An immune checkpoint-based score is a prognostic marker in retrospective cohort study of patients with gastric cancer

Introduction

Globally, gastric cancer (GC) continues to pose a great threat to human health. According to the report of GLOBOCAN 2018, the morbidity rate of GC ranks fifth, and the mortality rate ranks fourth (1). In 2016, nearly 400 thousand GC cases and 289 thousand GC deaths occurred in China (2). Moreover, approximately half of the GC are diagnosed at stage III or IV in China (3). Despite the use of multimodality therapy, the prognosis of locally advanced GC is poor, with a 5-year survival of 38.7% (4). Therefore, new therapeutic approaches to treat locally advanced GC is urgently needed.

The development of immune checkpoint inhibitors (ICIs), which target the programmed cell death protein 1/programmed death ligand 1 (PD-1/PD-L1 pathway, has revolutionized the treatment of cancer, providing robust and durable response in GC (5-7). The ATTRACTION-2 study was conducted to investigate the efficacy of anti PD-1 antibody, Nivolumab. This trial showed a significant survival advantage with Nivolumab in patients who have pretreated advanced GC (5). Furthermore, in the CheckMate-649 trial, compared to chemotherapy alone, nivolumab plus chemotherapy improved survival in previously untreated advanced GC (6). Additionally, the KEYNOTE-062 trial demonstrated that Pembrolizumab significantly provided a survival benefit in previously untreated advanced GC with PD-L1 combined positive score of 1 or greater (7). However, only a proportion of GC patients can benefit from ICIs therapy, with a range of response rates of 10–26% (6-8). Thus, more future work on identifying other potential immune targets in GC is urgently needed.

In the tumor microenvironment, the B7-CD28 family members play an essential role in the activation and function of T-cell, such as the well-studied PD-1/PD-L1 pathway. Previous studies indicated that other B7-CD28 members was also associated with immunoregulation and survival in many cancers (9,10), which prompted us to investigate whether B7-CD28 members could serve as potential immune targets and prognostic factors in GC. Although expression of B7-H3, B7-H4, PD-L1, PD-1, VISTA, and TIGIT, which belong to the B7-CD28 family, has been previously investigated in patients with GC (11-20), the interactions among these immune checkpoints and the prognosis in GC remain unknown. We previously investigated the expression of B7-H3, B7-H4, and PD-L1 in colorectal cancer (21). This study aimed to reveal the expression characteristics and to investigate the prognostic role of six immune checkpoints, including B7-H3, B7-H4, PD-L1, PD-1, VISTA, and TIGIT, in 478 stage I–III GC patients. We present this article in accordance with the REMARK reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1176/rc).

Methods

Study population and follow-up

The database included 478 GC patients with unselected GC who underwent surgical resection from 2002 to 2011 at Zhongnan Hospital of Wuhan University. Patients who had been pathologically confirmed gastric adenocarcinoma, undergone radical resection, and received no neoadjuvant treatment, were included in this study. However, patients with distant metastasis before surgery, or with other malignancies in their past or recurrence, or with incomplete survival data were excluded. The requirement for informed consent was waived due to the retrospective nature of this study. The independent ethics committees from Zhongnan Hospital of Wuhan University have approved this study (No. 2022152K). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Major clinicopathological characteristics, including sex, age, tumor location, pathological type, histological grade, and TNM stage were retrospectively collected. Generally, patients with stage II and III who have undergone radical resection, received adjuvant treatment. Totally, 398 (83.3%) patients received adjuvant chemotherapy. In accordance with the Chinese guidelines for GC, patients were followed up regularly after surgery (22). Overall survival (OS) was measured from the date of surgery to the date of death or last follow-up, which was last updated in June 2016.

Tissue microarray (TMA) and immunohistochemistry (IHC)

Representative tumor tissue areas were marked on HE-stained paraffin blocks by a pathologist (G.Y.), and sampled for TMA blocks. By using an automated tissue arrayer, the punched sample containing two 1.0-mm cores per patient was delivered to the recipient block.

For IHC, rabbit monoclonal antibodies from Cell Signaling Technology (Danvers, MA, USA) against B7-H3 (clone D9M2L), B7-H4 (clone D1M8I), PD-L1 (clone E1L3N), PD-1 (clone D4W2J), VISTA (clone D1L2G), and TIGIT (clone E5Y1W) were used in the current study, and a 1:200 dilution was used for all antibodies. IHC (4 µm thick) was performed using an automated immunostainer following standard procedures, which was described previously (21).

