The Immune Signatures Predict Gastric/Gastroesophageal Junction Cancer Response to First-line Anti-PD-1 Blockade or Chemotherapy: Clinical and Multiplex Immunofluorescence Analysis

doi:10.21203/rs.3.rs-4989092/v1

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The Immune Signatures Predict Gastric/Gastroesophageal Junction Cancer Response to First-line Anti-PD-1 Blockade or Chemotherapy: Clinical and Multiplex Immunofluorescence Analysis

https://doi.org/10.21203/rs.3.rs-4989092/v1

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Background

Anti-PD-1 immunotherapy and platinum-based chemotherapy are key components of first-line treatment for advanced Gastric or Gastroesophageal Junction Cancer (G/GEJ). However, the role of immune cells infiltrating the tumor microenvironment in predicting both therapy responses is still unclear.

Methods

We performed exploratory analyses of progression-free survival(PFS) and overall survival (OS) based on PD-L1 expression and a landmark statistical method, and developed a multiplexed immunofluorescence assay for CD4, CD8, PD-L1, CD68 and FoxP3 coupled with digital image analysis and machine learning to assess prognostic survival associations of immune cells.

Results

For patients with PD-L1 CPS < 10, greater disparities in survival between anti-PD-1 immunotherapy and chemotherapy were shown around 300 days after treatment. High expression of PD-L1 was associated with longer survival when receiving anti-PD-1 blockade, but showed less benefit when receiving platinum-based chemotherapy by subgroup analysis. The analysis of mIF also demonstrated significantly higher stromal density of PD-L1 in the well-responder group of patients receiving immunotherapy than the poor-response group, but tended to be lower in patients receiving chemotherapy. Besides, we found that high tumor stromal density of CD8 could be used as a biomarker of good prognosis in anti-PD-1 immunotherapy, and high tumor stromal density of CD4 was found to be associated with worse prognosis in platinum-based chemotherapy.

Conclusions

These findings indicate that increased PD-L1 expression was associated with an increased effect on anti-PD-1 immunotherapy and reduced benefit from chemotherapy. The signature of TME immune cells has the potential to predict the response of anti-PD-1 immunotherapy and chemotherapy in G/GEJ cancer.

Gastric/Gastroesophageal Junction Cancer

anti-PD-1 Blockade

Platinum-based Chemotherapy

the Tumor Immune Microenvironment

Predictive Biomarkers

Gastric and gastroesophageal junction (G/GEJ) cancer is one of the most common cancers worldwide, ranking fifth in incidence and fourth in mortality[1]. In China, new G/GEJ cancer cases account for approximately 40% of all new cases globally, and the vast majority are diagnosed at stage III or IV, missing the opportunity for surgical resection[2, 3]. Even after curative surgery, most patients develop local recurrence or distant metastases, with a 5-year survival rate of less than 25%[4–6].

Immune checkpoint inhibitors (ICIs) targeting programmed cell death-1 (PD-1) and programmed death-ligand 1 (PD-L1) have significantly revolutionized the treatment landscape of advanced G/GEJ cancers[7, 8]. Based on the results of the ORIENT-16 trials[9], sintilimab combined with chemotherapy as the first-line treatment for advanced gastric cancer, is more effective and safer than chemotherapy alone in China, resulting in a stronger and longer-lasting response. However, no significant differences were observed for patients with a combined positive score (CPS) less than 5. It seems that not all G/GEJ patients could benefit from inhibitors. The predictive value of PD-L1 in precision medicine remains to be explored. In addition, as the cornerstone treatment modality, fluoropyrimidine plus platinum-based chemotherapy is still an indispensable strategy for unresectable advanced or metastatic human epidermal growth factor receptor 2 (HER2)-negative G/GEJ adenocarcinoma, but its clinical outcome is far from satisfactory[10–15]. Therefore, there is an urgent need to study the potential factors that affect anti-PD-1/PD-L1 immunotherapy and platinum-based chemotherapy.

Alongside a growing understanding of the tumor immune microenvironment, researchers are increasingly focusing on components that may influence the treatment response, such as T cells, B cells, neutrophils, and macrophages[16–19]. In this context, studies have suggested that a high abundance of infiltrating CD8 + or CD3 + T cells within tumor tissues indicates a neoplastic "hot tumor" or an immune-inflamed state, suggesting a robust immune response[20]. PD-1 and PD-L1 blockade can also elicit a strong natural killer (NK) cell response[21], whereas β-catenin within the tumor can hinder dendritic cell recruitment, leading to PD-1/PD-L1 resistance[22]. The immune status of an individual can also be used to assess the effects of chemotherapy. Therefore, owing to the inherent heterogeneity of tumors and the complex immune response to treatment, single biomarkers are insufficient for identifying the potential benefits in gastric cancer treantments.

Advancements in multiplex immunofluorescence (mIF) allow simultaneous visualization of multiple antigen markers within the same tissue section. This technique, combined with digital image analysis and machine learning, facilitates characterization of the density and spatial distribution of the tumor immune microenvironment. However, mIF remains underutilized in the context of advanced gastric cancer. Consequently, factors within the tumor microenvironment that dictate the response to first-line anti-PD-1 immunotherapy and chemotherapy remain unclear.

In the present study, patients in the ORIENT16 study from the First Affiliated Hospital of Zhejiang University School of Medicine were included. We further analyzed the survival curves using the landmark statistical method and performed exploratory analyses of the efficacy of anti-PD-1 immunotherapy and platinum-based chemotherapy in PD-L1 CPS ≥ 10 and CPS < 10 subgroups. Using multiplexed immunofluorescence combined with digital image analysis and supervised machine learning, we quantified the immune cells in the tumor microenvironment and assessed the relationship between immune cell densities and treatment outcomes. These data will be used to investigate the immune and stromal features of good responders and poor responders, with the goal of identifying the prognostic significance of immune biomarkers of anti-PD-1 immunotherapy or platinum-based chemotherapy.

2.1 Study Design and Participants

The ORIENT16 study, a randomized, double-blind, phase 3 clinical trial, was conducted at 62 hospitals in China and registered on November 14, 2018, at ClinicalTrials.gov (NCT03745170) (https://clinicaltrials.gov/ct2/show/NCT03745170?term=NCT03745170&draw=2&rank=1). Our study collected patient information from the First Affiliated Hospital of Zhejiang University School of Medicine, which has the largest number of participants in the ORIENT16 study. The trial was conducted according to Good Clinical Practice Guideline. The protocol and all amendments were approved by an independent ethics committee and were consistent with the ORIENT16 study published previously[9].

