Exploration of the immune response of grass carp (Ctenopharyngodon idellus) erythrocytes during bacterial infection.

In teleost blood, red blood cells (RBCs) are the most common type of cell, and they differ from mammalian RBCs in having a nucleus and other organelles. As nucleated cells, teleost RBCs contribute to the immune response against pathogens, but their antibacterial mechanism remains unclear. Here, we utilized RNA-Seq to analyze gene expression patterns of grass carp (Ctenopharyngodon idellus) RBCs (GcRBCs) stimulated by Aeromonas hydrophila, Escherichia coli, and Staphylococcus aureus. Our transcriptomic data showed that bacterial stimulation generated many differentially expressed genes (DEGs). Furthermore, several inflammatory pathways responded to bacterial activation, and the TLR, IL-17, and tumor necrosis factor (TNF) signaling pathways were significantly activated based on Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Furthermore, the findings of qRT-PCR showed markedly elevated expression of various cytokines, including IL-1ß, IL4, IL6, IL8, IL12, and TNFα, in GcRBCs after incubation with bacteria. Reactive oxygen species (ROS) production in GcRBCs was markedly increased after the cells were stimulated with the three bacteria, and the expression of superoxide dismutase, glutathione peroxidase, and antioxidant enzymes, including catalase, was altered. Flow cytometry analysis showed that the apoptosis rate of GcRBCs was enhanced after stimulation with the three bacteria for different times. In summary, our findings reveal that bacterial stimulation activates the immune response of GcRBCs by regulating ROS release, cytokine expression, and the antioxidant system, leading to apoptosis of GcRBCs.

Zika Virus Infection Induces Interleukin-1ß-Mediated Inflammatory Responses by Macrophages in the Brain of an Adult Mouse Model.

During the 2015-2016 Zika virus (ZIKV) epidemic, ZIKV-associated neurological diseases were reported in adults, including microcephaly, Guillain-Barre syndrome, myelitis, meningoencephalitis, and fatal encephalitis. However, the mechanisms underlying the neuropathogenesis of ZIKV infection are not yet fully understood. In this study, we used an adult ZIKV infection mouse model (Ifnar1-/-) to investigate the mechanisms underlying neuroinflammation and neuropathogenesis. ZIKV infection induced the expression of proinflammatory cytokines, including interleukin-1ß (IL-1ß), IL-6, gamma interferon, and tumor necrosis factor alpha, in the brains of Ifnar1-/- mice. RNA-seq analysis of the infected mouse brain also revealed that genes involved in innate immune responses and cytokine-mediated signaling pathways were significantly upregulated at 6 days postinfection. Furthermore, ZIKV infection induced macrophage infiltration and activation and augmented IL-1ß expression, whereas microgliosis was not observed in the brain. Using human monocyte THP-1 cells, we confirmed that ZIKV infection promotes inflammatory cell death and increases IL-1ß secretion. In addition, expression of the complement component C3, which is associated with neurodegenerative diseases and known to be upregulated by proinflammatory cytokines, was induced by ZIKV infection through the IL-1ß-mediated pathway. An increase in C5a produced by complement activation in the brains of ZIKV-infected mice was also verified. Taken together, our results suggest that ZIKV infection in the brain of this animal model augments IL-1ß expression in infiltrating macrophages and elicits IL-1ß-mediated inflammation, which can lead to the destructive consequences of neuroinflammation. IMPORTANCE Zika virus (ZIKV) associated neurological impairments are an important global health problem. Our results suggest that ZIKV infection in the mouse brain can induce IL-1ß-mediated inflammation and complement activation, thereby contributing to the development of neurological disorders. Thus, our findings reveal a mechanism by which ZIKV induces neuroinflammation in the mouse brain. Although we used adult type I interferon receptor IFNAR knockout (Ifnar1-/-) mice owing to the limited mouse models of ZIKV pathogenesis, our conclusions contributed to the understanding ZIKV-associated neurological diseases to develop treatment strategies for patients with ZIKV infection based on these findings.

Transcriptomic Signatures of Human Immunodeficiency Virus Post-Treatment Control.