Assessment of immune checkpoints expression

Two experienced pathologists (F.Y. and G.Y.), blinded to patient data, separately assessed the slides. Discrepant results were reviewed and a consensus was ultimately reached. When the staining scores differed in two spots for same patient, the higher score was considered.

For GC, B7-H3, B7-H4, and PD-L1 mainly expressed in tumor cells (TCs), and B7-H3, and PD-L1 expression in stromal cell (SCs) in the tumor area was also recoded. However, PD-1, VISTA, and TIGIT mainly expressed in immune cells (ICs). The staining of B7-H3, B7-H4, and PD-L1 expression in TCs and SCs was only scored in terms of intensity, and positive expression was defined as weak, moderate, and strong staining. In addition to PD-1, VISTA, and TIGIT expression in ICs, the corresponding fraction of immunoreactive ICs (0–100%) was calculated. Given that TMA comprises a small portion of the tumor, a few positive cells in the core can be indicative of a positive expression. Thus, PD-1, VISTA, and TIGIT expression in over 5% ICs was defined as positive, which was reported previously (23).

Statistical analysis

The Chi-square analysis or Fisher’s exact test was used to compare categorical data, which were presented as number (percent). Spearman rank correlation coefficients was conducted to determine the correlations between biomarkers. OS rate was summarized and compared between two groups by Kaplan-Meier methods and the log-rank test, respectively. The independent factors, which were significantly associated with OS, were determined by the Cox proportional hazard model. A two-sided P<0.05 was deemed significantly different. All statistical analyses were carried out by SPSS software (Version 25.0) and GraphPad Prism software (Version 6.0).

Results

Immune checkpoints expression in GC

A total of 478 patients were included, and the baseline features is showed in Table 1. This study included 338 (70.7%) men and 140 (29.3%) women, and 66 (13.8%), 105 (22.0%), and 307 (64.2%) patients were diagnosed at stage I, II, and III, respectively. The Japanese classification of GC identified 129 (27.0%), 127 (26.6%), 193 (40.3%), and 29 (6.1%) patients with tumor in the upper, middle, lower, and whole stomach, respectively.

The investigation of six immune checkpoint proteins expression via IHC staining was performed in this cohort. As shown in Figure 1, different expression characteristics of immune checkpoints in GC were recorded. According to the expression scores, 173 (36.2%), 11 (2.3%), and 80 (16.7%) of patients showed positive expression of B7-H3, B7-H4, and PD-L1 in TCs, respectively. Additionally, 302 (63.2%), and 120 (25.1%) of patients showed positive expression of B7-H3, and PD-L1 in SCs, respectively. The proportions of PD-1, VISTA, and TIGIT positive expression in ICs were 282 (59.0%), 179 (37.4%), and 146 (30.5%), respectively.

Figure 1 Representative cases displaying positive expression of six immune checkpoints in gastric cancer via immunohistochemistry, which was magnified by 4 times. (A) B7-H3 expression in TCs; (B) B7-H3 expression in SCs; (C) PD-L1 expression in TCs; (D) PD-L1 expression in SCs; (E) B7-H4 expression in TCs; (F) PD-1 expression in ICs; (G) VISTA expression in ICs; (H) TIGIT expression in ICs. ICs, immune cells; SCs, stromal cells; TCs, tumor cells.

As shown in Table 2, except for B7-H4, other B7 family checkpoints expression were significantly positively correlated with each other (P<0.05). PD-L1 expression in TCs was moderately correlated with PD-L1 expression in SCs (ρ=0.658). TIGIT expression in ICs was also moderately correlated with PD-1 and VISTA expression in ICs (ρ=0.478, and ρ=0.407, respectively). However, correlation between other biomarkers was weak.

Association of immune checkpoints expression with clinicopathological features

The relationship between six immune markers and the baseline features is showed in Table S1. Compared to mucinous and signet-ring cell carcinoma, patients with adenocarcinoma had higher expression level of B7-H3 in TCs (P<0.001), B7-H3 in SCs (P<0.001), PD-L1 in SCs (P=0.009), and PD-1, TIGIT, and VISTA in ICs (P=0.007, P=0.017, and P=0.003, respectively). Patients with high histological grade had lower expression level of B7-H3 in TCs (P=0.002). Patients with low T stage had lower expression level of B7-H3 in SCs (P=0.003), but higher expression level of TIGIT in ICs (P<0.001). Meanwhile, patients with low TNM stage had higher expression level of TIGIT in ICs (P=0.01). In addition, patients with tumor location in upper stomach had higher expression level of B7-H3 in SCs (P=0.02).

