CD276 as a critical independent biomarker and immune checkpoint inhibitor target in epithelioid mesothelioma-TCGA study
Original Article

CD276 as a critical independent biomarker and immune checkpoint inhibitor target in epithelioid mesothelioma-TCGA study

Yuko Aoki1#, Ken Arimura2# ORCID logo, Kenzo Hiroshima3, Yasuto Sato4, Mitsuko Kondo2, Etsuko Tagaya2

1Tokyo Women’s Medical University, Tokyo, Japan; 2Department of Respiratory Medicine, Tokyo Women’s Medical University, Tokyo, Japan; 3Department of Pathology, Tokyo Women’s Medical University Yachiyo Medical Center, Chiba, Japan; 4Graduate School of Public Health, Shizuoka Graduate University of Public Health, Shizuoka, Japan

Contributions: (I) Conception and design: K Arimura, Y Aoki, K Hiroshima, M Kondo, E Tagaya; (II) Administrative support: K Arimura; (III) Provision of study materials or patients: K Arimura; (IV) Collection and assembly of data: K Arimura, Y Aoki, Y Sato; (V) Data analysis and interpretation: K Arimura, Y Aoki, Y Sato; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work as co-first authors.

Correspondence to: Ken Arimura, MD, PhD. Department of Respiratory Medicine, Tokyo Women’s Medical University, 8-1, Kawadacho, Shinjuku, Tokyo, Japan. Email: arimura.ken@twmu.ac.jp.

Background: CD276 is an immune checkpoint, and immune checkpoint inhibitors (ICIs) targeting CD276 have been tested against various cancers. However, the precise role of CD276 in mesothelioma subtypes is unknown. This study aimed to reveal the prognostic significance of CD276 in various cancers and explore CD276 as a target for ICIs in different mesothelioma subtypes.

Methods: We evaluated data from The Cancer Genome Atlas (TCGA) database retrospectively. The Wilcoxon rank-sum test was used to assess CD276 mRNA expression between cancer tissues and the adjacent normal tissues in the context of various cancers. The study involved 86 patients with mesothelioma. The mean number of patients was set as the cutoff value for comparing CD276 mRNA expression. The overall survival (OS) of patients with each mesothelioma subtype was estimated using the Kaplan-Meier method with CD276 mRNA expression. The factors affecting the correlation between OS and high/low CD276 expression in combination with/without a current existing molecular targets of programmed cell death 1 (PD-1), cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and vascular endothelial growth factor A (VEGFA) were assessed using a multivariate Cox proportional hazards model. The correlation between the mRNA expression of CD276 and expression of gene markers of tumor-infiltrating immune cells and those of different pathways was evaluated using Spearman’s correlation. The factors affecting correlations of CD276 mRNA expression were confirmed using a multivariate linear regression model.

Results: Upregulated CD276 mRNA expression was associated with a poor prognosis in various cancers, including epithelioid mesothelioma. The multivariate Cox proportional hazards model demonstrated that upregulated CD276 mRNA expression indicated the worst prognosis, including the combination of CD276 and PD-1, CTLA4, and VEGFA. In addition, using a multivariate linear regression model, CD276 mRNA expression was found to correlate with multiple glycolytic pathway mRNAs in epithelioid mesothelioma, especially PKM2.

Conclusions: CD276 is an independent prognostic biomarker in patients with epithelioid mesothelioma. It is associated with the glycolytic pathway and may contribute to ATP generation in epithelioid mesothelioma. CD276 inhibitors might contribute to better prognosis in patients with epithelioid mesothelioma.

Keywords: B7-H3/CD276; epithelioid mesothelioma; immune checkpoint inhibitor (ICI); novel prognostic biomarker; The Cancer Genome Atlas (TCGA)


Submitted Sep 26, 2024. Accepted for publication Dec 06, 2024. Published online Jan 22, 2025.

doi: 10.21037/jtd-24-1598


Highlight box

Key findings

• CD276 is an independent prognostic biomarker and immune checkpoint inhibitor (ICI) target in epithelioid mesothelioma. CD276 is associated with the glycolytic pathway and may be involved in ATP generation in epithelioid mesothelioma.

What is known and what is new?

• ICIs targeting CD276 have been tested against various cancers. However, the specific role of CD276 in mesothelioma subtypes has remained unknown.

• Here, we explored the prognostic significance of CD276 and its potential as a target for ICIs in different mesothelioma subtypes.

What is the implication and what should change now?

• CD276 is a target for ICIs in patients with epithelioid mesothelioma; CD276 inhibitors should be studied further for their potential in improving prognosis in patients with epithelioid mesothelioma.


Introduction

Background

Mesothelioma is a rare and refractory cancer (1,2). Its tumorigenesis is related to the exposure (3,4) of mesothelial cells (5) to asbestos following a latency period of 30–40 years (6,7). However, the mechanisms underlying mesothelioma tumorigenesis are not fully understood (3,5). Although some molecular targets and possible prognostic biomarkers for mesothelioma have been identified (8-10), they have been inconclusive. One reason for this inconclusiveness is that, despite the identification of tumor suppressor genes, mesothelioma-related oncogenes are not well understood (11-13). A combination of immune checkpoint inhibitors (ICIs), namely nivolumab and ipilimumab, which are programmed cell death 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA4) inhibitors (14), and chemotherapy with cisplatin and pemetrexed (15) with/without bevacizumab, which is a vascular endothelial growth factor A (VEGFA) inhibitor (16), have been confirmed to be effective in a phase 3 study of mesothelioma. However, the overall survival (OS) of patients administered these treatments was 12–18 months, with many patients eventually developing resistance to treatment (14,15). Mesothelioma consists of epithelioid and nonepithelioid subtypes, including biphasic and sarcomatoid subtypes. The prognosis and treatment-associated OS vary according to the subtype (2,3,5-11,13,14).

