT database contains genomic information such as the patient’s TMB score, gene mutations, allele frequencies, rearrangements, microsatellite instability (MSI) status, and clinicopathologic information, including the patient’s chemotherapeutic history with the response rate.
2.2. Multi-CGP Tests
Each of the patients had been examined by one of the following three multi-CGP tests: the FoundationOne® CDx test (F1CDx; Foundation Medicine Inc., Cambridge, MA, USA), the OncoGuide™ NCC Oncopanel System (NCC; Sysmex Co., Kobe, Japan), and the GenMineTOP® Cancer Genome Profiling System (GM-TOP; Konica Minolta Realm Co., Tokyo, Japan). The F1CDx analysis was performed using genomic DNA extracted from tumor tissues; the NCC analysis was performed using DNA from tumor tissues and circulating tumor DNA in blood; and the GM-TOP was performed using DNA and RNA extracted from tumor tissues and with DNA extracted from whole blood samples.
2.3. TMB Score and MSI Status
The TMB score was available for each of the three multi-CGP tests. The TMB score obtained by the F1CDx test is calculated as the total number of all synonymous and nonsynonymous mutations per million bases present at an allele frequency ≥5%. The TMB score for the NCC is calculated as being the total number of mutations detected by the total number of the target gene area per million bases. The TMB score provided by the GM-TOP is defined as the total number of nonsynonymous mutations per million bases that present at a variant allele frequency ≥5% or a reading depth ≥100. MSI status was detectable by F1CDx or NCC. F1CDx calculates MSI status from an approx. 2000-microsatellite area of the genome. The NCC maps DNA sequence data from tumor tissue and non-tumor tissue, tallying the number of homopolymer or microsatellite lesions in the DNA, and then calculates the MSI score. In the present series of 6403 breast cancer patients, 5623 (87.8%) were analyzed by the F1CDx test, 595 (9.3%) were examined by the NCC, and 185 (2.9%) were administered the GM-TOP.
2.4. Gene Alterations
The C-CAT also aggregates data on gene mutations, drugs, and clinical trials from various public databases related to genomic medicine worldwide. Gene alterations that had been categorized as ‘oncogenic’, ‘pathogenic’, ‘likely oncogenic,’ and ‘likely pathogenic’ in the C-CAT annotations were considered genomic abnormalities in this study. We excluded variants of unknown significance (VUS) from the genomic abnormalities.
2.5. The Response to Pembrolizumab and the Optimal Cutoff Value for TMB-High Status
Pembrolizumab had been administered to 175 of the TMB-high cases. We used these cases to investigate the optimal cutoff value for TMB-high status by obtaining the receiver operating characteristic (ROC) curve, in order to determine the relationship between the TMB levels and the treatment responses. Therapeutic efficacy was determined based on the patients’ responses to the pembrolizumab treatment, as follows: complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD), and not evaluable (NE). Overall response rate (ORR) was defined as CR+PR, and the disease control rate (DCR) was defined as CR+PR+SD. We used the cut-off value calculated from the ROC analysis to determine the patients’ overall survival (OS), defined as the time from the start of pembrolizumab treatment to death by any cause. The time to treatment failure (TTF) was defined as the length of time from pembrolizumab treatment to death or treatment discontinuation.
2.6. Statistical Analyses
Group comparisons were conducted using the χ2-test, or Fisher’s exact test with Bonferroni correction. An ROC analysis was performed to evaluate the effects of the pembrolizumab treatment. The patients’ OS and the TTF were calculated using the Kaplan–Meier method and log-rank tests. All of the statistical analyses were conducted using the EZR (Easy R) software package ver. 1.65 (Saitama Medical Center, Jichi Medical University, Saitama, Japan) and SPSS® ver. 28 (IBM Corp., Armonk, NY, USA).
3. Results
3.1. The Frequency of TMB-High Status
Figure 1 is a flow diagram of the breast cancer cases analyzed in this study. Of the 6403 breast cancer cases, 683 (10.7%) were observed to have TMB-high status defined as ≥10 mut/Mb. The TMB-high frequency associated with each multi-CGP test was 10.4% (585 of 5623 cases) for the F1CDx test, 14.1% (84 of 595 cases) for the NCC, and 7.6% (14 of 185 cases) for the GM-TOP. The TMB-high frequency in the NCC Oncopanel group was significantly higher than those in the F1CDx (p = 0.005) and GM-TOP (p = 0.018) groups (Figure 2A). The detection rates of breast cancer subtypes were as follows: HR+/HER2-, 11.1% (397 of 3580 cases); HR+/HER2+, 13.9% (47 of 339 cases); HR-/HER2+, 14.7% (31 of 211 cases); and TNBC, 8.4% (134 of 1597 cases). TNBC was significantly less frequent than the other subtypes (p < 0.01) (Figure 2B).