Eligible patients were 18 years or older with histologically confirmed unresectable locally advanced, recurrent, or metastatic G/GEJ adenocarcinoma. Patients who had received previous adjuvant or neoadjuvant chemotherapy or radiotherapy were also allowed at least 6 months after the last administration for disease recurrence. Additionally, patients needed to have at least one measurable or evaluable lesion, as defined in the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines (version 1.1). Patients with known human epidermal growth factor receptor 2 (HER2)-positive status; a history of active, known, or suspected autoimmune disease; or prior systemic treatment for advanced or metastatic G/GEJ adenocarcinoma were excluded from the trial. Written informed consent was obtained from all patients prior to enrollment.

All patients were randomly assigned to sintilimab plus chemotherapy group (sintilimab plus platinum-based chemotherapy) and placebo plus chemotherapy group (placebo plus platinum-based chemotherapy). Randomization was performed using an interactive web response system and stratified according to the Performance Status (PS) score of the Eastern Cooperative Oncology Group Performance Status (ECOG) (0 or 1), liver metastasis (yes or no), peritoneum metastasis (yes or no), and PD-L1 (Combined Positive Score (CPS) < 10 or ≥ 10). The patients, investigators, and study sponsor remained blinded to the treatment assignment throughout the study.

2.2 Outcomes

The primary endpoints of overall survival (OS) and the secondary endpoints of progression-free survival (PFS), objective response rate (ORR) and safety for the primary analysis populations of ORIENT16—the total, PD-L1 CPS ≥ 5, and CPS < 5 populations—have been reported. The efficacy outcomes for the PD-L1 CPS < 10 and CPS ≥ 10 subgroups (OS and PFS) were evaluated. Additionally, the prespecified exploratory endpoint evaluated the association between the efficacy of anti-PD-1 immunotherapy or platinum-based chemotherapy and PD-L1 expression levels as well as other biomarkers within the immune microenvironment. The efficacy endpoints were assessed by independent reviewers.

2.3 Biomarker Analysis

Formalin-fixed, paraffin-embedded samples from primary or metastatic lesions were evaluated during screening for PD-L1 expression. The evaluation was performed by a central laboratory (Covance, Shanghai, China) using PD-L1 IHC 22C3 pharmDx assay (Agilent Technologies, USA). A scoring system called the combined positive score (CPS) was used, which was obtained by dividing the number of PD-L1-positive tumor cells, lymphocytes, and macrophages by the total number of viable tumor cells, and then multiplying by 100.

Based on the abundant literature on the modulatory effects of the tumor microenvironment, the research team decided on a biomarker panel after further discussion. This panel included T cells (CD4[23], CD8[20]), regulatory T cells (FoxP3[24]), macrophages (CD68[25]), immune escape markers (PD-L1[26]), and Pan-CK. The Akoya OPAL Polaris Seven-Color Automation multiplex immunohistochemistry (mIHC) panels were used for mIF staining following the manufacturer's instructions. The concentration and staining order of the antibodies used in this study were optimized in advance. Primary antibodies raised against CD4 (Cell Signaling Technology, #25229, 1:50), CD8 (Cell Signaling Technology, #85336, 1:100), CD68 (Cell Signaling Technology, #76437, 1:200), FoxP3 (Cell Signaling Technology, #98377, 1:50), and PD-L1 (Cell Signaling Technology, #13684, 1:100), were used. Nucleic acids were stained with DAPI. Tumor parenchyma and stroma were differentiated based on pan-CK staining (Cell Signaling Technology, #4545, 1:250).

The immunofluorescence slides were scanned using the Vectra 3.0 Automated Quantitative Pathology Imaging System (Akoya Biosciences) equipped with a 20 × objective and visualized using Phenochart software. Two experienced pathologists reviewed all samples and excluded inappropriate regions from the analysis. Typical fields of view were selected with minimal overlap between regions and positioned to capture as much tissue as possible. The multispectral images were analyzed using the inForm software package(Akoya Biosciences). The density of various immune cell subsets was measured as the number of positively stained cells per square millimeter (cells/mm²).

2.4 Statistical analyses

Statistical analyses were performed using GraphPad Prism 9 and the IBM SPSS Statistics software (version 26.0). The chi-square test or Independent Samples t-test was performed to compare the baseline characteristics between the two treatment arms. Censoring for overall survival and progression-free survival occurred at the last date of survival and last tumor imaging assessment, respectively. Kaplan-Meier (KM) plots were generated to visualize the corresponding PFS and OS, and the stratified log-rank test was used to compare the treatment arms (sintilimab + chemotherapy vs. placebo + chemotherapy) and CPS score groups (≥ 10 vs. <10). Two-sided 95% confidence intervals (CIs) for the hazard ratios (HRs) were calculated. Subgroup analyses using the stratified Cox proportional hazards model assessed PFS and OS according to CPS scores and baseline characteristics (age, histological type, and metastases), ensuring a minimum sample size of 15 per subgroup. The independent sample t-test and Mann-Whitney U test were used to assess the association between immune cells in tumor microenvironment and treatment efficacy in the exploratory multiplexed immunofluorescence analysis.

3.1 Patients characteristics

From January 3, 2019, to July 20, 2020, 63 patients were screened for eligibility in our center. Of these, 54 were randomly assigned to treatment: 35 in the sintilimab plus chemotherapy group (sintilimab plus platinum-based chemotherapy) and 19 in the placebo plus chemotherapy group (placebo plus platinum-based chemotherapy) (Fig. 1). The baseline characteristics were generally well balanced between the two treatment groups (Table 1). Among 54 patients, 39 (72.2%) had gastric adenocarcinoma (sintilimab plus chemotherapy, 25/35 [71.4%]; placebo plus chemotherapy, 14/19 [73.7%]). Thirty-seven (68.5%) patients had a PD-L1 CPS ≥ 10 (sintilimab plus chemotherapy, 12/35 [34.3%]; placebo plus chemotherapy, 5/19 [26.3%]). Distant lymph nodes (33/54 [61.1%]) and peritoneal metastases (22/54 [40.7%]) were the most common presentations in patients with advanced disease. Of the patients in the immunotherapy group, 28.6% (n = 10/35) discontinued treatment within the first six cycles, compared to 52.6% (n = 10/19) in the chemotherapy group. Disease progression was the main reason for discontinuation (sintilimab plus chemotherapy, 5/35 [14.3%]; placebo plus chemotherapy, 6/19 [31.6%]). 65.7% (n = 23/35) of the patients in the sintilimab plus chemotherapy group, compared to 42.1% (n = 8/19) in the placebo plus chemotherapy group subsequent treatment. Additionally, 14.3% (n = 5/35) and 15.8% (n = 3/19) of the respective groups underwent subsequent gastrectomy.