Although ICIs such as nivolumab and ipilimumab have been demonstrated to be effective against nonepithelioid mesothelioma, their efficacy against epithelioid mesothelioma is unclear, and prognostic biomarkers are lacking (14). Identifying novel molecular targets and prognostic biomarkers for each subtype is essential for the personalized treatment of patients with mesothelioma. In a recent study, we demonstrated that ICIs targeting lymphocyte-activation gene 3 (LAG3) and PD-1 inhibitors could potentially contribute to better clinical outcomes, and LAG3 expression was identified as an independent prognostic biomarker for mesothelioma (17). With the development of novel ICIs, there has been improvement in cancer treatment outcomes (18). The B7 homolog 3 (B7-H3) protein encoded by CD276 was first reported in 2001; it is a member of the B7 family and a key immune checkpoint that is highly expressed on the membrane of normal and cancer cells (19). The structure of B7-H3 comprises an IgV domain, an IgC-like domain, a transmembrane region, and a diverse cytoplasmic tail (20). Although the receptor of B7-H3 has not been confirmed, B7-H3/CD276 is considered to play a key role in the escape of cancer cells from the immune system through the production of IL-10 and TGF-β1 (20). B7-H3/CD276 inhibits the proliferation, activity, and function of CD4/CD8+ T-cells, natural killer cells, macrophages, and dendritic cells and stimulates the function of regulatory T-cells (20,21). In addition, B7-H3/CD276 has been suggested to be associated with metabolic reprogramming via the glycolytic pathway (22), supporting the notion of the Warburg effect (23). It is also reportedly associated with the ferroptosis pathway that is correlated with cancer cell proliferation (24); angiogenesis via the NF-κB pathway (25); and the proliferation, migration, and invasion of cells via the JAK/STAT3, PIK3CA/AKT/mTOR and RAF/MEK pathways (26-28).

Rationale and knowledge gap

High expression of CD276 is correlated with a poor prognosis in various cancers (29,30), including mesothelioma. However, mesothelioma subtypes and multivariate Cox proportional hazards models were not considered in these analyses (31,32). Furthermore, CD276 inhibitors downregulated cancer cell proliferation in an in vivo study (33), and various clinical studies on CD276 inhibitors are currently ongoing (30).

Objective

While the exact significance of CD276 remains unknown in various cancer, particularly in each mesothelioma subtype, we hypothesize that CD276 could be a potentially novel biomarker and the therapeutic target for each mesothelioma subtype. Therefore, this study aimed to evaluate CD276 mRNA expression as a prognostic biomarker across various cancers and explore its potential as a therapeutic target for each mesothelioma subtype, considering the existing therapeutic strategies for mesothelioma using molecular targets of PD-1 (PDCD1), CTLA4, and VEGFA. Our study could provide a new perspective on the correlation between CD276 and various associated pathways in each mesothelioma subtype. We present this article in accordance with the REMARK reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1598/rc).


Methods

The Cancer Genome Atlas (TCGA) database

We extracted data from TCGA database, which is a cancer genomics project started by the National Cancer Institute in 2006, and evaluated the data retrospectively. CD276 mRNA expression between 17 types of cancer and normal tissues was analyzed using TCGA (https://cistrome.shinyapps.io/timer/), as previously described (17,34). To compare CD276 expression between cancer and the adjacent normal tissues, the mRNA expression was transformed to log2 transcripts per million (17,34). The CD276 mRNA expression and OS data of 36 human cancer types were analyzed using TCGA database (https://xena.ucsc.edu/), as previously described (17,34). To compare high and low CD276 expression in TCGA, the mean number of patients was used as a cutoff value. Number of patients, age, sex, disease stage, and histological evaluation from TCGA were used as clinical variables for assessing factors affecting the correlation between OS and high/low expression of CD276, PDCD1, CTLA4, and VEGFA mRNA, and the combinations of high/low expression of CD276 and PDCD1, CTLA4, VEGFA, and clinical variables (17). The correlation of CD276 mRNA expression with the expression of gene markers of tumor-infiltrating immune cells (TIICs) and the glycolytic, ferroptosis, NF-κB, JAK/STAT3, PIK3CA/AKT/mTOR, and RAF/MEK pathways in TCGA was also evaluated.

Statistical analysis

All statistical analyses were conducted using R 3.6.2 (The R Foundation for Statistical Computing, Vienna, Austria) and GraphPad PRISM 10.3 (GraphPad Software, La Jolla, CA, USA) (17,34). Comparison of mRNA expression between cancer and the adjacent normal tissues was performed using the Wilcoxon rank-sum test (17,34). The correlation of high/low CD276 mRNA expression with OS was evaluated via the Kaplan-Meier method using the log-rank test with the hazard ratio (HR) and 95% confidence interval (CI) (17,34). A multivariate Cox proportional hazards model adjusted for age, sex, and disease stage as basic data was used to evaluate factors affecting the correlation between OS and high/low CD276 mRNA expression (17,34).

