Background
Host and tumor tissues undergo extensive immune interactions, and the ability of the tumor to evade immune recognition often determines clinical outcomes. Immunotherapy has recently emerged as a novel approach in treating solid tumors. Tumor-infiltrating lymphocytes (TIL) play an essential role in mediating the response to immunotherapy and affect clinical outcomes in many cancer subtypes. The presence of TILs within the tumor microenvironment has been linked to better prognosis in gastric cancer [
1]. “Immunologic checkpoints” expressed on cells in the tumor microenvironment or on the surface of tumor cells (TCs) can promote immune escape by inducing apoptosis in immune effector cells. One such immune checkpoint is programmed cell death protein 1 (PD-1). The binding of PD-1 to its ligand programmed cell death 1 ligand 1 (PD-L1) leads to a blockade of kinases involved in T cell activation. PD-L1 expression on TCs is associated with worse prognosis in many malignancies [
2]. Many recent studies have reported that the response to immunotherapy primarily depends on the expression of PD-L1 in the tumor microenvironment. These findings suggest that the response to anti-PD-1 hinges on pre-existing anti-tumor immune response and that anti-PD-1 acts to free the CD8 T cells from inhibition to exert their anti-tumor activities [
3]. Furthermore, naturally occurring TILs can be detected in various solid tumors, even in metastatic stages [
4]. Immunosuppressive mechanisms within the tumor microenvironment have been associated with the failure of TILs [
5]. Biomarkers of immune phenotypes are most commonly identified using immunohistochemistry (IHC). Studies using quantitative IHC have identified CD8
+ T cell infiltration as an important prognostic factor in predicting outcomes in patients with gastric cancer [
6]. CD8
+ T cells are regulated by regulatory T cells (Tregs). Among all Tregs, Foxp3-expressing Tregs are well known to play a critical role in tumor immune evasion [
7], which has been reported in a wide array of human malignancies including our study in gastric cancer [
7,
8]. Furthermore, upregulation of Tregs is associated with significantly reduced CD8
+ T cell infiltration of tumors and with worse outcomes for cancer patients [
9]. However, the clinical implications of immunosuppressive processes related to immunologic checkpoints (PD-L1, CD8, and Foxp3) in tumors or immune cells in the tumor microenvironment remain controversial, and the potential use of these checkpoints as prognostic markers requires further study.
Tissue microarrays (TMAs) are commonly employed in clinical and basic-science research, it is a powerful tool for undertaking large-scale tissue-based biomarker studies [
10] and has been widely used in many studies that involved in immune infiltrates studies [
11,
12]. Tissue sections from TMAs also offer the opportunity to understand a patient’s disease condition, to make better prognostic evaluations and to select optimum treatments. But tissues are often assessed primarily based on visual analysis of one or two molecules, image analysis is starting to address the variability of human samples. This is in contrast to measure characteristics such as parameters revealed through co-expression, spatial relationships, heterogeneity, and low abundance molecules. Those factors are understood to be critical to develop effective therapeutic strategies [
13]. So far, TMA performance across multiple biomarkers has not been systematically explored. Here the multiplex immunohistochemistry (mIHC) was employed in our study for mapping the tumor microenvironment. This technology allows us to explore the relationship between various cell types in the peritumoral and intratumoral compartments through more comprehensive and efficient analysis of the tumor microenvironment. mIHC quantifies the change in expression or state of specific biomarkers and examines their impact on patient disease status for both mechanistic and diagnostic studies, potentially advancing our understanding of immune phenotypes and cell interactions in the microenvironment while also providing better direct patient treatment based on individual tumor microenvironment responses to immunotherapy, offering improved response rates with gastric disease [
14]. Here we developed a 4-color multispectral quantitative fluorescent immunohistochemistry methods to detect CD8, Foxp3 and PD-L1 simultaneously.
Discussion
We established a novel 4-color mIHC method that facilitates studying multiple parameters simultaneously in gastric disease tissues, which can illuminate important suppressive mechanisms within the tumor microenvironment [
20]. This technology may help overcome the limitations of conventional single-color immunohistochemistry approaches used to classify patients based on the degree of their CD3 and CD8 T cell infiltration [
21]. Here, our data revealed that the interactions between different immune populations serve as a better predictor compared with CD8 T cell density alone. Furthermore, by integrating this tool with unsupervised hierarchical analysis, we are able to observe the correlation patterns and signatures of CD8 and Foxp3 TIL densities and PD-L1 levels, which may indicate that PD-L1 regulates the immune response. This finding may be important in understanding the mechanisms of action of therapies and developing predictive biomarkers for more direct therapy.