Table 1

Baseline Characteristics of Study Patients
	Sintilimab + chemotherapy^a (N = 35)	Placebo + chemotherapy (N = 19)	P-value
Age(years)
Median	62	63	0.69
Range	41–74	44–72
Sex, n (%)
Female	9(25.7)	7(36.8)	0.39
Male	26(74.3)	12(63.2)
ECOG performance status, n (%)
0	10(28.6)	8(42.1)	0.31
1	25(71.4)	11(57.9)
Primary tumor location, n (%)
Gastric	35(100.0)	18(94.7)	0.75
Gastric-esophageal junction	0(0.0)	1(5.3)
Histological type, n (%)
Adenocarcinoma	25(71.4)	14(73.7)	0.86
Signet cell carcinoma	10(28.6)	5(26.3)
Lauren's classification, n (%)
Intestinal	6(16.7)	0(0.0)	0.2
Diffuse	4(11.1)	3(15.8)
Mixed	2(5.6)	3(15.8)
Unknown or unclassifiable	24(66.7)	13(68.4)
Previous gastrectomy, n (%)
No	28(80.0)	16(84.2)	0.79
Yes	7(20.0)	3(15.8)
Perioperative chemotherapy, n (%)
No	31(88.6)	17(89.5)	1
Yes	4(11.4)	2(10.5)
Extent of disease, n (%)
Metastatic	35(100.0)	16(84.2)	0.07
Locally advanced	0(0.0)	3(15.8)
Site of metastases, n (%)
Liver	8(22.9)	7(36.8)	NA
Peritoneum	14(40.0)	8(42.1)
Lung	2(5.7)	2(10.5)
Bone	3(8.6)	1(5.3)
Lymph node	22(62.9)	11(57.9)
Other	8(22.9)	6(31.6)
tumor cell PD-L1 expression
CPS < 10	23(65.7)	14(73.7)	0.55
CPS ≥ 10	12(34.3)	5(26.3)
^aChemotherapy: XELOX(Capecitabine plus oxaliplatin) ECOG: Eastern Cooperative Oncology Group; PD-L1: Programmed Death-Ligand 1; CPS: the Combined Proportional Score

3.2 Survival differences between anti-PD-1 therapy and chemotherapy: subgroup analyses and landmark analyses

The efficacy and safety analyses in the present study were in accordance with ORIENT16 observations, and each is indicated with a note in the supplementary materials. A CPS threshold of 10 was used as the randomization stratification factor in our study. Patients with a CPS of 10 or more appeared to benefit significantly more from sintilimab immunotherapy, with an estimated hazard ratio (HRs) of 0.14 (95% CI 0.02–1.01; P < 0.0001) for PFS and 0.19 (95% CI 0.03–1.09; P = 0.0009) (Fig. 2A and Fig. 2B). Conversely, no significant benefits were observed in patients with CPS less than 10 (mPFS, HR 0.66 [0.30–1.48]; P = 0.27; OS, HR 0.66 [0.30–1.48]; p = 0.25) (Fig. 2C and Fig. 2D). Therefore, we performed further analysis of CPS < 10 survival curves using the landmark method (Fig. 3) and found greater disparities in survival between the two groups in the later period after treatment (cut-off value = 300 days) (P = 0.008), with no difference observed in the early period(P = 0.761). Subgroup analyses of progression-free survival and overall survival are shown in Supplementary Figs. 3 and 4.

3.3 Survival analyses of both anti-PD-1 therapy and chemotherapy: predictive role of PD-L1 expression

We conducted an in-depth analysis of the efficacy of different PD-L1 expressions within the anti-PD-1 immunotherapy and platinum-based chemotherapy treatment (Fig. 4). For patients receiving sintilimab, the mPFS was 12.34 months in patinets with CPS of 10 or more and 6.47 months in patients with CPS less than 10 (P = 0.13) (Fig. 4B). Similarly, the mOS also improved in the CPS ≥ 10 group by 9.88 months (23.18 months vs. 13.30 months; HR 0.51 [95% CI: 0.23–1.13]; P = 0.12) (Fig. 4E). Patients with higher PD-L1 expression in immunotherapy showed longer mOS and mPFS, although the difference was not statistically significant.

For patients who received traditional platinum-based chemotherapy alone, there was a trend toward a shorter PFS in patients with CPS of 10 or more compared to patients with CPS less than 10 (3.40 months vs 4.33 months) and the between-group difference has reached borderline statistical significance (p = 0.07) (Fig. 4C). Furthermore, the median overall survival was numerically, though not statistically significantly, reduced in the CPS ≥ 10 group compared to the CPS < 10 group (4.40 months vs. 12.67 months; P = 0.11) (Fig. 4F). This exploratory analysis suggests that patients with high PD-L1 expression may be insensitive to platinum-based chemotherapy.

3.4 Relationships with TME immune cell subtypes and both anti-PD-1 therapy and chemotherapy: multiplex immunofluorescence analyses

To further explore whether the tumor immune microenvironment could predict the treatment response, biopsy samples of all patients collected before treatment were analyzed separately by multiplex immunofluorescence. Patients with no tumor progression within half a year were defined as well-responders, and those with tumor progression were defined as poor-responders. A total of 33 baseline biopsy samples (sintilimab plus chemotherapy group, n = 18; placebo plus chemotherapy group, n = 15) passed quality control and were assessable for the final analysis.