The correlation between the mRNA expression of CD276 and expression of gene markers of TIICs and those of glycolytic, ferroptosis, NF-κB, JAK/STAT3, PIK3CA/AKT/mTOR, and RAF/MEK pathways was evaluated using the Spearman’s rank correlation coefficient using r (17). The r values estimated using the 95% CI indicated the following: 0.80–1.0, very strong correlation; 0.60–0.79, strong; 0.40–0.59, moderate; 0.20–0.39, weak; and 0.001–0.19, very weak (17). A multivariate linear regression model was used to confirm the factors affecting the correlation of CD276 mRNA expression using β value, which is the regression coefficient with a 95% CI. Results were considered statistically significant at P value <0.05 (17).

Ethical statement

We used data from an anonymized public open database, which was outside the scope of the Japanese ethical guidelines and was thus exempt from ethical scrutiny. Obtaining patient consent was waived by the Institutional Review Board of Tokyo Women’s Medical University for this retrospective study. This manuscript does not include data from any human or animal studies conducted by the authors. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki (as revised in 2013).


Results

Comparison of CD276 mRNA expression between cancer and adjacent normal tissues in human cancers

To determine CD276 mRNA expression in cancer, we compared CD276 mRNA expression between cancer tissues and adjacent normal tissues in various human cancers. We found that CD276 mRNA expression was higher in all cancers, including bladder cancer, breast cancer, cholangiocarcinoma, colon cancer, esophageal cancer, head and neck cancer, kidney chromophobe, kidney clear cell carcinoma, kidney papillary cell carcinoma, liver cancer, lung adenocarcinoma, lung squamous cell carcinoma, prostate cancer, rectal cancer, thyroid cancer, and uterine endometrial carcinoma, than in normal tissues (P<0.001) (Figure 1).

Figure 1 Comparison of CD276 mRNA expression between cancer tissues and the adjacent normal tissues in various human cancers. Comparison of CD276 mRNA expression between cancer tissues and normal tissues in various human cancers was performed using TIMER (http://cistrome.org/TIMER/) and visualized using the Wilcoxon rank-sum test. CD276 mRNA expression in all cancer tissues, including bladder cancer, breast cancer, cholangiocarcinoma, colon cancer, esophageal cancer, head and neck cancer, kidney chromophobe, kidney clear cell carcinoma, kidney papillary cell carcinoma, liver cancer, lung adenocarcinoma, lung squamous cell carcinoma, prostate cancer, rectal cancer, thyroid cancer, and uterine endometrial carcinoma, was higher than that in normal tissues (***, P<0.001). Red: cancer tissues; blue: normal tissues. TPM, transcripts per million.

Prognostic significance of CD276 mRNA expression in various cancers

As CD276 mRNA expression was higher in cancer tissues than in normal tissues, we compared the OS between patients with various cancers exhibiting high and those exhibiting low CD276 mRNA expression. We found that high CD276 mRNA expression was associated with a poor prognosis in various cancers (Table 1). In particular, upregulated CD276 mRNA expression was associated with a poor prognosis in adrenocortical carcinoma, bladder cancer, colon cancer, glioblastoma multiforme, head and neck cancer, kidney chromophobe, kidney clear cell carcinoma, kidney clear cell carcinoma, lower-grade glioma, liver cancer, lung adenocarcinoma, mesothelioma, ocular melanoma, and pancreatic adenocarcinoma (Table 1). These results indicate that CD276 mRNA is a novel prognostic biomarker for these cancers.

Table 1

CD276 mRNA expression is associated with poor OS in various cancers

Cancer type N HR 95% CI P value
Adrenocortical carcinoma 79 1.784 1.236–2.574 0.002
Bladder cancer 406 1.293 1.042–1.605 0.02
Colon cancer 455 1.406 1.033–1.914 0.03
Glioblastoma multiforme 151 1.603 1.172–2.193 0.003
Head and neck cancer 520 1.191 1.014–1.398 0.03
Kidney chromophobe 65 2.686 1.007–7.165 0.048
Kidney clear cell carcinoma 533 1.451 1.112–1.894 0.006
Kidney papillary cell carcinoma 289 1.937 1.069–3.510 0.03
Lower-grade glioma 514 2.250 1.782–2.840 <0.001
Liver cancer 370 1.271 1.031–1.566 0.03
Lung adenocarcinoma 506 1.370 1.071–1.752 0.01
Mesothelioma 86 1.975 1.469–2.655 <0.001
Ocular melanoma 80 2.052 1.152–3.653 0.02
Pancreatic adenocarcinoma 179 1.352 1.011–1.807 0.042

OS, overall survival; HR, hazard ratio; CI, confidence interval.