3.2. Patient Background
Table 1 summarizes the clinicopathological features of the breast cancer cases. TMB-high status was significantly correlated with MSI-high and age ≥65 years (both p < 0.001). In contrast, no significant difference was found between the TMB and the other clinicopathologic features, including gender, tobacco smoking index, alcohol index, and PD-L1 expression.
3.3. Genomic Abnormalities
Table 2 lists the genetic mutations detected in all of the breast cancer cases in order of mutation frequency. Genetic mutation was detected in TP53 (3233 cases), PIK3CA (n = 2367), GATA3 (n = 666), ESR1 (n = 616), and PTEN (n = 515). The breast cancer cases with TMB-high status showed a significantly higher frequency of mutation (p < 0.05) on the following 18 genes compared to the cases with TMB-low status: TP53, PIK3CA, GATA3, ESR1, BRCA2, CDH1, RB1, ARID1A, NF1, MAP3K1, ERBB2, MAP2K4, TERT, SF3B1, TBX3, MSH6, MLH1, and MSH2. Notably, the three mismatch repair (MMR) genes MSH6, MLH1, and MSH2 were significantly higher in TMB-high breast cancer cases compared to the TMB-low breast cancer cases (p < 0.001).
3.4. TMB Status
A total of 175 TMB-high cases were treated with pembrolizumab. The treatment line at the time of pembrolizumab administration was first/second line in 26 cases (14.9%), third/fourth line in 19 cases (10.9%), fifth or later in 121 cases (69.1%), and unknown in 9 cases (5.1%). Of the 175 TMB-high cases, the multi-CGP tests were performed as follows: F1CDx, 154 cases (88.0%); NCC, 18 cases (10.3%); and GM-TOP, 3 cases (1.7%).
Subtypes included 84 HR+/HER2− cases (48.0%), 9 HR+/HER2+ cases (5.1%), 5 HR−/HER2+ cases (2.9%), 58 TNBC cases (33.1%), and 19 unclassifiable cases (10.9%). Of the 175 TMB-high cases, 11 were MSI-high (6.3%) and the other 164 cases (93.7%) were not MSI-high. The therapeutic effect of MSI-high was SD (n = 2 cases), PD (n = 4), and NE (n = 5). No CR or PR case was observed among the MSI-high cases. PD-L1 expression was positive in 21 (12.0%) of the 175 TMB-high cases and negative in 11 cases (6.3%). The PD-L1 expression of the other 143 cases (81.7%) was unknown.
Table 3 shows the correlation between TMB-high (as ≥10 mut/Mb) status and the therapeutic response to pembrolizumab. The efficacy of pembrolizumab for the 175 cases of breast cancer with TMB-high status was limited, as ORR was only 13.7% (n = 24) and DCR) was only 30.9% (n = 54).
3.5. Correlation Between TMB Status and the Therapeutic Efficacy of Pembrolizumab
We used the 175 TMB-high cases treated with pembrolizumab to re-evaluate the optimal cutoff value for TMB-high status, calculated from the TMB values and the best response effects. The best response effect was classified as positive when the patient achieved SD or better, i.e., PR or CR. An ROC analysis was performed to evaluate the therapeutic best effects of pembrolizumab for attaining a CR, PR, or SD. The area under the curve (AUC) from the ROC analysis was 0.591 (95% confidence interval: 0.501–0.682), and the optimal cut-off value for TMB-high status in these pembrolizumab-treated cases of breast cancer was 18.5 mut/Mb, as illustrated in Figure 3A.
