Integrated Analysis of Immune Infiltration Features for Cervical Carcinoma and Their Associated Immunotherapeutic Responses.
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ABSTRACT:
SUBMITTER: Kang Y
PROVIDER: S-EPMC8063060 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cervical cancer (CC) is one of the most common malignancies in women worldwide. Dismal prognosis rates have been associated with conventional therapeutic approaches, emphasizing the need for new strategies. Recently, immunotherapy has been used to treat various types of solid tumors, and different subtypes of the tumor microenvironment (TME) are associated with diverse responses to immunotherapy. Accordingly, understanding the complexity of the TME is pivotal for immunotherapy. Herein, we used two methods, "ssGSEA" and "xCell," to identify the immune profiles in CC and comprehensively assess the relationship between immune cell infiltration and genomic alterations. We found that more adaptive immune cells were found infiltrated in tumor tissues than in normal tissues, whereas the opposite was true for innate cells. Consensus clustering of CC samples based on the number of immune cells identified four clusters with different survival and immune statuses. Then, we subdivided the above four clusters into "hot" and "cold" tumors, where hot tumors exhibited higher immune infiltration and longer survival time. Enrichment analyses of differentially expressed genes (DEGs) revealed that the number of activated immune signaling pathways was higher in hot tumors than that in cold tumors. Keratin, type I cytoskeletal 23 (KRT23), was upregulated in cold tumors and negatively correlated with immune cell infiltration. In vitro experiments, real-time reverse transcription-quantitative polymerase chain reaction, cytometric bead arrays, and ELISA revealed that knockdown of KRT23 expression could promote the secretion of C-C motif chemokine ligand-5 and promote the recruitment of CD8+ T cells. We also constructed a model based on DEGs that exhibited a high predictive power for the survival of CC patients. Overall, our study provides deep insights into the immune cell infiltration patterns of CC. Moreover, KRT23 has huge prospects for application as an immunotherapeutic target. Finally, our model demonstrated a good predictive power for the prognosis of CC patients and may guide clinicians during immunotherapy.
| S-EPMC9263098 | biostudies-literature
Project description:BackgroundEsophageal cancer (EC) is one of the most aggressive and lethal malignancies in the world. The quantity and distribution of immune cells are very important factors in determining cancer. Tumor-infiltrating mast cells (TIM) are a class of immune cells with an important immune regulation function for tumor progression. However, tumor-infiltrating immune cells (TIICs) and their role in EC have not yet been investigated.MethodsThe RNA-seq data of an EC cohort were downloaded from The Cancer Genome Atlas (TCGA) website. In this study, we used the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm to compare different soakage of inflammatory cells in esophageal squamous cell carcinoma (ESCC) and normal tissue. Kaplan-Meier survival analysis was performed on different immune cell subpopulations and overall survival (OS) in 22 human immune cell phenotypes. Immunohistochemistry (IHC) was also carried out using our clinical tissue samples.ResultsThe proportion of tumor-infiltrating mast cells (TIM) significantly increased at the late of EC and a high percentage of mast cells indicated a poor OS of EC patients in TCGA database. The IHC staining of tryptase revealed that high level of TIM expression was an independent prognostic factor of survival time in the ESCC patients in our database. In addition, TIM accumulation and infiltration of CD8+T cells were shown to be negatively correlated.ConclusionsThis work revealed that TIM are related to prognosis in patients with EC and TIM may be an independent prognostic factor for EC.
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Project description:Immunotherapy, closely associated with immune infiltration and tumor mutation burden (TMB), is emerging as a promising strategy for treating tumors, but its low response rate in hepatocellular carcinoma (HCC) remains a major challenge. Herein, we applied two algorithms to uncover the immune infiltration landscape of the immune microenvironment in 491 HCC patients. Three immune infiltration patterns were defined using the CIBERSORT method, and the immune cell infiltration (ICI) scores were established using principal component analysis. In the high ICI score group, the activation of the Wnt/β-catenin pathway was significantly enriched and expressions of immune checkpoint genes increased, which showed a pessimistic outcome. The low ICI score group was characterized by increased TMB and enrichment of metabolism-related pathways. Further analysis found that the ICI score exhibited a significant difference in age ≥65/age <65, grade I/grade II-IV, and response to immunotherapy. Moreover, the CTNNB1 mutation status was found to be closely associated with prognosis and immunotherapeutic efficiency, significantly affecting the ICI score and TMB, which might be regarded as a potential marker for the treatment of HCC. The evaluation of immune infiltration patterns can improve the understanding of the tumor immune microenvironment and provide new directions for the study of individualized immunotherapy strategies for HCC.
