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Supplementary Figure 1 to 7, Supplementary Table 1

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Immunotherapy treatments with anti-PD-1 boost recovery in less than 30% of treated cancer patients, indicating the complexity of the tumor microenvironment. Expression of HLA-E is linked to poor clinical outcomes in mice and human patients. However, the contributions to immune evasion of HLA-E, a ligand for the inhibitory CD94/NKG2A receptor, when expressed on tumors, compared with adjacent tissue and peripheral blood mononuclear cells, remains unclear. In this study, we report that epithelial-derived cancer cells, tumor macrophages, and CD141+ conventional dendritic cells (cDC) contributed to HLA-E enrichment in carcinomas. Different cancer types showed a similar pattern of enrichment. Enrichment correlated to NKG2A upregulation on CD8+ tumor-infiltrating T lymphocytes (TIL) but not on CD4+ TILs. CD94/NKG2A is exclusively expressed on PD-1high TILs while lacking intratumoral CD103 expression. We also found that the presence of CD94/NKG2A on human tumor–specific T cells impairs IL2 receptor–dependent proliferation, which affects IFNγ-mediated responses and antitumor cytotoxicity. These functionalities recover following antibody-mediated blockade in vitro and ex vivo. Our results suggest that enriched HLA-E:CD94/NKG2A inhibitory interaction can impair survival of PD-1high TILs in the tumor microenvironment.

Presence of mucus layer and inlet air temperature variations can significantly affect the extent of particle transport and deposition in the mouth-throat airway for aerosol drug delivery applications. In addition, higher inlet air temperature can lead to thermal injuries as well. The main goal of the present paper is to investigate these effects in a highly idealized mouth-throat geometry in detail. Large eddy simulation was performed to accurately predict the air flow-fields and a Lagrangian particle tracking model has been employed to capture the particle deposition efficiencies and patterns. The effects of three different inlet air temperatures (15 °C, 26.7 °C and 45 °C) and three different particle sizes (3 μm, 5 μm and 6 μm) have been studied for inlet flow rates of 15 L/min and 30 L/min with and without mucus layer in the present investigation. Detailed velocity and temperature fields, as well as, particle deposition efficiencies and patterns were analyzed and it has been found out that (a) the particle deposition efficiencies varied significantly with changes in inlet air temperature and flow rates, particle diameters and in the presence of mucus layer, (b) the presence of recirculation zones and secondary vortices determined the rate of particle deposition at different inhalation flow rates and inlet air temperatures, and (c) the changes in temperature distribution near the mouth-throat wall in the presence of mucus layer have a dominant effect on particle deposition as compared to inertial deposition. The findings of the present work will provide useful information in understanding the heat transfer effects on particle transport and deposition for the design of pulmonary drug delivery devices under the influence of various environmental and human factors.

For patients with lung disease, dry powder inhalers (DPI) are profoundly beneficial. The current study introduces and develops a series of dry powder inhalers (DPIs). A capsule-based (size 0) active DPI was considered. The study aims to investigate whether swirling flow and outlet capillary diameter (dc_out) affect the percentage of emitted doses (ED) released from the capsule. Spiral vanes were added to the capillary inlet to produce a swirling flow. Computational fluid dynamics (CFD) was applied to simulate the problem. The results were compared with previous in vitro and numerical studies to validate the results. Based on the derived results, the small swirl parameter (SP) enhances the secondary flow and recirculation zone. It increases the central jet flow, which increases the ED value by about 5-20% compared to no-swirl flow. However, as the airflow rate increases, the recirculation zone enlarges, vorticities become dominant, and asymmetrical flow patterns emerge. Consequently, ED % drops significantly (more than 50%). As dc_out decreases, the vorticities around the outlet capillary become more potent, which is undesirable. Indeed, the emptying of the capsule does not happen ideally. The research provides a perspective on the device's design and DPI performance.

