Computational Image Analysis of T-Cell Infiltrates in Resectable Gastric Cancer: Association with Survival and Molecular Subtypes

The tumor immune composition of mismatch repair deficient and Epstein-Barr virus-positive gastric cancer: A systematic review

BACKGROUND

Gastric cancer (GC), known for its unfavorable prognosis, has been classified in four distinct molecular subtypes. These subtypes not only exhibit differences in their genome and transcriptome but also in the composition of their tumor immune microenvironment. The microsatellite instable (MSI) and Epstein-Barr virus (EBV) positive GC subtypes show clear clinical benefits from immune checkpoint blockade, likely due to a neoantigen-driven and virus-driven antitumor immune response and high expression of immune checkpoint molecule PD-L1. However, even within these subtypes response to checkpoint inhibition is variable, which is potentially related to heterogeneity in the tumor immune microenvironment (TIME) and expression of co-inhibitory molecules. We conducted a systematic review to outline the current knowledge about the immunological features on the TIME of MSI and EBV + GCs.

METHODS

A systematic search was performed in PubMed, EMBASE and Cochrane Library. All articles from the year 1990 and onwards addressing immune features of gastric adenocarcinoma were reviewed and included based on predefined in- and exclusion criteria.

RESULTS

In total 5962 records were screened, of which 139 were included that reported immunological data on molecular GC subtypes. MSI and EBV + GCs were reported to have a more inflamed TIME compared to non-MSI and EBV- GC subtypes. Compared to microsatellite stable (MSS) tumors, MSI tumors were characterized by higher numbers of CD8 + and FoxP3 + T cells, and tumor infiltrating pro- and anti-inflammatory macrophages. HLA-deficiency was most common in MSI tumors compared to other molecular GC subtypes and associated with lower T and B cell infiltrates compared to HLA-proficient tumors. EBV + was associated with a high number of CD8 + T cells, Tregs, NK cells and macrophages. Expression of PD-L1, CTLA-4, Granzyme A and B, Perforin and interferon-gamma was enriched in EBV + tumors. Overall, MSI tumors harbored a more heterogeneous TIME in terms of immune cell composition and immune checkpoints compared to the EBV + tumors.

DISCUSSION AND CONCLUSION

MSI and EBV + GCs are highly Handbook for Conducting a Literature-Based Health Assessment Using OHAT Approach for Systematic Review and Evidence Integration.; 2019pro-inflammatory immune cell populations. Although studies on the direct comparison of EBV + and MSI tumors are limited, EBV + tumors show less intra-subgroup heterogeneity compared to MSI tumors. More studies are needed to identify how Intra-subgroup heterogeneity impacts response to immunotherapy efficacy.

First-line camrelizumab (a PD-1 inhibitor) plus apatinib (an VEGFR-2 inhibitor) and chemotherapy for advanced gastric cancer (SPACE): a phase 1 study

Patients with advanced gastric cancer typically face a grim prognosis. This phase 1a (dose escalation) and phase 1b (dose expansion) study investigated safety and efficacy of first-line camrelizumab plus apatinib and chemotherapy for advanced gastric or gastroesophageal junction adenocarcinoma. The primary endpoints included maximum tolerated dose (MTD) in phase 1a and objective response rate (ORR) across phase 1a and 1b. Phase 1a tested three dose regimens of camrelizumab, apatinib, oxaliplatin, and S-1. Dose regimen 1: camrelizumab 200 mg on day 1, apatinib 250 mg every other day, oxaliplatin 100 mg/m² on day 1, and S-1 40 mg twice a day on days 1-14. Dose regimen 2: same as dose regimen 1, but oxaliplatin 130 mg/m². Dose regimen 3: same as dose regimen 2, but apatinib 250 mg daily. Thirty-four patients were included (9 in phase 1a, 25 in phase 1b). No dose-limiting toxicities occurred so no MTD was identified. Dose 3 was set for the recommended phase 2 doses and administered in phase 1b. The confirmed ORR was 76.5% (95% CI 58.8-89.3). The median progression-free survival was 8.4 months (95% CI 5.9-not evaluable [NE]), and the median overall survival (OS) was not mature (11.6-NE). Ten patients underwent surgery after treatment and the multidisciplinary team evaluation. Among 24 patients without surgery, the median OS was 19.6 months (7.8-NE). Eighteen patients (52.9%) developed grade ≥ 3 treatment-emergent adverse events. Camrelizumab plus apatinib and chemotherapy showed favorable clinical outcomes and manageable safety for untreated advanced gastric cancer (ChiCTR2000034109).