We compared the prognosis between the TMB < 18.5 mut/Mb group and the TMB ≥18.5 mut/Mb group. The average OS period was 574 days in the TMB < 18.5 mut/Mb group and 468 days in the ≥18.5 mut/Mb group, which was a nonsignificant difference (p = 0.092), although the prognosis tended to be worse in the ≥18.5 mut/Mb group (Figure 3B). Of 154 cases treated with pembrolizumab, 104 had a TMB < 18.5 mut/Mb; the other 50 cases had a TMB ≥ 18.5 mut/Mb. The average TTF was 352 days in the TMB < 18.5 mut/Mb group and 293 days in the ≥18.5 mut/Mb group. The treatment duration was significantly longer in the TMB < 18.5 mut/Mb group (p = 0.007) (Figure 3C).
Table 3 provides data regarding the effect of pembrolizumab treatment in the TMB-high cases divided into two groups: the patients with a TMB < 18.5 mut/Mb, and the patients with a TMB ≥ 18.5 mut/Mb. The ORR was 13.7% (24 of 175 cases), and the DCR was 30.9% (54 of 175 cases). The ORR was significantly better in the TMB < 18.5 mut/Mb group (21.4%) compared to the TMB ≥ 18.5 mut/Mb group (10.1%) (p = 0.041). The DCR was also significantly better in the TMB < 18.5 mut/Mb group (42.9%) versus the ≥18.5 mut/Mb group (25.2%) (p = 0.018).
4. Discussion
The cutoff value for TMB-high status used as an indication for treatment with an ICI has been widely defined as ≥10 mut/Mb in various solid cancers. Our present investigation’s use of C-CAT data revealed that TMB-high status accounted for 10.7% (n = 683) of the total of 6403 breast cancer cases examined herein; however, the response rate to ICIs in the group of breast cancer patients with a TMB-high, i.e., ≥10 mut/Mb status, was only 7.1% [5,6]. We re-evaluated the appropriate cutoff value for TMB-high status in breast cancers by analyzing the effect of pembrolizumab, utilizing the Japanese C-CAT database and the multi-CGP test results provided in the database. The C-CAT data indicated that the efficacy of pembrolizumab was limited, because the ORR and DCR values were only 13.7% and 30.9%, respectively, in the breast cancer cases with TMB-high (≥10 mut/Mb) status in this study. The ROC curve demonstrated that the optimal cutoff value for TMB-high status in breast cancer is 18.5 mut/Mb. With the use of this cutoff value, the ORR and DCR values were significantly higher in the ≥18.5 mut/Mb group. In addition, the OS tended to be better in the patients with ≥18.5 mut/Mb, and the TTF in the ≥18.5 mut/Mb patients was significantly longer. ORR and DCR for the breast cancer cases with TMB-high status were significantly higher than the cases with TMB-low status. Patients with TMB ≥ 18.5 mut/Mb had a better prognosis and longer TTF than those with TMB < 18.5 mut/Mb, suggesting that ICI treatment is considered to be effective in patients with TMB ≥ 18.5 mut/Mb. While a recent report indicated that patients with a TMB ≥ 14 mut/Mb achieved a good response rate sensitivity and specificity [12], our present analyses indicate that the use of TMB ≥ 14 mut/Mb is not sufficient to distinguish the efficacy of ICIs (Supplement Figure S1). Our findings suggest that ICIs might be more effective in breast cancer patients with a TMB ≥ 18.5 mut/Mb. Other studies have suggested that optimal cutoff values for TMB-high need to be determined for each cancer type.
We observed that among the three multi-CGP tests used, the NCC detected the TMB-high status at the highest frequency. One of the reasons for the difference in the frequency of TMB-high status might be that the TMB score is determined by differing calculation methods in the three multi-CGP tests [13]. The NCC calculates the TMB score based on the number of genetic mutations detected per million bases in the length of the target region, whereas the F1CDx test provides a TMB score based on the total number of all synonymous and nonsynonymous mutations that exist at an allele frequency of ≥5%. The GM-TOP calculates the TMB score based on the number of nonsynonymous mutations that exist at a mutant allele frequency of ≥5% and a read depth ≥100. The F1CDx test and the GM-TOP do not count allele frequencies<5% or a read depth ≥100, but the NCC does not limit its criteria. It is thus understandable that the NCC recognized more TMB-high cases in the present study. The frequency of the TMB-high status among the present TNBC cases was significantly lower than those in the other breast cancer subtypes. These might be cause for TNBC to detect low frequency of gene abnormalities such as ERBB2 and ESR1 and do not contain specific genes for TNBC in the three CGP tests.