Association of immune checkpoints expression with survival outcome

After a median follow-up period of 21.4 (range, 0.8–102.3) months, 191 (40.0%) patients died, and the 5-year OS rate was 43.9%. As shown in Figure 2, expression of PD-L1 in TCs, PD-L1 in SCs, TIGIT in ICs, and VISTA in ICs was significantly correlated with favorable OS (P<0.05). Expression of B7-H3 in TCs (5-year OS 51.0% vs. 40.3%, P=0.09) tended to be correlated with favorable OS.

Figure 2 Kaplan-Meier survival curves according to six immune checkpoints expression in gastric cancer. (A) Overall survival according to B7-H3 expression in TCs; (B) overall survival according to B7-H3 expression in SCs; (C) overall survival according to PD-L1 expression in TCs; (D) overall survival according to PD-L1 expression in SCs; (E) overall survival according to B7-H4 expression in TCs; (F) overall survival according to PD-1 expression in ICs; (G) overall survival according to VISTA expression in ICs; (H) overall survival according to TIGIT expression in ICs. ICs, immune cells; SCs, stromal cells; TCs, tumor cells.

In order to investigate the prognostic role of six immune markers in GC, an immune score (IS) using four prognostic markers (B7-H3, PD-L1, TIGIT, and VISTA) was constructed. Expression of PD-L1 in TCs, PD-L1 in SCs, TIGIT in ICs, VISTA in ICs, or B7-H3 in TCs with good prognosis was counted as 1. The IS was calculated and classified as follows: high IS [2–5], and low IS [0–1]. In this cohort, 195 (40.8%) patients were classified as high IS, and 283 (59.2%) as low IS. As shown in Table S2, patients with adenocarcinoma, low histological grade, and low TNM stage had higher IS.

Compared to low IS group, the high IS group was significantly associated with favorable OS (5-year OS 31.7% vs. 60.4%, P<0.001), as shown in Figure 3. Multivariate analyses were performed to examine whether IS was independently associated with favorable OS, and it showed IS to be served independently as a predictor of OS, as shown in Table 3.

Figure 3 Kaplan-Meier survival curves according to the IS. IS, immune score.

Discussion

In the current study, we first assessed the expression of six immune checkpoints in GC and investigated their association with clinicopathological features and survival outcome. Then, the IS, based on the expression of four immune checkpoints, was developed and we showed the IS as a novel prognostic biomarker, which could predict the survival of GC patients. To our knowledge, it is the first study to comprehensively evaluate the expression of the common immune checkpoints in a large GC cohort, and construct an IS prognostic model, which may be used as a tool for selecting immunotherapy targets for GC patients.

The four immune checkpoints, B7-H3, PD-L1, VISTA and TIGIT, were selected to construct the IS prognostic model to predict OS. B7-H3, a member of B7 family, plays a vital role in T-cell-mediated immunity and the activation of natural killer cell (24,25). Moreover, B7-H3 overexpression was found in many cancers, and was significantly correlated with tumor progression and poor survival outcomes (21,26-28). Importantly, chimeric antigen receptor T-cell targeting B7-H3 has shown a satisfactory treatment effect in cancer therapy (29). As to GC, previous reports have demonstrated that B7-H3 was remarkably expressed in both TCs and SCs, ranging from 33.6% to 88% (11,12,30). Moreover, in vitro experiments suggested B7-H3 to promote GC cell migration and invasion, indicating that B7-H3 may be used as a poor prognostic predictor for GC patients (31,32). In this study, we found that B7-H3 expression was observed in TCs and SCs, and B7-H3 overexpression in SCs was more remarkable. However, our study indicated that expression of B7-H3 in TCs had a tendency of favorable OS, which was consistent with Wu’s report (33). This discrepant could be because of different antibodies, analytical methods, and sample sizes.

