An Immunity-Related Gene Model Predicts Prognosis in Cholangiocarcinoma
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ABSTRACT:
SUBMITTER: Guo H
PROVIDER: S-EPMC9283581 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Glioma is the most common primary tumor of the central nervous system. The conventional glioma treatment strategies include surgical excision and chemo- and radiation-therapy. Interferon Gamma (IFN-γ) is a soluble dimer cytokine involved in immune escape of gliomas. In this study, we sought to identify IFN-γ-related genes to construct a glioma prognostic model to guide its clinical treatment. Methods: RNA sequences and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the China Glioma Genome Atlas (CGGA). Using univariate Cox analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, IFN-γ-related prognostic genes were selected to construct a risk scoring model, and analyze its correlation with the clinical features. A high-precision nomogram was drawn to predict prognosis, and its performance was evaluated using calibration curve. Finally, immune cell infiltration and immune checkpoint molecule expression were analyzed to explore the tumor microenvironment characteristics associated with the risk scoring model. Results: Four out of 198 IFN-γ-related genes were selected to construct a risk score model with good predictive performance. The expression of four IFN-γ-related genes in glioma tissues was significantly increased compared to normal brain tissue (p < 0.001). Based on ROC analysis, the risk score model accurately predicted the overall survival rate of glioma patients at 1 year (AUC: The Cancer Genome Atlas 0.89, CGGA 0.59), 3 years (AUC: TCGA 0.89, CGGA 0.68), and 5 years (AUC: TCGA 0.88, CGGA 0.70). Kaplan-Meier analysis showed that the overall survival rate of the high-risk group was significantly lower than that of the low-risk group (p < 0.0001). Moreover, high-risk scores were associated with wild-type IDH1, wild-type ATRX, and 1P/19Q non-co-deletion. The nomogram predicted the survival rate of glioma patients based on the risk score and multiple clinicopathological factors such as age, sex, pathological grade, and IDH Status, among others. Risk score and infiltrating immune cells including CD8 T-cell, resting CD4 memory T-cell, regulatory T-cell (Tregs), M2 macrophages, resting NK cells, activated mast cells, and neutrophils were positively correlated (p < 0.05). In addition, risk scores closely associated with expression of immune checkpoint molecules such as PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, TIGIT, CD48, CD226, and CD96. Conclusion: Our risk score model reveals that IFN-γ -associated genes are an independent prognostic factor for predicting overall survival in glioma, which is closely associated with immune cell infiltration and immune checkpoint molecule expression. This model will be helpful in predicting the effectiveness of immunotherapy and survival rate in patients with glioma.
| S-EPMC9880184 | biostudies-literature
Project description:Osteosarcoma has been the most common malignant bone tumor in children and adolescents, while the 5-y survival of osteosarcoma patients gained no significant improvement over the past decades. This study aimed to explore the role of ferroptosis-related genes (FRGs) in the development and prognosis of osteosarcoma. The datasets of osteosarcoma patients including RNA sequencing data and clinical information were acquired from the TRGET and Gene Expression Omnibus (GEO) databases. The identification of molecular subgroups with different FRG expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. The prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis. The ESTIMATE algorithm was applied for determining the stromal score, immune score, ESTIMA score, and tumor purity of osteosarcoma patients. Functional analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were conducted to explore the underlying mechanisms in the development and prognosis of osteosarcoma. Two molecular subgroups with different FRGs expression patterns were identified. The molecular subgroups with higher immune score and more active immune status showed better prognostic survival. On the basis of FRGs, a prognostic model and a nomogram integrating clinical characteristics were constructed and their prediction efficiency for osteosarcoma prognosis were well validated. Gene functional enrichment analysis showed that these differentially expressed FRGs were mainly enriched in immunity-related signaling pathways, indicating that FRGs may affect the development and prognosis of osteosarcoma by regulating the immune microenvironment. The expression profiles of FRGs were closely related to the immunity status and prognostic survival of osteosarcoma patients. The interaction between ferroptosis and immunity in the development of osteosarcoma could provide a new insight into the exploration of molecular mechanisms and targeted therapies of osteosarcoma patients.