Deciphering the relationships between genes and complex traits could help us better understand the biological mechanisms leading to phenotypic variations and disease onset. Univariate gene-based analyses are widely used to characterize gene-phenotype relationships, but are subject to the influence of confounders. Furthermore, while some genes directly contribute to traits variations, others may exert their effects through other genes. How to quantify individual genes’ direct and indirect effects on complex traits remains an important yet challenging question. We presented a novel framework (BN-GWAS) to decipher the total and direct causal effects of individual genes using imputed gene expression data from GWAS and raw gene expression from GTEx. The study was partially motivated by the quest to differentiate “core” genes (genes with direct causal effect on the phenotype) from “peripheral” ones. Our proposed framework is based on a Bayesian network (BN) approach, which produces a directed graph showing the relationship between genes and the phenotype. The approach aims to uncover the overall causal structure, to examine the role of individual genes and quantify the direct and indirect effects by each gene. An important advantage and novelty of the proposed framework is that it allows gene expression and disease trait(s) to be evaluated in different samples, significantly improving the flexibility and applicability of the approach. It uses IDA and jointIDA incorporating a novel p-value-based regularization approach to quantify the causal effects (including total causal effects, direct causal effects, and medication effects) of genes. The proposed approach can be extended to decipher the joint causal network of 2 or more traits, and has high specificity and precision (a.k.a., positive predictive value), making it particularly useful for selecting genes for follow-up studies. We verified the feasibility and validity of the proposed framework by extensive simulations and applications to 52 traits across 14 tissues in the UK Biobank (UKBB). Split-half replication and stability selection analyses were performed to demonstrate the accuracy and efficiency of our proposed method to identify causally relevant genes. The identified (direct) causal genes were found to be significantly enriched for genes highlighted in the OpenTargets database, and the enrichment was stronger than achieved by conventional univariate gene-based tests. Encouragingly, many enriched pathways were supported by the literature, and some of the enriched drugs have been tested or used to treat patients in clinical practice. Our proposed framework provides a powerful way to prioritize genes with large direct or indirect causal effects and to estimate the ‘variable importance’ of such genes.

BackgroundT cell epitopes are polypeptide fragments presented to T cell receptors by MHC molecules encoded by human leukocyte antigen (HLA) genes after antigen-presenting cell processing, which is the basis for the study of antigen immune mechanism and multi-epitope vaccine. This study investigated T cell response to HPV16 E6 and E7 in patients with cervical squamous cell carcinoma (CSCC). Also, the HLA-A allele distribution was compared among patients and evaluated as a factor to predict prognosis in these patients.Materials and methodsThis study recruited a total of 76 patients with International Federation of Gynaecology and Obstetrics (FIGO) stage IIB–IIIB CSCC. Mononuclear cells were isolated from the peripheral blood before any treatment and then enzyme-linked immunosorbent spot (ELISpot) assay was employed to measure the E6 and E7-specific T cell response. HLA‐A alleles were typed using Sanger sequencing‐based typing techniques with DNA extracted from the peripheral blood. The correlation between the T cell responses, HLA‐A allele distribution and patient prognosis were analysed using the Kaplan–Meier method, univariate and multivariate Cox proportional hazard models.ResultsThe frequency of HPV E6-specific T cell responses in patients with pelvic lymph node metastasis was lower than that in patients without metastasis (P = 0.022). The 5-year overall survival (OS) rates of patients were 87.5% for those responding to multiple overlapping peptides, 72.7% for those responding to 1–2 overlapping peptides and 47.7% for non-responders (P = 0.032). Cox regression analysis indicated that the presence of HLA*A02:07 was independently associated with worse OS (hazard ratio [HR] 3.042; 95% confidence interval [CI] 1.348–6.862;P = 0.007), while concurrent chemoradiation therapy (CCRT) was independently associated with better OS (HR 0.475; 95% CI 0.232–0.975;P = 0.042).ConclusionThe results of our study demonstrated that the level of HPV16 E6-specific T cell response and HLA*A02:07 were correlated with prognosis in patients with advanced CSCC.