Posttreatment controllers (PTCs) are rare HIV-infected individuals who can limit viral rebound after antiretroviral therapy interruption (ATI), but the mechanisms of this remain unclear. To investigate these mechanisms, we quantified various HIV RNA transcripts (via reverse transcription droplet digital PCR [RT-ddPCR]) and cellular transcriptomes (via RNA-seq) in blood cells from PTCs and noncontrollers (NCs) before and two time points after ATI. HIV transcription initiation did not significantly increase after ATI in PTCs or in NCs, whereas completed HIV transcripts increased at early ATI in both groups and multiply-spliced HIV transcripts increased only in NCs. Compared to NCs, PTCs showed lower levels of HIV DNA, more cell-associated HIV transcripts per total RNA at all times, no increase in multiply-spliced HIV RNA at early or late ATI, and a reduction in the ratio of completed/elongated HIV RNA after early ATI. NCs expressed higher levels of the IL-7 pathway before ATI and expressed higher levels of multiple cytokine, inflammation, HIV transcription, and cell death pathways after ATI. Compared to the baseline, the NCs upregulated interferon and cytokine (especially TNF) pathways during early and late ATI, whereas PTCs upregulated interferon and p53 pathways only at early ATI and downregulated gene translation during early and late ATI. In NCs, viral rebound after ATI is associated with increases in HIV transcriptional completion and splicing, rather than initiation. Differences in HIV and cellular transcription may contribute to posttreatment control, including an early limitation of spliced HIV RNA, a delayed reduction in completed HIV transcripts, and the differential expression of the IL-7, p53, and TNF pathways. IMPORTANCE The findings presented here provide new insights into how HIV and cellular gene expression change after stopping ART in both noncontrollers and posttreatment controllers. Posttreatment control is associated with an early ability to limit increases in multiply-spliced HIV RNA, a delayed (and presumably immune-mediated) ability to reverse an initial rise in processive/completed HIV transcripts, and multiple differences in cellular gene expression pathways. These differences may represent correlates or mechanisms of posttreatment control and may provide insight into the development and/or monitoring of therapeutic strategies that are aimed at a functional HIV cure.

Alterações sistêmicas na assinatura do ciclo celular de pacientes com COVID-19 / Systemic changes in the cell cycle signature of patients with COVID-19

Com base nas perturbações fosfoproteômicas de moléculas associadas ao ciclo celular em células infectadas pelo coronavírus causador da síndrome respiratória aguda grave (SARSCoV)-2, a hipótese de inibidores do ciclo celular como uma terapia potencial para a doença de coronavírus 2019 (COVID-19) foi proposta. No entanto, o cenário das alterações do ciclo celular em COVID-19 permanece inexplorado. Aqui, realizamos uma análise integrativa de sistemas imunológicos de proteoma publicamente disponível (espectrometria de massa) e dados de transcriptoma (sequenciamento de RNA em massa e de célula única [scRNAseq]), com o objetivo de caracterizar mudanças globais na assinatura do ciclo celular de pacientes com COVID-19. Além de módulos de co-expressão de genes significativos enriquecidos associados ao ciclo celular, encontramos uma rede interconectada de proteínas diferencialmente expressas associadas ao ciclo celular (DEPs) e genes (DEGs) integrando dados moleculares de 1.480 indivíduos (974 pacientes infectados por SARS-CoV-2 e 506 controles [controles saudáveis ou indivíduos com outras doenças respiratórias]). Entre esses DEPs e DEGs estão várias ciclinas (CCNs), ciclo de divisão celular (CDCs), quinases dependentes de ciclinas (CDKs) e proteínas de manutenção de minicromossomos (MCMs). Embora os pacientes com COVID-19 compartilhem parcialmente o padrão de expressão de algumas moléculas associadas ao ciclo celular com outras doenças respiratórias, eles exibiram uma expressão significativamente maior de moléculas associadas ao ciclo celular relacionadas à gravidade da doença. Notavelmente, a assinatura do ciclo celular predominou nos leucócitos do sangue dos pacientes, mas não nas vias aéreas superiores. Os dados de scRNAseq de 229 indivíduos (159 pacientes com COVID- 19 e 70 controles) revelaram que as alterações das assinaturas do ciclo celular predominam nas células B, T e NK. Esses resultados fornecem uma compreensão global única das alterações nas moléculas associadas ao ciclo celular em pacientes com COVID-19, sugerindo novas vias putativas para intervenção terapêutica