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Project description:Background: Although multiple metabolic pathways are involved in the initiation, progression, and therapy of lung adenocarcinoma (LUAD), the tumor microenvironment (TME) for immune cell infiltration that is regulated by metabolic enzymes has not yet been characterized. Methods: 517 LUAD samples and 59 non-tumor samples were obtained from The Cancer Genome Atlas (TCGA) database as the training cohort. Kaplan-Meier analysis and Univariate Cox analysis were applied to screen the candidate metabolic enzymes for their role in relation to survival rate in LUAD patients. A prognostic metabolic enzyme signature, termed the metabolic gene risk score (MGRS), was established based on multivariate Cox proportional hazards regression analysis and was verified in an independent test cohort, GSE31210. In addition, we analyzed the immune cell infiltration characteristics in patients grouped by their Risk Score. Furthermore, the prognostic value of these four enzymes was verified in another independent cohort by immunohistochemistry and an optimized model of the metabolic-immune protein risk score (MIPRS) was constructed. Results: The MGRS model comprising 4 genes (TYMS, NME4, LDHA, and SMOX) was developed to classify patients into high-risk and low-risk groups. Patients with a high-risk score had a poor prognosis and exhibited activated carbon and nucleotide metabolism, both of which were associated with changes to TME immune cell infiltration characteristics. In addition, the optimized MIPRS model showed more accurate predictive power in prognosis of LUAD. Conclusion: Our study revealed an integrated metabolic enzyme signature as a reliable prognostic tool to accurately predict the prognosis of LUAD.
| S-EPMC8361602 | biostudies-literature
Project description:BackgroundCutaneous melanoma is a common but aggressive tumor. Ferroptosis is a recently discovered cell death with important roles in tumor biology. Nevertheless, the prognostic power of ferroptosis-linked genes remained unclear in cutaneous melanoma.MethodsCutaneous melanoma patients of TCGA (The Cancer Genome Atlas) were taken as the training cohort while GSE65904 and GSE22153 as the validation cohorts. Multifactor Cox regression model was used to build a prognostic model, and the performance of the model was assessed. Functional enrichment and immune infiltration analysis were used to clarify the mechanisms.ResultsA five ferroptosis-linked gene predictive model was developed. ALOX5 and GCH1 were illustrated as independent predictive factors. Functional assessment showed enriched immune-linked cascades. Immune infiltrating analysis exhibited the distinct immune microenvironment.ConclusionHerein, a novel ferroptosis-related gene prognostic model was built in cutaneous melanoma. This model could be used for prognostic prediction, and maybe helpful for the targeted and immunotherapies.
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Project description:BackgroundThe prognosis and survival of lung adenocarcinoma (LUAD) patients are still not promising despite recent breakthroughs in treatment. Endoplasmic reticulum stress (ERS) is a self-protective mechanism resulting from an imbalance in quality control of unfolded proteins when cells are stressed, which plays an active role in lung cancer development, but the relationship between ERS and the pathological characteristics and clinical prognosis of LUAD patients remains unclear.MethodsLASSO and Cox regression were applied based on sequencing information to construct the model, which was validated to be robust. The risk scores of the patients were calculated using the formula provided by the model, and the patients were divided into high and low-risk groups according to the median cut-off of risk scores. Cox regression analysis identifies independent prognostic factors for these patients, and enrichment analysis of prognosis-related genes was also performed. The relationship between risk scores and tumor mutation burden (TMB), cancer stem cell index, and drug sensitivity was explored.ResultsWe constructed a 13-gene prognostic model for LUAD patients. Patients in the high-risk group had worse overall survival, lower immune score and ESTIMATE score, higher TMB, higher cancer stem cell index, and higher sensitivity to conventional chemotherapeutic agents. In addition, we constructed a nomogram that predicts 5-year survival in LUAD patients, which helps clinicians to foresee the prognosis from a new perspective.ConclusionsOur results highlight the association of ERS with LUAD and the potential use of ERS in guiding treatment.