Prognostic significance of CD276 mRNA expression in mesothelioma subtypes

Owing to its association with a poor prognosis in various cancers, including mesothelioma, we investigated CD276 mRNA expression as a prognostic biomarker in each mesothelioma subtype: epithelioid and nonepithelioid, which comprises biphasic and sarcomatoid mesothelioma. In particular, we assessed the association between clinical variables and CD276 mRNA expression in 86 patients with mesothelioma. The characteristics of the patients (number of patients, age, sex, stage, histological evaluation, and high/low CD276 mRNA expression) are described in Table 2. The OS analysis using the Kaplan-Meier method demonstrated that upregulated CD276 mRNA expression was associated with a poor prognosis in epithelioid mesothelioma (HR =2.864, 95% CI: 1.550–5.291, P<0.001, Figure 2A), whereas it was not associated with a poor prognosis in biphasic and sarcomatoid mesothelioma (HR =1.549, 95% CI: 0.658–3.646, P=0.27, Figure 2B). As CD276 mRNA expression was associated with a poor prognosis in epithelioid mesothelioma, we performed further analysis of OS using a multivariate Cox proportional hazards model. We found that upregulated CD276 mRNA expression was associated with worse OS after adjusting the model for age, sex, and stage (HR =4.157, 95% CI: 2.014–8.921, Table 3), even when considering the currently available molecular-targeted therapeutic strategies. Therefore, our results suggest that CD276 mRNA expression is an independent prognostic biomarker and therapeutic target in epithelioid mesothelioma.

Table 2

Patients’ characteristics

Characteristic Value (N=86)
Age, years, mean 63.1
Sex, n (%)
   Male 70 (81.4)
   Female 16 (18.6)
Stage, n (%)
   I 10 (11.6)
   II 16 (18.6)
   III 44 (51.2)
   IV 16 (18.6)
Histology, n (%)
   Epithelioid 57 (66.3)
   Biphasic 23 (26.7)
   Sarcomatoid 1 (1.2)
   Unknown 5 (5.8)
Figure 2 CD276 mRNA expression was associated with a poor prognosis in epithelioid mesothelioma. Overall survival analysis using the Kaplan-Meier method for CD276 expression in epithelioid (A) and biphasic and sarcomatoid (B) mesothelioma. The log-rank test demonstrated that upregulated CD276 mRNA expression was associated with a poor prognosis in epithelioid mesothelioma (HR =2.864, 95% CI: 1.550–5.291, P<0.001), whereas it was not associated with a poor prognosis in biphasic and sarcomatoid mesothelioma (HR =1.549, 95% CI: 0.658–3.646, P=0.27). HR, hazard ratio; CI, confidence interval.

Table 3

Multivariate Cox proportion hazards model for OS demonstrating elevated CD276 mRNA expression as an independent prognostic biomarker and therapeutic target in epithelioid mesothelioma

Model HR 95% CI
Model 1 (CD276)
   Target 4.157 2.014–8.921
   Age 1.026 0.988–1.066
   Sex 0.856 0.391–1.757
   Stage 0.83 0.565–1.237
Model 2 (PDCD1)
   Target 0.843 0.456–1.553
   Age 0.999 0.965–1.035
   Sex 1.259 0.583–2.550
   Stage 0.912 0.632–1.326
Model 3 (CTLA4)
   Target 1.167 0.642–2.129
   Age 0.999 0.965–1.035
   Sex 1.259 0.582–2.560
   Stage 0.886 0.617–1.295
Model 4 (VEGFA)
   Target 1.58 0.829–3.035
   Age 0.999 0.967–1.034
   Sex 1.029 0.465–2.154
   Stage 0.875 0.608–1.275
Model 5 (CD276 + PDCD1)
   Target 2.297 1.025–5.021
   Age 1.008 0.972–1.046
   Sex 0.871 0.372–1.909
   Stage 0.886 0.617–1.289
Model 6 (CD276 + CTLA4)
   Target 2.36 1.108–4.872
   Age 1.01 0.975–1.047
   Sex 1.242 0.572–2.530
   Stage 0.796 0.534–1.194
Model 7 (CD276 + VEGFA)
   Target 2.455 1.215–4.833
   Age 1.013 0.978–1.050
   Sex 1.021 0.469–2.085
   Stage 0.912 0.622–1.360

OS, overall survival; HR, hazard ratio; CI, confidence interval.

Correlation between the mRNA expression of CD276 and expression of genes of each pathway in epithelioid mesothelioma

Our study demonstrated that CD276 mRNA expression is an independent prognostic biomarker and therapeutic target in epithelioid mesothelioma. Therefore, we explored the correlation between CD276 and the gene markers of TIICs and each pathway involved in epithelioid mesothelioma (Table 4). CD276 mRNA expression weakly correlated with the expression of 3 of the 37 markers of TIICs in epithelioid mesothelioma (Table 4). These results suggest that CD276 mRNA expression does not correlate with various TIICs in epithelioid mesothelioma. However, we identified a strong positive correlation between CD276 and PKM2 expression (r=0.603, 95% CI: 0.399–0.749, P<0.001). We also identified moderate positive correlations between the expression of CD276 and SLC2A1 (r=0.423, 95% CI: 0.175–0.620, P=0.001), HK1 (r=0.544, 95% CI: 0.323–0.709, P<0.001), GAPDH (r=0.440, 95% CI: 0.195–0.633, P=0.001), SLC3A2 (r=0.420, 95% CI: 0.171–0.618, P=0.001), SLC38A1 (r=0.489, 95% CI: 0.255–0.669, P<0.001), and VEGFC (r=0.473, 95% CI: 0.234–0.657, P<0.001) markers in epithelioid mesothelioma (Table 5, Table S1). These results illustrate that CD276 mRNA expression is associated with the glycolytic pathway. In addition, we confirmed the factors influencing the correlation between the expression of CD276 and that of SLC2A1, HK1, GAPDH, PKM2, PDP1, and LDHB in the glycolytic pathway using a multivariate linear regression model. After adjusting for six gene markers, we observed that the expression of CD276 mostly correlated with that of PKM2 (β=0.443, 95% CI: 0.087–0.799, P=0.01) (Table 6). PKM2 plays an important role in generating two molecules of adenosine triphosphate (ATP) in the glycolytic pathway, which is essential for metabolic reprogramming during cancer progression. Our results show that CD276 mRNA expression may regulate the glycolytic pathway in epithelioid mesothelioma.

