Clinical significance of immune cell infiltration within gallbladder cancer.
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ABSTRACT:
SUBMITTER: Nakakubo Y
PROVIDER: S-EPMC2394404 | biostudies-other | 2003 Nov
REPOSITORIES: biostudies-other
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Project description:BackgroundDisabled homolog 2-interacting protein is a new member of the Ras GTPase superfamily involved in the regulation of cell proliferation, apoptosis, and metastasis. However, the expression of disabled homolog 2-interacting protein in renal cell carcinoma, its correlation with cancer prognosis, and tumor infiltrating lymphocytes remains unclear.MethodsThe expression of disabled homolog 2-interacting protein was analyzed by UALCAN database, GEPIA database and the evaluation of disabled homolog 2-interacting protein effects on clinical prognosis. Prognostic factor analysis was used to identify the correlations between disabled homolog 2-interacting protein and cancer immune infiltration via the TIMER database. In addition, COXPRESdb database was used to analyze the enrichment of disabled homolog 2-interacting protein co-expression genes.ResultsCompared to the normal tissues, the messenger RNA expression levels of DAB2IP are higher in 8 while lower in 15 types of tumor tissues. Furthermore, disabled homolog 2-interacting protein has high expression in kidney chromophobe and low expression in both kidney renal clear cell carcinoma and kidney renal papillary cell carcinoma. The messenger RNA expression levels of disabled homolog 2-interacting protein decrease gradually due to the increasing tumor staging which positively correlates with disease-free survival and overall survival in both kidney renal clear cell carcinoma and kidney renal papillary cell carcinoma. The expression levels of disabled homolog 2-interacting protein also positively correlate with the tumor purity of kidney chromophobe, kidney renal clear cell carcinoma, and kidney renal papillary cell carcinoma samples. Besides, the expression of disabled homolog 2-interacting protein in renal cell carcinoma has negative correlation with the immune infiltration, and the immune infiltration of B cells and CD8+ T cells affects the prognosis of kidney renal papillary cell carcinoma. Enrichment analysis of disabled homolog 2-interacting protein co-expressed genes suggested that its biological role was mainly in regulating GTPase activity.ConclusionsThese findings suggest that disabled homolog 2-interacting protein functions as a tumor suppressor in the progression of renal cell carcinoma, and the expression of disabled homolog 2-interacting protein is related to the immune infiltrating cells and affects the survival of renal cell carcinoma. Disabled homolog 2-interacting protein can be a novel clinical biomarker for patients with renal cell carcinoma, which also provides new insights for the future treatments of renal cell carcinoma.
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Project description:Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.
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Project description:The host immune system plays a significant role in tumor control, although most cancers escape immune surveillance through a variety of mechanisms. The aim of the present study was to evaluate the clinicopathological significance of a novel co-inhibitory receptor, B and T lymphocyte attenuator (BTLA), the anergy cell marker Casitas-B-lineage lymphoma protein-b (Cbl-b), and clinical implications of tumor-infiltrating immune cells in gallbladder cancer (GBC) tissues. We investigated 211 cases of GBC, 21 cases of chronic cholecystitis (CC), and 11 cases of xanthogranulomatous cholecystitis (XGC) using immunohistochemistry to detect tissue-infiltrating immune cells and their expression of BTLA and Cbl-b, and carried out correlation and survival analyses. The density of infiltrating T cells was significantly higher in CC and XGC than in GBC. The density ratio of BTLA(+) cells to CD8(+) T cells (BTLA/CD8) and that of Cbl-b(+) cells to CD8(+) T cells (Cbl-b/CD8) were significantly higher in GBC than in CC and XGC. The FOXP3/CD4, BTLA/CD8, and Cbl-b/CD8 ratios were significantly correlated with each other, and also with malignant phenotypes. Survival analyses revealed that a lower density of tumor-infiltrating CD8(+) cells, and higher Foxp3/CD4, BTLA/CD8, and Cbl-b/CD8 ratios were significantly associated with shorter overall survival and disease-free survival in GBC patients. Multivariate analyses showed that M factor, perineural invasion, BTLA/CD8, and Cbl-b/CD8 were closely associated with shorter overall survival. These findings suggest that higher ratios of BTLA/CD8 and Cbl-b/CD8 are independent indicators of unfavorable outcome in GBC patients, and that upregulation of BTLA in cancer tissues is involved in inhibition of antitumor immunity.
