Neuroendocrine neoplasms (NENs) are a highly heterogeneous group of tumors originating from the neuroendocrine system. The cells giving rise to these tumors are widely distributed throughout the body, so NENs can occur almost anywhere in the body, but they are most commonly found in the gastrointestinal tract, pancreas, or lungs (1, 2). Based on the degree of differentiation of tumor cells, NENs can be further classified into well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Of these, gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) account for approximately 70% of NENs (3). In recent years, the incidence of GEP-NENs is rising in Europe and the United States (4, 5), posing a public health challenge. Rindi et al. demonstrated that GEP-NENs can be stratified into three grades based on tumor cell morphology (well-differentiated vs. poorly-differentiated), along with mitotic rate and/or Ki-67 proliferation index (6). Grading has a significant impact on the development of treatment regimens. Currently, surgical resection is an effective treatment for low-grade GEP-NENs (7). However, some patients are not suitable for radical surgery due to large tumors or distant metastases, and GEP-NENs also have a high rate of postoperative recurrence (8). At this point, for patients, including high-grade GEP-NENs, chemotherapy, radiation effect therapies, biologic therapies, and other treatments are available but still have limited effectiveness (9–12). Therefore, there is an urgent need to find effective therapeutic targets to enable more targeted and personalized treatment.

Cancer immunotherapy, as an emerging therapeutic strategy, has made remarkable scientific progress in the past few years. It identifies and attacks tumor cells by activating or enhancing the body’s own immune system, and has made key breakthroughs in the field of precision targeted tumor therapy. Programmed cell death protein 1 (PD-1) and its ligand (programmed death ligand 1, PD-L1) are important immune checkpoint molecules. Binding between PD-L1 and PD-1 leads to apoptosis of activated T cells, a mechanism by which tumor cells evade host immunity and survive (13). The use of PD-1/PD-L1 inhibitors blocks the interaction between PD-1 and PD-L1, removes the braking effect of inhibitory receptors on the surface of T cells, and activates the anti-tumor immune response, a known mechanism that leads to T cell dysfunction (14, 15). Recent advances in immunotherapy have led to an increasing interest in the study of PD-L1 as a biomarker for predicting prognosis and determining a patient’s eligibility for targeted therapy.PD-L1 has been shown to be expressed in a wide variety of tumors. Therefore, PD-1/PD-L1 inhibitors have also been more widely used in a variety of cancers, such as melanoma, lung and breast cancers (16–18). Currently, several experiments have demonstrated that GEP-NENs tumor tissues can also express PD-L1, and correlations between PD-L1 and patients’ pathological features, immune markers and prognosis have been found. However, the findings of these studies are inconsistent, which greatly limits the clinical use of immunotherapy and related biomarkers in GEP-NENs. Furthermore, due to the rarity of NENs, the sample sizes in relevant clinical trials are limited, which may affect the statistical significance of research findings and the scalability of clinical applications.

Therefore, this study aims to integrate currently published clinical research data through meta-analysis to systematically analyze the potential relationship between PD-L1 expression and clinical-pathological characteristics and prognosis in GEP-NENs. It also seeks to preliminarily explore its potential application as a prognostic biomarker, provide clinical insights for specific GEP-NENs patients receiving PD-1/PD-L1 inhibitor therapy, and accumulate foundational data and theoretical references for future research in this field.

The study was conducted in strict adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (19). It was registered with the International Registry of Prospective Systematic Reviews (PROSPERO) under the registration number CRD420251048602 (available at: https://www.crd.york.ac.uk/prospero).

This systematic review and meta-analysis aimed to investigate the correlation between PD-L1 expression and the clinical-pathological characteristics, immune markers (such as PD-1 expression), and prognosis of GEP-NENs. Our primary findings are summarized as follows: (1) High PD-L1 expression was significantly associated with higher WHO tumor grades, including well-differentiated grade 3 NET (NET G3) and poorly differentiated NEC); (2) High PD-L1 expression correlated with PD-1 expression in the tumor microenvironment; (3) High PD-L1 expression predicted poorer OS. These findings suggest PD-L1 may serve as an independent prognostic marker for GEP-NENs and further propose the hypothesis that immune checkpoint inhibitors (ICIs), such as PD-1/PD-L1 inhibitors, may demonstrate therapeutic efficacy in high-grade GEP-NENs. However, a critical limitation should be highlighted upfront: PFS—a key prognostic indicator for GEP-NENs that reflects disease progression and treatment response—was not analyzed in this meta-analysis due to insufficient data reporting in included studies, which limits the comprehensiveness of our prognostic assessment. Most included studies were retrospective, and the lack of direct correlation between PD-L1 expression and ICI efficacy metrics (such as objective response rate [ORR] and PFS) further limits the applicability of these findings to clinical treatment decisions.”