Table 4

Correlation between CD276 mRNA expression and that of gene markers of TIICs in epithelioid mesothelioma

Immune cells Gene markers r 95 % CI P value
Immune checkpoint CD274 −0.001 −0.268 to 0.267 0.99
PDCD1 0.194 −0.078 to 0.439 0.14
CTLA4 0.147 −0.126 to 0.399 0.27
ICOS 0.037 −0.233 to 0.302 0.78
Macrophages CD68 0.041 −0.229 to 0.306 0.76
M1-type (classically activated) macrophages NOS2 0.282 0.0150 to 0.511 0.03*
M2-type (alternatively activated) macrophages ARG1 −0.004 −0.271 to 0.264 0.97
MRC1 0.159 −0.113 to 0.410 0.23
Tumor-associated macrophages HLA-G −0.047 −0.311 to 0.223 0.72
CD80 0.142 −0.131 to 0.395 0.29
CD86 0.052 −0.219 to 0.315 0.70
Monocytes CD14 −0.118 −0.374 to 0.155 0.38
Natural killer cells XCL1 −0.163 −0.412 to 0.110 0.22
KIR3DL1 −0.257 −0.491 to 0.012 0.054
CD7 −0.023 −0.288 to 0.247 0.86
Neutrophils MPO 0.014 −0.254 to 0.281 0.91
Dendritic cells CD1C −0.100 −0.358 to 0.173 0.46
B-cells CD19 −0.289 −0.516 to −0.022 0.03*
CD38 −0.159 −0.409 to 0.114 0.23
CD8+ T-cells CD8A 0.079 −0.193 to 0.340 0.55
CD8B 0.149 −0.123 to 0.401 0.26
Follicular helper T-cells CXCR5 −0.026 −0.291 to 0.244 0.85
BCL6 0.117 −0.155 to 0.373 0.38
T helper-1 cells IL12RB2 0.127 −0.145 to 0.382 0.34
T helper-2 cells CCR3 0.053 −0.217 to 0.317 0.69
STAT6 −0.387 −0.593 to −0.133 0.003**
GATA3 0.030 −0.239 to 0.296 0.82
T helper-9 cells TGFBR2 0.007 −0.261 to 0.275 0.95
IRF4 −0.169 −0.418 to 0.103 0.20
SPI1 −0.019 −0.285 to 0.250 0.88
T helper-17 cells IL-21R 0.129 −0.144 to 0.384 0.33
IL-23R −0.163 −0.412 to 0.110 0.22
T helper-22 cells CCR10 0.186 −0.086 to 0.432 0.16
AHR −0.035 −0.300 to 0.235 0.79
Regulatory T-cells FOXP3 0.120 −0.152 to 0.376 0.37
CCR8 0.161 −0.111 to 0.411 0.23

**, P<0.01; *, P<0.05. TIICs, tumor-infiltrating immune cells; CI, confidence interval.

Table 5

Correlation between mRNA expression of CD276 and expression of gene markers of the glycolytic pathway in epithelioid mesothelioma

Pathway Gene marker r 95% CI P value
Glycolytic SLC2A1 0.423 0.175 to 0.620 0.001**
HK1 0.544 0.323 to 0.709 <0.001***
GPI 0.152 −0.121 to 0.403 0.26
PFKP 0.199 −0.072 to 0.444 0.13
PFKL 0.241 −0.028 to 0478 0.070
ALDOA −0.060 −0.323 to 0.211 0.65
GAPDH 0.440 0.195 to 0.633 0.001**
PGK1 0.164 −0.109 to 0.414 0.22
PGAM5 0.263 −0.005 to 0.496 0.048*
BPGM −0.101 −0.359 to 0.171 0.45
ENO1 0.136 −0.137 to 0.389 0.31
ENO2 0.332 0.070 to 0.551 0.01*
ENO3 0.055 −0.216 to 0.318 0.68
PKM2 0.603 0.399 to 0.749 <0.001***
PDP1 0.299 0.034 to 0.525 0.02*
LDHA 0.001 −0.267 to 0.269 0.99
LDHB 0.336 0.075 to 0.554 0.01*
ME2 0.123 −0.150 to 0.378 0.36
PCK1 −0.172 −0.421 to 0.100 0.20

***, P<0.001; **, P<0.01; *, P<0.05. CI, confidence interval.

Table 6

Correlation between mRNA expression of CD276 and expression of gene markers of the glycolytic pathway in epithelioid mesothelioma using a multivariate linear regression model

Gene markers β 95% CI P value
SLC2A1 0.088 −0.039 to 0.216 0.17
HK1 0.182 −0.044 to 0.408 0.11
GAPDH −0.103 −0.446 to 0.240 0.54
PKM2 0.443 0.087 to 0.799 0.01
PDP1 0.087 −0.131 to 0.305 0.42
LDHB 0.144 −0.112 to 0.401 0.26

β, regression coefficient; CI, confidence interval.