Based on phosphoproteomics perturbations of cell cycle-associated molecules in severe acute respiratory syndrome coronavirus (SARS-CoV)-2-infected cells, the hypothesis of cell cycle inhibitors as a potential therapy for Coronavirus disease 2019 (COVID-19) has been proposed. However, the landscape of cell cycle alterations in COVID-19 remains mostly unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome (mass spectrometry) and transcriptome data (bulk and single-cell RNA sequencing [scRNAseq]), aiming to characterize global changes in the cell cycle signature of COVID-19 patients. Beyond significant enriched cell cycle-associated gene co-expression modules, we found an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating molecular data of 1,480 individuals (974 SARS-CoV- 2 infected patients and 506 controls [either healthy controls or individuals with other respiratory illness]). Among these DEPs and DEGs are several cyclins (CCNs), cell division cycle (CDCs), cyclin-dependent kinases (CDKs), and mini-chromosome maintenance proteins (MCMs). Although COVID-19 patients partially shared the expression pattern of some cell cycleassociated molecules with other respiratory illnesses, they exhibited a significantly higher expression of cell cycle-associated molecules associated with disease severity. Notably, the cell cycle signature predominated in the patients blood leukocytes but not in the upper airways. The scRNAseq data from 229 individuals (159 COVID-19 patients and 70 controls) revealed that the alterations of cell cycle signatures predominate in B, T, and NK cells. These results provide a unique global comprehension of the alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention

Prognostic value and immune relevancy of a combined autophagy-, apoptosis- and necrosis-related gene signature in glioblastoma.

BACKGROUND: Glioblastoma (GBM) is considered the most malignant and devastating intracranial tumor without effective treatment. Autophagy, apoptosis, and necrosis, three classically known cell death pathways, can provide novel clinical and immunological insights, which may assist in designing personalized therapeutics. In this study, we developed and validated an effective signature based on autophagy-, apoptosis- and necrosis-related genes for prognostic implications in GBM patients. METHODS: Variations in the expression of genes involved in autophagy, apoptosis and necrosis were explored in 518 GBM patients from The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox analysis were performed to construct a combined prognostic signature. Kaplan-Meier survival, receiver-operating characteristic (ROC) curves and Cox regression analyses based on overall survival (OS) and progression-free survival (PFS) were conducted to estimate the independent prognostic performance of the gene signature. The Chinese Glioma Genome Atlas (CGGA) dataset was used for external validation. Finally, we investigated the differences in the immune microenvironment between different prognostic groups and predicted potential compounds targeting each group. RESULTS: A 16-gene cell death index (CDI) was established. Patients were clustered into either the high risk or the low risk groups according to the CDI score, and those in the low risk group presented significantly longer OS and PFS than the high CDI group. ROC curves demonstrated outstanding performance of the gene signature in both the training and validation groups. Furthermore, immune cell analysis identified higher infiltration of neutrophils, macrophages, Treg, T helper cells, and aDCs, and lower infiltration of B cells in the high CDI group. Interestingly, this group also showed lower expression levels of immune checkpoint molecules PDCD1 and CD200, and higher expression levels of PDCD1LG2, CD86, CD48 and IDO1. CONCLUSION: Our study proposes that the CDI signature can be utilized as a prognostic predictor and may guide patients' selection for preferential use of immunotherapy in GBM.

SLAMF7 engagement superactivates macrophages in acute and chronic inflammation.

Macrophages regulate protective immune responses to infectious microbes, but aberrant macrophage activation frequently drives pathological inflammation. To identify regulators of vigorous macrophage activation, we analyzed RNA-seq data from synovial macrophages and identified SLAMF7 as a receptor associated with a superactivated macrophage state in rheumatoid arthritis. We implicated IFN-γ as a key regulator of SLAMF7 expression and engaging SLAMF7 drove a strong wave of inflammatory cytokine expression. Induction of TNF-α after SLAMF7 engagement amplified inflammation through an autocrine signaling loop. We observed SLAMF7-induced gene programs not only in macrophages from rheumatoid arthritis patients but also in gut macrophages from patients with active Crohn's disease and in lung macrophages from patients with severe COVID-19. This suggests a central role for SLAMF7 in macrophage superactivation with broad implications in human disease pathology.

Single-cell transcriptomics reveals a low CD8+ T cell infiltrating state mediated by fibroblasts in recurrent renal cell carcinoma.