Artificial Intelligence-Enabled Gastric Cancer Interpretations: Are We There yet?

The integration of digital pathology and artificial intelligence (AI) is revolutionizing pathology by providing pathologists with new tools to improve workflow, enhance diagnostic accuracy, and undertake novel discovery. The capability of AI to recognize patterns and features in digital images beyond human perception is particularly valuable, thereby providing additional information for prognostic and predictive purposes. AI-based tools diagnose gastric carcinoma in digital images, detect gastric carcinoma metastases in lymph nodes, automate Ki-67 scoring in gastric neuroendocrine tumors, and quantify tumor-infiltrating lymphocytes. This article provides an overview of all of these applications of AI pertaining to gastric cancer.

Prognostic Value of T-Cell Density in the Tumor Center and Outer Margins in Gastric Cancer

Tumor-infiltrating lymphocytes are associated with the survival of gastric cancer patients. T-cell densities in the tumor and its periphery were previously identified as prognostic T-cell markers for resectable gastric cancer. Immunohistochemistry for 5 T-cell markers, CD3, CD45RO, CD8, FOXP3, and granzyme B was performed on serial sections of N = 251 surgical resection specimens of patients treated with surgery only in the D1/D2 trial. Positive T cells were digitally quantified into tiles of 0.25 mm2 across 3 regions: the tumor center (TC), the inner invasive margin, and the outer invasive margin (OIM). A classification and regression tree model was employed to identify the optimal combination of median T-cell densities per region with cancer-specific survival (CSS) as the outcome. All statistical tests were 2-sided. CD8OIM was identified as the most dominant prognostic factor, followed by FOXP3TC, resulting in a decision tree containing 3 prognostically distinct subgroups with high (Hi) or low (Lo) density of the markers: CD8OIMHi, CD8OIMLo/FOXP3TCHi, and CD8OIMLo/FOXP3TCLo. In a multivariable Cox regression analysis, which included pathological T and N stages, Lauren histologic types, EBV status, microsatellite instability, and type of surgery, the immune subgroups were independent predictors for CSS. CSS was lower for CD8OIMLo/FOXP3TCHi (HR: 5.02; 95% CI: 2.03-12.42) and for CD8OIMLo/FOXP3TCLo (HR: 7.99; 95% CI: 3.22-19.86), compared with CD8OIMHi (P < .0001). The location and density of both CD8+ and FOXP3+ T cells in resectable gastric cancer are independently associated with survival. The combination of CD8OIM and FOXP3TC T-cell densities is a promising stratification factor that should be validated in independent studies.

Epigenetic Modification-Associated Molecular Classification of Gastric Cancer

Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric cancer (GC) to identify signature genes that accurately predict prognosis and the efficacy of immunotherapy. Least absolute shrinkage and selection operator and multivariate Cox regression analysis were conducted to develop an epigenetic modification-associated molecular classification. We investigated the significance of PIP4P2, an independent prognostic factor of the classification system, in predicting the prognosis and immunotherapy efficacy of patients with GC. The epigenetic modification-associated molecular classification was highly associated with the clinicopathological characteristics of patients and the existing classification of GC. PIP4P2 was highly expressed in GC tissue and tumor-associated macrophages. High PIP4P2 expression in GC tissue-induced tumor progression by activating PI3K/AKT signal transduction had a negative impact on immunotherapy efficacy. High expression of PIP4P2 in macrophages was correlated with poor prognosis in patients with GC. PIP4P2 is an independent unfavorable prognostic factor of epigenetic modification-associated molecular classification, is involved in tumorigenic progression, and is essential for assessing the prognosis and immunotherapy efficacy of GC.