Discussion

Key findings

In this study, upregulated CD276 mRNA expression correlated with a poor prognosis, and it was confirmed as an independent prognostic biomarker and therapeutic target in epithelioid mesothelioma. In addition, we demonstrated that CD276 mRNA expression may regulate the expression of genes associated with the glycolytic pathway, particularly PKM2.

Upregulated CD276 mRNA expression was associated with a poor prognosis in patients with epithelioid mesothelioma (Figure 2A,2B). CD276 mRNA expression was associated with a poor OS in epithelioid mesothelioma, as determined using the multivariate Cox proportional hazards model, even when available therapeutic strategies targeting PDCD1, CTLA4, and VEGFA were taken into consideration. Therefore, CD276 is an independent prognostic biomarker and a therapeutic target for epithelioid mesothelioma.

Strengths and limitations

Our study highlighted the significance of CD276 expression in epithelioid mesothelioma, which is a rare and refractory cancer. However, it had some limitations. First, as our study was retrospective and had a limited number of patients, prospective studies with larger populations will be necessary to validate the results. Second, our results were based on a clinical database; therefore, in vivo and in vitro studies will be necessary to clarify the significance and role of CD276 in epithelioid mesothelioma.

Comparison with similar research and explanations of findings

High expression of CD276 is correlated with a poor prognosis in mesothelioma, however, its subtypes and multivariate Cox proportional hazards models were not considered in these analyses (31,32). Further, age, sex, and stage were not associated with the prognosis of epithelioid mesothelioma, as determined using the multivariate Cox proportional hazards model. However, it should be noted that in multivariate analysis, a strong prognostic factor may mask the effects of other potential prognostic variables (35). As CD276 mRNA expression was identified to be a strong factor influencing OS, age, sex, and stage may not be prognostic markers.

CD276 mRNA expression does not correlate with various TIICs in epithelioid mesothelioma including PDCD1 and CTLA4 mRNA, which are the existing therapeutic target for mesothelioma, except for the expression of 3 of the 37 markers of TIICs. Further, the correlation of 3 markers of TIICs were weak correlation in epithelioid mesothelioma. In addition, CD276 mRNA expression does not correlate with VEGFA mRNA, which is another existing therapeutic target for mesothelioma. In fact, CD276 mRNA expression was independent prognostic biomarker using the multivariate Cox proportional hazards model, considering PDCD1, CTLA4, and VEGFA in epithelioid mesothelioma. Based on these results, CD276 mRNA may be the independent immune checkpoint different from immune checkpoint with existing ICIs and therapeutic target in epithelioid mesothelioma.

Notably, CD276 mRNA expression correlated well with gene markers of the glycolytic pathway (Table 5). This result indicates that CD276 regulates the glycolytic pathway in epithelioid mesotheliomas. The strongest correlation was identified between CD276 and PKM2, and a moderate correlation was identified between CD276 and SLC2A1 and HK1 (Table 5). PKM2 generates two ATP molecules via this pathway, which is essential for metabolic reprogramming for cancer progression (36). Thus, CD276 mRNA expression is strongly associated with PKM2 expression and ATP generation in the glycolytic pathway of epithelioid mesotheliomas. In addition, PKM2 and HK1, which encode enzymes that control two of the three irreversible reactions in the glycolytic pathway, play crucial roles (36) after glucose intake into the cytoplasm via GLUT1, encoded by SLC2A1 (37). However, irreversible reactions, including those controlled by PDP1, which weakly correlated with CD276 mRNA expression, lead to the tricarboxylic acid (TCA) cycle for ATP generation for metabolic reprogramming (38). A recent study has demonstrated that cancer cells rely on the TCA cycle and the glycolytic pathway for ATP generation (38). Therefore, our results suggest that CD276 mRNA expression may affect the TCA cycle and glycolytic pathway. Increased levels of PKM1, an enzyme that converts phosphoenolpyruvate to pyruvate, similar to PKM2, lead to upregulation of the glycolytic pathway and induction of the TCA cycle (39). However, the dataset used in this study did not include data on PKM1 mRNA expression, warranting studies on the correlation between CD276 and PKM1 in epithelioid mesotheliomas.

Implications and actions needed

Although evidence suggests that CD276 is associated with ferroptosis (24); angiogenesis (25); and the JAK2/STAT3, PIK3CA/AKT/mTOR, and RAF/MEK pathways (26-28) in various cancer, our results illustrated that CD276 expression was not well associated with these pathways in epithelioid mesothelioma. Based on the results of a previous in vivo study (33) and our study, CD276 is a target for ICIs in epithelioid mesothelioma and contributes to achieving better OS in patients with epithelioid mesothelioma.


