Distinct Immune Cell Research Articles

Two Distinct Immune Cell Signatures Predict the Clinical Outcomes in Patients With Amyopathic Dermatomyositis With Interstitial Lung Disease.

Amyopathic dermatomyositis (ADM) is a heterogeneous and life-threatening autoimmune disease with a high mortality rate. In particular, anti-melanoma differentiation-associated protein 5 antibody-positive patients are at a high risk of developing rapidly progressive interstitial lung disease (RPILD). This study was undertaken to identify immunologic signatures among patients who have ADM with ILD (ADM-ILD) and to discover the biomarkers predicting prognosis. The landscape of 42 immune cell phenotypes in the peripheral blood of 82 ADM-ILD patients and 82 age- and sex-matched healthy donors was assessed by multicolor flow cytometry. Patients were stratified using an unsupervised machine learning method (hierarchical clustering analysis) by immune cell subsets. Multiple Wilcoxon's signed rank tests and supervised machine learning methods were performed to identify important immune cell subsets. Kaplan-Meier survival analysis with log rank tests was used to create survival curves. We identified 2 distinct clusters correlating with different disease activities and clinical outcomes in ADM-ILD. Cluster 1 was enriched in the activated CD45RA+HLA-DR+CD8+ T cells with decreased CD56dim natural killer cell proportions and showed a higher prevalence of RPILD and higher mortality. In contrast, the other subgroup, cluster 2 (the nonactivated T cell-dominant cluster), displayed favorable clinical outcomes with high survival rates. Our data also revealed that immunophenotype was an independent risk factor associated with 1-year survival. Peripheral immunologic features may have the potential to stratify patients with ADM-ILD according to different disease severity and clinical outcomes, which may have implications for outcome prediction, pathogenesis study, and therapy selection.

Systems-level identification of key transcription factors in immune cell specification.

Transcription factors (TFs) are crucial for regulating cell differentiation during the development of the immune system. However, the key TFs for orchestrating the specification of distinct immune cells are not fully understood. Here, we integrated the transcriptomic and epigenomic measurements in 73 mouse and 61 human primary cell types, respectively, that span the immune cell differentiation pathways. We constructed the cell-type-specific transcriptional regulatory network and assessed the global importance of TFs based on the Taiji framework, which is a method we have previously developed that can infer the global impact of TFs using integrated transcriptomic and epigenetic data. Integrative analysis across cell types revealed putative driver TFs in cell lineage-specific differentiation in both mouse and human systems. We have also identified TF combinations that play important roles in specific developmental stages. Furthermore, we validated the functions of predicted novel TFs in murine CD8+ T cell differentiation and showed the importance of Elf1 and Prdm9 in the effector versus memory T cell fate specification and Kdm2b and Tet3 in promoting differentiation of CD8+ tissue resident memory (Trm) cells, validating the approach. Thus, we have developed a bioinformatic approach that provides a global picture of the regulatory mechanisms that govern cellular differentiation in the immune system and aids the discovery of novel mechanisms in cell fate decisions.

Relationships of Cuproptosis-Related Genes With Clinical Outcomes and the Tumour Immune Microenvironment in Hepatocellular Carcinoma.

Background: Cuproptosis is a recently identified form of regulated cell death that plays a critical role in the onset and progression of various cancers. However, the effects of cuproptosis-related genes (CRGs) on hepatocellular carcinoma (HCC) are poorly understood. This study aimed to identify the cuproptosis subtypes and established a novel prognostic signature of HCC. Methods: We collected gene expression data and clinical outcomes from the TCGA, ICGC, and GEO datasets, analysed and identified 16 CRGs and the different subtypes of cuproptosis related to overall survival (OS), and further examined the differences in prognosis and immune infiltration among the subtypes. Subtypes-related differentially expressed genes (DEGs) were employed to build a prognostic signature. The relationship of the signature with the immune landscape as well as the sensitivity to different therapies was explored. Moreover, a nomogram was constructed to predict the outcome based on different clinicopathological characteristics. Results: Three cuproptosis subtypes were identified on the basis of 16 CRGs, and subtype B had an advanced clinical stage and worse OS. The immune response and function in subtype B were significantly suppressed, which may be an important reason for its poor prognosis. Based on the DEGs among the three subtypes, a prognostic model of five CRGs was constructed in the training set, and its predictive ability was validated in two external validation sets. HCC patients were classified into high and low-risk subgroups according to the risk score, and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (p < 0.001). The independent predictive performance of the risk score was assessed and verified by multivariate Cox regression analysis (p < 0.001). We further created an accurate nomogram to improve the clinical applicability of the risk score, showing good predictive ability and calibration. Low- and high-risk patients exhibit distinct immune cell infiltration and immune checkpoint changes. By further analyzing the risk score, patients in the high-risk group were found to be resistant to immunotherapy and a variety of chemotherapy drugs. Conclusion: Our study identified three cuproptosis subtypes and established a novel prognostic model that provides new insights into HCC subtype prognostic assessment and guides more effective treatment regimens.