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Project description:Six Gasdermins (GSDM) family members participate in various biological processes especially pyroptosis, as well as in the initiation and development of many types of cancer. However, the systematic analysis of the GSDM family in hepatocellular carcinoma (HCC) is lacking. In this study, several bioinformatics databases were recruited to analyze the roles of the GSDMs in differential expression, prognostic correlation, functional enrichment exploration, immune modulation, genetic alterations, and methylated modification in patients with HCC. Consequently, the mRNA expression of all the six GSDMs was accordantly increased in HCC, while only the protein expressions of GSDMB, GSDMD, and GSDME were apparently increased in HCC tissue. The expression of all the GSDMs (except GSDMA) was significantly higher in tumor stage 1-3 subgroups, compared with that in normal subgroups. Higher GSDME expression was significantly associated with shorter overall survival (OS) and disease specific survival (DSS) in patients with HCC. GSDMD had the highest genetic alteration rate among the GSDMs. The three signal pathways which were most likely related to GSDMs-associated molecules were the cell adhesion, growth regulation, and hormone metabolic process. The majority of GSDMs members were positively correlated with the infiltration of B cells, neutrophils, and dendritic cells, however negatively correlated with macrophage. All of the six GSDM members showed remarkably decreased methylation levels in HCC tissues. In conclusion, the GSDM family (especially GSDME) had the potential to become essential biomarkers to better improve the diagnosis and prognosis of HCC, as well as provided insight for the development of therapeutic targets.
| S-EPMC8610125 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies examining the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. In the present study, we found that HSF2 expression was significantly upregulated in HCC tissues compared with normal liver tissues using the TCGA, ICGC, GEO, UALCAN, HCCDB and HPA databases. High HSF2 expression was associated with shorter survival of patients with HCC. Cox regression analyses and nomogram were used to evaluate the association of HSF2 expression with the prognosis of patients with HCC. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and gene set enrichment analysis (GSEA) revealed that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells using the TIMER database and CIBERSORT algorithm. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC tissues. Knockdown of HSF2 significantly inhibited the proliferation, migration, invasion and colony formation ability of HCC cells. In summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.
| S-EPMC8669829 | biostudies-literature
Project description:The immune composition of the tumor microenvironment influences response and resistance to immunotherapies. While numerous studies have identified somatic correlates of immune infiltration, germline features that associate with immune infiltrates in cancers remain incompletely characterized. We analyze seven million autosomal germline variants in the TCGA cohort and test for association with established immune-related phenotypes that describe the tumor immune microenvironment. We identify one SNP associated with the amount of infiltrating follicular helper T cells; 23 candidate genes, some of which are involved in cytokine-mediated signaling and others containing cancer-risk SNPs; and networks with genes that are part of the DNA repair and transcription elongation pathways. In addition, we find a positive association between polygenic risk for rheumatoid arthritis and amount of infiltrating CD8+ T cells. Overall, we identify multiple germline genetic features associated with tumor-immune phenotypes and develop a framework for probing inherited features that contribute to differences in immune infiltration.
| S-EPMC7082123 | biostudies-literature
Project description:Tumor spheroids play an increasingly important role in cancer research. Their ability to recapitulate crucial features of tumor biology that are lost in the classically used 2D models along with their relative simplicity and handiness have made them the most studied 3D tumor model. Their application as a theranostic tool or as a means to study tumor-host interaction is now well-established in various cancers. However, their use in the field of Renal Cell Carcinoma (RCC) remains very limited. The aim of this work is to present methods to implement a basic RCC spheroid model. These methods cover the steps from RCC tumor dissociation to spheroid infiltration by immune cells. We present a protocol for RCC dissociation using Liberase TM and introduce a culture medium containing Epithelial Growth Factor and Hydrocortisone allowing for faster growth of RCC primary cells. We show that the liquid overlay technique allows for the formation of spheroids from cell lines and from primary cultures. We present a method using morphological criteria to select a homogeneous spheroid population based on a Fiji macro. We then show that spheroids can be infiltrated by PBMCs after activation with OKT3 or IL-15. Finally, we provide an example of application by implementing an immune spheroid killing assay allowing observing increased spheroid destruction after treatment with PD-1 inhibitors. Thus the straightforward methods presented here allow for efficient spheroid formation for a simple RCC 3D model that can be standardized and infused with immune cells to study immunotherapies.