Conclusions

Our study indicated that CD276 mRNA expression is associated with poor prognosis in various cancers, especially epithelioid mesothelioma. Moreover, CD276 mRNA expression was identified to be an independent prognostic biomarker in epithelioid mesothelioma. Our results showed that CD276 mRNA expression correlated with gene markers of the glycolytic pathway, especially PKM2. Thus, CD276 could be associated with the glycolytic pathway and contribute to ATP generation in epithelioid mesotheliomas. Based on these findings, CD276 is a target for ICIs in future therapeutic approaches; CD276 inhibitors could improve prognosis in patients with epithelioid mesothelioma. An ICIs against CD276 should be confirmed for obtaining a better prognosis in patients with epithelioid mesothelioma in the near future.


Acknowledgments

We thank Fumio Nakamura (Department of Biochemistry, Tokyo Women’s Medical University, Shinjuku, Tokyo, Japan) for his assistance and the patients who participated in this study.

Funding: This work was supported by JSPS KAKENHI (grant number 22K16203 to K.A.).


Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1598/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1598/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1598/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Ethical approval for the study was not required as we used data from an anonymized public open database and individual consent for this retrospective analysis was waived by the Institutional Review Board of Tokyo Women’s Medical University.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


References

  1. Yates DH, Corrin B, Stidolph PN, et al. Malignant mesothelioma in south east England: clinicopathological experience of 272 cases. Thorax 1997;52:507-12. [Crossref] [PubMed]
  2. Remon J, Lianes P, Martínez S, et al. Malignant mesothelioma: new insights into a rare disease. Cancer Treat Rev 2013;39:584-91. [Crossref] [PubMed]
  3. Janes SM, Alrifai D, Fennell DA. Perspectives on the Treatment of Malignant Pleural Mesothelioma. N Engl J Med 2021;385:1207-18. [Crossref] [PubMed]
  4. Robinson BW, Musk AW, Lake RA. Malignant mesothelioma. Lancet 2005;366:397-408. [Crossref] [PubMed]
  5. Yap TA, Aerts JG, Popat S, et al. Novel insights into mesothelioma biology and implications for therapy. Nat Rev Cancer 2017;17:475-88. [Crossref] [PubMed]
  6. Reid A, de Klerk NH, Magnani C, et al. Mesothelioma risk after 40 years since first exposure to asbestos: a pooled analysis. Thorax 2014;69:843-50. [Crossref] [PubMed]
  7. Liu B, van Gerwen M, Bonassi S, et al. Epidemiology of Environmental Exposure and Malignant Mesothelioma. J Thorac Oncol 2017;12:1031-45. [Crossref] [PubMed]
  8. Szlosarek PW, Steele JP, Nolan L, et al. Arginine Deprivation With Pegylated Arginine Deiminase in Patients With Argininosuccinate Synthetase 1-Deficient Malignant Pleural Mesothelioma: A Randomized Clinical Trial. JAMA Oncol 2017;3:58-66. [Crossref] [PubMed]
  9. Zauderer MG, Szlosarek PW, Le Moulec S, et al. EZH2 inhibitor tazemetostat in patients with relapsed or refractory, BAP1-inactivated malignant pleural mesothelioma: a multicentre, open-label, phase 2 study. Lancet Oncol 2022;23:758-67. [Crossref] [PubMed]
  10. Fennell DA, King A, Mohammed S, et al. Abemaciclib in patients with p16ink4A-deficient mesothelioma (MiST2): a single-arm, open-label, phase 2 trial. Lancet Oncol 2022;23:374-81. [Crossref] [PubMed]
  11. Tranchant R, Quetel L, Tallet A, et al. Co-occurring Mutations of Tumor Suppressor Genes, LATS2 and NF2, in Malignant Pleural Mesothelioma. Clin Cancer Res 2017;23:3191-202. [Crossref] [PubMed]
  12. Walpole S, Pritchard AL, Cebulla CM, et al. Comprehensive Study of the Clinical Phenotype of Germline BAP1 Variant-Carrying Families Worldwide. J Natl Cancer Inst 2018;110:1328-41. [Crossref] [PubMed]
  13. Sekido Y. Molecular pathogenesis of malignant mesothelioma. Carcinogenesis 2013;34:1413-9. [Crossref] [PubMed]
  14. Baas P, Scherpereel A, Nowak AK, et al. First-line nivolumab plus ipilimumab in unresectable malignant pleural mesothelioma (CheckMate 743): a multicentre, randomised, open-label, phase 3 trial. Lancet 2021;397:375-86. [Crossref] [PubMed]
  15. Vogelzang NJ, Rusthoven JJ, Symanowski J, et al. Phase III study of pemetrexed in combination with cisplatin versus cisplatin alone in patients with malignant pleural mesothelioma. J Clin Oncol 2003;21:2636-44. [Crossref] [PubMed]