A combined spatial score of granzyme B and CD68 surpasses CD8 as an independent prognostic factor in TNM stage II colorectal cancer

BackgroundPrevious assessments of peritumoral inflammatory infiltrate in colorectal cancer (CRC) have focused on the role of CD8+ T lymphocytes. We sought to compare the prognostic value of CD8 with downstream indicators of active immune cell function, specifically granzyme B (GZMB) and CD68 in the tumour microenvironment.MethodsImmunohistochemical (IHC) staining was performed for CD8, GZMB, CD68 and CD163 on next-generation tissue microarrays (ngTMAs) in a primary cohort (n = 107) and a TNM stage II validation cohort (n = 151). Using digital image analysis, frequency of distinct immune cell types was calculated for tumour proximity (TP) zones with varying radii (10 μm-100 μm) around tumour cells.ResultsAssociations notably of advanced TNM stage were observed for low density of CD8 (p = 0.002), GZMB (p < 0.001), CD68 (p = 0.034) and CD163 (p = 0.011) in the primary cohort. In the validation cohort only low GZMB (p = 0.036) was associated with pT4 stage. Survival analysis showed strongest prognostic effects in the TP25μm zone at the tumour centre for CD8, GZMB and CD68 (all p < 0.001) in the primary cohort and for CD8 (p = 0.072), GZMB (p = 0.035) and CD68 (p = 0.004) in the validation cohort with inferior prognostic effects observed at the tumour invasive margin. In a multivariate survival analysis, joint analysis of GZMB and CD68 was similarly prognostic to CD8 in the primary cohort (p = 0.007 vs. p = 0.002) and superior to CD8 in the validation cohort (p = 0.005 vs. p = 0.142).ConclusionCombined high expression of GZMB and CD68 within 25 μm to tumour cells is an independent prognostic factor in CRC and of superior prognostic value to the well-established CD8 in TNM stage II cancers. Thus, assessment of antitumoral effect should consider the quality of immune activation in peritumoral inflammatory cells and their actual proximity to tumour cells.

The prognostic value of a 4-factor neoimmunologic score system in non-small cell lung cancer.

The role of distinct immune cell types in modulating cancer progression has recently gained attention. The immune context is indicated by the abundance of immune infiltration based on quantified lymphocytes in the core of tumors (CT) and invasive tumor margin (IM). Novel immune biomarkers could potentially complement tumor-node-metastasis (TNM) classification for non-small cell lung cancers (NSCLCs), thereby improving prognostic accuracy. This study evaluated the prognostic value of a newly established immunologic score (neo-IS) in patients with NSCLC. We detected 10 immune biomarkers, including CD45RO, CD3, CD8, CD68, CD163, CD66b, FoxP3, PD-1, PD-L1, and TIM-3, in 350 patients with NSCLC from 2 cohorts using immunohistochemistry (IHC). The 3- and 5-year survival and overall survival (OS) rates were evaluated. An immunologic prediction model specifically for NSCLC patients, the neo-immunologic score (neo-ISNSCLC ), was constructed using a Cox proportional hazards regression model. In the discovery cohort (n=250), the establishment of neo-ISNSCLC was based on 4 immune biomarkers: CD3+IM , CD8+CT , FoxP3+IM , and PD-1+IM . Significant prognostic differences were found upon comparing low-ISNSCLC patients and high-ISNSCLC patients. The OS rate in the high-ISNSCLC group was significantly longer than that in the low-ISNSCLC group (67.5 months vs. 51.2 months, p<0.001). The neo-ISNSCLC was validated in the validation cohort (n=100), and the results were confirmed. Multivariate analyses indicated that neo-ISNSCLC was an independent indicator of prognosis in patients with NSCLC. Finally, we combined neo-ISNSCLC with clinicopathologic factors to establish a tumor-node-metastasis-immune (TNM-I) staging system for clinical use, which showed better prediction accuracy than the TNM stage.