Killer cell lectin-like receptor G1 (KLRG1) and 2B4 play important roles in the immune regulation and immune tolerance to tumor cells by inhibiting T cell function. However, the clinical relevance of KLRG1 and 2B4 to cervical cancer remains to be understood.We measured the frequency of KLRG1+ or 2B4+ cells in CD4+ or CD8 + T cells derived from peripheral blood or tumour biopsies in cervical cancer patients by flow cytometry.Compared with healthy controls, the level of KLRG1 and 2B4 on CD8 + T cells in the blood of the patients increased significantly (KLRG1 level on T cells was related to age and HPV in patients with cervical cancer, while 2B4 level on T cells was related to age, underlying their roles in the host immune response to cervical cancer. Radiotherapy can improve the immune function of patients.

Images captured in the sand-dust weather often suffer from serious colour cast and poor contrast, and this has serious implications for outdoor computer vision systems. To address these problems, a normalised gamma transformation-based contrast-limited adaptive histogram equalisation (CLAHE) with colour correction in Lab colour space for sand-dust image enhancement is proposed in this study. This method consists of image contrast enhancement and image colour correction. To avoid producing new colour deviation, the input sand-dust images are first transformed from red, green, and blue colour space into Lab colour space. Then, the contrast of the lightness component (L channel) of the sand-dust image is enhanced using CLAHE. To avoid unbalanced contrast, as well as to reduce the overincreased brightness caused by CLAHE, a normalised gamma correction function is introduced to CLAHE. After that, the a and b chromatic components are recovered by a grey-world-based colour correction method. Experiments on real sand-dust images demonstrate that the proposed method can obtain the highest percentage of new visible edges for all testing images. The contrast restoration exhibits good colour fidelity and proper brightness.

To investigate the impacts of upper airway deformation on the airflow structures, the airflow fields in the trachea are simulated using three geometrical models considering three different levels of airway deformations. Structured grids are used to create the high-quality grids. Large eddy simulation with the Smagorinsky sub-grid model is adopted to solve the three-dimensional in-compressible Navier–Stokes equations using the solver pisoFoam in the open-source CFD software OpenFOAM. The numerical results demonstrate that the airway deformation influences the main airflow structures depending on the deformation level. Particularly, it slightly impacts on the laryngeal jet such as the profile and the strength of laryngeal jet. The strength of the laryngeal jet increases slightly for the heavy deformation. In contrast, it impacts on the recirculation zone, secondary vortices, and turbulent kinetic energy more obviously. The increasing airway deformation will produce stronger secondary flow, smaller recirculation zone, and weaker turbulent kinetic energy. The turbulence intensity distribution varies as well. The obviously impacted flow region is mainly within the region of one to six tracheal diameters downstream the glottis.