In patients receiving anti-PD-1 immunotherapy, patients in the well-responder group showed higher densities of PD-L1 expression than those in the poor-responder group (P = 0.02). Interestingly, high expression of CD8 + T cells was also positively associated with ICI therapy in our mIF analysis. Compared with patients in the poor-responder group. Tumor-infiltrating T cells had higher CD8 + T cells in patients with a better response (P = 0.04), whereas there were no major differences in CD4 + T cells, CD68 + macrophages, or Foxp3 + Tregs between the well-responder and poor-responder groups, both in the context of tumor and stromal cells (Fig. 5B).

Surprisingly, as shown in Fig. 5D, in patients receiving platinum-based chemotherapy alone, the number of CD4 + T cells was significantly higher in patients with poor chemotherapeutic efficacy (P = 0.03). Similarly, the expression levels of PD-L1 in the poor-responder group were also higher than those in the well-responder group (P = 0.07), consistent with our results of clinical analysis, although not reaching statistical significance limited by the small sample size. However, no apparent differences were observed in the intensity of CD8, CD68, and FoxP3 staining between the two responder groups in the context of chemotherapy.

In recent years, immunotherapy for advanced G/GEJ cancer has attracted widespread attention. Prospective clinical trials, such as CheckMate 649[7], Orient 16[9], and RATIONALE 305[27] have demonstrated an effective clinical response in patients with advanced HER2-negative gastric cancer. Our results, consistent with the results of the ORIENT16 study, further demonstrate the efficacy and safety of adding anti-PD-1 sintilimab to platinum-based chemotherapy, which resulted in a statistically significant and clinically meaningful improvement in both progression-free survival and overall survival compared to chemotherapy alone, not only in the overall population but also in patients with strong PD-L1 expression.

However, the efficacy of anti-PD-1 treatment in tumors with low PD-L1 expression remains unclear. The results of patients with a CPS less than 5 have been shown to have a non-significant survival benefit in the ORIENT16 study. The level of PD-L1 expression was reclassified and two PD-L1 subgroups (CPS < 10 and CPS ≥ 10) were identified in our study, finding that for patients with CPS less than 10, no significant difference was observed between the anti-PD-1 immunotherapy plus chemotherapy group and placebo plus chemotherapy group (P = 0.761). This finding is further supported by Zhao et al.'s study[28], which demonstrated no significant differences in overall survival and progression-free survival between ICI-chemotherapy combinations and chemotherapy alone in the CheckMate-649 PD-L1 CPS 1–4 and KEYNOTE-062 PD-L1 CPS 1–9 subgroups (P ≥ 0.05). Interestingly, our landmark analysis demonstrated a survival advantage in patients with low PD-L1–expressing tumors approximately 300 days after treatment offered by the addition of anti-PD-1 blockade to conventional chemotherapy. This long-term survival discrepancy is likely attributable to the tailing effect of anti-PD-L1 treatment. Compared to traditional chemotherapy, which kills tumor cells directly, immunotherapy can be targeted to initiate immune-tumor interactions and amplify the immune effect. In addition, sustained antigen release shapes memory T cells and is responsible for long-term immunity. Gauci et al.[29] conducted a long-term analysis of solid tumor patients responding to anti-PD-1/PD-L1 therapy and found that 48/76 patients developed an objective response at 3 months regardless of PD-L1 expression. Similarly, the tailing effect, which depends on the immune status of an individual and tumor heterogeneity, was also embodied in long-term follow-up data of some clinical trials such as CheckMate153 of NSCLC[30] and RATIONALE-305[31] of advanced GC, especially striking in patients with high PD-L1 expression. This conclusion has also been validated in patients with CPS < 10 in our study and a time point of 300 days was proposed. Moreover, consolidation chemotherapy was initiated after six cycles of combination therapy in both groups and continued for up to a maximum of 2 years. Therefore, we proposed an alternative hypothesis that applications of immunotherapy might increase the sensitivity of the tumor to subsequent chemotherapy. Exposure to immune checkpoint inhibitors may elicit the antitumor activity of chemotherapy, which can lead to a high response rate[32]. A retrospective CLARITY study[33] also supported that for NSCLC patients who progressed to previous ICIs administered as first- or second-line therapy, salvage chemotherapy could yield a survival-favorable response. However, the underlying mechanisms and impact factors need to be investigated. Taken together, these findings could provide recommendations for clinicians in selecting first-line treatments for patients with CPS < 10, based on their clinical benefits. The combination therapeutic effect was restricted for early treatment owing to the involvement of immunotherapy in patients with a limited life expectancy. For most patients, immunotherapy should be initiated as early as possible in the treatment course and could be continued as maintenance therapy after 4–6 cycles of complete routine first-line therapy, and disease control (CR/PR/SD) was reached in order to increase the survival benefit.

In addition, we found that only a subset of patients could benefit from anti-PD-1 immunotherapy or platinum-based chemotherapy due to the high heterogeneity of gastric cancer (GC). For patients receiving anti-PD-1 immunotherapy, high PD-L1 expression was correlated with long PFS and OS which has been widely recognized in clinical trials such as KEYNOTE-061[34] and KEYNOTE-062[35]. This notion was further supported by PD-L1 staining of mIF analysis. While our study suggests that the expression of PD-L1 could predict outcomes in advanced G/GEJ cancer, PD-L1 expression could not be a single indicator for predicting the efficacy of immunotherapy.

The potential immune microenvironment[36] on the prognostic impact of ICIs on gastric cancer, such as interferon (IFN)[37], neutrophil-to-lymphocyte ratio (NLR)[38], and specific genes like ARID1A[39], POLE or POLD1[40], and TP53[41], have attracted significant attention in recent year. Interestingly, our mIF analysis for the immune TME showed that CD8 + T cells, which act as the key effector of anti-tumor immunity, were more significantly enriched in well responders compared with poor responders in patients with advanced gastric cancer. However, the role of CD8 + T cells in the immunotherapy response remains unclear, which may be due to the functional heterogeneity of CD8 + T cell subtypes on one hand. Tc1 cells, which possess typical CD8 + T cell-related cytotoxic signatures, have been shown to promote the production of perforin, granzymes B and interferon(IFN)-γ[42] in order to kill tumor cells. Tc2[43] and Tc22[44] cells expressing granzyme B are highly cytolytic and demonstrate robust cytotoxic abilities. A special subtype of CD8 + tissue-resident memory T (TRM) cells, marked by CD103 (ITGAE) expression, was also been found to positively correlated with patient survival time[45]. Conversely, the CD8 + Tc9 subtype[46] has been shown to produce relatively little IFN-γ and granzyme B, and is thought to promote disease progression, as well as the Tc17 subtype[47–49]. In our mIF analysis, the prognosis of patients with high CD8 + T expression was significantly better than that of patients with low CD8 + T expression, suggesting that CD8 Tc subsets with strong cytotoxic functions such as Tc1s, Tc2s, or Tc22s account for the majority of the TME in our gastric cancer samples. Regrettably, no trials included in this analysis provided CD8 + T cell subset analysis, and the underlying predictive mechanism remains unclear and requires further investigation.