Expression and Prognostic Value of Chromobox Family Proteins in Esophageal Cancer.

Background: Esophageal cancer (EC) is one of the most common human malignant tumors worldwide. Chromobox (CBX) family proteins are significant components of epigenetic regulatory complexes. It is reported that CBXs play critical roles in the oncogenesis and development of various tumors. Nonetheless, their functions and specific roles in EC remain vague and obscure. Methods and Materials: We used multiple bioinformatics tools, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), UALCAN, Kaplan–Meier plotter, cBioPortal, Metascape, TIMER2 and TISIDB, to investigate the expression profile, gene alterations and prognostic roles of CBX family proteins, as well as their association with clinicopathologic parameters, immune cells and immune regulators. In addition, RT-qPCR, Western blot, CCK8, colony formation, wound healing and transwell assays were performed to investigate the biological functions of CBX3 in EC cells. Results: CBX3 and CBX5 were overexpressed in EC compared to normal tissues. Survival analysis revealed that high expression of CBX1 predicted worse disease-free survival (DFS) in EC patients. Functionally, CBXs might participate in mismatch repair, spliceosome, cell cycle, the Fanconi anemia pathway, tight junction, the mRNA surveillance pathway and the Hippo signaling pathway in EC development. Furthermore, CBXs were related to distinct immune cells infiltration and immune regulators. Additionally, depletion of CBX3 inhibited the proliferation, migration and invasion abilities of EC cells. Conclusions: Our study comprehensively investigated the expression pattern, prognostic value, and gene alterations of CBXs in EC, as well as their relationships with clinicopathologic variables, immune cells infiltration and immune regulators. These results suggested that CBX family proteins, especially CBX3, might be potential biomarkers in the progression of EC.

Inhibition of APOC1 promotes the transformation of M2 into M1 macrophages via the ferroptosis pathway and enhances anti-PD1 immunotherapy in hepatocellular carcinoma based on single-cell RNA sequencing

Single-cell RNA-sequencing (scRNA-seq) presents better insights into cell behavior in the context of a complex tumor microenvironment by profiling single-cell populations. However, the mechanisms underlying treatment failure in hepatocellular carcinoma (HCC) are poorly understood. In this study, we performed deep scRNA-seq on immune cells under the isolation in peripheral blood, cancer tissues, and nearby common tissues of four HCC cases and two non-cancer controls, and 212,494 cells were included in the analysis. We identified distinct immune cell subtypes, enriched pathways for differential genes, and delineated associated developmentally relevant trajectories. APOC1 was found over-expressed in tumor-associated macrophages (TAMs) of HCC tissues than in normal tissues. Inhibition of APOC1 reversed the M2 phenotype to the M1 phenotype via the ferroptosis pathway in TAMs from HCC. Tumors in APOC1 −/− C57BL/6 mice demonstrated consistent attenuation compared to wild-type (WT) mice. Mass spectrometry results revealed that the relative proportion of M2 macrophages, B cells, and CD4+ T cells in the APOC1 −/− group exhibited a downward expression compared with the WT group, whereas CD8+ T cells, M1 macrophages, and NK cells exhibited an upward trend. Finally, APOC1 was found to be negatively correlated with the expression of PD1/PD-L1 in human HCC samples. In conclusion, the present study demonstrated that inhibiting APOC1 can promote the transformation of M2 macrophages into M1 macrophages via the ferroptosis pathway, thereby reshaping the tumor immune microenvironment and improving the anti-PD1 immunotherapy for HCC, providing a new strategy for improving the therapeutic effect of anti-PD1, and bringing new hope to HCC patients.

415.6: Exploring Cell-Specific Mechanisms of Ischemia/Reperfusion Injury Mediated Reactivation of Cytomegalovirus From Latency in the Orthotopic Mouse Lung Transplantation