PURPOSE: Recurrent renal cell carcinoma(reRCC) is associated with poor prognosis and the underlying mechanism is not yet clear. A comprehensive understanding of tumor microenvironment (TME) of reRCC may aid in designing effective anticancer therapies, including immunotherapies. Single-cell transcriptomics holds great promise for investigating the TME, however, this technique has not been used in reRCC. Here, we aimed to explore the difference in the TME and gene expression pattern between primary RCC (pRCC) and reRCC at single-cell level. EXPERIMENTAL DESIGN: We performed single-cell RNA sequencing analyses of 32,073 cells from 2 pRCC, 2 reRCC, and 3 adjacent normal kidney samples. 41 pairs of pRCC and reRCC samples were collected as a validation cohort to assess differences observed in single-cell sequencing. The prognostic significance of related cells and markers were studied in 47 RCC patients underwent immunotherapy. The function of related cells and markers were validated via in vitro and in vivo experiments. RESULTS: reRCC had reduced CD8+ T cells but increased cancer-associated fibroblasts (CAFs) infiltration compared with pRCC. Reduced CD8+ T cells and increased CAFs infiltration were significantly associated with a worse response from immunotherapy. Remarkably, CAFs showed substantial expression of LGALS1 (Gal1). In vitro, CAFs could induce CD8+ T cells apoptosis via Gal1. In vivo, knockdown of Gal1 in CAFs suppressed tumor growth, increased CD8+ T cells infiltration, reduced the proportion of apoptotic CD8+ T cells and enhanced the efficacy of immunotherapy. CONCLUSIONS: We delineated the heterogeneity of reRCC and highlighted an innovative mechanism that CAFs acted as a suppressor of CD8+ T cells via Gal1. Targeting Gal1 combined with anti-PD1 showed promising efficacy in treating RCC.

Digital gene expression analysis of NSCLC-patients reveals strong immune pressure, resulting in an immune escape under immunotherapy.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are currently one of the most promising therapy options in the field of oncology. Although the first pivotal ICI trial results were published in 2011, few biomarkers exist to predict their therapy outcome. PD-L1 expression and tumor mutational burden (TMB) were proven to be sometimes-unreliable biomarkers. We have previously suggested the analysis of processing escapes, a qualitative measurement of epitope structure alterations under immune system pressure, to provide predictive information on ICI response. Here, we sought to further validate this approach and characterize interactions with different forms of immune pressure. METHODS: We identified a cohort consisting of 48 patients with advanced non-small cell lung cancer (NSCLC) treated with nivolumab as ICI monotherapy. Tumor samples were subjected to targeted amplicon-based sequencing using a panel of 22 cancer-associated genes covering 98 mutational hotspots. Altered antigen processing was predicted by NetChop, and MHC binding verified by NetMHC. The NanoString nCounter® platform was utilized to provide gene expression data of 770 immune-related genes. Patient data from 408 patients with NSCLC were retrieved from The Cancer Genome Atlas (TCGA) as a validation cohort. RESULTS: The two immune escape mechanisms of PD-L1 expression (TPS score) (n = 18) and presence of altered antigen processing (n = 10) are mutually non-exclusive and can occur in the same patient (n = 6). Both mechanisms have exclusive influence on different genes and pathways, according to differential gene expression analysis and gene set enrichment analysis, respectively. Interestingly, gene expression patterns associated with altered processing were enriched in T cell and NK cell immune activity. Though both mechanisms influence different genes, they are similarly linked to increased immune activity. CONCLUSION: Pressure from the immune system will lay the foundations for escape mechanisms, leading to acquisition of resistance under therapy. Both PD-L1 expression and altered antigen processing are induced similarly by pronounced immunoactivity but in different context. The present data help to deepen our understanding of the underlying mechanisms behind those immune escapes.

Early Changes in Immune Cell Count, Metabolism, and Function Following Sleeve Gastrectomy: A Prospective Human Study.

OBJECTIVE: To characterize longitudinal changes in blood biomarkers, leukocyte composition, and gene expression following laparoscopic sleeve gastrectomy (LSG). BACKGROUND: LSG is an effective treatment for obesity, leading to sustainable weight loss and improvements in obesity-related comorbidities and inflammatory profiles. However, the effects of LSG on immune function and metabolism remain uncertain. METHODS: Prospective data were collected from 23 enrolled human subjects from a single institution. Parameters of weight, comorbidities, and trends in blood biomarkers and leukocyte subsets were observed from preoperative baseline to 1 year postsurgery in 3-month follow-up intervals. RNA sequencing was performed on pairs of whole blood samples from the first 6 subjects of the study (baseline and 3 months postsurgery) to identify genome-wide gene expression changes associated with undergoing LSG. RESULTS: LSG led to a significant decrease in mean total body weight loss (18.1%) at 3 months and among diabetic subjects a reduction in hemoglobin A1c. Improvements in clinical inflammatory and hormonal biomarkers were demonstrated as early as 3 months after LSG. A reduction in neutrophil-lymphocyte ratio was observed, driven by a reduction in absolute neutrophil counts. Gene set enrichment analyses of differential whole blood gene expression demonstrated that after 3 months LSG induced transcriptomic changes not only in inflammatory cytokine pathways but also in several key metabolic pathways related to energy metabolism. CONCLUSIONS: LSG induces significant changes in the composition and metabolism of immune cells as early as 3 months postoperatively. Further evaluation is required of bariatric surgery's effects on immunometabolism and the consequences for host defense and metabolic disease.