Estimating the Global Burden of Epstein-Barr Virus-Associated Gastric Cancer: A Systematic Review and Meta-Analysis

BACKGROUND & AIMS

Evidence suggests that a fraction of new gastric cancer cases may be etiologically associated with Epstein-Barr virus (EBV), a known carcinogenic agent. We aimed to systematically explore the proportion of EBV-positive gastric cancer.

METHODS

We did a systematic review (PROSPERO CRD42020164473) from January 1990 to August 2021. For each country and geographical region with available data, pooled prevalence and corresponding 95% confidence intervals (CIs) of EBV in gastric tumors were calculated for 3 subtypes of gastric adenocarcinoma (conventional adenocarcinoma, lymphoepithelioma-like gastric carcinoma, and remnant/stump carcinoma). For conventional adenocarcinoma, prevalence ratios (PRs) were presented for sex, Lauren's classification, gastric cancer stage, and anatomical location of the stomach.

RESULTS

In 220 eligible studies including over 68,000 cases of conventional gastric adenocarcinoma, EBV prevalence in tumor cells was 7.5% (95% CI, 6.9%-8.1%) and was higher in men compared with women (PR, 2.1; 95% CI, 1.9-2.4), in diffuse type compared with intestinal type (PR, 1.3; 95% CI, 1.1-1.5), and in the proximal region compared with the distal region (PR, 2.5; 95% CI, 2.0-3.1). There was no difference in EBV prevalence by gastric cancer stage. EBV prevalence was 75.9% (95% CI, 62.8%-85.5%) among lymphoepithelioma-like gastric carcinoma and 26.3% (95% CI, 22.2%-32.0%) among remnant or stump carcinoma.

CONCLUSIONS

Assuming a causal association between EBV and gastric cancer, our findings, when applied to the GLOBOCAN 2020 gastric cancer incidence, suggest that primary prevention such as the development of an effective EBV vaccine might prevent 81,000 EBV-associated gastric cancer cases worldwide annually.

Evaluation of multiple immune cells and patient outcomes in esophageal squamous cell carcinoma

Recent reports indicate that immune cells in solid cancers have significant predictive and therapeutic value. IgG4 is a subclass of IgG and we recently found that it exerted an inhibitory effect in tumor immunity. We aimed to assess the significance of IgG4 and T cell subtypes in tumor prognosis. We investigated the density, distribution and relationship of five immune markers CD4, CD8, Foxp3, IL-10 and IgG4 with multiple immunostaining method in 118 esophageal squamous cell carcinoma (ESCC) together with clinical data. The relationship among different immune cell types and with clinical data were analyzed with Kaplan-Meier survival analysis and Cox proportional hazards model to identify independent risk factors among immune and clinicopathological parameters. Five-year survival rate of these patients treated with surgery reached 61%. Higher number of CD4⁺ plus CD8⁺ T cells predicted better prognosis (p=0.01) in tertiary lymphoid structure (TLS) and could add to the value of TNM staging. Density of the newly identified immune inhibitor IgG4⁺ B lymphocytes was found positively correlated to that of CD4⁺ cells (p=0.02) and IL-10⁺ cells (p=0.0005), but number of infiltrating IgG4⁺ cells by itself was not an independent factor for prognosis. However, increased serum concentration of IgG4 indicated a poor prognosis of ESCC (p=0.03). 5-year survival rate of esophageal cancer after surgery has been significantly improved. Increased T cells in TLS predicted better survival, suggesting that T cells in TLS may actively participate in anti-tumor immunity. Serum IgG4 could be a useful predictor of prognosis.