Purpose: Cytomegalovirus (CMV) is the most common opportunistic infection in lung transplant recipients, with the highest risk seen in CMV seronegative recipients (R-) of seropositive organs (D+). This study aims to explore key molecular pathways responsible for transplant-mediated CMV reactivation by using single-cell RNA sequencing (scRNA-seq) in a mouse model of syngeneic D+/R- lung transplantation. Methods: Left lungs from naïve (D-) mice or MCMV latently infected (D+) mice were transplanted to syngeneic R- recipients, while the contralateral right lungs served as controls. Lung tissues from the transplants at day 2 post-transplant (POD) or controls were harvested for viral RNA analysis and single cell isolation. CD31+ and CD45+ enriched single cell suspensions were processed using 10X Genomics, followed by sequencing. The sequenced data were processed using Cell Ranger pipeline and Seurat. Additional transplants were treated with small molecule Myd88 inhibitor to determine whether innate immunity plays a role in transplant induced CMV reactivation. Results: MCMV IE-1 mRNA transcripts were significantly upregulated at POD 2, but were not detectable in the controls, indicating that transcriptional activation is induced in the early phase of transplant and ischemia/reperfusion (I/R) injury associated with the transplant procedures is an important contributing factor. In addition, viral DNA amplification was detected in the salivary glands of D+/R- recipients at POD14, confirming that transplant of a D+ graft results in viral reactivation and dissemination. These data support the mouse lung transplant model as a viable approach to study mechanisms of CMV reactivation. Data from scRNAseq analysis showed distinct lung and immune cell clusters in lung transplants and controls. There were minimal differences in transcriptome landscapes between D- and D+ lungs prior to transplant (controls). In contrast, the differences were prominent between lungs from D-/R- transplant vs D+/R- lung grafts in the myeloid populations [e.g. neutrophils, macrophages (Macs)] and endothelial cells. Gene expression of Macs showed more differences between transplant lungs and control lungs than any endothelial cells or neutrophils. Pathway analysis of differentially expressed genes for myeloid cell types showed several significant immune response pathways including MIF regulation of innate immunity and communication between innate and adaptive immune cells. Expression of Myd88 and c-fos were increased in the lung grafts regardless of latent MCMV infection. Furthermore, our preliminary study using a Myd88 inhibitor showed a trend of CMV viral load reduction in lung grafts. Conclusions: Early I/R injury following lung transplant resulted significant alterations of transcriptome landscape unique to different cell types. Myd88/AP-1 plays a critical role in CMV reactivation; thus targeting Myd88 has a great therapeutic potential to prevent I/R injury-mediated CMV reactivation. NIH NIAID R21AI163876. NIH/NIAID P01AI112522.

699P The molecular and immune landscape of recurrent head and neck squamous cell carcinoma (HNSCC) in patients undergoing definitive therapy

Patients with recurrent head and neck squamous cell carcinoma (HNSCC) have dismal outcomes despite advances in salvage definitive therapies. Aiming to expand our understanding of recurrent HNSCC, we characterize the molecular and immune landscape of HNSCC patients enrolled in a Phase II trial of adjuvant nivolumab after salvage resection (NCT03355560). Tissue-based DNA and RNA sequencing utilizing a commercially available CLIA-certified assay (Caris Life Sciences) were used to analyze tissue samples from HNSCC patients enrolled in the trial. NGS, WES and WTS was performed on 37 tumors. TMB cutoff point of ≥10 was used. PD-L1 expression was tested by IHC (22c3 antibody, ≥1 CPS being positive). Statistical significance was determined using Fisher’s-Exact or X2 test with Benjamini-Hochberg correction. Gene expression was analyzed using the Limma R package. Immune cell abundance was measured using Microenvironment Cell Populations-counter (MCP) method. In patients with recurrent H&N cancers treated with Nivolumab, distinct immune cell abundance and molecular alterations were not found between patients who developed a relapsed disease (n= 11) and those who did not (n= 26). Molecular alterations in TP53 (86%, 100%, 0%; q < 0.01), P1K3CA (0%, 0%, 57%; q< 0.01) and p16 IHC (8%, 0%, 86%; q < 0.01) were detected in tumors from the larynx, oral cavity, and oropharynx. Myeloid dendritic cell (FC= 1.3; p < 0.05) and endothelial cell (FC = 1.2; p < 0.05) abundance were increased in patients who received RT only vs ChemRT. ABCA10 gene expression decreased in patients treated previously with ChemRT (logFC = -1.4; p < 0.05), compared to RT only. TMB-High tumors exhibited increased SNRPFP1 gene expression (logFC = 1.2; p < 0.01). Well differentiated tumors showed increased gene expression in SEMA3G (logFC = 1.4; p < 0.05) and HS3ST6 (logFC = 1.4; p < 0.05) genes compared to poorly/moderately differentiated tumors. Recurrent HNSCC cancers manifest heterogeneous molecular and immune profiles on subgroups analysis with no clear marker to predict response to Nivolumab in the adjuvant setting. Larger prospective trials are needed to explore this area further.

Patients with Lung Cancer of Different Racial Backgrounds Harbor Distinct Immune Cell Profiles.