On the other hand, some researchers have uncovered that a high degree of CD8 + T cell infiltration could increase the expression of immune checkpoint receptors such as PD-1 and CTLA-4 and sensitize tumors to ICI, which may be another reason for the good immunotherapy response of CD8 + T cells. Chiaravalli et al.[50] demonstrated that a high number of CD8 + TILs was associated with a high level of PD-L1 mRNA and represented a favourable prognostic factor. Therefore, immune treatment based on CD8 + T cells could be a promising strategy to potentiate the efficacy of anti-PD‐1 immunotherapy. The immune checkpoint receptor CTLA-4 is expressed on CD8 + effector T cells, and CTLA-4 blockade enhances the response of CD8 + T cells in the TME[51]. Currently, the combination of anti-PD-1 and anti-CTLA-4 mAb (such as nivolumab plus ipilimumab) has been approved for the treatment of melanoma[52], non-small cell lung cancer[53], hepatocellular carcinoma[54], mismatch repair deficient colorectal cancer[55], while lack of sufficient evidence on advanced gastric cancer. The COMPASSION-04 clinical trial[56], reported by the 2024 American Association for Cancer Research (AACR), showed promising clinical activity and manageable safety of a bispecific antibody targeting PD-1 and CTLA-4 as first-line treatment in patients with G/GEJ adenocarcinoma, regardless of PD-L1 expression. Furthermore, several clinical trials of anti-CTLA immunotherapy for gastric cancer are still underway. Taken together, our results demonstrate that CD8 + T cells play a pivotal role in predicting ICI treatment responses. A combination of PD-1 and CTLA-4 blockade could have synergistic effects by potentiating the antitumor activity and provide more therapeutic options for patients with low PD-L1 expression, and, hopefully, to be a new first-line treatment option for gastric or GEJ adenocarcinoma.

Many studies have reported potential biomarkers of GC for ICI therapy. Whether immune cells in the TME are associated with traditional platinum-based chemotherapy remains to be elucidated. Generally, chemotherapeutic drugs can specifically induce a cellular immune response, which results in tumor cell death or stimulates immune effector molecules to relieve the suppressed immune response. Therefore, tumor immune status can be used to evaluate the effects of chemotherapy. Interestingly, we observed that those with a CPS of 10 or more were more insensitive to chemotherapy and had significantly shorter PFS than patients with a CPS of less than 10. To further validate the association between PD-L1 expression and chemotherapy efficacy, we also analyzed the microenvironmental components using multiple immunohistochemical analyses and found that high PD-L1 expression may be more resistant to chemotherapy. Lou et al.[57] used intracellular PD-L1 as an RNA-binding protein that enhances the efficacy of chemotherapy by inhibiting DNA damage response and repair. Another study by Frank Sinicrope[58] examined the potential role of tumor cell-intrinsic PD-L1 in regulating chemosensitivity in human CRC cells and found that the deletion of PD-L1 could suppress BH3-only BIM and BIK proteins, causing chemoresistance and survival reduction. In contrast to the ability of PD-L1 mentioned above, knockdown of PD-L1 has been shown to sensitize breast cancer[59], small-cell lung cancer[60], and lymphoma cells[61] to chemotherapy-induced apoptosis. These reported differences may be attributed to the functional diversity of PD-L1 and tumor cell type specificity. In GC, the team of Shin K[62] evaluated the correlation among serum-derived exoPD-L1, plasma sPD-L1, immune-related markers, and circulating immune cells. The low sPD-L1 group showed significantly better overall survival (OS) and progression-free survival (PFS) than the high sPD-L1 group, considering pretreatment plasma-derived sPD-L1 level as a prognostic marker for patients receiving cytotoxic chemotherapy. In the tumor microenvironment, low PD-L1 expression also predicted sensitivity in our study. However, few studies in the prior literature have reported the role of PD-L1 in TME against traditional chemotherapy and the underlying mechanisms remain to be further explored.

In addition, we found significantly higher expression of CD4 + T cells in the poor-responder group than in the well-responder group, supporting that the relatively higher expression of CD4 + T cells in tumor tissues limits patients from benefiting from chemotherapy. CD4 + T cells could be used as promising markers for predicting the efficacy of chemotherapy. Immunohistochemistry (IHC) of the T-cell marker CD4 + was performed on GC patients who received XELOX therapy to evaluate tumor-infiltrating lymphocytes (TILs) at Fudan University[63]. As a result, from patients in the XELOX non-sensitive group(XNSG), we observed that the percentage of CD4 positive cells was significantly higher than that in the XELOX sensitive group(XSG)(54.2% and 2.9%, respectively) (P < 0.05). Similarly, another study on esophageal cancer (EC)[64] showed that regulatory T cells (Tregs), a subset of CD4 + T cells, play a pivotal role in the prognosis of non-operative chemoradiotherapy. Patients with a high proportion of regulatory T cells before chemoradiotherapy had a significantly worse OS than patients with a low proportion of regulatory T cells, which may be partially related to the expression of inhibitory receptors (such as IL-10) and depletion of T cells. Consequently, platinum-based chemotherapy may also be a surprising option for patients with high CD4 + proportion. Despite the close association between CD4 + T cell density and chemotherapy response, our study had notable limitations. Further validation in a larger sample is needed, and the mechanism of chemoresistance in CD4 + Ts is far from fully understood.

LIMITATIONS

Despite its strengths and implications for future research, our study has some limitations. First and most importantly, combined with results from the ORIENT16 clinical trial, the subgroup analyses regarding PD-L1 expression should be stratified based on CPS 0–5, 5–10 or CPS ≥ 10 for more precision treatment. There were a limited number of data and also a limited number of patients to allow meaningful analyses of this subgroup. Additionally, although we observed some significant tendency toward treatment response in patients with different components of the tumor microenvironment, the trend is still require further evaluation in larger patient populations. Finally, we only performed a quantitative analysis of each biomarker separately. Further studies, including colocalization analyses and spatial transcriptomics, are essential, with the potential to provide additional biological insights into the TME in GC and present an opportunity to improve patient selection for novel diagnostics and therapeutics.