A lncRNA signature associated with tumor immune heterogeneity predicts distant metastasis in locoregionally advanced nasopharyngeal carcinoma

Increasing evidence has revealed the roles of long noncoding RNAs (lncRNAs) as tumor biomarkers. Here, we introduce an immune-associated nine-lncRNA signature for predicting distant metastasis in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). The nine lncRNAs are identified through microarray profiling, followed by RT–qPCR validation and selection using a machine learning method in the training cohort (n = 177). This nine-lncRNA signature classifies patients into high and low risk groups, which have significantly different distant metastasis-free survival. Validations in the Guangzhou internal (n = 177) and Guilin external (n = 150) cohorts yield similar results, confirming that the signature is an independent risk factor for distant metastasis and outperforms anatomy-based metrics in identifying patients with high metastatic risk. Integrative analyses show that this nine-lncRNA signature correlates with immune activity and lymphocyte infiltration, which is validated by digital pathology. Our results suggest that the immune-associated nine-lncRNA signature can serve as a promising biomarker for metastasis prediction in LA-NPC.

Long noncoding RNAs (lncRNAs) can be used for the development of prognostic signatures to predict tumour metastasis. Here the authors identify an immune-associated nine-lncRNA signature for predicting metastasis in a multicentre cohort of locoregionally advanced nasopharyngeal cancer patients.

Tumor Microenvironment in Mixed Neuroendocrine Non-Neuroendocrine Neoplasms: Interaction between Tumors and Immune Cells, and Potential Effects of Neuroendocrine Differentiation on the Tumor Microenvironment

The tumor microenvironment is considered to play a pivotal role in various human malignancies. Neuroendocrine and non-neuroendocrine neoplasms are considered to have different tumor microenvironments. However, owing to differences in the systemic and/or local immune statuses, tumor microenvironments in different patients may be difficult to compare. Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs), although rare, could be useful for exploring the effects of neuroendocrine differentiation on the tumor microenvironment, because both neuroendocrine and non-neuroendocrine components are present in the same tumor. Here, we examined 33 cases of histologically confirmed MiNENs and evaluated the influence of neuroendocrine differentiation on the tumor microenvironment by comparing tumor-infiltrating lymphocytes, tumor-associated macrophages, and other relevant factors in the two components the same tumor. The immunoreactivity of those examined above was evaluated quantitatively. The values of vasohibin-1-positive density (p < 0.0001) and immunoreactivity (p < 0.0001) (representing the neoangiogenesis status) were significantly higher in neuroendocrine as compared to non-neuroendocrine areas of the same tumors. In addition, the Foxp3/CD8 (p = 0.0717) and the PD-1/CD8 ratios (p = 0.0176) (representing tumor immunity suppression) tend to increase in neuroendocrine carcinomas. Immunoreactivity of CD163, a marker of M2-like macrophages, was also higher in the neuroendocrine areas. Our findings indicate that neuroendocrine and non-neuroendocrine tumors differ from each other with respect to the characteristics of both tumor cells and the tumor microenvironment.

Tumor Microenvironment in Mixed Neuroendocrine Non-Neuroendocrine Neoplasms: Interaction between Tumors and Immune Cells, and Potential Effects of Neuroendocrine Differentiation on the Tumor Microenvironment

The tumor microenvironment is considered to play a pivotal role in various human malignancies. Neuroendocrine and non-neuroendocrine neoplasms are considered to have different tumor microenvironments. However, owing to differences in the systemic and/or local immune statuses, tumor microenvironments in different patients may be difficult to compare. Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs), although rare, could be useful for exploring the effects of neuroendocrine differentiation on the tumor microenvironment, because both neuroendocrine and non-neuroendocrine components are present in the same tumor. Here, we examined 33 cases of histologically confirmed MiNENs and evaluated the influence of neuroendocrine differentiation on the tumor microenvironment by comparing tumor-infiltrating lymphocytes, tumor-associated macrophages, and other relevant factors in the two components the same tumor. The immunoreactivity of those examined above was evaluated quantitatively. The values of vasohibin-1-positive density (p < 0.0001) and immunoreactivity (p < 0.0001) (representing the neoangiogenesis status) were significantly higher in neuroendocrine as compared to non-neuroendocrine areas of the same tumors. In addition, the Foxp3/CD8 (p = 0.0717) and the PD-1/CD8 ratios (p = 0.0176) (representing tumor immunity suppression) tend to increase in neuroendocrine carcinomas. Immunoreactivity of CD163, a marker of M2-like macrophages, was also higher in the neuroendocrine areas. Our findings indicate that neuroendocrine and non-neuroendocrine tumors differ from each other with respect to the characteristics of both tumor cells and the tumor microenvironment.