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Project description:BackgroundThe human copper Cu proteome, also termed Cu-binding proteins (CBP), is responsible for transporting "free" Cu to the cell that is related to cuproptosis. However, their role in gastric cancer (GC) has not been reported.MethodsRNA expression data of 946 GC patients were collected. A series of machine learning and bioinformatic approaches were combined to build a CBP signature to predict survival and immune microenvironment and guide the priority treatment. Immunohistochemistry and multicolor immunofluorescence (mIF) in 1076 resection slides were used to verify immune features.ResultsA CBP signature was constructed using the machine learning method from TCGA that classifies cases as CBP_low and CBP_high groups. Multivariable Cox analysis confirmed that the CBP signature was an independent prognostic factor in the training and validation cohorts. Additionally, GC patients with low CBPscores showed an increase in anti-tumor immune microenvironment, which was further verified by mIF in pathological resections following immunotherapy. Importantly, patients with low CBPscores had higher levels of TMB/MSI and responded well to immunotherapy.ConclusionsWe conducted the first and comprehensive CBP analysis of GC patients and established a clinically feasible CBP signature for predicting survival and response to treatment, which will be helpful for guiding personalized medicine.
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Project description:Signal transducer and activator of transcription 3 (STAT3) is a transcription factor and regulates tumorigenesis. However, the functions of STAT3 in immune and drug response in cancer remain elusive. Hence, we aim to reveal the impact of STAT3 in immune infiltration and drug response comprehensively by bioinformatics analysis. The expression of STAT3 and its relationship with tumor stage were explored by Tumor Immune Estimation Resource (TIMER), Human Protein Altas (HPA), and UALCAN databases. The correlations between STAT3 and immune infiltration, gene markers of immune cells were analyzed by TIMER. Moreover, the association between STAT3 and drug response was evaluated by the Cancer Cell Line Encyclopedia (CCLE) and Cancer Therapeutics Response Portal (CTRP). The results suggested that the mRNA transcriptional level of STAT3 was lower in tumors than normal tissues and mostly unrelated to tumor stage. Besides, the protein expression of STAT3 decreased in colorectal and renal cancer compared with normal tissues. Importantly, STAT3 was correlated with immune infiltration and particularly regulated tumor-associated macrophage (TAM), M2 macrophage, T-helper 1 (Th1), follicular helper T (Treg), and exhausted T-cells. Remarkably, STAT3 was closely correlated with the response to specified inhibitors and natural compounds in cancer. Furthermore, the association between STAT3 and drug response was highly cell line type dependent. Significantly, the study provides thorough insight that STAT3 is associated with immunosuppression, as well as drug response in clinical treatment.
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Project description:ObjectiveTo perform gene set enrichment analysis (GSEA) and analysis of immune cell infiltration on non-small-cell lung cancer (NSCLC) expression profiling microarray data based on bioinformatics, construct TICS scoring model to distinguish prognosis time, screen key genes and cancer-related pathways for NSCLC treatment, explore differential genes in NSCLC patients, predict potential therapeutic targets for NSCLC, and provide new directions for the treatment of NSCLC.MethodsTranscriptome data of 81 NSCLC patients and the GEO database were used to download matching clinical data (access number: GSE120622). Form the expression of non-small cell lung cancer (NSCLC). TICS values were calculated and grouped according to TICS values, and we used mRNA expression profile data to perform GSEA in non-small-cell lung cancer patients. Biological process (GO) analysis and DAVID and KOBAS were used to undertake pathway enrichment (KEGG) analysis of differential genes. Use protein interaction (PPI) to analyze the database STRING, and construct a PPI network model of target interaction.ResultsWe obtained 6 significantly related immune cells including activated B cells through the above analysis (Figure 1(b), p < 0.001). Based on the TICS values of significantly correlated immune cells, 41 high-risk and 40 low-risk samples were obtained. TICS values and immune score values were subjected to Pearson correlation coefficient calculation, and TICS and IMS values were found to be significantly correlated (Cor = 0.7952). Based on non-small-cell lung cancer mRNA expression profile data, a substantial change in mRNA was found between both the high TICS group as well as the low TICS group (FDR 0.01, FC > 2). The researchers discovered 730 mRNAs that were considerably upregulated in the high TICS group and 121 mRNAs that were considerably downregulated in the low TICS group. High confidence edges (combined score >0.7) were selected using STRING data; then, 191 mRNAs were matched to the reciprocal edges; finally, an undirected network including 164 points and 777 edges was constructed. Important members of cellular chemokine-mediated signaling pathways, such as CCL19, affect patient survival time.Conclusion(1) The longevity of patients with non-small-cell lung cancer was substantially connected with the presence of immature B cells, activated B cells, MDSC, effector memory CD4 T cells, eosinophils, and regulatory T cells. (2) Immune-related genes such as CX3CR1, CXCR4, CXCR5, and CCR7, which are associated with the survival of NSCLC, affect the prognosis of NSCLC patients by regulating the immune process.