Our analyses revealed that the TMB-high status was significantly correlated with age ≥65 years. It has been suggested that because a TMB is the total number of tumor mutations in the tumor genome and since the TMB-high status is caused by a high accumulation of tumor mutations, aging might cause genetic mutations on cells, including tumor cells, resulting in the TMB-high status [14,15].
Many gene alterations were detected at significantly higher frequencies in the present study’s breast cancer cases with TMB-high status, which might suggest that frequent pathogenic mutations are present in TMB-high cases of breast cancer. These genes included potential therapeutic targets such as PIK3CA, BRCA2, and ERBB2. Recent clinical trials suggested that the combination of ICIs and poly (ADP-ribose) polymerase (PARP) inhibitors for the treatment of advanced solid tumors may synergistically enhance the antitumor effect through the enhancement of immunogenicity induced by the PARP inhibitors [16,17]. PARP inhibitors work by arresting the ability of the PARP enzyme to repair cellular and genetic damage, inducing the accumulation of DNA damage and cell death for the cancers deficient in DNA double-strand break repair, as a synthetic lethal therapeutic approach [18,19]. Unrepaired DNA damage accumulates, enabling a synthetic lethality approach against cancers with the ability to repair double-strand breaks via homologous recombination. BRCA gene mutations are one of causes of unrepaired DNA promoted immune responses, leading to adaptive upregulation of PD-L1 expression. Combination therapy with ICIs and PARP inhibitors is expected to be effective.
In these trials, the treatment was well tolerated and primarily effective in the patients with BRCA mutations. The combination therapy of ICIs and PARP inhibitors might be promising for breast cancer patients. It may be necessary to evaluate the cutoff value for the TMB-high status among cases treated with a combination of ICIs and PARP inhibitors.
Recent studies have shown that MICA/B regulation correlates with overall survival in patients treated with ICIs [20] ligand expression and ameloblastoma recurrence (a retrospective immunohistological pilot study), suggesting that in other cancer types, it is necessary to evaluate immune biomarkers rather than relying solely on TMB. However, C-CAT lacks data on NKG2D ligand genes (MICA/B, ULBP). We anticipate that NKG2D ligand genes will be incorporated into cancer gene panel testing and registered in C-CAT in the near future.
In melanoma and prostate cancer, androgen receptor (AR) positivity has been suggested to potentially inhibit the efficacy of ICIs [21]; however, the significance of AR positivity in breast cancer remains unclear. While some reports indicated that AR expression confers a protective effect against malignancy, some studies report that AR positivity in HER2-positive patients increases the recurrence rate of distant metastases and mortality [22]. Further investigation is needed regarding the significance of AR positivity in breast cancer and its impact on ICI response
In addition to the TMB-high status, the MSI-high status has been a useful biomarker to predict the efficacy of ICIs. MSI-high status occurs due to defects in DNA mismatch repair (MMR) genes [23]. Our present investigation identified 23 cases with the MSI-high status, 21 of which also had TMB-high status. The MSI-high status was detected significantly more frequently in the TMB-high group. The frequencies of MMR gene mutations such as MSH6, MLH1, and MSH2 were high in our TMB-high group, which might be one of the reasons for the frequent MSI-high status in the TMB-high breast cancer cases.
Study Limitations
This study was limited by missing patient data in the C-CAT database. We did not conduct an analysis of the patients’ prognoses, such as a determination of the progression-free survival (PFS) rate; instead, we used the TTF. Since the TTF is closely associated with PFS, TTF might be accepted as a practical endpoint.
5. Conclusions
Our analyses of the cases of 6403 patients with breast cancer registered in Japan’s C-CAT database revealed that the optimal cutoff value for TMB-high status for the pembrolizumab treatment is 18.5 mut/Mb or higher.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app151810173/s1, Figure S1: Optimal TMB cutoff value by ORR.
Author Contributions
Methodology, T.S. (Tomoya Sano) and D.I.; software, K.K. and C.F.; formal analysis, D.M., T.S. (Takashi Sakuma) and Y.Y.; investigation, K.M.; writing—original draft, H.N.; project administration, M.Y. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
This study was approved by the C-CAT review committee (C-CAT management number: CDU2022-044N) and by the medical ethics committee of Osaka Metropolitan University (approval number 2022-111). The medical ethics committee of Osaka Metropolitan University approved on 15 September 2022.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The datasets presented in this article are not readily available because the data are part of an ongoing study or due to limitations. Requests to access the datasets should be directed to the Center for Cancer Genomics and Advanced Therapeutics (C-CAT).