In conclusion, we identified the predictive value of PD-L1 in both anti-PD-1 immunotherapy and platinum-based chemotherapy by further analyzing the survival curves stratified by PD-L1 expression and an interesting phenomenon was discovered by landmark statistical method that clear differences between anti-PD-1 immunotherapy and chemotherapy would display around 300 days after first-day treatment for patients with CPS < 10. Multiplexed immunofluorescence exploration of the tumor microenvironment showed that immune cells such as CD4 and CD8 were closely correlated with therapy efficacy and would offer critical insights into the complex and heterogeneous immune landscape associated with immunotherapy and chemotherapy treatment response.

G/GEJ Cancer: Gastric and Gastroesophageal Junction Cancer

ICIs: Immune Checkpoint Inhibitors

PD-1: Programmed Death-1

PD-L1: Programmed Death-ligand 1

CPS: Combined Positive Score

HER2: Human Epidermal Growth Factor Receptor 2

NK cell: Natural Killer cell

mIF: multiplex Immunofluorescence

RECIST guidelines: Response Evaluation Criteria in Solid Tumors guidelines

PS score: Performance Status score

ECOG: the Eastern Cooperative Oncology Group

OS: Overall Survival

PFS: Progression-free Survival

ORR: Objective Response Rate

CR: Complete Response

PR: Partial Response

SD:Stable Disease

95% CIs: 95% Confidence Intervals

HRs: Hazard Ratios

GC: Gastric Cancer

NSCLC: Non-Small Cell Lung Cancer

EC: Esophageal Cancer

IFN: Interferon

NLR: Neutrophil-to-Lymphocyte Ratio

TRM cells: Tissue-resident Memory T cells

TILs:Tumor-Infiltrating Lymphocytes

TME:Tumor Microenvironment

AACR: American Association for Cancer Research

XNSG: XELOX non-sensitive group

XSG: XELOX sensitive group

Funding: None

Author Contributions: All authors contributed to the conception and design of this study. The ideas for this review have been provided by H.J. The clinical data was analyzed by H.W. and W.S., and the multiplex immunofluorescence was performed by HW and QL. The first draft of the manuscript was written by H.W. and W.S., and H.J. and Y.D. critically revised the manuscript. All authors commented on the previous versions of the manuscript and approved the final manuscript.

Conflicts of Interest: The authors declare that they have no conflict of interest.

Data Access Statement: Research data supporting this publication are available from the ClinicalTrials.gov(NCT03745170)(https://clinicaltrials.gov/ct2/show/NCT03745170?term=NCT03745170&draw=2&rank=1)