BackgroundVaccines for COVID-19 represent a breakthrough in the fight against the pandemic. However, worries about adverse effects led to vaccine hesitancy in some people. On the other hand, as COVID-19 may be associated with various sequelae, the vaccine may protect against these diseases.MethodsWe leveraged a large prospective cohort, the UK-Biobank(UKBB), and studied associations of at least one dose of COVID-19 vaccination(BioNTech-BNT162b2 or Oxford-AstraZeneca-ChAdOx1) with hospitalization from cardiovascular and other diseases (N=393,544; median follow-up of 54 days in vaccinated). Multivariable Cox and Poisson regression was conducted controlling for main confounders. Besides all hospitalizations, we also conducted separate analysis for new-onset and recurrent cases. We also performed other sensitivity analyses, including adjustment for prior event rate ratio (PERR) to reduce residual confounding.ResultsWe observed that COVID-19 vaccination(at least one dose) was associated with lower risks of hospitalizations from stroke (hazard ratio[HR]=0.178, 95% CI: 0.127-0.250, p=1.50e-23), VTE (HR=0.426, 95% CI: 0.270-0.673, p=2.51e-4), dementia (HR=0.114, 95% CI 0.060-0.216; p=2.24e-11), non-COVID-19 pneumonia (NCP) (HR=0.108, 95% CI 0.0.080-0.145; p=2.20e-49), CAD (HR=0.563, 95% CI: 0.416-0.762; p=2.05e-4), COPD (HR=0.212, 95% CI 0.126-0.357; p=4.92e-9), T2DM (HR= 0.216, 95% CI: 0.096 - 0.486, p=2.12e-4), heart failure (HR=0.174, 95% CI, 0.118-0.256, p=1.34e-18) and renal failure (HR=0.415, 0.255-0.677, p=4.19e-4).After adjusting for HRs of hospitalization between the two groupsbeforethe introduction of vaccination, COVID-19 vaccination was still significantly associated with reduced hazards of hospitalization due to CAD (HR=0.517, 95% CI: 0.327-0.817; p=4.70e-03), COPD (HR=0.317, 95% CI: 0.138-0.726; p=6.60e-03), dementia (HR=0.406, 95% CI: 0.180-0.919; p=3.06e-02), heart failure (HR=0.305, 95% CI: 0.179-0.519; p=1.18e-05), NCP (HR=0.191, 95% CI: 0.123-0.295; p=1.02e-13) and stroke (HR=0.222, 95% CI: 0.130-0.382; p=4.94e-08), although the estimated protective effects were weaker.ConclusionsTaken together, this study provides further support to the safety and benefits of COVID-19 vaccination, and such benefits may extend beyond reduction of infection risk or severity per se. As an observational study, causal relationship cannot be concluded and further studies are required to verify the findings.

In rainy conditions, especially at night with low illumination, the visual of images obtained by outdoor computer vision systems is degraded significantly, leading to a significant negative effect on the work of the outdoor computer vision system. In this paper, we develop a new rainy image model to describe rain scenes at night with low illumination. From this model, we propose a joint deep neural network-based method for single nighttime rainy image enhancement. First, a decom-net based on Retinex theory is employed for image decomposition, and the purpose of this sub-net is to extract the reflection image and the illumination image from the input image. Then, an enhancement net is proposed for illumination adjustment. The goal of this sub-net is to remove the negative effect (low visual) caused by low illumination. Finally, a symmetric sub-net termed multi-stream network-based contextual autoencoder is developed, where rain features are directly learned from the enhanced nighttime rainy images in a recurrent way. The goal of this sub-net is to effectively remove rain streaks from the illumination-enhanced image. The experimental results show the advantage and effectiveness of the proposed method, and evident improvements over existing state-of-the-art methods are obtained with the proposed method.

The images that are captured in sand storms often suffer from low contrast and serious color cast that are caused by sand dust, and these issues will have significant negative effects on the performance of an outdoor computer vision system. To address these problems, a method based on halo-reduced dark channel prior (DCP) dehazing for sand dust image enhancement is proposed in this paper. It includes three components in sequence: color correction in the LAB color space based on gray world theory, dust removal using a halo-reduced DCP dehazing method, and contrast stretching in the LAB color space using a Gamma function improved contrast limited adaptive histogram equalization (CLAHE), in which a guided filter is used to improve the artifacts of the histogram equalization. Experiments on a large number of real sand dust images demonstrate that the proposed method can well remove the overall yellowing tone and dust haze effect and obtain normal visual colors and a detailed clear image.

A low false positive (FP) rate is of great importance for the use of a Computer Aided Detection (CAD) system to detect pulmonary nodules in thoracic Computed Tomography (CT). However, due to the variations of nodules in appear and size, it is still a very challenging task to obtain a low FP rate. In this paper, we propose a deep Convolutional Neural Network (CNN) based transfer learning method for FP reduction in pulmonary nodule detection on CT slices. We utilized one of the state-of-the-art CNN models, VGG-16 [4], as a feature extractor to obtain nodule features, and used a support vector machine (SVM) for nodule classification. Firstly we transferred all the layers from a pre-trained VGG-16 model in ImageNet to our target networks. Then, we tuned the last fully connected layers to adjust the computer-vision-task-trained CNN model to pulmonary nodule classification task. The initial CNN filter weights were then optimized using the training data, i.e., the pulmonary nodule patch images and corresponding labels through back-propagation so that they better reflected the modalities in the pulmonary nodule image dataset. Finally, features learned in the fine-tuned CNN were used to train a SVM classifier. The output of the trained SVM was used for final classification. Experimental results show that the overall sensitivity of the proposed method was 87.2% with 0.39 FPs per scan, which is higher than 85.4% with 4 FPs per scan obtained by other state of art method.

