immune infiltration
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2022 ◽  
Vol 103 ◽  
pp. 108454
Yunzhu Shen ◽  
Baoguo Zhang ◽  
Xiaowei Wei ◽  
Xiaoxiang Guan ◽  
Wenwen Zhang

2022 ◽  
Bohan Li ◽  
Hua Duan ◽  
Sha Wang ◽  
Jiajing Wu ◽  
Yazhu Li

Abstract Objectives: This study was anchored on the state of local immune-infiltration in the endometrium, which acts as critical factors affecting embryonic implantation, and aimed at establishing novel approaches to assess endometrial receptivity for patients with IVF failure.Methods: Immune-infiltration levels in the GSE58144 dataset (n=115) from GEO were analyzed by digital deconvolution and validated by immunofluorescence (n=30), illustrating that dysregulation of the ratio of Mf1 to Mf2 is an important factor contributing to implantation failure. Then, modules most associated with M1/M2 macrophages (Mfs) and their hub genes were then selected by weighted gene co-expression network and univariate analyses, then validated by GSE5099 macrophage dataset, qPCR analysis (n=16), and western blot. It revealed that closely related gene modules dominated three biological processes in macrophages: antigen presentation, interleukin−1−mediated signalling pathway, and phagosome acidification, respectively. Their hub genes were significantly altered in patients and related with ribosomal, lysosome, and proteasomal pathways. Finally, the artificial neural network (ANN) and nomogram models were established from hub genes, of which efficacy was compared and validated in the GSE165004 dataset (n=72). Models established by the selected hub genes exhibited excellent predictive values in both datasets, and ANN performed best with an accuracy of 98.3% and an AUC of 0.975 (95% CI 0.945-1). Conclusions: Macrophages, proven to be essential for endometrial receptivity, were regulated by gene modules dominating antigen presentation, interleukin−1−mediated signalling pathway, and phagosome acidification. Selected hub genes can effectively assess endometrial dysfunction receptivity for IVF outcomes by the ANN approach.

2022 ◽  
Vol 12 ◽  
Yi Chen ◽  
Didi Chen ◽  
Qiang Wang ◽  
Yajing Xu ◽  
Xiaowei Huang ◽  

BackgroundCancer immunotherapy has produced significant positive clinical effects in a variety of tumor types. However, pancreatic ductal adenocarcinoma (PDAC) is widely considered to be a “cold” cancer with poor immunogenicity. Our aim is to determine the detailed immune features of PDAC to seek new treatment strategies.MethodsThe immune cell abundance of PDAC patients was evaluated with the single-sample gene set enrichment analysis (ssGSEA) using 119 immune gene signatures. Based on these data, patients were classified into different immune subtypes (ISs) according to immune gene signatures. We analyzed their response patterns to immunotherapy in the datasets, then established an immune index to reflect the different degrees of immune infiltration through linear discriminant analysis (LDA). Finally, potential prognostic markers associated with the immune index were identified based on weighted correlation network analysis (WGCNA) that was functionally validated in vitro.ResultsThree ISs were identified in PDAC, of which IS3 had the best prognosis across all three cohorts. The different expressions of immune profiles among the three ISs indicated a distinct responsiveness to immunotherapies in PDAC subtypes. By calculating the immune index, we found that the IS3 represented higher immune infiltration, while IS1 represented lower immune infiltration. Among the investigated signatures, we identified ZNF185, FANCG, and CSTF2 as risk factors associated with immune index that could potentially facilitate diagnosis and could be therapeutic target markers in PDAC patients.ConclusionsOur findings identified immunologic subtypes of PDAC with distinct prognostic implications, which allowed us to establish an immune index to represent the immune infiltration in each subtype. These results show the importance of continuing investigation of immunotherapy and will allow clinical workers to personalized treatment more effectively in PDAC patients.

BMC Genomics ◽  
2022 ◽  
Vol 23 (1) ◽  
Jiaxin Fan ◽  
Mengying Chen ◽  
Shuai Cao ◽  
Qingling Yao ◽  
Xiaodong Zhang ◽  

Abstract Background Ischemic stroke (IS) is a principal contributor to long-term disability in adults. A new cell death mediated by iron is ferroptosis, characterized by lethal aggregation of lipid peroxidation. However, a paucity of ferroptosis-related biomarkers early identify IS until now. This study investigated potential ferroptosis-related gene pair biomarkers in IS and explored their roles in immune infiltration. Results In total, we identified 6 differentially expressed ferroptosis-related genes (DEFRGs) in the metadata cohort. Of these genes, 4 DEFRGs were incorporated into the competitive endogenous RNA (ceRNA) network, including 78 lncRNA-miRNA and 16 miRNA-mRNA interactions. Based on relative expression values of DEFRGs, we constructed gene pairs. An integrated scheme consisting of machine learning algorithms, ceRNA network, and gene pair was proposed to screen the key DEFRG biomarkers. The receiver operating characteristic (ROC) curve witnessed that the diagnostic performance of DEFRG pair CDKN1A/JUN was superior to that of single gene. Moreover, the CIBERSORT algorithm exhibited immune infiltration landscapes: plasma cells, resting NK cells, and resting mast cells infiltrated less in IS samples than controls. Spearman correlation analysis confirmed a significant correlation between plasma cells and CDKN1A/JUN (CDKN1A: r = − 0.503, P < 0.001, JUN: r = − 0.330, P = 0.025). Conclusions Our findings suggested that CDKN1A/JUN could be a robust and promising gene-pair diagnostic biomarker for IS, regulating ferroptosis during IS progression via C9orf106/C9orf139-miR-22-3p-CDKN1A and GAS5-miR-139-5p/miR-429-JUN axes. Meanwhile, plasma cells might exert a vital interplay in IS immune microenvironment, providing an innovative insight for IS therapeutic target.