PD-L1 is one ligand of PD-1, and targeting PD-1/PD-L1 has shown a satisfactory treatment effect in various cancers, including GC. Moreover, PD-1 inhibitors have shown a favorable survival benefit in GC with PD-L1 overexpression, and PD-L1 expression in GC has been assessed in previous reports. Angell et al. demonstrated that 16.4% of GC patients showed PD-L1 positive expression in TCs, while 90.2% showed PD-L1 positive expression in ICs (16). In a large cohort of GC patients, Chen et al. demonstrated that 62.3% of patients expressed PD-L1 (34). PD-L1 positive expression in the TCs and SCs of GC was also detected in another study (35). In the current study, PD-L1 expression was detected in both TCs and SCs, however, compared to published studies mentioned above, the positive rate of PD-L1 expression was lower, possibly due to different analysis methods and antibodies. Several studies showed that PD-L1 positive expression was correlated with better survival outcome (36,37). However, Geng et al. found that PD-L1 was significantly correlated with lymph node metastasis and tumor invasion, and PD-L1 was a negative prognostic predictor in GC (38). Our study indicated that PD-L1 expression in TCs and SCs was both correlated with favorable OS, which might explain why patients with PD-L1 overexpression, receiving PD-1 inhibitors, had a favorable survival benefit (7).

VISTA, belonging to the B7 family, is found to be used as a receptor and a ligand (39). Previous studies demonstrated that VISTA was overexpressed in myeloid cells and suppressed T-cell activation (40). Moreover, in vivo experiments indicated that anti-VISTA monoclonal antibodies might be a promising new cancer treatment option (40,41). Previous studies revealed that VISTA could be expressed in many human cancers and VISTA expression was correlated with poor survival outcome (42,43). However, recent studies suggested that VISTA expression was correlated with superior survival in patients with ovarian, breast, colorectal, and cervical cancer (44-47), consistent with our study, which indicated that VISTA expression in ICs was a good prognostic predictor for GC patients.

TIGIT, a novel immunosuppressive molecule, was found to be expressed on T-cell or natural killer cells, and can inhibit the anti-tumor response (48). In GC, previous studies demonstrated that overexpression of TIGIT was significantly correlated with inferior prognosis and functional exhaustion of CD8 T-cell, and blocking TIGIT could enhance the proliferation capacity of CD8 T-cell and improve survival in tumor-bearing mice (18). Meanwhile, Lim et al. suggested that TIGIT was also expressed on B-cell, and GC patients with high TIGIT expression on B-cell had inferior survival outcome (19). In this study, we found that TIGIT was mainly expressed in the ICs of GC, however, TIGIT expression was correlated with favorable OS. The possible explanation is that TIGIT expression in different ICs may be correlated with different survival outcomes. Multiple immunofluorescence to elucidate the relationship between TIGIT expression and different ICs in a large GC cohort is mandatory in the future. In summary, these four immune checkpoints may play a vital role in tumor development and could be a prognostic factor and potential immune targets in patients with GC.

Mucinous and signet-ring cell carcinoma are special types of adenocarcinoma in GC, with poor prognosis and insensitivity to chemotherapy. In our study, we found that compared to patients with adenocarcinoma, patients with mucinous and signet-ring cell carcinoma expressed a lower level of immune checkpoints, including B7-H3, PD-L1, PD-1, TIGIT, and VISTA, which might indicate that these patients were also insensitive to immunotherapy. However, the sample size of patients with mucinous and signet-ring cell carcinoma in this study was small, the distinct immune checkpoints expression and efficacy to immunotherapy should be investigated in a large GC cohort in the future.

The immune characteristics of tumor environment can affect the response to immunotherapy. Thus, it is important to elucidate immune characteristics and identify the prognostic role of immune checkpoints. In cervical cancer, Zong et al. showed that the expression of different immune checkpoints was positively correlated with each other. Moreover, they found double expression of B7-H4 and VISTA was associated with excellent survival outcome (47). In neuroblastoma, Zeng et al. suggested an IS using OX40, B7-H3, ICOS, and TIM-3, was an independent prognostic factor, which might serve as indicators for immunotherapy (49). In breast cancer, Lee et al. indicated that an immune recurrence score based on the expression of seven immune markers was also an independent prognostic factor, which might reflect microenvironment immune status (50). In this study, six immune checkpoints were selected to elucidate immune characteristics of GC, and we found that except for B7-H4, other immune markers were positively correlated with each other, indicating that multi-checkpoint blockade might be effective in GC patients. Meanwhile, we devised an IS based on the expression of four immune markers, which was independent prognostic factor. However, the prognostic value of the IS should be further confirmed by other cohorts. In addition, future work on the relationship between the IS and immunotherapy response is urgently needed.