Face shield is a common personal protection equipment for pandemic. In the present work, three-dimensional computational fluid dynamic (CFD) method is used to simulate a cough jet from an emitter who wears a face shield. A realistic manikin model with a simplified mouth cavity is employed. A large eddy simulation with a dynamic structure subgrid scale model is applied to model the turbulence. An Eulerian-Lagrangian approach is adopted to model the two-phase flows, with which the droplets are represented by a cloud of particles. The droplet breakup, evaporation, dispersion, drag force, and wall impingement are considered in this model. An inlet velocity profile that is based on a variable mouth opening area is considered. Special attentions have been put the vortex structure and droplet re-distribution induced by the face shield. It is found that the multiple vortices are formed when the cough jet impinges on the face shield. Some droplets move backward and others move downward after the impinging. It is also found that a small modification of the face shield significantly modifies the flow field and droplet distribution. We conclude that face shield significantly reduces the risk factor in the front of the emitter, meanwhile the risk factor in the back of the emitter increases. When the receiver standing in front of the emitter is shorter than the emitter, the risk is still very high. More attentions should be paid on the design of the face field, clothes cleaning and floor cleaning of the emitters with face shields. Based on the predicted droplet trajectory, a conceptual model for droplet flux is proposed for the scenario with the face shield.

It is critical to understand the airflow structures in the respiratory system toward increasing the drug delivery efficiency via inhalation. A whole-lung airway model is created by connecting a three-dimensional cast-based mouth–throat model and a one-dimensional conduit describing the other lung airways according to the literature. Constant displacement of the bottom surface in the geometrical model is used to simulate the respiratory process. Large eddy simulation with the dynamic structure sub-grid scale model is used to model the turbulent flow via a commercial computational fluid dynamics software, ConvergeTM. The innovative findings are as follows: (1) shear layer as well as vortical flow is observed in the lower airway at the inspiration phase; (2) the main airflow structures in the upper airway of this model are close to the case using the mouth–throat model; (3) the airflow structures, in particular the reversed laryngeal jet, are highly unsteady during the expiration phase. It is shown that this whole-lung airway model is suitable to analyze the airflow field in the upper airway but not in the lower airway, although it has been used a lot by a few researchers. More investigations should be carried out to study the dynamics of airflow structures during the expiration phase toward understanding airflow properties of human respiratory process.

Polygenic risk scores (PRS) have the potential to identify individuals at risk of diseases, optimizing treatment, and predicting survival outcomes. Here, we construct and validate a genome-wide association study (GWAS) derived PRS for nasopharyngeal carcinoma (NPC), using a multi-center study of six populations (6 059 NPC cases and 7 582 controls), and evaluate its utility in a nested case-control study. We show that the PRS enables effective identification of NPC high-risk individuals (AUC = 0.65) and improves the risk prediction with the PRS incremental deciles in each population (Ptrend ranging from 2.79 × 10−7 to 4.79 × 10−44). By incorporating the PRS into EBV-serology-based NPC screening, the test’s positive predictive value (PPV) is increased from an average of 4.84% to 8.38% and 11.91% in the top 10% and 5% PRS, respectively. In summary, the GWAS-derived PRS, together with the EBV test, significantly improves NPC risk stratification and informs personalized screening.