In malignant tumors, PD-L1 expression is commonly regarded as a poor prognostic factor (48) and is closely associated with key clinical-pathological features such as tumor grading (49, 50). Consistent with these findings, our study confirms that high PD-L1 expression in GEP-NENs is significantly correlated with higher WHO grades (including NET G3 and NEC), potentially reflecting increased tumor invasiveness and immune evasion mechanisms. This conclusion is supported by existing research: interferon-γ (IFN-γ)-induced PD-L1 expression in tumor cells is a key mechanism of adaptive immune resistance, suppressing T-cell activity. Notably, PD-L1 expression is more pronounced in tumors with higher malignancy (accompanied by stronger immune pressure) (51). Furthermore, high PD-L1 expression in high-grade GEP-NENs frequently accompanies adverse pathological features (e.g., high Ki67 index) and an immunosuppressive tumor microenvironment (52, 53). Luo et al. demonstrated that miR-23a/27a/24 cluster upregulation correlates with tumor immune evasion and PD-L1 overexpression, a phenomenon more pronounced in patients with higher malignancy and poorer prognosis (54). Yang et al. demonstrated that activation of the mitogen-activated protein kinase (MAPK) pathway—commonly observed in aggressive tumors—directly induces PD-L1 accumulation on the cell surface, thereby accelerating immune evasion and drug resistance development (55). Notably, PD-L1 expression patterns may vary across GEP-NENs subtypes. For instance, in pancreatic NETs, PD-L1 expression correlates with differentiation grade, with higher-grade tumors more likely to be PD-L1-positive, suggesting tumor heterogeneity may influence immune checkpoint expression (56, 57).

This meta-analysis further confirms that high PD-L1 expression in GEP-NENs correlates with PD-1 expression and poorer OS, highlighting PD-L1’s pivotal role in mediating tumor immune escape. The PD-1/PD-L1 pathway is central to this process: PD-L1 expressed by tumor or immune cells binds to PD-1 on T-cell surfaces, suppressing antitumor function and inducing T-cell exhaustion. The co-occurrence of high PD-L1 and PD-1 expression observed in this study directly validates the activity of this pathway in GEP-NENs. This finding aligns with previous research linking PD-L1 positivity to T cell exhaustion (e.g., CD8+ T cell dysfunction) and poor prognosis (53, 58). This also suggests that PD-L1 expression in GEP-NENs may reflect an “immunohot” yet simultaneously immunosuppressive tumor microenvironment (characterized by abundant tumor-infiltrating lymphocytes), thereby impacting patient survival (58). Importantly, the association between PD-L1 positivity and poor OS has been widely reported across multiple cancers, including hepatocellular carcinoma (59), gastric cancer (60), and urothelial carcinoma (61). In GEP-NENs, this correlation may be amplified due to tumor biological heterogeneity; for example, PD-L1 expression in high-grade tumors correlates closely with metastasis and drug resistance (62). Collectively, these findings not only confirm high PD-L1 expression as a potential prognostic marker for GEP-NENs but also suggest that patients with high-grade GEP-NENs may benefit from immunotherapy, consistent with existing research evidence.

Beyond its prognostic value, PD-L1 status is a recognized predictor of ICI efficacy across multiple cancer types (61, 63), and emerging data also suggest that patients with high-grade GEP-NENs may have therapeutic response potential to PD-1/PD-L1 inhibitors. For example, response rates to dual CTLA-4/PD-1 targeting range from 9% to 44% (64, 65), and PD-L1-positive tumors demonstrate higher sensitivity to agents such as avelumab (66). However, it is important to note that the overall response rate to ICIs in NEN patients remains generally low, indicating that PD-L1 is not the sole determinant of treatment efficacy. Characteristics of the tumor immune microenvironment, such as tumor-infiltrating lymphocyte density, also play a significant role (67). Therefore, combining PD-L1 with other biomarkers may further optimize prognostic assessment and treatment prediction models for GEP-NENs.

To address the variability in PD-L1 assessment methods across studies, this research conducted a multidimensional subgroup analysis targeting key heterogeneity factors in PD-L1 evaluation, including antibody clones, cutoff definitions, tumor area detection, and scoring systems. Results revealed that antibody clones SP142, 28-8, 22C3, and SP263; the “other” category cutoff versus the traditional 1% cutoff (for OS assessment); combined detection of tumor cells and immune cells versus tumor cell-only detection (for OS prediction); and CPS/TPS versus standalone TPS/CPS scoring demonstrated superior correlations with tumor grade, histological differentiation, PD-1 expression, and OS. Furthermore, the analysis identified the E1L3N antibody, the “Other” cutoff group, and the tumor cell/combined detection group as primary sources of heterogeneity, offering optimized detection strategies for different clinical scenarios. These findings support standardized PD-L1 testing (prioritizing high-quality antibodies, combined detection, or customized scoring systems) and personalized decision-making (adjusting cutoffs based on disease characteristics). However, limitations such as data gaps, high heterogeneity, and uncontrolled confounders in certain subgroups should be acknowledged. These issues also underpin the study limitations discussed later. Future efforts should focus on expanding sample sizes, establishing unified testing standards, and integrating other immunobiomarkers for combined assessment to enhance the precision of identifying patients likely to benefit from immunotherapy.