There are several limitations in this study. First, a single-center retrospective study might result in selection bias. Second, the IS model was significantly correlated with OS, however, whether it could predict tumor recurrence and immunotherapy sensitivity should be further investigated. Third, there was not a validation cohort to support our results, and future work to validate our results is needed. Last, it might be difficult to compare with other studies because of different antibodies and analysis methods used in our study.

Conclusions

In conclusion, our data identified different expression patterns of six immune checkpoints in GC. Furthermore, the IS model using four immune checkpoints could predict OS in GC. Altogether, these findings might provide potential immune targets in GC patients.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1176/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1176/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1176/prf

Funding: This work was supported by the Science, Technology and Innovation Seed Fund of Zhongnan Hospital of Wuhan University (No. CXPY2022015), and the Program of Excellent Doctoral (Postdoctoral) of Zhongnan Hospital of Wuhan University (No. ZNYB2021013 to Z.L.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1176/coif). Z.L. reports this work was supported by the Science, Technology and Innovation Seed Fund of Zhongnan Hospital of Wuhan University (No. CXPY2022015), and the Program of Excellent Doctoral (Postdoctoral) of Zhongnan Hospital of Wuhan University (No. ZNYB2021013). The other 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 and its subsequent amendments. The study was approved by the independent ethics committees from Zhongnan Hospital of Wuhan University (No. 2022152K) and individual consent for this retrospective analysis was waived.