Rain image enhancement is important for outdoor computer vision applications. In this study, the authors propose a multi-stage filtering method for single rainy image enhancement. It is based on their new rainy image model, and consists of two main operations: rain streaks removal and rain fog removal. For rain streaks removal, based on one key observation that the low-pass version of a rainy image and that of a non-rainy image of the same scene are almost the same after appropriate low-pass filtering, they remove rain streaks from rainy images by decomposing an input rainy image (or a rainy component image) into the low-frequency (LF) part and the high-frequency (HF) part via an LF smooth filter, i.e. the traditional Gaussian filter with a simple subtraction operation in multiple different stages. After rain streaks removal, dark channel prior-based method was employed for rain fog removal. Experimental results show that the proposed algorithm generated comparable outputs with most of the state-of-the-art algorithms with low computation cost.

Background: Development of innovative immunotherapy is imperative to improve the poor survival of the nasopharyngeal carcinoma (NPC ) patients. In this study, we evaluated the T cell response to melanoma-associated antigen (MAGE)-A1, MAGE-A3, or synovial sarcoma X-2 (SSX-2) in the peripheral blood of treatment-naive NPC patients. The relationship of responses among the three proteins and the human leukocyte antigen (HLA)-A types were analyzed to provide evidence of designing novel therapy. Methods: Sixty-one NPC patients admitted into the Tumor Hospital affiliated to the Xinjiang Medical University between March 2015 and July 2016 were enrolled. Mononuclear cells were isolated from the peripheral blood before any treatment. HLA-A alleles were typed with Sanger sequence-based typing technique. The T cell response to the MAGE-A1, MAGE-A3, or SSX-2 was evaluated with the Enzyme-Linked ImmunoSpot assay. Mann-Whitney U-test was used to compare the T cell responses from different groups. Spearman’s rank correlation was used to analyze the relationship of T cell responses. Results: HLA-A*02:01, A*02:07, and A*24:02 were the three most frequent alleles (18.9%, 12.3%, and 11.5%, respectively) among the 22 detected alleles. 31.1%, 19.7%, and 16.4% of the patients displayed MAGE-A1, MAGE-A3, or SSX-2-specific T cell response, respectively. The magnitudes of response to the three proteins were 32.5, 38.0, and 28.7 SFC/106 peripheral blood mononuclear cells, respectively. The T cell response against the three proteins correlated with each other to different extent. The percentage of A*02:01 and A*24:02 carriers were significantly higher in patients responding to any of the three proteins compared to the nonresponders. Conclusion: MAGE-A1, MAGE-A3, or SSX-2-specific T cell responses were detectable in a subgroup of NPC patients, the frequency and magnitude of which were correlated. Key words: Human Leukocyte Antigen-A; Melanoma-Associated Antigen-A; Nasopharyngeal Carcinoma; Synovial Sarcoma X-2; T Cell Response

MicroRNA‑29a (miR‑29a) has recently been in the spotlight as a tumor suppressor whose encoding gene is frequently suppressed in cancers. The aim of the present study was to investigate the biological functions and underlying molecular mechanism by which miR‑29a‑3p suppresses gastric cancer peritoneum metastasis. Cell proliferation, colony‑forming, wound healing and Transwell migration assays were performed in the present study. MiR‑29a‑3p expression was markedly decreased in gastric cancer cell lines with stronger metastatic potential. Silencing miR‑29a‑3p expression promoted gastric cancer cell proliferation, colony‑forming, migration and invasion. By contrast, overexpression of miR‑29a‑3p inhibited these biological phenotypes. In addition, it was revealed that miR‑29a‑3p functioned through downregulating hyaluronan synthase 3 expression. Collectively, dysregulated miR‑29a‑3p expression in gastric cancer cells was associated with malignant properties primarily relevant to migration and metastasis. The results suggest that miR‑29a‑3p may be a potential therapeutic target for gastric cancer.