Prognostic value of immune-related genes and comparative analysis of immune cell infiltration in lung adenocarcinoma: sex differences

Background

Lung adenocarcinoma (LUAD) is one of the most important subtypes of lung cancer. Compared with male LUAD patients, female patients have a higher incidence, but better long-term survival rate, with unknown reasons. In this study, we aimed to explore the effect of sex differences on immune cell infiltration in lung tumor microenvironment (TME), and tried to clarify the reasons for the different clinical characteristics of male and female LUAD patients, by conducting a comparative analysis of the TME.

Methods

Using ESTIMATE algorithm, we calculated immune and stromal scores of tumor samples downloaded from TCGA database according to immune or stromal components in TME. GO and KEGG enrichment analysis were conducted to reveal biological processes of these intersecting genes of high- and low-score groups. Cox regression analysis and protein–protein interaction (PPI) network analysis were performed to screen immune-related prognostic genes in female (CCR2, LCP2, and PTPRC) and male (BTK and CCR2) patients. Kaplan–Meier survival analysis was used to evaluate prognostic value of these identified genes. Mann–Whitney test was used to compare various indicators of male patients and female patients. The main results were subsequently validated in 420 cases from GSE72094.

Results

304 and 368 intersecting genes were identified in female and male patients, respectively. The immune score ranged from −943.17 to 3229.35 among female patients and from −541.75 to 3441.78 among male patients. The stromal score ranged from −1790.23 to 2097.27 among female patients and from −1786.94 to 1722.70 among male patients. The immune and stromal scores of women were higher than those of men (p < 0.05). CCR2, LCP2 and PTPRC were identified as the most important immune-related prognostic genes in female LUAD patients. BTK and CCR2 were identified as the most important immune-related prognostic genes in male LUAD patients. Female patients had a higher proportion of memory B cells than that of male patients, while the percentage of T cells CD4 naïve and resting NK cells was lower in female patients (p < 0.05).

Conclusions

This study comprehensively compared the differences in tumor immune microenvironment between male and female LUAD patients, and identified prognosis-related genes for patients of different sexes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13293-021-00406-y.

We presented a detailed and comprehensive analysis of immune cell infiltration in tumor microenvironment (TME) of female and male patients with lung adenocarcinoma (LUAD).

We compared the differences in the tumor immune microenvironment between female and male LUAD patients.

The density of memory B cells in TME of female patients with LUAD was significantly higher than that of male patients, which may explain that female patients with LUAD have a better prognosis than that of male patients.

We identified immune-related genes that predicted the prognosis of female and male LUAD patients, respectively, and their predictive value were verified by another independent cohort.

Harnessing biomarkers of response to improve therapy selection in esophago-gastric adenocarcinoma

Advanced esophago-gastric (OG) adenocarcinomas have a high mortality rate and new therapeutic options are urgently required. Despite recent advances in understanding the molecular characteristics of OG cancers, tumor heterogeneity poses a challenge in developing new therapeutics capable of improving patient outcomes. Consequently, chemotherapy remains the mainstay of systemic treatment, with the HER2 being the only predictive biomarker routinely targeted in clinical practice. Recent data indicate that immunotherapy will be incorporated into first-line chemotherapy, but further research is required to refine patient selection. This review will summarize the clinical strategies being evaluated to utilize our knowledge of predictive biomarkers with reference to novel therapeutics, and discuss the barriers to implementing precision oncology in OG adenocarcinoma.