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. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424. [Crossref] [PubMed]
2. Zheng RS, Zhang SW, Sun KX, et al. Cancer statistics in China, 2016. Zhonghua Zhong Liu Za Zhi 2023;45:212-20. [PubMed]
3. Zeng H, Ran X, An L, et al. Disparities in stage at diagnosis for five common cancers in China: a multicentre, hospital-based, observational study. Lancet Public Health 2021;6:e877-87. [Crossref] [PubMed]
4. Petrelli F, Ghidini M, Barni S, et al. Neoadjuvant chemoradiotherapy or chemotherapy for gastroesophageal junction adenocarcinoma: A systematic review and meta-analysis. Gastric Cancer 2019;22:245-54. [Crossref] [PubMed]
5. Kang YK, Boku N, Satoh T, et al. Nivolumab in patients with advanced gastric or gastro-oesophageal junction cancer refractory to, or intolerant of, at least two previous chemotherapy regimens (ONO-4538-12, ATTRACTION-2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 2017;390:2461-71. [Crossref] [PubMed]
6. Janjigian YY, Shitara K, Moehler M, et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet 2021;398:27-40. [Crossref] [PubMed]
7. Shitara K, Van Cutsem E, Bang YJ, et al. Efficacy and Safety of Pembrolizumab or Pembrolizumab Plus Chemotherapy vs Chemotherapy Alone for Patients With First-line, Advanced Gastric Cancer: The KEYNOTE-062 Phase 3 Randomized Clinical Trial. JAMA Oncol 2020;6:1571-80. [Crossref] [PubMed]
8. Salas-Benito D, Pérez-Gracia JL, Ponz-Sarvisé M, et al. Paradigms on Immunotherapy Combinations with Chemotherapy. Cancer Discov 2021;11:1353-67. [Crossref] [PubMed]
9. Andrews LP, Yano H, Vignali DAA. Inhibitory receptors and ligands beyond PD-1, PD-L1 and CTLA-4: breakthroughs or backups. Nat Immunol 2019;20:1425-34. [Crossref] [PubMed]
10. Qin S, Xu L, Yi M, et al. Novel immune checkpoint targets: moving beyond PD-1 and CTLA-4. Mol Cancer 2019;18:155. [Crossref] [PubMed]
11. Shao X, Zhan S, Quan Q, et al. Clinical significance of B7-H3 and HER2 co-expression and therapeutic value of combination treatment in gastric cancer. Int Immunopharmacol 2022;110:108988. [Crossref] [PubMed]
12. Ulase D, Behrens HM, Krüger S, et al. Gastric Carcinomas with Stromal B7-H3 Expression Have Lower Intratumoural CD8+ T Cell Density. Int J Mol Sci 2021;22:2129. [Crossref] [PubMed]
13. Arigami T, Uenosono Y, Ishigami S, et al. Clinical significance of the B7-H4 coregulatory molecule as a novel prognostic marker in gastric cancer. World J Surg 2011;35:2051-7. [Crossref] [PubMed]
14. Jiang J, Zhu Y, Wu C, et al. Tumor expression of B7-H4 predicts poor survival of patients suffering from gastric cancer. Cancer Immunol Immunother 2010;59:1707-14. [Crossref] [PubMed]
15. Ying L, Yan F, Meng Q, et al. PD-L1 expression is a prognostic factor in subgroups of gastric cancer patients stratified according to their levels of CD8 and FOXP3 immune markers. Oncoimmunology 2018;7:e1433520. [Crossref] [PubMed]
16. Angell HK, Lee J, Kim KM, et al. PD-L1 and immune infiltrates are differentially expressed in distinct subgroups of gastric cancer. Oncoimmunology 2019;8:e1544442. [Crossref] [PubMed]
17. Böger C, Behrens HM, Krüger S, et al. The novel negative checkpoint regulator VISTA is expressed in gastric carcinoma and associated with PD-L1/PD-1: A future perspective for a combined gastric cancer therapy? Oncoimmunology 2017;6:e1293215. [Crossref] [PubMed]
18. He W, Zhang H, Han F, et al. CD155T/TIGIT Signaling Regulates CD8(+) T-cell Metabolism and Promotes Tumor Progression in Human Gastric Cancer. Cancer Res 2017;77:6375-88. [Crossref] [PubMed]
19. Liu H, Wu J, Xu X, et al. Peritumoral TIGIT(+)CD20(+) B cell infiltration indicates poor prognosis but favorable adjuvant chemotherapeutic response in gastric cancer. Int Immunopharmacol 2022;108:108735. [Crossref] [PubMed]
20. Xu D, Zhao E, Zhu C, et al. TIGIT and PD-1 may serve as potential prognostic biomarkers for gastric cancer. Immunobiology 2020;225:151915. [Crossref] [PubMed]
21. Lu Z, Zhao ZX, Cheng P, et al. B7-H3 immune checkpoint expression is a poor prognostic factor in colorectal carcinoma. Mod Pathol 2020;33:2330-40. [Crossref] [PubMed]
22. Wang FH, Zhang XT, Li YF, et al. The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021. Cancer Commun (Lond) 2021;41:747-95. [Crossref] [PubMed]
23. Lu Z, Cheng P, Huang F, et al. Significance of Siglec-15 expression in colorectal cancer: association with advanced disease stage and fewer tumor-infiltrating lymphocytes. J Pathol Clin Res 2023;9:121-8. [Crossref] [PubMed]
24. 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]
25. Yonesaka K, Haratani K, Takamura S, et al. B7-H3 Negatively Modulates CTL-Mediated Cancer Immunity. Clin Cancer Res 2018;24:2653-64. [Crossref] [PubMed]