2022 ◽  
Vol 12 ◽  
Maolin Yao ◽  
Lanyi Fu ◽  
Xuedong Liu ◽  
Dong Zheng

Aberrant activation of calmodulin 1 (CALM1) has been reported in human cancers. However, comprehensive understanding of the role of CALM1 in most cancer types has remained unclear. We systematically analyzed the expression landscape, DNA methylation, gene alteration, immune infiltration, clinical relevance, and molecular pathway of CALM1 in multiple cancers using various online tools, including The Cancer Genome Atlas, cBioPortal and the Human Protein Atlas databases. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to explore the prognostic and diagnostic potential of CALM1 expression. Multivariate analyses were used to evaluate whether the CALM1 expression could be an independent risk factor. A nomogram predicting the overall survival (OS) of patients was developed, evaluated, and compared with the traditional Tumor-Node-Metastasis (TNM) model using decision curve analysis. R language was employed as the main tool for analysis and visualization. Results revealed CALM1 to be highly expressed in most cancers, its expression being regulated by DNA methylation in multiple cancers. CALM1 had a low mutation frequency (within 3%) and was associated with immune infiltration. We observed a substantial positive correlation between CALM1 expression and macrophage and neutrophil infiltration levels in multiple cancers. Different mutational forms of CALM1 hampered immune cell infiltration. Additionally, CALM1 expression had high diagnostic and prognostic potential. Multivariate analyses revealed CALM1 expression to be an independent risk factor for OS. Therefore, our newly developed nomogram had a higher clinical value than the TNM model. The concordance index, calibration curve, and time-dependent ROC curves of the nomogram exhibited excellent performance in terms of predicting the survival rate of patients. Moreover, elevated CALM1 expression contributes to the activation of cancer-related pathways, such as the WNT and MAPK pathways. Overall, our findings improved our understanding of the function of CALM1 in human cancers.

2022 ◽  
Yuying Tan ◽  
Liqing Lu ◽  
Xujun Liang ◽  
Yongheng Chen

Abstract Background: Colon adenocarcinoma (COAD) is one of the most common malignant tumors and diagnosed at an advanced stage with poor prognosis in the world. Pyroptosis is involved in the initiation and progression of tumors. This research focused on constructing a pyroptosis-related ceRNA network to generate a reliable risk model for risk prediction and immune infiltration analysis of COAD.Methods: Transcriptome data, miRNA-sequencing data and clinical information were downloaded from the TCGA database. Firstly, differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs) were identified to construct a pyroptosis-related ceRNA network. Secondly, a pyroptosis-related lncRNA risk model was developed applying univariate Cox regression analysis and least absolute shrinkage and selection operator method (LASSO) regression analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were utilized to functionally annotate RNAs contained in the ceRNA network. In addition, Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, univariate and multivariate Cox regression, and nomogram were applied to validate this risk model. Finally, the relationship of this risk model with immune cells and immune checkpoint blockade (ICB) related genes were analyzed.Results: Totally 5373 DEmRNAs, 1159 DElncRNAs and 355 DEmiRNAs were identified. A pyroptosis-related ceRNA regulatory network containing 132 lncRNAs, 7miRNAs and 5 mRNAs was constructed and a ceRNA-based pyroptosis-related risk model including 11 lncRNAs was built. Tumor tissues were classified into high- and low- risk groups according to the median risk score. Kaplan-Meier analysis showed that the high-risk group had a shorter survival time; ROC analysis, independent prognostic analysis and nomogram further indicated the risk model was a significant independent prognostic factor which had excellent ability to predict patients’ risk. Moreover, immune infiltration analysis indicated that the risk model was related to immune infiltration cells (i.e., B cells naïve, T cells follicular helper, Macrophages M1, etc.) and ICB-related genes (i.e., PD-1, CTLA4, HAVCR2, etc).Conclusions: This pyroptosis-related lncRNA risk model possessed good prognostic value and the ability to predict the outcome of ICB immunotherapy in COAD.