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Project description:The immune infiltration of patients with gastric cancer (GC) is closely associated with clinical prognosis. However, previous studies failed to explain the different subsets of immune cells involved in immune responses and diverse functions. The present study aimed to uncover the differences in immunophenotypes in a tumor microenvironment (TME) between adjacent and tumor tissues and to explore their therapeutic targets. In our study, the relative proportion of immune cells in 229 GC tumor samples and 22 paired matched tissues was evaluated with a Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) algorithm. The correlation between immune cell infiltration and clinical information was analyzed. The proportion of 22 immune cell subsets was assessed to determine the correlation between each immune cell type and clinical features. Three molecular subtypes were identified with 'CancerSubtypes' R-package. Functional enrichment was analyzed in each subtype. The profiles of immune infiltration in the GC cohort from The Cancer Genome Atlas (TCGA) varied significantly between the 22 paired tissues. TNM stage was associated with M1 macrophages and eosinophils. Follicular helper T cells were activated at the late stage. Monocytes were associated with radiation therapy. Three clustering processes were obtained via the 'CancerSubtypes' R-package. Each cancer subtype had a specific molecular classification and subtype-specific characterization. These findings showed that the CIBERSOFT algorithm could be used to detect differences in the composition of immune-infiltrating cells in GC samples, and these differences might be an important driver of GC progression and treatment response.
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Project description:AbstractPancreatic ductal adenocarcinoma (PDAC) is 1 of the highly fatal and most aggressive types of malignancies and accounts for the vast majority of Pancreatic Cancer. Numerous studies have reported that the tumor microenvironment (TME) was significantly correlated with the oncogenesis, progress, and prognosis of various malignancies. Therefore, mining of TME-related genes is reasonably important to improve the overall survival of patients with PDAC.The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm was applied to identify differential expressed genes. Functional and pathway enrichment analyses, protein-protein interaction network construction and module analysis, overall survival analysis and tumor immune estimation resource database analysis were then performed on differential expressed genes.Data analysis indicated that higher immune scores were correlated with better overall survival (P = 0.033). Differential expression analysis obtained 90 intersection genes influencing both stromal and immune scores. Among these intersection genes, CA9, EBI3, SPOCK2, WDFY4, CD1D, and CCL22 were significantly correlated with overall survival in PDAC patients. Moreover, multivariate Cox analysis revealed that CA9, SPOCK2, and CD1D were the most significant prognostic genes, and were closely correlated with immune infiltration in TCGA cohort. Further analysis indicated that CD1D were significantly related with immune cell biomarkers for PDAC patients.In summary, our findings provide a more comprehensive insight into TME and show a list of prognostic immune associated genes in PDAC. However, further studies on these genes need to be performed to gain additional understanding of the association between TME and prognosis in PDAC.
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Project description:Mammalian target of rapamycin (mTOR), a serine/threonine kinase involved in cell proliferation, survival, metabolism and immunity, was reportedly activated in various cancers. However, the clinical role of mTOR in renal cell carcinoma (RCC) is controversial. Here we detected the expression and prognosis of total mTOR and phosphorylated mTOR (p-mTOR) in clear cell RCC (ccRCC) patients, and explored the interactions between mTOR and immune infiltrates in ccRCC. The protein level of mTOR and p-mTOR was determined by western blotting (WB), and their expression was evaluated in 145 ccRCC and 13 non-tumor specimens by immunohistochemistry (IHC). The relationship to immune infiltration of mTOR was further investigated using TIMER and TISIDB databases, respectively. WB demonstrated the ratio of p-mTOR to mTOR was higher in ccRCC than adjacent specimens (n = 3), and IHC analysis elucidated that p-mTOR expression was positively correlated with tumor size, stage and metastasis status, and negatively correlated with cancer-specific survival (CSS). In univariate analysis, high grade, large tumor, advanced stage, metastasis, and high p-mTOR expression were recognized as prognostic factors of poorer CSS, and multivariate survival analysis elucidated that tumor stage, p-mTOR and metastasis were of prognostic value for CSS in ccRCC patients. Further TIMER and TISIDB analyses uncovered that mTOR gene expression was significantly associated with numerous immune cells and immunoinhibitors in patients with ccRCC. Collectively, these findings revealed p-mTOR was identified as an independent predictor of poor survival, and mTOR was associated with tumor immune infiltrates in ccRCC patients, which validated mTOR could be implicated in the initiation and progression of ccRCC.
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Project description:Immune cell infiltration varies widely between different glioblastomas (GBMs). The underlying mechanism, however, remains unknown. Here we show that TGF-beta regulates proliferation, migration, and tumorigenicity of mesenchymal GBM cancer stem cells (CSCs) in vivo and in vitro. In contrast, proneural GBM CSCs resisted TGF-beta due to TGFR2 deficiency. In vivo, a substantially increased infiltration of immune cells was observed in mesenchymal GBMs, while immune infiltrates were rare in proneural GBMs. On a functional level, proneural CSC lines caused a significantly stronger TGF-beta-dependent suppression of NKG2D expression on CD8(+) T and NK cells in vitro providing a mechanistic explanation for the reduced immune infiltration of proneural GBMs. Thus, the molecular subtype of CSCs TGF-beta-dependently contributes to the degree of immune infiltration.
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