We report biological racial differences among patients with lung cancer where Caucasians present a hot tumor microenvironment compared with cold tumor in AAs. Treatment plans should be customized to maximize therapeutic outcomes.

Classification of stomach adenocarcinoma based on fatty acid metabolism-related genes frofiling.

Background: Fatty acid metabolism (FAM)-related genes play a key role in the development of stomach adenocarcinoma (STAD). Although immunotherapy has led to a paradigm shift in STAD treatment, the overall response rate of immunotherapy for STAD is low due to heterogeneity of the tumor immune microenvironment (TIME). How FAM-related genes affect TIME in STAD remains unclear. Methods: The univariate Cox regression analysis was performed to screen prognostic FAM-related genes using transcriptomic profiles of the Cancer Genome Atlas (TCGA)-STAD cohort. Next, the consensus clustering analysis was performed to divide the STAD cohort into two groups based on the 13 identified prognostic genes. Then, gene set enrichment analysis (GSEA) was carried out to identify enriched pathways in the two groups. Furthermore, we developed a prognostic signature model based on 7 selected prognostic genes, which was validated to be capable in predicting the overall survival (OS) of STAD patients using the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses. Finally, the “Estimation of STromal and Immune cells in MAlignant Tumours using Expression data” (ESTIMATE) algorithm was used to evaluate the stromal, immune, and ESTIMATE scores, and tumor purity of each STAD sample. Results: A total of 13 FAM-related genes were identified to be significantly associated with OS in STAD patients. Two molecular subtypes, which we named Group 1 and Group 2, were identified based on these FAM-related prognostic genes using the consensus clustering analysis. We showed that Group 2 was significantly correlated with poor prognosis and displayed higher programmed cell death ligand 1 (PD-L1) expressions and distinct immune cell infiltration patterns. Furthermore, using GSEA, we showed that apoptosis and HCM signaling pathways were significantly enriched in Group 2. We constructed a prognostic signature model using 7 selected FAM-related prognostic genes, which was proven to be effective for prediction of STAD (HR = 1.717, 95% CI = 1.105–1.240, p < 0.001). After classifying the patients into the high- and low-risk groups based on our model, we found that patients in the high-risk group tend to have more advanced T stages and higher tumor grades, as well as higher immune scores. We also found that the risk scores were positively correlated with the infiltration of certain immune cells, including resting dendritic cells (DCs), and M2 macrophages. We also demonstrated that elevated expression of gamma-glutamyltransferase 5 (GGT5) is significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and increased immune cell infiltration, suggesting that STAD patients with high GGT5 expression in the tumor tissues might have a better response to immunotherapy. Conclusion: FAM-related genes play critical roles in STAD prognosis by shaping the TIME. These genes can regulate the infiltration of various immune cells and thus are potential therapeutic targets worthy of further investigation. Furthermore, GGT5 was a promising marker for predicting immunotherapeutic response in STAD patients.

HLJ1 amplifies endotoxin-induced sepsis severity by promoting IL-12 heterodimerization in macrophages.

Heat shock protein (HSP) 40 has emerged as a key factor in both innate and adaptive immunity, whereas the role of HLJ1, a molecular chaperone in HSP40 family, in modulating endotoxin-induced sepsis severity is still unclear. During lipopolysaccharide (LPS)-induced endotoxic shock, HLJ1 knockout mice shows reduced organ injury and IFN-γ (interferon-γ)-dependent mortality. Using single-cell RNA sequencing, we characterize mouse liver nonparenchymal cell populations under LPS stimulation, and show that HLJ1 deletion affected IFN-γ-related gene signatures in distinct immune cell clusters. In CLP models, HLJ1 deletion reduces IFN-γ expression and sepsis mortality rate when mice are treated with antibiotics. HLJ1 deficiency also leads to reduced serum levels of IL-12 in LPS-treated mice, contributing to dampened production of IFN-γ in natural killer cells but not CD4+ or CD8+ T cells, and subsequently to improved survival rate. Adoptive transfer of HLJ1-deleted macrophages into LPS-treated mice results in reduced IL-12 and IFN-γ levels and protects the mice from IFN-γ-dependent mortality. In the context of molecular mechanisms, HLJ1 is an LPS-inducible protein in macrophages and converts misfolded IL-12p35 homodimers to monomers, which maintains bioactive IL-12p70 heterodimerization and secretion. This study suggests HLJ1 causes IFN-γ-dependent septic lethality by promoting IL-12 heterodimerization, and targeting HLJ1 has therapeutic potential in inflammatory diseases involving activated IL-12/IFN-γ axis.