Immune landscape and subtypes in primary resectable oral squamous cell carcinoma: prognostic significance and predictive of therapeutic response

BACKGROUND

Immune landscape of cancer has been increasingly recognized as a key feature affecting disease progression, prognosis and therapeutic response. Here, we sought to comprehensively characterize the patterns of tumor-infiltrating immune cells (TIIs) in primary oral squamous cell carcinoma (OSCC) and develop immune features-derived models for prognostication and therapeutic prediction.

METHODS

A total number of 392 patients with OSCC receiving ablative surgery at three independent centers were retrospectively enrolled and defined as training, testing and validation cohorts. Detailed features of 12 types of TIIs at center of tumor and invasive margin were assessed by immunohistochemistry coupled with digital quantification. TIIs abundance in OSCC was also estimated by bioinformatics approaches using multiple publicly available data sets. Prognostic models based on selected immune features were trained via machine learning approach, validated in independent cohorts and evaluated by time-dependent area under the curves and concordance index (C-index). Immune types of OSCC were further identified by consensus clustering and their associations with genetic, molecular features and patient survival were clarified.

RESULTS

Patterns of TIIs infiltration varied among patients and dynamically evolved along with tumor progression. Prognostic models based on selected TIIs were identified as efficient and sensitive biomarkers to stratify patients into subgroups with favorable or inferior survival as well as responders or non-responders to postoperative radiotherapy or immunotherapy. These models outperformed multiple conventional biomarkers and immune-related scores in prognostic prediction. Furthermore, we identified two main immune subtypes of OSCC (immune-hot and immune-cold) which harbored characteristic TIIs infiltrations and genomic and molecular features, and associated with patient survival.

CONCLUSIONS

Our results delineated immune landscape and subtypes in OSCC, consolidated their clinical values as robust biomarkers to predict patient survival and therapeutic benefits and reinforced key roles of TIIs and tumor-immune interactions underlying oral tumorigenesis, ultimately facilitating development of tailed immunotherapeutic strategies.

Machine learning for cell classification and neighborhood analysis in glioma tissue

Multiplexed and spatially resolved single-cell analyses that intend to study tissue heterogeneity and cell organization invariably face as a first step the challenge of cell classification. Accuracy and reproducibility are important for the downstream process of counting cells, quantifying cell-cell interactions, and extracting information on disease-specific localized cell niches. Novel staining techniques make it possible to visualize and quantify large numbers of cell-specific molecular markers in parallel. However, due to variations in sample handling and artifacts from staining and scanning, cells of the same type may present different marker profiles both within and across samples. We address multiplexed immunofluorescence data from tissue microarrays of low-grade gliomas and present a methodology using two different machine learning architectures and features insensitive to illumination to perform cell classification. The fully automated cell classification provides a measure of confidence for the decision and requires a comparably small annotated data set for training, which can be created using freely available tools. Using the proposed method, we reached an accuracy of 83.1% on cell classification without the need for standardization of samples. Using our confidence measure, cells with low-confidence classifications could be excluded, pushing the classification accuracy to 94.5%. Next, we used the cell classification results to search for cell niches with an unsupervised learning approach based on graph neural networks. We show that the approach can re-detect specialized tissue niches in previously published data, and that our proposed cell classification leads to niche definitions that may be relevant for sub-groups of glioma, if applied to larger data sets.

Association of tumor-infiltrating T lymphocytes with intestinal-type gastric cancer molecular subtypes and outcome

While host immune response is likely to be important for the prognosis of gastric cancer patients, detailed information on the T lymphocyte infiltration in different gastric cancer subtypes is lacking. Here, we studied the presence of CD3, CD8, and FOXP3 (Forkhead box p3) expressing T lymphocytes in a retrospective cohort of 190 intestinal gastric and gastroesophageal adenocarcinomas. The cancers represented four distinct molecular subtypes: Epstein-Barr virus-positive (EBV+), mismatch-repair-deficient (MMR-D), aberrant TP53, and the "other" subtype. The absolute numbers of CD3+, CD8+, and FOXP3+ T lymphocytes were analyzed in relation with these molecular subtypes and selected clinicopathological parameters. Overall, there was a large variation in the amount of infiltrating T lymphocyte in all molecular subtypes. Among the subtypes, EBV+ cancers differed from the other subtypes in increased lymphocyte infiltration and high CD8+/FOXP3+ ratio. While the TP53 aberrant subtype did not differ in the absolute amount of T lymphocyte, the ratio of CD8+/FOXP3+ and CD3+/FOXP3+ cells was highest in this subtype, possibly reflecting immunosuppression associated with genomic instability. Increased CD3+ and CD8+ T lymphocyte infiltrates were associated with better survival, and remained as independent prognostic factors in a multivariate analysis. This study is the first to investigate lymphocytic infiltration within four molecular subtypes of intestinal-type gastric cancer in a European cohort. The results provide an important addition to the current knowledge of T lymphocyte-dependent immune response in gastric cancer and its prognostic significance.