In summary, our findings confirm that PD-L1 expression in GEP-NENs correlates positively with high WHO grading (NET G3/NEC) and PD-1 expression. These results support the hypothesis that this patient subgroup relies heavily on the PD-1/PD-L1 pathway for immune evasion and may therefore benefit from anti-PD-1/PD-L1 therapy. In clinical practice, PD-L1 testing can be combined with WHO grading and molecular features (e.g., DLL3 mutation) for patient stratification (52, 57). Prospective exploration of ICIs or combination therapies (e.g., avelumab + anti-angiogenic agents) warrants consideration in high PD-L1-positive cases (64, 66). Future research on GEP-NENs should focus on four key directions (classified by research objectives): (1) Validation: Multicenter studies to validate the association between PD-L1 expression and clinical-pathological features, immune markers, and prognosis; (2) Mechanistic exploration: Elucidate PD-L1 regulatory mechanisms through multi-omics analysis (68) and clarify the molecular role of the PD-1/PD-L1 pathway in GEP-NENs pathogenesis; (3) Clinical translation: Conduct PD-L1-guided RCTs (69), systematically evaluate the clinical efficacy, safety, and predictive value of PD-1/PD-L1 pathway-targeted antibodies through prospective trials (establishing their association with ORR and PFS), and validate the hypothesis that PD-L1 expression guides immunotherapy selection in high-grade GEP-NENs; (4) Methodological Standardization: Develop standardized PD-L1 detection guidelines to reduce heterogeneity. Furthermore, future studies should adopt more rigorous designs, expand sample sizes, standardize survival analysis methods, extend follow-up periods, and increase implementation of high-quality clinical research such as RCTs to enrich data dimensions, reduce study bias, and enhance the reliability of conclusions.

Although this meta-analysis provides compelling evidence, several limitations exist: (1) Most notably, lack of standardization in PD-L1 assessment across included studies, including variations in antibody clones (e.g., 22C3, SP263), cutoff values (TPS ranging from 1% to 5%), scoring systems (TPS vs. CPS), and tumor regions (tumor cells vs. immune cells). This heterogeneity may have compromised the consistency of results and hindered direct comparisons between studies. Furthermore, the small sample sizes in each subgroup significantly impaired the quality of subgroup analyses, substantially reducing the power to assess the impact of these factors on heterogeneity. Therefore, standardizing PD-L1 testing in GEP-NENs is urgently needed to enhance the reliability of its clinical application. (2) Despite including 22 studies, key subgroup analyses (e.g., FOXP3, MMR status, histopathological subtype) were based on only 2–3 studies, resulting in insufficient statistical power. Conclusions remain preliminary and require further validation. Furthermore, the association between PD-L1 expression and tumor metastasis is unstable: sensitivity analysis revealed significant shifts in the pooled effect size after excluding one study, indicating dependence on individual studies and potential confounding by the proportion of high-grade/advanced patients. (3) Some studies lacked raw survival data, necessitating indirect estimation of HRs from Kaplan-Meier curves; This indirect method may introduce errors, compromising the validity of pooled results. (4) Correlation does not imply causation: This analysis confirms only an association between PD-L1 expression and prognosis, not causality. Potential biological mechanisms require further experimental validation. (5) Study design limitations: Research on GEP-NENs remains scarce and predominantly retrospective. Existing prognostic studies predominantly focus on OS while neglecting critical indicators like PFS. This omission prevents a comprehensive evaluation of PD-L1’s prognostic value, as PFS often complements OS by capturing early treatment responses that OS may not reflect in GEP-NENs. Research on staging for GEP-NETs and GEP-NECs is also scarce. Furthermore, inconsistencies in study focus (e.g., age groups, primary tumor sites) limited literature inclusion, resulting in high heterogeneity among enrolled studies. Additionally, prognostic analyses failed to effectively distinguish between GEP-NETs and GEP-NECs, further compromising result accuracy.

This meta-analysis demonstrated that PD-L1 is aberrantly expressed in GEP-NENs and significantly correlated with tumor grade, PD-1 expression, and OS. Therefore, PD-L1 holds promise as a highly prospective prognostic biomarker and potential therapeutic target for immunotherapy interventions in GEP-NENs, warranting further in-depth investigation. Future studies should focus on elucidating the underlying molecular mechanisms of the PD-1/PD-L1 pathway in GEP-NENs pathogenesis and systematically assessing the clinical efficacy, safety, and predictive value of antibody-based therapies targeting this pathway. Notably, due to the inherent limitations of the current meta-analysis (e.g., heterogeneity among included studies, potential publication bias), large-scale, multicenter prospective cohort studies and mechanistic explorations using robust preclinical models are imperative to validate and extend these findings. Such efforts will provide more robust evidence to support the optimization of precision medicine strategies for GEP-NENs, ultimately facilitating the translation of scientific insights into improved clinical outcomes for patients with this disease.