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Rui Dou ◽  
Xiong Wang ◽  
Jin Zhang

Ovarian cancer (OC) often presents at an advanced stage and is still one of the most frequent causes of gynecological cancer-related mortality worldwide. The nuclear factor erythroid-2 (NFE2) transcription factors include nuclear factor, erythroid 2 like 1 (NFE2L1), NFE2L2, and NFE2L3. NFE2 members bind to the antioxidant-response element (ARE) region and activate the expression of targeted genes. The distinct functions of NFE2 members in OC remain poorly elucidated. Several online bioinformatics databases were applied to determine gene expression, prognosis, mutations, and immune infiltration correlation in OC patients. NFE2L1 and NFE2L2 were decreased in OC, whereas NFE2L3 was increased. NFE2L2 and NFE2L3 were significantly correlated with the clinical stages of OC. High NFE2L1 level was significantly associated with short progression-free survival (PFS) in patients with OC ( HR = 1.18 , P = 0.021 ), while high NFE2L2 expression strongly correlated with long PFS ( HR = 0.77 , P = 0.00067 ). High NFE2L3 expression was associated with better overall survival and postprogression survival in OC. Functional analysis showed that NFE2 members mainly focused on transcription coactivator activities. Genetic alterations of NFE2 members were found in 13% of OC patients, and amplification ranked the top. The expression of NFE2 members was significantly correlated with immune infiltration of CD4+ T cells, CD8+ T cells, B cells, macrophages, and neutrophils in OC. Our study provides novel insights into the roles and prognostic potential of NFE2 family members in OC.

2022 ◽  
Vol 2022 ◽  
pp. 1-21
Jiamin Xu ◽  
Fuqin Kang ◽  
Wei Wang ◽  
Shujun Liu ◽  
Jianhui Xie ◽  

Background. Clinical research found that TCM is therapeutic in treating gastric cancer. Clearing heat is the most common method, while some antirheumatic medicines are widely used in treatment as well. To explore the pharmacological mechanism, we researched the comparison between heat-clearing medicine and antirheumatic medicine in treating gastric cancer. Methods. First, related ingredients and targets were searched, respectively, and are shown in an active ingredient-target network. Combining the relevant targets of gastric cancer, we constructed a PPI network and MCODE network. Then, GO and KEGG enrichment analyses were conducted. Molecular docking experiments were performed to verify the affinity of targets and ligands. Finally, we analyzed the tumor immune infiltration on gene expression, somatic CNA, and clinical outcome. Results. A total of 31 ingredients and 90 targets of heat-clearing medicine, 31 ingredients and 186 targets of antirheumatic medicine, and 12,155 targets of gastric cancer were collected. Antirheumatic medicine ranked the top in all the enrichment analyses. In the KEGG pathway, both types of medicines were related to pathways in cancer. In the KEGG map, AR, MMP2, ERBB2, and TP53 were the most crucial targets. Key targets and ligands were docked with low binding energy. Analysis of tumor immune infiltration showed that the expressions of AR and ERBB2 were correlated with the abundance of immune infiltration and made a difference in clinical outcomes. Conclusions. Quercetin is an important ingredient in both heat-clearing medicine and antirheumatic medicine. AR signaling pathway exists in both types of medicines. The mechanism of the antitumor effect in antirheumatic medicine was similar to trastuzumab, a targeted drug aimed at ERBB2. Both types of medicines were significant in tumor immune infiltration. The immunology of gastric tumor deserves further research.

2022 ◽  
Vol 8 ◽  
Fei Chen ◽  
Yumei Fan ◽  
Xiaopeng Liu ◽  
Jianhua Zhang ◽  
Yanan Shang ◽  

Heat shock factor 2 (HSF2), a transcription factor, plays significant roles in corticogenesis and spermatogenesis by regulating various target genes and signaling pathways. However, its expression, clinical significance and correlation with tumor-infiltrating immune cells across cancers have rarely been explored. In the present study, we comprehensively investigated the expression dysregulation and prognostic significance of HSF2, and the relationship with clinicopathological parameters and immune infiltration across cancers. The mRNA expression status of HSF2 was analyzed by TCGA, GTEx, and CCLE. Kaplan-Meier analysis and Cox regression were applied to explore the prognostic significance of HSF2 in different cancers. The relationship between HSF2 expression and DNA methylation, immune infiltration of different immune cells, immune checkpoints, tumor mutation burden (TMB), and microsatellite instability (MSI) were analyzed using data directly from the TCGA database. HSF2 expression was dysregulated in the human pan-cancer dataset. High expression of HSF2 was associated with poor overall survival (OS) in BRCA, KIRP, LIHC, and MESO but correlated with favorable OS in LAML, KIRC, and PAAD. The results of Cox regression and nomogram analyses revealed that HSF2 was an independent factor for KIRP, ACC, and LIHC prognosis. GO, KEGG, and GSEA results indicated that HSF2 was involved in various oncogenesis- and immunity-related signaling pathways. HSF2 expression was associated with TMB in 9 cancer types and associated with MSI in 5 cancer types, while there was a correlation between HSF2 expression and DNA methylation in 27 types of cancer. Additionally, HSF2 expression was correlated with immune cell infiltration, immune checkpoint genes, and the tumor immune microenvironment in various cancers, indicating that HSF2 could be a potential therapeutic target for immunotherapy. Our findings revealed the important roles of HSF2 across different cancer types.

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