26. Aung PP, Parra ER, Barua S, et al. B7-H3 Expression in Merkel Cell Carcinoma-Associated Endothelial Cells Correlates with Locally Aggressive Primary Tumor Features and Increased Vascular Density. Clin Cancer Res 2019;25:3455-67. [Crossref] [PubMed]
27. Lin L, Cao L, Liu Y, et al. B7-H3 promotes multiple myeloma cell survival and proliferation by ROS-dependent activation of Src/STAT3 and c-Cbl-mediated degradation of SOCS3. Leukemia 2019;33:1475-86. [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. Du H, Hirabayashi K, Ahn S, et al. Antitumor Responses in the Absence of Toxicity in Solid Tumors by Targeting B7-H3 via Chimeric Antigen Receptor T Cells. Cancer Cell 2019;35:221-237.e8. [Crossref] [PubMed]
30. Li D, Xiang S, Shen J, et al. Comprehensive understanding of B7 family in gastric cancer: expression profile, association with clinicopathological parameters and downstream targets. Int J Biol Sci 2020;16:568-82. [Crossref] [PubMed]
31. Li Y, Yang X, Wu Y, et al. B7-H3 promotes gastric cancer cell migration and invasion. Oncotarget 2017;8:71725-35. [Crossref] [PubMed]
32. Zhan S, Liu Z, Zhang M, et al. Overexpression of B7-H3 in α-SMA-Positive Fibroblasts Is Associated With Cancer Progression and Survival in Gastric Adenocarcinomas. Front Oncol 2019;9:1466. [Crossref] [PubMed]
33. Wu CP, Jiang JT, Tan M, et al. Relationship between co-stimulatory molecule B7-H3 expression and gastric carcinoma histology and prognosis. World J Gastroenterol 2006;12:457-9. [Crossref] [PubMed]
34. Chen X, Zhang H, Wang M, et al. Relationship Between Programmed Death Ligand 1 Expression and Other Clinicopathological Features in a Large Cohort of Gastric Cancer Patients. Front Immunol 2022;13:783695. [Crossref] [PubMed]
35. Thompson ED, Zahurak M, Murphy A, et al. Patterns of PD-L1 expression and CD8 T cell infiltration in gastric adenocarcinomas and associated immune stroma. Gut 2017;66:794-801. [Crossref] [PubMed]
36. Böger C, Behrens HM, Mathiak M, et al. PD-L1 is an independent prognostic predictor in gastric cancer of Western patients. Oncotarget 2016;7:24269-83. [Crossref] [PubMed]
37. Kim DH, Bae GE, Suh KS, et al. Clinical Significance of Tumor and Immune Cell PD-L1 Expression in Gastric Adenocarcinoma. In Vivo 2020;34:3171-80. [Crossref] [PubMed]
38. Geng Y, Wang H, Lu C, et al. Expression of costimulatory molecules B7-H1, B7-H4 and Foxp3+ Tregs in gastric cancer and its clinical significance. Int J Clin Oncol 2015;20:273-81. [Crossref] [PubMed]
39. Lines JL, Sempere LF, Broughton T, et al. VISTA is a novel broad-spectrum negative checkpoint regulator for cancer immunotherapy. Cancer Immunol Res 2014;2:510-7. [Crossref] [PubMed]
40. Le Mercier I, Chen W, Lines JL, et al. VISTA Regulates the Development of Protective Antitumor Immunity. Cancer Res 2014;74:1933-44. [Crossref] [PubMed]
41. Liu J, Yuan Y, Chen W, et al. Immune-checkpoint proteins VISTA and PD-1 nonredundantly regulate murine T-cell responses. Proc Natl Acad Sci U S A 2015;112:6682-7. [Crossref] [PubMed]
42. Wu L, Deng WW, Huang CF, et al. Expression of VISTA correlated with immunosuppression and synergized with CD8 to predict survival in human oral squamous cell carcinoma. Cancer Immunol Immunother 2017;66:627-36. [Crossref] [PubMed]
43. Kuklinski LF, Yan S, Li Z, et al. VISTA expression on tumor-infiltrating inflammatory cells in primary cutaneous melanoma correlates with poor disease-specific survival. Cancer Immunol Immunother 2018;67:1113-21. [Crossref] [PubMed]
44. Zong L, Zhou Y, Zhang M, et al. VISTA expression is associated with a favorable prognosis in patients with high-grade serous ovarian cancer. Cancer Immunol Immunother 2020;69:33-42. [Crossref] [PubMed]
45. Zong L, Mo S, Yu S, et al. Expression of the immune checkpoint VISTA in breast cancer. Cancer Immunol Immunother 2020;69:1437-46. [Crossref] [PubMed]
46. Zong L, Yu S, Mo S, et al. High VISTA Expression Correlates With a Favorable Prognosis in Patients With Colorectal Cancer. J Immunother 2021;44:22-8. [Crossref] [PubMed]
47. Zong L, Gu Y, Zhou Y, et al. Expression of B7 family checkpoint proteins in cervical cancer. Mod Pathol 2022;35:786-93. [Crossref] [PubMed]
48. Anderson AC, Joller N, Kuchroo VK. Lag-3, Tim-3, and TIGIT: Co-inhibitory Receptors with Specialized Functions in Immune Regulation. Immunity 2016;44:989-1004. [Crossref] [PubMed]
49. Zeng L, Xu H, Li SH, et al. Cross-cohort analysis identified an immune checkpoint-based signature to predict the clinical outcomes of neuroblastoma. J Immunother Cancer 2023;11:e005980. [Crossref] [PubMed]
50. Lee DW, Ryu HS, Jin MS, et al. Immune recurrence score using 7 immunoregulatory protein expressions can predict recurrence in stage I-III breast cancer patients. Br J Cancer 2019;121:230-6. [Crossref] [PubMed]