Glucocorticoid-induced Fingerprints on Visceral Adipose Tissue Transcriptome and Epigenome.

CONTEXT: Chronic glucocorticoid (GC) overexposure, resulting from endogenous Cushing's syndrome (CS) or exogenous GC therapy, causes several adverse outcomes, including persistent central fat accumulation associated with a low-grade inflammation. However, no previous multiomics studies in visceral adipose tissue (VAT) from patients exposed to high levels of unsuppressed GC during active CS or after remission are available yet. OBJECTIVE: To determine the persistent VAT transcriptomic alterations and epigenetic fingerprints induced by chronic hypercortisolism. METHODS: We employed a translational approach combining high-throughput data on endogenous CS patients and a reversible CS mouse model. We performed RNA sequencing and chromatin immunoprecipitation sequencing on histone modifications (H3K4me3, H3K27ac, and H3K27me3) to identify persistent transcriptional and epigenetic signatures in VAT produced during active CS and maintained after remission. RESULTS: VAT dysfunction was associated with low-grade proinflammatory status, macrophage infiltration, and extracellular matrix remodeling. Most notably, chronic hypercortisolism caused a persistent circadian rhythm disruption in VAT through core clock genes modulation. Importantly, changes in the levels of 2 histone modifications associated to gene transcriptional activation (H3K4me3 and H3K27ac) correlated with the observed differences in gene expression during active CS and after CS remission. CONCLUSION: We identified for the first time the persistent transcriptional and epigenetic signatures induced by hypercortisolism in VAT, providing a novel integrated view of molecular components driving the long-term VAT impairment associated with CS.

TLR2 and TLR4 Signaling Pathways and Gastric Cancer: Insights from Transcriptomics and Sample Validation

Background: Pattern recognition receptors, especially toll-like receptors (TLRs), as the first line of defense for pathogen detection, were found to be associated with H.¬ pylori infection and gastric cancer (GC). However, the expression levels of TLRs, i.e. TLR2 and TLR4, as the main receptors sensed by H.¬ pylori, still remain largely ambiguous. We aimed to investigate the patterns of key transcripts of TLR2 and TLR4 in 100 GC transcriptome data. Additionally, we evaluated TLR2 and TLR4 gene expressions in gastric biopsies of Iranian GC patients, in order to validate RNA-seq outputs. Methods: For this study, 100 runs of GC samples and controls were processed and analyzed using map read to reference. Differential gene expression method was used to distinguish between GC and normal samples in the expression of TLRs and other innate immune molecules. Also, using qRT-PCR assay, transcripts of TLRs molecules for 15 GC and 15 control samples were analyzed based on the analysis of variance and least significant differences. Results: The results clearly showed that all signaling pathways molecules of TLR4, especially TLR4 (p = 0.019), NF-κB (p ¬= 0.047), IL-1ß (p = 0.0096), and TNF-α (p = 0.048), were upregulated in a cancerous condition in different parts and at various stages of GC. Conclusion: Our findings suggested that molecules involved in inflammation, including TLR4 and its related pro-inflammatory cytokines, may be responsible for the development and progression of GC. Accordingly, the control of H. pylori infection reduces inflammation in the gastric system and can play an important role in preventing gastrointestinal disorders.

A novel model based on liquid-liquid phase separation-Related genes correlates immune microenvironment profiles and predicts prognosis of lung squamous cell carcinoma.