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49.
Pennathur A, Gibson MK, Jobe BA, Luketich JD. Oesophageal carcinoma. Lancet. 2013;381(9864):400–12.
Qiu H, Cao S, Xu R. Cancer incidence, mortality, and burden in China: a time-trend analysis and comparison with the United States and United Kingdom based on the global epidemiological data released in 2020. Cancer Commun (Lond). 2021;41(10):1037–48.
Wilke H, Muro K, Van Cutsem E, Oh SC, Bodoky G, Shimada Y, et al. Ramucirumab plus paclitaxel versus placebo plus paclitaxel in patients with previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (RAINBOW): a double-blind, randomised phase 3 trial. Lancet Oncol. 2014;15(11):1224–35.
Fuchs CS, Tomasek J, Yong CJ, Dumitru F, Passalacqua R, Goswami C, et al. Ramucirumab monotherapy for previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (REGARD): an international, randomised, multicentre, placebo-controlled, phase 3 trial. Lancet. 2014;383(9911):31–9.
Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 2014;513(7517):202–9.
Janjigian YY, Shitara K, Moehler M, Garrido M, Salman P, Shen L, 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(10294):27–40.
Shiravand Y, Khodadadi F, Kashani SMA, Hosseini-Fard SR, Hosseini S, Sadeghirad H, et al. Immune Checkpoint Inhibitors in Cancer Therapy. Curr Oncol. 2022;29(5):3044–60.
Xu J, Jiang H, Pan Y, Gu K, Cang S, Han L, et al. Sintilimab Plus Chemotherapy for Unresectable Gastric or Gastroesophageal Junction Cancer: The ORIENT-16 Randomized Clinical Trial. JAMA. 2023;330(21):2064–74.
Smyth EC, Verheij M, Allum W, Cunningham D, Cervantes A, Arnold D. Gastric cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2016;27(suppl 5):v38–49.
Wang FH, Zhang XT, Li YF, Tang L, Qu XJ, Ying JE, 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(8):747–95.
Japanese gastric cancer treatment guidelines 2018 (5th edition). Gastric Cancer. 2021;24(1):1–21.
Catenacci DVT, Tebbutt NC, Davidenko I, Murad AM, Al-Batran SE, Ilson DH, et al. Rilotumumab plus epirubicin, cisplatin, and capecitabine as first-line therapy in advanced MET-positive gastric or gastro-oesophageal junction cancer (RILOMET-1): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2017;18(11):1467–82.
Lordick F, Kang YK, Chung HC, Salman P, Oh SC, Bodoky G, et al. Capecitabine and cisplatin with or without cetuximab for patients with previously untreated advanced gastric cancer (EXPAND): a randomised, open-label phase 3 trial. Lancet Oncol. 2013;14(6):490–9.
Shah MA, Bang YJ, Lordick F, Alsina M, Chen M, Hack SP, et al. Effect of Fluorouracil, Leucovorin, and Oxaliplatin With or Without Onartuzumab in HER2-Negative, MET-Positive Gastroesophageal Adenocarcinoma: The METGastric Randomized Clinical Trial. JAMA Oncol. 2017;3(5):620–7.
Wang TT, Zhao YL, Peng LS, Chen N, Chen W, Lv YP, et al. Tumour-activated neutrophils in gastric cancer foster immune suppression and disease progression through GM-CSF-PD-L1 pathway. Gut. 2017;66(11):1900–11.
Huang YK, Wang M, Sun Y, Di Costanzo N, Mitchell C, Achuthan A, et al. Macrophage spatial heterogeneity in gastric cancer defined by multiplex immunohistochemistry. Nat Commun. 2019;10(1):3928.
Cabrita R, Lauss M, Sanna A, Donia M, Skaarup Larsen M, Mitra S, et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature. 2020;577(7791):561–5.
Hedrick CC, Malanchi I. Neutrophils in cancer: heterogeneous and multifaceted. Nat Rev Immunol. 2022;22(3):173–87.
Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515(7528):568–71.
Hsu J, Hodgins JJ, Marathe M, Nicolai CJ, Bourgeois-Daigneault MC, Trevino TN, et al. Contribution of NK cells to immunotherapy mediated by PD-1/PD-L1 blockade. J Clin Invest. 2018;128(10):4654–68.
Ruiz de Galarreta M, Bresnahan E, Molina-Sánchez P, Lindblad KE, Maier B, Sia D, et al. β-Catenin Activation Promotes Immune Escape and Resistance to Anti-PD-1 Therapy in Hepatocellular Carcinoma. Cancer Discov. 2019;9(8):1124–41.
Rosenberg JE, Hoffman-Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A, et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet. 2016;387(10031):1909–20.
Kamada T, Togashi Y, Tay C, Ha D, Sasaki A, Nakamura Y, et al. PD-1(+) regulatory T cells amplified by PD-1 blockade promote hyperprogression of cancer. Proc Natl Acad Sci U S A. 2019;116(20):9999–10008.
Hensler M, Kasikova L, Fiser K, Rakova J, Skapa P, Laco J et al. M2-like macrophages dictate clinically relevant immunosuppression in metastatic ovarian cancer. J Immunother Cancer. 2020;8(2).
Kim ST, Cristescu R, Bass AJ, Kim KM, Odegaard JI, Kim K, et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med. 2018;24(9):1449–58.
Markus H, Moehler KK, Arkenau H-T, Oh D-Y. Rationale 305: Phase 3 study of tislelizumab plus chemotherapy vs placebo plus chemotherapy as first-line treatment (1L) of advanced gastric or gastroesophageal junction adenocarcinoma (GC/GEJC). 2023 ASCO GIAbstract 286. 2023.
Zhao JJ, Yap DWT, Chan YH, Tan BKJ, Teo CB, Syn NL, et al. Low Programmed Death-Ligand 1-Expressing Subgroup Outcomes of First-Line Immune Checkpoint Inhibitors in Gastric or Esophageal Adenocarcinoma. J Clin Oncol. 2022;40(4):392–402.
Gauci ML, Lanoy E, Champiat S, Caramella C, Ammari S, Aspeslagh S, et al. Long-Term Survival in Patients Responding to Anti-PD-1/PD-L1 Therapy and Disease Outcome upon Treatment Discontinuation. Clin Cancer Res. 2019;25(3):946–56.
Waterhouse DM, Garon EB, Chandler J, McCleod M, Hussein M, Jotte R, et al. Continuous Versus 1-Year Fixed-Duration Nivolumab in Previously Treated Advanced Non-Small-Cell Lung Cancer: CheckMate 153. J Clin Oncol. 2020;38(33):3863–73.
Qiu MZ, Oh DY, Kato K, Arkenau T, Tabernero J, Correa MC, et al. Tislelizumab plus chemotherapy versus placebo plus chemotherapy as first line treatment for advanced gastric or gastro-oesophageal junction adenocarcinoma: RATIONALE-305 randomised, double blind, phase 3 trial. BMJ. 2024;385:e078876.
Emens LA, Middleton G. The interplay of immunotherapy and chemotherapy: harnessing potential synergies. Cancer Immunol Res. 2015;3(5):436–43.
Bersanelli M, Buti S, Giannarelli D, Leonetti A, Cortellini A, Russo GL, et al. Chemotherapy in non-small cell lung cancer patients after prior immunotherapy: The multicenter retrospective CLARITY study. Lung Cancer. 2020;150:123–31.
Shitara K, Özgüroğlu M, Bang YJ, Di Bartolomeo M, Mandalà M, Ryu MH, et al. Pembrolizumab versus paclitaxel for previously treated, advanced gastric or gastro-oesophageal junction cancer (KEYNOTE-061): a randomised, open-label, controlled, phase 3 trial. Lancet. 2018;392(10142):123–33.
Shitara K, Van Cutsem E, Bang YJ, Fuchs C, Wyrwicz L, Lee KW, 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(10):1571–80.