Acknowledgments
This work was supported by JST SPRING (Grant Number JPMJSP2139).
Conflicts of Interest
The authors declare no conflicts of interest.
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Figure 1.
Flow diagram of breast cases. Patient background and enrollment flow. The numbers of excluded cases, cases used in the analysis, and TMB-high cases are shown. TMB: tumor mutational burden.
Figure 1.
Flow diagram of breast cases. Patient background and enrollment flow. The numbers of excluded cases, cases used in the analysis, and TMB-high cases are shown. TMB: tumor mutational burden.
Figure 2.
TMB-High Frequency. The frequency of TMB-high status. (A) The frequency of TMB-high cases shown by the three multi-CGP tests: 10.4% by the F1CDx test, 14.1% by the NCC, and 7.6% by the GM-TOP. The frequency revealed by the NCC was significantly higher than those shown by the F1CDx (p = 0.005) and GM-TOP (p = 0.018). (B) The frequency of TMB-high cases in each subtype of breast cancer. HR+/HER2−: 11.1%, HR+/HER2+: 13.9%, HR−/HER2+: 14.7%, and TNBC: 8.4%. The frequency was significantly lower in the TNBC group compared to the other subtypes. * p < 0.05, ** p < 0.001. F1CDx: FoundationOne® Liquid CDx, GM-TOP: GenMineTOP, HER2: human epidermal growth factor receptor type 2, HR: hormone receptor, NCC: OncoGuide™ NCC Oncopanel System, TMB: tumor mutational burden, TNBC: triple-negative breast cancer.
Figure 2.
TMB-High Frequency. The frequency of TMB-high status. (A) The frequency of TMB-high cases shown by the three multi-CGP tests: 10.4% by the F1CDx test, 14.1% by the NCC, and 7.6% by the GM-TOP. The frequency revealed by the NCC was significantly higher than those shown by the F1CDx (p = 0.005) and GM-TOP (p = 0.018). (B) The frequency of TMB-high cases in each subtype of breast cancer. HR+/HER2−: 11.1%, HR+/HER2+: 13.9%, HR−/HER2+: 14.7%, and TNBC: 8.4%. The frequency was significantly lower in the TNBC group compared to the other subtypes. * p < 0.05, ** p < 0.001. F1CDx: FoundationOne® Liquid CDx, GM-TOP: GenMineTOP, HER2: human epidermal growth factor receptor type 2, HR: hormone receptor, NCC: OncoGuide™ NCC Oncopanel System, TMB: tumor mutational burden, TNBC: triple-negative breast cancer.
Figure 3.
Optimal TMB cutoff value. The optimal cutoff value for TMB-high status. (A) The ROC curve. The best response effect was defined as positive when the patient achieved stable disease (SD) or better. The optimal cut-off value for TMB-high status in the present cases of breast cancer treated with pembrolizumab was 18.5 mut/Mb. (B) The overall survival (OS) of the 147 patients with pembrolizumab initiation. The average OS was 574 days in the TMB < 18.5 mut/Mb group (n = 99) and 468 days in the ≥18.5 mut/Mb group (n = 48). The OS of the TMB < 18.5 mut/Mb group tended to be worse (p = 0.092) compared to that of the TMB ≥ 18.5 mut/Mb group. Thick line: the TMB ≥ 18.5 mut/Mb patients. Dotted line: the TMB < 18.5 mut/Mb patients. (C) The two groups’ time to treatment failure. The treatment duration was significantly longer in a TMB < 18.5 mut/Mb group (n = 104, dotted line) compared to a ≥18.5 mut/Mb group (n = 50, thick line) (p = 0.007).
Figure 3.