The Prognostic Value of AT-Rich Interaction Domain (ARID) Family Members in Patients with Hepatocellular Carcinoma

Objective Hepatocellular carcinoma (HCC) is one of the most lethal malignancies with a poor prognosis. The AT-rich interaction domain (ARID) family plays an essential regulatory role in the pathogenesis and progression of cancers. This study aims to evaluate the prognostic value and clinical significance of human ARID family genes in HCC. Methods ONCOMINE and The Cancer Genome Atlas (TCGA) databases were employed to retrieve ARIDs expression profile and clinicopathological information of HCC. Kaplan–Meier plotter and MethSurv were applied to the survival analysis of patients with HCC. CBioPortal was used to analyze genetic mutations of ARIDs. Gene Expression Profiling Interactive Analysis (GEPIA) and Metascape were used to perform hub gene identification and functional enrichment. Results Expression levels of 11 ARIDs were upregulated in HCC, and 2 ARIDs were downregulated. Also, 4 ARIDs and 5 ARIDs were correlated with pathologic stages and histologic grades, respectively. Furthermore, higher expression of ARID1A, ARID1B, ARID2, ARID3A, ARID3B, ARID5B, KDM5A, KDM5B, KDM5C, and JARID2 was remarkably correlated with worse overall survival of patients with HCC, and the high ARID3C/KDM5D expression was related to longer overall survival. Multivariate Cox analysis indicated that ARID3A, KDM5C, and KDM5D were independent risk factors for HCC prognosis. Moreover, ARIDs mutations and 127 CpGs methylation in all ARIDs were observed to be significantly associated with the prognosis of HCC patients. Besides, our data showed that ARIDs could regulate tumor-related pathways and distinct immune cells in the HCC microenvironment. Conclusions ARIDs present the potential prognostic value for HCC. Our findings suggest that ARID3A, KDM5C, and KDM5D may be the prognostic biomarkers for patients with HCC.

Integrated analysis of senescence-associated genes in pancreatic ductal adenocarcinoma.

Background: Cellular senescence plays a critical role in the occurrence and development, and immune modulation of cancer. This research primarily investigated the role of senescence-associated genes (SAGs) in the survival and tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC). Methods: From the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, the gene expression profiles and clinical data of PDAC samples were downloaded. SAGs in the TCGA cohort were used to build a novel prognostic model and validated in the ICGC cohort. The relationship of signature with the immune landscape, tumor mutational burden (TMB), as well as the sensitivity of different therapies, was explored. Moreover, a nomogram was developed to predict the overall survival of PDAC patients. Results: A prognostic signature was constructed on basis of three SAGs, and patients in the low-risk score group had a longer survival time. The accuracy of the signature to distinguish different score groups was confirmed through principal component analysis (PCA) and the Receiver operator curves curve. The mRNA expression of the three signature genes was also verified in normal pancreatic and PDAC cell lines by RT-qPCR. The signature could independently predict the prognosis of PDAC patients and had broad applicability. Meanwhile, the nomogram predicted that 1- and 3-years survival rates were in good agreement with the observed overall survival rates. Low-risk patients had lower tumor mutational burden, and low-TMB patients had a better prognosis. Low- and high-risk patients exhibit distinct immune cell infiltration and immune checkpoint changes. By further analyzing the risk score, patients in the low-risk group were more responsive to immunotherapy and a variety of commonly used chemotherapeutic drugs. Conclusion: The prognostic signature can well predict the prognosis and assess the possibility of immunotherapy in personalized PDAC treatment.

Single-cell transcriptomic atlas reveals distinct immunological responses between COVID-19 vaccine and natural SARS-CoV-2 infection.