Wang J, Ma X, Ma Z, Ma Y, Wang J, Cao B. Research Progress of Biomarkers for Immune Checkpoint Inhibitors on Digestive System Cancers. Front Immunol. 2022;13:810539.
Fehrenbacher L, Spira A, Ballinger M, Kowanetz M, Vansteenkiste J, Mazieres J, et al. Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicentre, open-label, phase 2 randomised controlled trial. Lancet. 2016;387(10030):1837–46.
Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A, et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst. 2014;106(6):dju124.
Hu G, Tu W, Yang L, Peng G, Yang L. ARID1A deficiency and immune checkpoint blockade therapy: From mechanisms to clinical application. Cancer Lett. 2020;473:148–55.
Wang F, Zhao Q, Wang YN, Jin Y, He MM, Liu ZX, et al. Evaluation of POLE and POLD1 Mutations as Biomarkers for Immunotherapy Outcomes Across Multiple Cancer Types. JAMA Oncol. 2019;5(10):1504–6.
Zhong J, Pan R, Gao M, Mo Y, Peng X, Liang G, et al. Identification and validation of a T cell marker gene-based signature to predict prognosis and immunotherapy response in gastric cancer. Sci Rep. 2023;13(1):21357.
Yang Y, Ochando JC, Bromberg JS, Ding Y. Identification of a distant T-bet enhancer responsive to IL-12/Stat4 and IFNgamma/Stat1 signals. Blood. 2007;110(7):2494–500.
Kemp RA, Ronchese F. Tumor-specific Tc1, but not Tc2, cells deliver protective antitumor immunity. J Immunol. 2001;167(11):6497–502.
Zhang S, Fujita H, Mitsui H, Yanofsky VR, Fuentes-Duculan J, Pettersen JS, et al. Increased Tc22 and Treg/CD8 ratio contribute to aggressive growth of transplant associated squamous cell carcinoma. PLoS ONE. 2013;8(5):e62154.
Banchereau R, Chitre AS, Scherl A, Wu TD, Patil NS, de Almeida P et al. Intratumoral CD103 + CD8 + T cells predict response to PD-L1 blockade. J Immunother Cancer. 2021;9(4).
Visekruna A, Ritter J, Scholz T, Campos L, Guralnik A, Poncette L, et al. Tc9 cells, a new subset of CD8(+) T cells, support Th2-mediated airway inflammation. Eur J Immunol. 2013;43(3):606–18.
Kryczek I, Wei S, Zou L, Altuwaijri S, Szeliga W, Kolls J, et al. Cutting edge: Th17 and regulatory T cell dynamics and the regulation by IL-2 in the tumor microenvironment. J Immunol. 2007;178(11):6730–3.
Kuang DM, Peng C, Zhao Q, Wu Y, Zhu LY, Wang J, et al. Tumor-activated monocytes promote expansion of IL-17-producing CD8 + T cells in hepatocellular carcinoma patients. J Immunol. 2010;185(3):1544–9.
Zhuang Y, Peng LS, Zhao YL, Shi Y, Mao XH, Chen W, et al. CD8(+) T cells that produce interleukin-17 regulate myeloid-derived suppressor cells and are associated with survival time of patients with gastric cancer. Gastroenterology. 2012;143(4):951–e628.
Chiaravalli AM, Feltri M, Bertolini V, Bagnoli E, Furlan D, Cerutti R, et al. Intratumour T cells, their activation status and survival in gastric carcinomas characterised for microsatellite instability and Epstein-Barr virus infection. Virchows Arch. 2006;448(3):344–53.
Parry RV, Chemnitz JM, Frauwirth KA, Lanfranco AR, Braunstein I, Kobayashi SV, et al. CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Mol Cell Biol. 2005;25(21):9543–53.
Hodi FS, Chiarion-Sileni V, Gonzalez R, Grob JJ, Rutkowski P, Cowey CL, et al. Nivolumab plus ipilimumab or nivolumab alone versus ipilimumab alone in advanced melanoma (CheckMate 067): 4-year outcomes of a multicentre, randomised, phase 3 trial. Lancet Oncol. 2018;19(11):1480–92.
Reck M, Schenker M, Lee KH, Provencio M, Nishio M, Lesniewski-Kmak K, et al. Nivolumab plus ipilimumab versus chemotherapy as first-line treatment in advanced non-small-cell lung cancer with high tumour mutational burden: patient-reported outcomes results from the randomised, open-label, phase III CheckMate 227 trial. Eur J Cancer. 2019;116:137–47.
Yau T, Kang YK, Kim TY, El-Khoueiry AB, Santoro A, Sangro B, et al. Efficacy and Safety of Nivolumab Plus Ipilimumab in Patients With Advanced Hepatocellular Carcinoma Previously Treated With Sorafenib: The CheckMate 040 Randomized Clinical Trial. JAMA Oncol. 2020;6(11):e204564.
Overman MJ, McDermott R, Leach JL, Lonardi S, Lenz HJ, Morse MA, et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study. Lancet Oncol. 2017;18(9):1182–91.
Gao X, Ji K, Jia Y, Shan F, Chen Y, Xu N, et al. Cadonilimab with chemotherapy in HER2-negative gastric or gastroesophageal junction adenocarcinoma: the phase 1b/2 COMPASSION-04 trial. Nat Med. 2024;30(7):1943–51.
Tu X, Qin B, Zhang Y, Zhang C, Kahila M, Nowsheen S, et al. PD-L1 (B7-H1) Competes with the RNA Exosome to Regulate the DNA Damage Response and Can Be Targeted to Sensitize to Radiation or Chemotherapy. Mol Cell. 2019;74(6):1215–e264.
Feng D, Qin B, Pal K, Sun L, Dutta S, Dong H, et al. BRAF(V600E)-induced, tumor intrinsic PD-L1 can regulate chemotherapy-induced apoptosis in human colon cancer cells and in tumor xenografts. Oncogene. 2019;38(41):6752–66.
Ghebeh H, Lehe C, Barhoush E, Al-Romaih K, Tulbah A, Al-Alwan M, et al. Doxorubicin downregulates cell surface B7-H1 expression and upregulates its nuclear expression in breast cancer cells: role of B7-H1 as an anti-apoptotic molecule. Breast Cancer Res. 2010;12(4):R48.
Yan F, Pang J, Peng Y, Molina JR, Yang P, Liu S. Elevated Cellular PD1/PD-L1 Expression Confers Acquired Resistance to Cisplatin in Small Cell Lung Cancer Cells. PLoS ONE. 2016;11(9):e0162925.
Liu J, Quan L, Zhang C, Liu A, Tong D, Wang J. Over-activated PD-1/PD-L1 axis facilitates the chemoresistance of diffuse large B-cell lymphoma cells to the CHOP regimen. Oncol Lett. 2018;15(3):3321–8.
Shin K, Kim J, Park SJ, Lee MA, Park JM, Choi MG, et al. Prognostic value of soluble PD-L1 and exosomal PD-L1 in advanced gastric cancer patients receiving systemic chemotherapy. Sci Rep. 2023;13(1):6952.
Li Y, Xu C, Wang B, Xu F, Ma F, Qu Y, et al. Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals new therapeutic strategies. Nat Commun. 2022;13(1):5723.
Lan F, Xu B, Li J. A low proportion of regulatory T cells before chemoradiotherapy predicts better overall survival in esophageal cancer. Ann Palliat Med. 2021;10(2):2195–202.

No competing interests reported.

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The Immune Signatures Predict Gastric/Gastroesophageal Junction Cancer Response to First-line Anti-PD-1 Blockade or Chemotherapy: Clinical and Multiplex Immunofluorescence Analysis

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

INTRODUCTION

METHODS

2.1 Study Design and Participants

2.2 Outcomes

2.3 Biomarker Analysis

2.4 Statistical analyses

RESULTS

3.1 Patients characteristics

3.2 Survival differences between anti-PD-1 therapy and chemotherapy: subgroup analyses and landmark analyses

3.3 Survival analyses of both anti-PD-1 therapy and chemotherapy: predictive role of PD-L1 expression

DISCUSSION

LIMITATIONS

CONCLUSIONS

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1