Optimal TMB cutoff value. The optimal cutoff value for TMB-high status. (A) The ROC curve. The best response effect was defined as positive when the patient achieved stable disease (SD) or better. The optimal cut-off value for TMB-high status in the present cases of breast cancer treated with pembrolizumab was 18.5 mut/Mb. (B) The overall survival (OS) of the 147 patients with pembrolizumab initiation. The average OS was 574 days in the TMB < 18.5 mut/Mb group (n = 99) and 468 days in the ≥18.5 mut/Mb group (n = 48). The OS of the TMB < 18.5 mut/Mb group tended to be worse (p = 0.092) compared to that of the TMB ≥ 18.5 mut/Mb group. Thick line: the TMB ≥ 18.5 mut/Mb patients. Dotted line: the TMB < 18.5 mut/Mb patients. (C) The two groups’ time to treatment failure. The treatment duration was significantly longer in a TMB < 18.5 mut/Mb group (n = 104, dotted line) compared to a ≥18.5 mut/Mb group (n = 50, thick line) (p = 0.007).
Table 1.
Clinical characteristics by TMB status of breast cancer.
| TMB-Low (TMB < 10 mut/Mb) (n = 5720) | TMB-High (TMB ≥ 10 mut/Mb) (n = 683) | p-Value | |
|---|---|---|---|
| Age | <0.001 | ||
| <65 (n = 4701) | 4243 (74.2%) | 458 (67.1%) | |
| ≥65 (n = 1702) | 1477 (25.8%) | 225 (32.9%) | |
| Gender | n.s. | ||
| Woman (n = 6364) | 5685 (99.4%) | 679 (99.4%) | |
| Man (n = 39) | 35 (0.6%) | 4 (0.6%) | |
| Smoking a | n.s. | ||
| Smoking (n = 1256) | 1135 (21.2%) | 121 (19.0%) | |
| No Smoking (n = 4745) | 4228 (78.8%) | 517 (81.0%) | |
| Alcohol b | n.s. | ||
| Heavy alcohol (n = 297) | 273 (5.4%) | 24 (4.0%) | |
| No heavy alcohol (n = 5387) | 4813 (94.6%) | 574 (96.0%) | |
| MSI c | <0.001 | ||
| MSI-high (n = 23) | 2 (0.0%) | 21 (3.5%) | |
| Non MSI-high (n = 5450) | 4872 (100.0%) | 578 (96.5%) | |
| PD-L1 protein d | n.s. | ||
| Positive (n = 230) | 205 (47.1%) | 25 (47.2%) | |
| Negative (n = 258) | 230 (52.9%) | 28 (52.8%) |
TMB, tumor mutational burden; MSI, microsatellite instability; PD-L1, Programmed cell death ligand 1, n.s., not significant. a Data available for 6001 patients.; b Data available for 5684 patients.; c Data available for 5473 patients.; d Data available for 488 patients.
Table 2.
Frequency of the top 20 genetic alterations according to TMB status.
| Genes | TMB Status | p-Value | |
|---|---|---|---|
| TMB-Low (TMB < 10 mut/Mb) (n = 5612) | TMB-High (TMB ≥ 10 mut/Mb) (n = 681) | ||
| TP53 (n = 3233) | 2832 (50.5%) | 401 (58.9%) | <0.001 |
| PIK3CA (n = 2367) | 2017 (35.9%) | 350 (51.4%) | <0.001 |
| GATA3 (n = 666) | 620 (11.0%) | 46 (6.8%) | <0.001 |
| ESR1 (n = 616) | 520 (9.3%) | 96 (14.1%) | <0.001 |
| PTEN (n = 515) | 451 (8.0%) | 64 (9.4%) | n.s. |
| AKT1 (n = 513) | 446 (7.9%) | 67 (9.8%) | n.s. |
| BRCA2 (n = 418) | 341 (6.1%) | 77 (11.3%) | <0.001 |
| CDH1 (n = 400) | 307 (5.5%) | 93 (13.7%) | <0.001 |
| RB1 (n = 364) | 284 (5.1%) | 80 (11.7%) | <0.001 |
| ARID1A (n = 338) | 260 (4.6%) | 78 (11.5%) | <0.001 |
| NF1 (n = 308) | 239 (4.3%) | 69 (10.1%) | <0.001 |
| MAP3K1 (n = 285) | 236 (4.2%) | 49 (7.2%) | <0.001 |
| STK11 (n = 249) | 217 (3.9%) | 32 (4.7%) | n.s. |
| ERBB2 (n = 222) | 188 (3.3%) | 34 (5.0%) | 0.02 |
| BRCA1 (n = 176) | 152 (2.7%) | 24 (3.5%) | n.s. |
| MAP2K4 (n = 175) | 145 (2.6%) | 30 (4.4%) | <0.001 |
| TERT (n = 147) | 139 (2.5%) | 8 (1.2%) | 0.03 |
| MUTYH (n = 142) | 128 (2.3%) | 14 (2.1%) | n.s. |
| SF3B1 (n = 139) | 132 (2.4%) | 7 (1.0%) | 0.02 |
| TBX3 (n = 128) | 103 (1.8%) | 25 (3.7%) | 0.001 |
| MSH6 (n = 112) | 88 (1.6%) | 24 (3.5%) | <0.001 |
| MLH1 (n = 27) | 19 (0.3%) | 8 (1.2%) | <0.001 |
| PMS2 (n = 22) | 17 (0.3%) | 5 (0.7%) | n.s. |
| MSH2 (n = 14) | 6 (0.1%) | 8 (1.2%) | <0.001 |
TMB, tumor mutational burden, n.s., not significant.