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Project description:BackgroundTo identify potential immune-related biomarkers, molecular mechanism, and therapeutic agents of intracranial aneurysms (IAs).MethodsWe identified the differentially expressed genes (DEGs) between IAs and control samples from GSE75436, GSE26969, GSE6551, and GSE13353 datasets. We used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis to identify immune-related hub genes. We evaluated the expression of hub genes by using qRT-PCR analysis. Using miRNet, NetworkAnalyst, and DGIdb databases, we analyzed the regulatory networks and potential therapeutic agents targeting hub genes. Least absolute shrinkage and selection operator (LASSO) logistic regression was performed to identify optimal biomarkers among hub genes. The diagnostic value was validated by external GSE15629 dataset.ResultsWe identified 227 DEGs and 22 differentially infiltrating immune cells between IAs and control samples from GSE75436, GSE26969, GSE6551, and GSE13353 datasets. We further identified 41 differentially expressed immune-related genes (DEIRGs), which were primarily enriched in the chemokine-mediated signaling pathway, myeloid leukocyte migration, endocytic vesicle membrane, chemokine receptor binding, chemokine activity, and viral protein interactions with cytokines and their receptors. Among 41 DEIRGs, 10 hub genes including C3AR1, CD163, CCL4, CXCL8, CCL3, TLR2, TYROBP, C1QB, FCGR3A, and FCGR1A were identified with good diagnostic values (AUC >0.7). Hsa-mir-27a-3p and transcription factors, including YY1 and GATA2, were identified the primary regulators of hub genes. 92 potential therapeutic agents targeting hub genes were predicted. C3AR1 and CD163 were finally identified as the best diagnostic biomarkers using LASSO logistic regression (AUC = 0.994). The diagnostic value of C3AR1 and CD163 was validated by the external GSE15629 dataset (AUC = 0.914).ConclusionsThis study revealed the importance of C3AR1 and CD163 in immune infiltration in IAs pathogenesis. Our finding provided a valuable reference for subsequent research on the potential targets for molecular mechanisms and intervention of IAs.
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Project description:Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The role of molecular alterations and the immune microenvironment in ESCC development has not been fully elucidated. The present study aimed to elucidate key candidate genes and immune cell infiltration characteristics in ESCC by integrated bioinformatics analysis. Nine gene expression datasets from the Gene Expression Omnibus (GEO) database were analysed to identify robust differentially expressed genes (DEGs) using the robust rank aggregation (RRA) algorithm. Functional enrichment analyses showed that the 152 robust DEGs are involved in multiple processes in the tumor microenvironment (TME). Immune cell infiltration analysis based on the 9 normalized GEO microarray datasets was conducted with the CIBERSORT algorithm. The changes in macrophages between ESCC and normal tissues were particularly obvious. In ESCC tissues, M0 and M1 macrophages were increased dramatically, while M2 macrophages were decreased. A robust DEG-based protein-protein interaction (PPI) network was used for hub gene selection with the CytoHubba plugin in Cytoscape. Nine hub genes (CDA, CXCL1, IGFBP3, MMP3, MMP11, PLAU, SERPINE1, SPP1 and VCAN) had high diagnostic efficiency for ESCC according to receiver operating characteristic (ROC) curve analysis. The expression of all hub genes except MMP3 and PLAU was significantly related to macrophage infiltration. Univariate and multivariate regression analyses showed that a 7-gene signature constructed from the robust DEGs was useful for predicting ESCC prognosis. Our results might facilitate the exploration of potential targeted TME therapies and prognostic evaluation in ESCC.
| S-EPMC8371051 | biostudies-literature
Project description:ObjectiveOverexpression of survivin has been reported in many human tumors. However, the clinicopathological features associated with survivin overexpression in cervical carcinoma remain controversial. Thus, the current meta-analysis was performed to assess the clinicopathological significance of survivin in cervical carcinoma.MethodsPubMed, EMBASE, and Web of Science databases were searched for relevant studies published through November 1, 2015. A meta-analysis was performed to evaluate the association between survivin expression and clinicopathological outcome in cervical carcinoma.ResultsEleven eligible studies with a total of 865 patients were included. Survivin overexpression was closely related to lymph node metastasis (odds ratio [OR] = 0.679, 95% confidence interval [CI]: 0.509-0.905, P = 0.008) but was not significantly associated with tumor FIGO stage (I+II vs. III+IV) (OR = 0.843, 95% CI: 0.626-1.137, P = 0.264), tumor grade (G1+G2 vs. G3) (OR = 0.913, 95% CI: 0.689-1.210, P = 0.527), tumor size (>4 vs. ?4 cm) (OR = 0.825, 95% CI: 0.434-1.570, P = 0.559), or stromal involvement (OR = 0.820, 95% CI: 0.545-1.233, P = 0.340). The correlation between survivin expression and overall survival was evaluated among a total of 238 patients from three eligible studies. The pooled HR was 1.129 (95% CI: 0.597-1.661; P = 0.000), indicating that survivin expression was significantly associated with poor survival in cervical carcinoma.ConclusionsBased on the current meta-analysis, survivin is strongly associated with lymph node metastasis and poor prognosis. Additionally, survivin is a novel clinicopathological marker of cervical carcinoma and thus may be a therapeutic target for cervical carcinoma.
| S-EPMC5072693 | biostudies-literature