To control the ongoing coronavirus disease‐2019 (COVID‐19) pandemic, CoronaVac (Sinovac), an inactivated vaccine, has been granted emergency use authorization by many countries. However, the underlying mechanisms of the inactivated COVID‐19 vaccine‐induced immune response remain unclear, and little is known about its features compared to (Severe acute respiratory syndrome coronavirus 2) SARS‐CoV‐2 infection. Here, we implemented single‐cell RNA sequencing (scRNA‐seq) to profile longitudinally collected PBMCs (peripheral blood mononuclear cells) in six individuals immunized with CoronaVac and compared these to the profiles of COVID‐19 infected patients from a Single Cell Consortium. Both inactivated vaccines and SARS‐CoV‐2 infection altered the proportion of different immune cell types, caused B cell activation and differentiation, and induced the expression of genes associated with antibody production in the plasma. The inactivated vaccine and SARS‐COV‐2 infection also caused alterations in peripheral immune activity such as interferon response, inflammatory cytokine expression, innate immune cell apoptosis and migration, effector T cell exhaustion and cytotoxicity, however, the magnitude of change was greater in COVID‐19 patients, especially those with severe disease, than in immunized individuals. Further analyses revealed a distinct peripheral immune cell phenotype associated with CoronaVac immunization (HLA class II upregulation and IL21R upregulation in naïve B cells) versus SARS‐CoV‐2 infection (HLA class II downregulation and IL21R downregulation in naïve B cells from severe disease individuals). There were also differences in the expression of important genes associated with proinflammatory cytokines and thrombosis. In conclusion, this study provides a single‐cell atlas of the systemic immune response to CoronaVac immunization and revealed distinct immune responses between inactivated vaccines and SARS‐CoV‐2 infection.

Oncogenic signaling pathway mediated by Notch pathway-related genes induces immunosuppression and immunotherapy resistance in hepatocellular carcinoma.

The Notch pathway is a highly conserved signaling pathway involved in the regulation of cell proliferation and differentiation. However, the relationships between Notch pathway-related genes (NPRGs), immunosuppression, and immunotherapy resistance of hepatocellular carcinoma (HCC) remain unclear. Gene expression data and clinical information were extracted from GSE14520, GSE36376, GSE76427, LIRI-JP, TCGA-LIHC, GSE20140, GSE27150, and IMvigor210 datasets. A consensus clustering analysis based on 10 NPRGs was performed to determine the molecular subtypes, and then a notchScore was constructed based on differentially expressed and prognostic genes between molecular subtypes. Two molecular subgroups with significantly distinct survival and immune cell infiltration were identified. Then, a notchScore was constructed to quantify the Notch index of each patient with HCC. Next, we investigated the correlations between the clinical characteristics and the notchScore using logistic regression. Furthermore, multivariate Cox analysis showed that a high notchScore was an independent predictor of poor overall survival (OS) in the TCGA and LIRI-JP datasets and was associated with higher pathological stages. Additionally, a high notchScore was associated with higher immune cells, higher ESTIMATE score, higher immune score, higher stromal score, higher immune checkpoint, and lower tumor purity, which was consistent with the "immunity tidal model theory." Importantly, a high notchScore was sensitive to immunotherapy. Additionally, GSEA indicated that several GO and KEGG items associated with apoptosis, immune-related pathways, and cell cycle signal pathways were significantly enriched in the high notchScore phenotype pathway. Our findings propose that a high notchScore is a prognostic biomarker and correlates with immune infiltration and sensitivity to immunotherapy in HCC.

059 Enhanced and suppressed tumor immunity is mediated by IL-1R1 on distinct immune cells

Inflammation is necessary for immune defense against pathogens and a functional antitumor immune response, but chronic inflammation promotes tumor growth and enables tumors to escape from immune-mediated destruction. Recently, we and others demonstrated that deficiency of IL1β strongly favors antitumor immunity, and multiple clinical trials involving antibody mediated IL1β blockade in multiple cancers are underway. The mechanism, however, remains obscure. We demonstrated that intact IL1α signaling was required for IL1β blockade-induced antitumor immunity, leading to the hypothesis that its interaction with the IL1 type I receptor (IL1R1) and subsequent signaling was required for the antitumor immune response.

Recognition of Glycometabolism-Associated lncRNAs as Prognosis Markers for Bladder Cancer by an Innovative Prediction Model.