Table 3.
Therapeutic response for cases that received pembrolizumab.
| 10.0 mut/Mb < TMB (n = 175) | 10.0 mut/Mb < TMB < 18.5 mut/Mb (n = 119) | TMB ≥ 18.5 mut/Mb (n = 56) | p-Value | |
|---|---|---|---|---|
| CR (n = 1) | 1 (0.6%) | 0 (0%) | 1 (1.8%) | |
| PR (n = 23) | 11 (6.3%) | 12 (10.1%) | 11 (19.6%) | |
| SD (n = 30) | 12 (6.9%) | 18 (15.1%) | 12 (21.4%) | |
| PD (n = 62) | 15 (8.6%) | 47 (39.5%) | 15 (26.8%) | |
| NE (n = 59) | 17 (9.7%) | 42 (35.3%) | 17 (30.4%) | |
| ORR; CR+PR (n = 24) | 24 (13.7%) | 12 (10.1%) | 12 (21.4%) | 0.041 |
| DCR; CR+PR+SD (n = 54) | 54 (30.9%) | 30 (25.2%) | 24 (42.9%) | 0.018 |
TMB, tumor mutational burden; CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; NE, not evaluable; ORR, overall response rate; DCR, disease control rate.
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Nishikubo, H.; Kawabata, K.; Ma, D.; Sano, T.; Imanishi, D.; Sakuma, T.; Maruo, K.; Fan, C.; Yamamoto, Y.; Yashiro, M. Optimal Cutoff Value of the Tumor Mutation Burden for Immune Checkpoint Inhibitors: A Lesson from 175 Pembrolizumab-Treated Cases Among 6403 Breast Cancer Patients. Appl. Sci. 2025, 15, 10173. https://doi.org/10.3390/app151810173
AMA Style
Nishikubo H, Kawabata K, Ma D, Sano T, Imanishi D, Sakuma T, Maruo K, Fan C, Yamamoto Y, Yashiro M. Optimal Cutoff Value of the Tumor Mutation Burden for Immune Checkpoint Inhibitors: A Lesson from 175 Pembrolizumab-Treated Cases Among 6403 Breast Cancer Patients. Applied Sciences. 2025; 15(18):10173. https://doi.org/10.3390/app151810173
Chicago/Turabian StyleNishikubo, Hinano, Kyoka Kawabata, Dongheng Ma, Tomoya Sano, Daiki Imanishi, Takashi Sakuma, Koji Maruo, Canfeng Fan, Yurie Yamamoto, and Masakazu Yashiro. 2025. "Optimal Cutoff Value of the Tumor Mutation Burden for Immune Checkpoint Inhibitors: A Lesson from 175 Pembrolizumab-Treated Cases Among 6403 Breast Cancer Patients" Applied Sciences 15, no. 18: 10173. https://doi.org/10.3390/app151810173
APA StyleNishikubo, H., Kawabata, K., Ma, D., Sano, T., Imanishi, D., Sakuma, T., Maruo, K., Fan, C., Yamamoto, Y., & Yashiro, M. (2025). Optimal Cutoff Value of the Tumor Mutation Burden for Immune Checkpoint Inhibitors: A Lesson from 175 Pembrolizumab-Treated Cases Among 6403 Breast Cancer Patients. Applied Sciences, 15(18), 10173. https://doi.org/10.3390/app151810173
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