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Project description:FoxM1 is an oncoprotein that is significantly overexpressed in many malignancies including hepatocellular carcinoma, but its role in intrahepatic cholangiocarcinoma (ICC) remains unclear. This study explores the expression of FoxM1 in human ICC, its relationships with clinical outcomes, and its role in the proliferation, migration, and invasion of ICC in vitro and in vivo. The results show that FoxM1 was markedly elevated in tumor tissues versus the paired peritumoral tissues. Overexpression of FoxM1 was correlated with multiple tumor nodules, tumor size > 5 cm, positive lymph node metastasis and advanced TNM stage. Cox analysis revealed that overexpression of FoxM1 is an independent prognostic indicator for both the overall survival and disease-free survival of ICC patients after hepatectomy. Furthermore, up/downregulation of FoxM1 markedly promoted/inhibited ICC cell proliferation, migration, and invasion in vitro and in vivo. Bioinformatic analysis indicated that overexpression of FoxM1 resulted in the dysregulation of multiple signaling pathways in ICC, and selected components of some key signaling pathways such as c-Myc signaling were confirmed in vitro. In addition, overexpression of FoxM1 enhanced MMP-9 and MMP-2 protein expression in ICC cells. In conclusion, FoxM1 promotes ICC progression and is a reliable predictor of poor prognosis in ICC.
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Project description:ObjectiveTo identify the gene subtypes related to immune cells of cholangiocarcinoma and construct an immune score model to predict the immunotherapy efficacy and prognosis for cholangiocarcinoma.MethodsBased on principal component analysis (PCA) algorithm, The Cancer Genome Atlas (TCGA)-cholangiocarcinoma, GSE107943 and E-MTAB-6389 datasets were combined as Joint data. Immune genes were downloaded from ImmPort. Univariate Cox survival analysis filtered prognostically associated immune genes, which would identify immune-related subtypes of cholangiocarcinoma. Least absolute shrinkage and selection operator (LASSO) further screened immune genes with prognosis values, and tumor immune score was calculated for patients with cholangiocarcinoma after the combination of the three datasets. Kaplan-Meier curve analysis determined the optimal cut-off value, which was applied for dividing cholangiocarcinoma patients into low and high immune score group. To explore the differences in tumor microenvironment and immunotherapy between immune cell-related subtypes and immune score groups of cholangiocarcinoma.Results34 prognostic immune genes and three immunocell-related subtypes with statistically significant prognosis (IC1, IC2 and IC3) were identified. Among them, IC1 and IC3 showed higher immune cell infiltration, and IC3 may be more suitable for immunotherapy and chemotherapy. 10 immune genes with prognostic significance were screened by LASSO regression analysis, and a tumor immune score model was constructed. Kaplan-Meier (KM) and receiver operating characteristic (ROC) analysis showed that RiskScore had excellent prognostic prediction ability. Immunohistochemical analysis showed that 6 gene (NLRX1, AKT1, CSRP1, LEP, MUC4 and SEMA4B) of 10 genes were abnormal expressions between cancer and paracancer tissue. Immune cells infiltration in high immune score group was generally increased, and it was more suitable for chemotherapy. In GSE112366-Crohn's disease dataset, 6 of 10 immune genes had expression differences between Crohn's disease and healthy control. The area under ROC obtained 0.671 based on 10-immune gene signature. Moreover, the model had a sound performance in Crohn's disease.ConclusionThe prediction of tumor immune score model in predicting immune microenvironment, immunotherapy and chemotherapy in patients with cholangiocarcinoma has shown its potential for indicating the effect of immunotherapy on patients with cholangiocarcinoma.