Immune cell infiltrates as prognostic biomarkers in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis

Immune cell infiltration has been identified as a prognostic biomarker in several cancers. However, no immune based biomarker has yet been validated for use in pancreatic ductal adenocarcinoma (PDAC). We undertook a systematic review and meta-analysis of immune cell infiltration, measured by immunohistochemistry (IHC), as a prognostic biomarker in PDAC. All other IHC prognostic biomarkers in PDAC were also summarised. MEDLINE, EMBASE and Web of Science were searched between 1998 and 2018. Studies investigating IHC biomarkers and prognosis in PDAC were included. REMARK score and Newcastle-Ottawa scale were used for qualitative analysis. Random-effects meta-analyses were used to pool results, where possible. Twenty-six articles studied immune cell infiltration IHC biomarkers and PDAC prognosis. Meta-analysis found high infiltration with CD4 (hazard ratio [HR] = 0.65, 95% confidence interval [CI] = 0.51-0.83.) and CD8 (HR = 0.68, 95% CI = 0.55-0.84.) T-lymphocytes associated with better disease-free survival. Reduced overall survival was associated with high CD163 (HR = 1.62, 95% CI = 1.03-2.56). Infiltration of CD3, CD20, FoxP3 and CD68 cells, and PD-L1 expression was not prognostic. In total, 708 prognostic biomarkers were identified in 1101 studies. In summary, high CD4 and CD8 infiltration are associated with better disease-free survival in PDAC. Increased CD163 is adversely prognostic. Despite the publication of 708 IHC prognostic biomarkers in PDAC, none has been validated for clinical use. Further research should focus on reproducibility of prognostic biomarkers in PDAC in order to achieve this.

M1-like TAMs are required for the efficacy of PD-L1/PD-1 blockades in gastric cancer

The efficacy of PD-1/PD-L1 blockades is heterogeneous in different molecular subtypes of gastric cancer (GC). In this study, we analyzed relevant clinical trials to identify the molecular subtypes associated with the efficacy of PD-1/PD-L1 blockades, and public datasets, patient samples, and GC cell lines were used for investigating potential mechanisms. We found that GC with EBV-positive, MSI-H/dMMR, TMB-H or PIK3CA mutant subtype had enhanced efficacy of PD-L1/PD-1 blockades. Also, differentially expressed genes of these molecular subtypes shared the same gene signature and functional annotations related to immunity. Meanwhile, CIBERSORT identified that the overlapping landscapes of tumor-infiltrating immune cells in the four molecular subtypes were mainly M1-like macrophages (M1). The relationships between M1 and clinical characteristics, M1, and gene signatures associated with PD-1/PD-L1 blockades also revealed that M1 was associated with improved prognosis and required for the efficacy of PD-L1/PD-1 blockades in GC. We identified that tumor-infiltrating CD68⁺CD163⁻ macrophages could represent M1 calculated by CIBERSORT in clinical application, and CXCL9, 10, 11/CXCR3 axis was involved in the mechanism of CD68⁺CD163⁻ macrophages in the enhanced efficacy of PD-L1/PD-1 blockades. In conclusion, CD68⁺CD163⁻ macrophages are required for the efficacy of PD-L1/PD-1 blockades and expand the applicable candidates in GC patients without the molecular subtypes.