Through the application of digital pathology tools for biomarker discovery and validation, CD8
+ T cell infiltrates have been shown to have prognostic value in various types of cancer. High densities of CD8 and PD-L1 staining correlate with responses to anti-PD-1 immunotherapy agents in renal cell carcinoma (RCC), melanoma and non-small cell lung cancer (NSCLC) [
22]. Patients with both high levels of T cell infiltrates and high PD-L1 expression in their tumors may fail to respond to anti-PD-L1 therapy. Complex tumor microenvironments are difficult to encapsulate with single markers such as CD8 and PD-L1. Thus, utilizing multiparametric analyses of immune checkpoints, including PD-L1, CD8 and Foxp3, to study the interactions between cell types may provide a more comprehensive view of immune phenotypes and signatures in the tumor microenvironment, which may help develop predictions and accurately stratify patients compared with CD8 alone.
The link between PD-L1 expression and immunotherapeutic outcomes can vary, possibly due to different IHC assays. Unresolved issues, including different staining protocols, different antibody protocols, and different scoring methods for identifying target cells as TCs, tumor-infiltrating immune cells (TIICs), etc., likely contribute to the unstable PD-L1 landscape. We used the E13LN clone from Cell Signaling Technologies, which demonstrates greater antibody sensitivity compared with other PD-L1 antibodies. We also optimized the experimental conditions to compare traditional IHC and 4-color mIHC using the same antibodies. Automatic identification of specific cells and tissue compartment types using trainable feature recognition algorithms was also implemented for our pattern and morphology analysis.
Immune responsiveness to the presence of a tumor is dependent on the proximity lymphocytes to the tumor. Endogenous CD8
+ tumor-infiltrating T cells have been identified in a small series of patients with advanced gastric cancer [
23]. These naturally occurring CD8
+ TILs can specifically recognize autologous tumor-derived cells. However, in tumor regression during late-stage gastric cancers, TILs are rarely seen in the tumor microenvironment, suggesting that TILs are more common in early-stage disease which we selected stage II cancer patients and that advanced gastrointestinal malignancies are less immunogenic due to the selection pressure of some cancer cell during disease progression [
24]. Multiple large studies have shown that increased PD-L1 expression correlates with worse prognosis, highlighting the prognostic power of PD-L1 expression in gastric cancers [
25]. Elevated the expression of PD-L1 is associated with advanced stage, more nodal metastases and worse outcomes [
26]. The PD-L1 pathway has become an important target in cancer immunotherapy. However, the prognostic value of PD-L1 for gastric cancer still remains controversial due to the complexity of the tumor and immune cells interaction. For this propose, to comprehensive evaluation of PD-L1 expression, Foxp3 and CD8
+ T cells is necessary and superior to predicting these interactions.
Recent study showed that molecular classification dividing gastric cancer into four subtypes: (1) tumors positive for Epstein–Barr virus, which display recurrent
PIK3CA mutations, (2) extreme DNA hypermethylation, (3) amplification of
JAK2,
CD274 (
PD-
L1) and
PDCD1LG2 (
PD-
L2); (4) microsatellite unstable tumors (Microsatellite instability, MSI), which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins [
27]. Those interesting data showed that PD-L1/2 expression was elevated in EBV-positive tumors by 9p amplifications, which were enriched in the EBV subgroup (15% of tumors). These results may indicate that those molecular classification associated with immune phenotype (checkpoint), will be worth to follow up in the association between checkpoint and expression of EBV, phenotype of MSI in a much larger number of gastric cancer tissues and also relative survival data in our future study.
The main aim of this study was to analyze the tumor microenvironment by analyzing 3 markers on 4-μm-thick gastric disease tissue sections. Overall, we found that the method was reproducible. Our data showed that PD-L1 was expressed in gastric ulcers, TCs and TIICs but not in normal gastric mucosa or other gastric intraepithelial neoplasia tissues. Furthermore, the ratios of CD8
+T:Foxp3 and CD8
+T:PD-L1 were suppressed in tumor tissues. Using the CD8
+T:PD-L1 ratio, we were able to divide the samples into three class groups, and further integrating the CD8
+T:Foxp3 ratio, which increased the complicity of immune phenotypes status, we defined 6–7 signatures and allowed the separation of gastric cancer patients at the same stage into different risk-group subsets (Fig.
6). Thus, increasing tumor PD-L1 expression correlated with response rate in a recent PD-1 inhibitor (KEYNOTE-012) phase I clinical trial, which supported a trend toward improved overall response rate (ORR) and progression-free survival (PFS) [
28]. However, a few cases with lower responses also had high levels PD-L1 expression, suggesting that using the CD8
+T:Foxp3 and CD8
+T:PD-L1 ratios to define 6–7 clusters to separate gastric cancer patients into different risk subgroups may be useful for predicting and guiding PD-L1 therapy.
Authors’ contributions
LY, FY, DX and YH contributed to concept, design of the study and wrote the manuscript. LY performed the experiments, LY and FY analyzed the data. QM, XY, LY, BRW, DWC, LS, YT, PN and XW helped to acquire experimental data and contributed to the reagents. All authors read and approved the final manuscript.