The alteration of glycometabolism is a characteristic of cancer cells. Long non-coding RNAs (lncRNAs) have been documented to occupy a considerable position in glycometabolism regulation. This research aims to construct an effective prediction model for the prognosis of bladder cancer (BC) based on glycometabolism-associated lncRNAs (glyco-lncRNAs). Pearson correlation analysis was applied to get glyco-lncRNAs, and then, univariate cox regression analysis was employed to further filtrate survival time-associated glyco-lncRNAs. Multivariate cox regression analysis was utilized to construct the prediction model to divide bladder cancer (BC) patients into high- and low-risk groups. The overall survival (OS) rates of these two groups were analyzed using the Kaplan–Meier method. Next, gene set enrichment analysis and Cibersortx were used to explore the enrichment and the difference in immune cell infiltration, respectively. pRRophetic algorithm was applied to explore the relation between chemotherapy sensitivity and the prediction model. Furthermore, reverse transcriptase quantitative polymerase chain reaction was adopted to detect the lncRNAs constituting the prediction signature in tissues and urine exosomal samples of BC patients. A powerful model including 6 glyco-lncRNAs was proposed, capable of suggesting a risk score for each BC patient to predict prognosis. Patients with high-risk scores demonstrated a shorter survival time both in the training cohort and testing cohort, and the risk score could predict the prognosis without depending on the traditional clinical traits. The area under the receiver operating characteristic curve of the risk score was higher than that of other clinical traits (0.755 > 0.640, 0.485, 0.644, or 0.568). The high- and low-risk groups demonstrated very distinct immune cells infiltration conditions and gene set enriched terms. Besides, the high-risk group was more sensitive to cisplatin, docetaxel, and sunitinib. The expression of lncRNA AL354919.2 featured with an increase in low-grade patients and a decrease in T3-4 and Stage III–IV patients. Based on the experiment results, lncRNA AL355353.1, AC011468.1, and AL354919.2 were significantly upregulated in tumor tissues. This research furnishes a novel reference for predicting the prognosis of BC patients, assisting clinicians with help in the choice of treatment.

Heparanase is a prognostic biomarker independent of tumor purity and hypoxia based on bioinformatics and immunohistochemistry analysis of esophageal squamous cell carcinoma

BackgroundEsophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract with a poor prognosis. The tumor microenvironment (TME) is mainly composed of tumor cells, stromal cells, and immune cells and plays an important role in ESCC development. There are substantial differences in tumor purity among different parts of ESCC tissues, consisting of distinct immune and stromal cells and variations in the status of hypoxia. Thus, prognostic models of ESCC based on bioinformatic analysis of tumor tissues are unreliable.MethodDifferentially expressed genes (DEGs) independent of tumor purity and hypoxia were screened by Spearman correlation analysis of public ESCC cohorts. Subsequently, the DEGs were subjected to Cox regression analysis. Then, we constructed a protein–protein interaction (PPI) network of the DEGs using Cytoscape. Intersection analysis of the univariate Cox and PPI results indicated that heparanase (HPSE), an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains, was a predictive factor. Gene set enrichment analysis (GSEA) was used to reveal the potential function of HPSE, and single-cell sequencing data were analyzed to evaluate the distribution of HPSE in immune cells. Furthermore, a human ESCC tissue microarray was used to validate the expression and prognostic value of HPSE.ResultWe found that HPSE was downregulated in ESCC tissues and was not correlated with tumor purity or hypoxia status. HPSE is involved in multiple biological processes. ESCC patients with low HPSE expression in cancerous tissues exhibited poor prognosis.ConclusionsThese results indicate that low HPSE expression in cancerous tissues correlates with poor prognosis in patients with ESCC. HPSE is a novel prognostic biomarker independent of tumor purity and hypoxia status in ESCC.

DNA Methylation Profiling Identifies Subgroups of Lung Adenocarcinoma with Distinct Immune Cell Composition, DNA Methylation Age, and Clinical Outcome.

Lung adenocarcinoma (LUAD) is a clinically heterogeneous disease, which is highlighted by the unpredictable recurrence in low-stage tumors and highly variable responses observed in patients treated with immunotherapies, which cannot be explained by mutational profiles. DNA methylation-based classification and understanding of microenviromental heterogeneity may allow stratification into clinically relevant molecular subtypes of LUADs. We characterize the genome-wide DNA methylation landscape of 88 resected LUAD tumors. Exome sequencing focusing on a panel of cancer-related genes was used to genotype these adenocarcinoma samples. Bioinformatic and statistical tools, the immune cell composition, DNA methylation age (DNAm age), and DNA methylation clustering were used to identify clinically relevant subgroups. Deconvolution of DNA methylation data identified immunologically hot and cold subsets of LUADs. In addition, concurrent factors were analyzed that could affect the immune microenvironment, such as smoking history, ethnicity, or presence of KRAS or TP53 mutations. When the DNAm age was calculated, a lower DNAm age was correlated with the presence of a set of oncogenic drivers, poor overall survival, and specific immune cell populations. Unsupervised DNA methylation clustering identified six molecular subgroups of LUAD tumors with distinct clinical and microenvironmental characteristics. Our results demonstrate that DNA methylation signatures can stratify LUAD into clinically relevant subtypes, and thus such classification of LUAD at the time of resection may lead to better methods in predicting tumor recurrence and therapy responses.