  16. Zalcman G, Mazieres J, Margery J, et al. Bevacizumab for newly diagnosed pleural mesothelioma in the Mesothelioma Avastin Cisplatin Pemetrexed Study (MAPS): a randomised, controlled, open-label, phase 3 trial. Lancet 2016;387:1405-14. [Crossref] [PubMed]
  17. Arimura K, Hiroshima K, Nagashima Y, et al. LAG3 is an independent prognostic biomarker and potential target for immune checkpoint inhibitors in malignant pleural mesothelioma: a retrospective study. BMC Cancer 2023;23:1206. [Crossref] [PubMed]
  18. Tawbi HA, Schadendorf D, Lipson EJ, et al. Relatlimab and Nivolumab versus Nivolumab in Untreated Advanced Melanoma. N Engl J Med 2022;386:24-34. [Crossref] [PubMed]
  19. Chapoval AI, Ni J, Lau JS, et al. B7-H3: a costimulatory molecule for T cell activation and IFN-gamma production. Nat Immunol 2001;2:269-74. [Crossref] [PubMed]
  20. Hwang JY, Jeong JM, Kwon MG, et al. Olive flounder CD276 (B7-H3) a coinhibitory molecule for T cells: Responses during viral hemorrhagic septicemia virus (VHSV) stimulation. Fish Shellfish Immunol 2018;73:228-33. [Crossref] [PubMed]
  21. Lu H, Shi T, Wang M, et al. B7-H3 inhibits the IFN-γ-dependent cytotoxicity of Vγ9Vδ2 T cells against colon cancer cells. Oncoimmunology 2020;9:1748991. [Crossref] [PubMed]
  22. Lim S, Liu H, Madeira da Silva L, et al. Immunoregulatory Protein B7-H3 Reprograms Glucose Metabolism in Cancer Cells by ROS-Mediated Stabilization of HIF1α. Cancer Res 2016;76:2231-42. [Crossref] [PubMed]
  23. DeBerardinis RJ, Lum JJ, Hatzivassiliou G, et al. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab 2008;7:11-20. [Crossref] [PubMed]
  24. Jin H, Zhu M, Zhang D, et al. B7H3 increases ferroptosis resistance by inhibiting cholesterol metabolism in colorectal cancer. Cancer Sci 2023;114:4225-36. [Crossref] [PubMed]
  25. Wang R, Ma Y, Zhan S, et al. B7-H3 promotes colorectal cancer angiogenesis through activating the NF-κB pathway to induce VEGFA expression. Cell Death Dis 2020;11:55. [Crossref] [PubMed]
  26. Liu H, Tekle C, Chen YW, et al. B7-H3 silencing increases paclitaxel sensitivity by abrogating Jak2/Stat3 phosphorylation. Mol Cancer Ther 2011;10:960-71. [Crossref] [PubMed]
  27. Li Z, Liu J, Que L, et al. The immunoregulatory protein B7-H3 promotes aerobic glycolysis in oral squamous carcinoma via PI3K/Akt/mTOR pathway. J Cancer 2019;10:5770-84. [Crossref] [PubMed]
  28. Liu Z, Zhang W, Phillips JB, et al. Immunoregulatory protein B7-H3 regulates cancer stem cell enrichment and drug resistance through MVP-mediated MEK activation. Oncogene 2019;38:88-102. [Crossref] [PubMed]
  29. Liu S, Liang J, Liu Z, et al. The Role of CD276 in Cancers. Front Oncol 2021;11:654684. [Crossref] [PubMed]
  30. Getu AA, Tigabu A, Zhou M, et al. New frontiers in immune checkpoint B7-H3 (CD276) research and drug development. Mol Cancer 2023;22:43. [Crossref] [PubMed]
  31. Dai L, Guo X, Xing Z, et al. Multi-omics analyses of CD276 in pan-cancer reveals its clinical prognostic value in glioblastoma and other major cancer types. BMC Cancer 2023;23:102. [Crossref] [PubMed]
  32. Ding J, Sun Y, Sulaiman Z, et al. Comprehensive Analysis Reveals Distinct Immunological and Prognostic Characteristics of CD276/B7-H3 in Pan-Cancer. Int J Gen Med 2023;16:367-91. [Crossref] [PubMed]
  33. Lee YH, Martin-Orozco N, Zheng P, et al. Inhibition of the B7-H3 immune checkpoint limits tumor growth by enhancing cytotoxic lymphocyte function. Cell Res 2017;27:1034-45. [Crossref] [PubMed]
  34. Arimura K, Kammer M, Rahman SMJ, et al. Elucidating the role of EPPK1 in lung adenocarcinoma development. BMC Cancer 2024;24:441. [Crossref] [PubMed]
  35. Schmoor C, Schumacher M. Effects of covariate omission and categorization when analysing randomized trials with the Cox model. Stat Med 1997;16:225-37. [Crossref] [PubMed]
  36. Christofk HR, Vander Heiden MG, Harris MH, et al. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature 2008;452:230-3. [Crossref] [PubMed]
  37. Deng D, Xu C, Sun P, et al. Crystal structure of the human glucose transporter GLUT1. Nature 2014;510:121-5. [Crossref] [PubMed]
  38. Anderson NM, Mucka P, Kern JG, et al. The emerging role and targetability of the TCA cycle in cancer metabolism. Protein Cell 2018;9:216-37. [Crossref] [PubMed]
  39. Morita M, Sato T, Nomura M, et al. PKM1 Confers Metabolic Advantages and Promotes Cell-Autonomous Tumor Cell Growth. Cancer Cell 2018;33:355-367.e7. [Crossref] [PubMed]
Cite this article as: Aoki Y, Arimura K, Hiroshima K, Sato Y, Kondo M, Tagaya E. CD276 as a critical independent biomarker and immune checkpoint inhibitor target in epithelioid mesothelioma-TCGA study. J Thorac Dis 2025;17(1):109-120. doi: 10.21037/jtd-24-1598

Download Citation