Mimetics of antibody-binding sites represent particularly interesting targets, however they are difficult to identify. In most cases, naturally derived CDR3 peptides show a much lower activity and affinity. In this study, we identified a CDR3 domain antibody with framework 3 (FR3) and FR4 in the flank by screening a lysozyme-immunized phage display VHH library. This antibody has a potent enzyme inhibiting activity and high thermal stability. With sequence alignment and site-directed mutagenic analysis, we found that the cysteine residue at amino acid position 88 in FR3 might play a key role in maintaining the stability of the CDR3 antibody. The small-sized CDR3 domain antibody might act as a new scaffold for affinity transfer, hence making a useful contribution to the understanding of antigen-antibody interactions.

Summary Background and objective We aimed to investigate the effects of microRNA-214 (miR-214) on peritoneal metastasis as well as to elucidate its regulatory mechanism in gastric cancer (GC). Methods The expression levels of miR-214 in human GC cell lines MKN-28NM, MKN-28M, GC9811 and GC9811-P were analyzed by quantitative real-time PCR. Lentiviral miR-214, lentiviral miR-214 inhibitor, and empty lentiviral vector were transfected to GC cell lines, respectively. The roles of miR-214 in cell invasion, migration, proliferation and colony-forming ability were then analyzed. Besides, the expression levels of PTEN in different transfected cells were determined by western blot analysis. Results We found that miR-214 was up-regulated in GC9811-P cells with high metastatic potential to the peritoneum compared with that in GC9811 cells. In addition, in vitro overexpression of miR-214 promoted cell invasion, migration, proliferation and colony-forming ability of GC9811 cells, while down-regulation of miR-214 had opposite effects in GC9811-P cells. Besides, overexpression of miR-214 in GC9811 cells markedly down-regulated PTEN expression, whereas down-regulation of miR-214 in GC9811-P cells significantly increased PTEN expression. Conclusions Our findings indicate that miR-214 may promote peritoneal metastasis of GC cells via down-regulation of PTEN, thus leading to the progression of GC.

Immunotherapy treatments with anti-PD-1 boost recovery in less than 30% of treated cancer patients, indicating the complexity of the tumor microenvironment. Expression of HLA-E is linked to poor clinical outcomes in mice and human patients. However, the contributions to immune evasion of HLA-E, a ligand for the inhibitory CD94/NKG2A receptor, when expressed on tumors, compared with adjacent tissue and peripheral blood mononuclear cells, remains unclear. In this study, we report that epithelial-derived cancer cells, tumor macrophages, and CD141+ conventional dendritic cells (cDC) contributed to HLA-E enrichment in carcinomas. Different cancer types showed a similar pattern of enrichment. Enrichment correlated to NKG2A upregulation on CD8+ tumor-infiltrating T lymphocytes (TIL) but not on CD4+ TILs. CD94/NKG2A is exclusively expressed on PD-1high TILs while lacking intratumoral CD103 expression. We also found that the presence of CD94/NKG2A on human tumor–specific T cells impairs IL2 receptor–dependent proliferation, which affects IFNγ-mediated responses and antitumor cytotoxicity. These functionalities recover following antibody-mediated blockade in vitro and ex vivo. Our results suggest that enriched HLA-E:CD94/NKG2A inhibitory interaction can impair survival of PD-1high TILs in the tumor microenvironment.

Gastric cancer is a type of cancer with increasing incidence and high mortality rates, but molecular biomarkers of diagnostic and therapeutic value are currently lacking. The aim of the present study was to examine the expression pattern of the interleukin 1 receptor-like 1 (ST2) protein and assess its clinicopathological significance in gastric cancer. Western blot analysis of 12 gastric cancer specimens and paired adjacent tissues demonstrated that the protein levels of 2 isoforms of ST2, soluble secreted ST2 and the ST2 variant without the third immunoglobulin motif and splicing in the C-terminal, were markedly decreased in cancer tissues compared with non-cancerous tissues. Immunohistochemical analysis demonstrated that ST2 protein expression was markedly decreased in primary gastric cancer tissues (39.1%, 90/230) compared with adjacent non-cancerous tissues (60.7%, 54/89) (P