OBJECTIVE: The aim of the study was to construct and validate a robust prognostic model based on liquid-liquid phase separation (LLPS)-related genes in lung squamous cell carcinoma (LUSC). METHODS: The Cancer Genome Atlas dataset was used as the discovery set to identify the LLPS-related differentially expressed genes (DEGs) between LUSC and normal tissue. These DEGs were screened by the LASSO Cox regression analysis to identify the genes with nonzero coefficient, which were next included in the multivariate Cox regression analysis to construct the prediction model. The dataset GSE41271 was adopted as the validation set to verify the efficacy of the model. Enrichment analysis and the CIBERSORT were performed to illustrate potential immune mechanisms underlying the prediction model. RESULTS: A total of 48 LLPS-related genes were aberrantly expressed in LUSC. Among them, 7 genes were selected by the LASSO Cox regression analysis to construct the prediction model. Risk index (RI) was calculated according to the model for each patient. The prognosis was significantly different between the patients with high and low RI in the discovery set and the validation set (p < 0.001 and p = 0.028, respectively). The multivariate survival analysis confirmed RI as an independent prognostic factor in LUSC (in the discovery set: p < 0.001, HR = 2.643, 95% CI = 1.986-3.518; in the validation set: p = 0.042, HR = 2.144, 95% CI = 1.026-4.480). A series of pathways involving immune cells were found to be related to RI. The distribution pattern of immune cells and chemokines varied according to the value of RI. CONCLUSION: The prediction model based on LLPS-related genes was constructed and validated as a robust prognostic tool for LUSC using multiple datasets. LLPS might have an impact on LUSC through immune pathways.

Construction of a novel immune-related lncRNA signature and its potential to predict the immune status of patients with hepatocellular carcinoma.

BACKGROUND: The accuracy of existing biomarkers for predicting the prognosis of hepatocellular carcinoma (HCC) is not satisfactory. It is necessary to explore biomarkers that can accurately predict the prognosis of HCC. METHODS: In this study, original transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related long noncoding ribonucleic acids (irlncRNAs) were identified by coexpression analysis, and differentially expressed irlncRNA (DEirlncRNA) pairs were distinguished by univariate analysis. In addition, the least absolute shrinkage and selection operator (LASSO) penalized regression was modified. Next, the cutoff point was determined based on the area under the curve (AUC) and Akaike information criterion (AIC) values of the 5-year receiver operating characteristic (ROC) curve to establish an optimal model for identifying high-risk and low-risk groups of HCC patients. The model was then reassessed in terms of clinicopathological features, survival rate, tumor-infiltrating immune cells, immunosuppressive markers, and chemotherapy efficacy. RESULTS: A total of 1009 pairs of DEirlncRNAs were recognized in this study, 30 of these pairs were included in the Cox regression model for subsequent analysis. After regrouping according to the cutoff point, we could more effectively identify factors such as aggressive clinicopathological features, poor survival outcomes, specific immune cell infiltration status of tumors, high expression level of immunosuppressive biomarkers, and low sensitivity to chemotherapy drugs in HCC patients. CONCLUSIONS: The nonspecific expression level signature involved with irlncRNAs shows promising clinical value in predicting the prognosis of HCC patients.

Identification of Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma.

Accumulating evidence indicates that immunotherapy helped to improve the survival and quality-of-life of patients with lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC) besides chemotherapy and gene targeting treatment. This study aimed to develop immune-related gene signatures in LUAD and LUSC subtypes, respectively. LUAD and LUSC samples were divided into high- and low-abundance groups of immune cell infiltration (Immunity_H and Immunity_L) based on the abundance of immune cell infiltrations. The distribution of immune cells was significantly different between the high- and low-immunity subtypes in LUAD and LUSC samples. The differentially expressed genes (DEGs) between those two groups in LUAD and LUSC contain some key immune-related genes, such as PDL1, PD1, CTLA-4, and HLA families. The DEGs were enriched in multiple immune-related pathways. Furthermore, the seven-immune-related-gene-signature (CD1B, CHRNA6, CLEC12B, CLEC17A, CLNK, INHA, and SLC14A2) prognostic model-based high- and low-risk groups were significantly associated with LUAD overall survival and clinical characteristics. The eight-immune-related-gene-signature (C4BPB, FCAMR, GRAPL, MAP1LC3C, MGC2889, TRIM55, UGT1A1, and VIPR2) prognostic model-based high- and low-risk groups were significantly associated with LUSC overall survival and clinical characteristics. The prognostic models were tested as good ones by receiver operating characteristic, principal component analysis, univariate and multivariate analysis, and nomogram. The verifications of these two immune-related-gene-signature prognostic models showed consistency in the train and test cohorts of LUAD and LUSC. In addition, patients with LUAD in the low-risk group responded better to immunotherapy than those in the high-risk group. This study revealed two reliable immune-related-gene-signature models that were significantly associated with prognosis and tumor microenvironment cell infiltration in LUAD and LUSC, respectively. Evaluation of the integrated characterization of multiple immune-related genes and pathways could help to predict the response to immunotherapy and monitor immunotherapy strategies.

Immune landscape of advanced gastric cancer tumor microenvironment identifies immunotherapeutic relevant gene signature.

BACKGROUND: Advanced gastric cancer (AGC) is a disease with poor prognosis due to the current lack of effective therapeutic strategies. Immune checkpoint blockade treatments have shown effective responses in patient subgroups but biomarkers remain challenging. Traditional classification of gastric cancer (GC) is based on genomic profiling and molecular features. Therefore, it is critical to identify the immune-related subtypes and predictive markers by immuno-genomic profiling. METHODS: Single-sample gene-set enrichment analysis (ssGSEA) and ESTIMATE algorithm were used to identify the immue-related subtypes of AGC in two independent GEO datasets. Weighted gene co-expression network analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm were applied to identify hub-network of immune-related subtypes. Hub genes were confirmed by prognostic data of KMplotter and GEO datasets. The value of hub-gene in predicting immunotherapeutic response was analyzed by IMvigor210 datasets. MTT assay, Transwell migration assay and Western blotting were performed to confirm the cellular function of hub gene in vitro. RESULTS: Three immune-related subtypes (Immunity_H, Immunity_M and Immunity_L) of AGC were identified in two independent GEO datasets. Compared to Immunity_L, the Immuntiy_H subtype showed higher immune cell infiltration and immune activities with favorable prognosis. A weighted gene co-expression network was constructed based on GSE62254 dataset and identified one gene module which was significantly correlated with the Immunity_H subtype. A Hub-network which represented high immune activities was extracted based on topological features and Molecular Complex Detection (MCODE) algorithm. Furthermore, ADAM like decysin 1 (ADAMDEC1) was identified as a seed gene among hub-network genes which is highly associated with favorable prognosis in both GSE62254 and external validation datasets. In addition, high expression of ADAMDEC1 correlated with immunotherapeutic response in IMvigor210 datasets. In vitro, ADAMDEC1 was confirmed as a potential protein in regulating proliferation and migration of gastric cancer cell. Deficiency of ADAMDEC1 of gastric cancer cell also associated with high expression of PD-L1 and Jurkat T cell apoptosis. CONCLUSIONS: We identified immune-related subtypes and key tumor microenvironment marker in AGC which might facilitate the development of novel immune therapeutic targets.

Single-cell transcriptomic analysis reveals the critical molecular pattern of UV-induced cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) is the second most common nonmelanoma skin cancer characterized by high invasiveness, heterogeneity, and mainly occurs in the ultraviolet (UV)-exposed regions of the skin, but its pathogenesis is still unclear. Here, we generated single-cell transcriptome profiles for 350 cells from six primary UV-induced cSCCs, together with matched adjacent skin samples, and three healthy control skin tissues by single-cell RNA-sequencing technology based on Smart-seq2 strategy. A series of bioinformatics analyses and in vitro experiments were used to decipher and validate the critical molecular pattern of cSCC. Results showed that cSCC cells and normal keratinocytes were significantly distinct in gene expression and chromosomal copy number variation. Furthermore, cSCC cells exhibited 18 hallmark pathways of cancer by gene set enrichment analysis. Differential expression analysis demonstrated that many members belonging to S100 gene family, SPRR gene family, and FABP5 were significantly upregulated in cSCC cells. Further experiments confirmed their upregulation and showed that S100A9 or FABP5 knockdown in cSCC cells inhibited their proliferation and migration through NF-κB pathway. Taken together, our data provide a valuable resource for deciphering the molecular pattern in UV-induced cSCC at a single-cell level and suggest that S100A9 and FABP5 may provide novel targets for therapeutic intervention of cSCC in the future.

Transcriptome study of receptive endometrium in overweight and obese women shows important expression differences in immune response and inflammatory pathways in women who do not conceive.

Obesity and being overweight are growing worldwide health problems that also affect women of reproductive age. They impair women's fertility and are associated with lower IVF success rates. The mechanism by which increased body weight disrupts fertility has not yet been established. One possibility is that it affects the process of embryo implantation on the endometrial level. The purpose of our study was to determine the differences in enriched biological pathways in the endometrium of overweight and obese women undergoing IVF procedures. For this purpose, 14 patients (5 pregnant, 9 non-pregnant) were included in the study. Endometrial samples were obtained during the window of implantation and RNA sequencing was performed. There were no differences in general patient's and IVF cycle characteristics between pregnant and non-pregnant women. In the endometrial samples of women who did not conceive, pathways related to the immune response, inflammation, and reactive oxygen species production were over-expressed. Our findings show that the reason for implantation failure in overweight and obese women could lie in the excessive immune and inflammatory response at the endometrial level.

Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer.

Pancreatic cancer (PAAD) is one of the most malignant cancers and immune microenvironment has been proved to be involved in pathogenesis of PAAD. m6A modification, related to the expression of m6A regulators, participates in the development of multiple cancers. However, the correlation between m6A regulators and immune microenvironment was largely unknown in PAAD. And because of the small sample size of pancreatic cancer in the TCGA database, it is not enough to draw a convincing conclusion. In the present study, we downloaded seven pancreatic cancer datasets with survival data and removed batch effects among these datasets to be used as the PAAD cohort to analyze the immune landscape of PAAD and the expression pattern of m6A regulators and divided the integrated dataset into cluster 1 and cluster 2 by consensus clustering for m6A regulators. Lower m6A regulators were found to be related to higher immune cell infiltration and a better survival. Moreover, we identified six m6A regulators and constructed the prognostic signature of m6A regulators. Patients with low-risk score had a higher response to immune checkpoint inhibitor and a longer overall survival. To figure out the underlying mechanism, we analyzed the cancer immunity cycle, most altered genes, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) in risk subtypes. In summary, the present study proved m6A regulators modulated the PAAD immune microenvironment. And risk scores served as predictive indicator for immunotherapy and played a prognostic role for PAAD patients. Our study provided novel therapeutic targets to improve immunotherapy efficacy.

Prognostic and immune infiltration signatures of proteasome 26S subunit, non-ATPase (PSMD) family genes in breast cancer patients.

The complexity of breast cancer includes many interacting biological processes that make it difficult to find appropriate therapeutic treatments. Therefore, identifying potential diagnostic and prognostic biomarkers is urgently needed. Previous studies demonstrated that 26S proteasome delta subunit, non-ATPase (PSMD) family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcriptional expressions of PSMD family genes in breast cancer still remain largely unexplored. Consequently, we used a holistic bioinformatics approach to explore PSMD genes involved in breast cancer patients by integrating several high-throughput databases, including The Cancer Genome Atlas (TCGA), cBioPortal, Oncomine, and Kaplan-Meier plotter. These data demonstrated that PSMD1, PSMD2, PSMD3, PSMD7, PSMD10, PSMD12, and PSMD14 were expressed at significantly higher levels in breast cancer tissue compared to normal tissues. Notably, the increased expressions of PSMD family genes were correlated with poor prognoses of breast cancer patients, which suggests their roles in tumorigenesis. Meanwhile, network and pathway analyses also indicated that PSMD family genes were positively correlated with ubiquinone metabolism, immune system, and cell-cycle regulatory pathways. Collectively, this study revealed that PSMD family members are potential prognostic biomarkers for breast cancer progression and possible promising clinical therapeutic targets.

Immuno-transcriptomic profiling of extracranial pediatric solid malignancies.

We perform an immunogenomics analysis utilizing whole-transcriptome sequencing of 657 pediatric extracranial solid cancer samples representing 14 diagnoses, and additionally utilize transcriptomes of 131 pediatric cancer cell lines and 147 normal tissue samples for comparison. We describe patterns of infiltrating immune cells, T cell receptor (TCR) clonal expansion, and translationally relevant immune checkpoints. We find that tumor-infiltrating lymphocytes and TCR counts vary widely across cancer types and within each diagnosis, and notably are significantly predictive of survival in osteosarcoma patients. We identify potential cancer-specific immunotherapeutic targets for adoptive cell therapies including cell-surface proteins, tumor germline antigens, and lineage-specific transcription factors. Using an orthogonal immunopeptidomics approach, we find several potential immunotherapeutic targets in osteosarcoma and Ewing sarcoma and validated PRAME as a bona fide multi-pediatric cancer target. Importantly, this work provides a critical framework for immune targeting of extracranial solid tumors using parallel immuno-transcriptomic and -peptidomic approaches.