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Project description:Background With the feature of destructive and biliary malignancy, intrahepatic cholangiocarcinoma (ICC), presents unclear molecular mechanisms which contributes to typically poor prognosis for patients. Seizure-related 6 homolog-like 2 (SEZ6L2) is a gene that encodes for a seizure-associated protein localized on the cell surface. Thus far, the function of SEZ6L2 in ICC has not been reported. Methods We used data from The Cancer Genome Atlas and the Gene Expression Omnibus to analyze dynamics behind and levels of expression of SEZ6L2 in ICC. Then we used qRT-PCR and Immunohistochemical staining to detect levels of expression of SEZ6L2 and thereby determined the potential clinical significance of this protein in ICC. Results According to qRT-PCR and immunohistochemical analysis results, SEZ6L2 was overexpressed in ICC. Kaplan-Meier and Cox proportional hazard analyses indicated that patients afflicted by ICC with high levels of relative expression of SEZ6L2 have a poorer prognosis and that SEZ6L2 may be an independent prognostic factor which enables to the accurate prediction of overall survival (OS) and disease-free survivals’ (DFS) expected rates. Subcutaneous xenograft models used to explore the role of SEZ6L2 in tumor formation in vivo. The dynamics of the SEZ6L2 gene being promote angiogenesis in cholangiocarcinoma are related to increasing expressive growth factors which include EGF, VEGF, PDGF and the activation of the P38-MAPK pathway. Conclusions Our findings suggest that SEZ6L2 can serve as an advanced biomarker that can be used to accurately predict a patient prognosis and be used as a target for ICC treatment.
| S-EPMC8798643 | biostudies-literature
Project description:Background: Despite recent improvements in the diagnosis and therapy of intrahepatic cholangiocarcinoma (ICC), the prognosis for ICC patients remains poor. Therefore, it is needed to identify new biological indicators for ICC progression. Methods: Immunohistochemistry was engaged to inspect the ecto-5'-nucleotidase (CD73) and CD8 expressions in tissue microarrays including tissues from 140 ICC patients. Then, the association between the level of CD73/CD8 and clinicopathologic characteristics of ICC was analysed. Finally, the prognostic value of CD73 and CD8 levels in ICC patients was assessed by Kaplan-Meier and multivariate and univariate analyses. Results: The CD73 expression was evidently upregulated in ICC tissues compared to the corresponding peritumoral tissues. The elevated CD73 expression was positively related to the lymphatic metastasis (p=0.049). While the level of tumour-infiltrating CD8 T+ cells in tumour tissues was negatively associated with serum AFP (p=0.019), tumor size (p=0.028), and lymphatic metastasis (p=0.039). Additionally, patients with elevated CD73 expression or low tumour-infiltrating CD8+ T cells exhibited shorter overall survival (OS) and higher disease-free survival (DFS) rates than patients with low CD73 expression and/or high tumour-infiltrating CD8+ T cells. Notably, the overexpression of CD73 or low tumour-infiltrating CD8+ T cells was an independent indicator for predicting the OS and DFS of ICC patients. Conclusions: We revealed that CD73 expression and low tumour-infiltrating CD8+T cells are valuable predictors of survival and recurrence in patients with ICC.
| S-EPMC8210563 | biostudies-literature
Project description:BackgroundAlthough the outcome of patients with gastric cancer (GC) has improved significantly with the recent implementation of annual screening programs. Reliable prognostic biomarkers are still needed due to the disease heterogeneity. Increasing pieces of evidence revealed an association between immune signature and GC prognosis. Thus, we aim to build an immune-related signature that can estimate prognosis for GC.MethodsFor identification of a prognostic immune-related gene signature (IRGS), gene expression profiles and clinical information of patients with GC were collected from 3 public cohorts, divided into training cohort (n = 300) and 2 independent validation cohorts (n = 277 and 433 respectively).ResultsWithin 1811 immune genes, a prognostic IRGS consisting of 16 unique genes was constructed which was significantly associated with survival (hazard ratio [HR], 3.9 [2.78-5.47]; P < 1.0 × 10). In the validation cohorts, the IRGS significantly stratified patients into high- vs low-risk groups in terms of prognosis across (HR, 1.84 [1.47-2.30]; P = 6.59 × 10) and within subpopulations with stage I&II disease (HR, 1.96 [1.34-2.89]; P = 4.73 × 10) and was prognostic in univariate and multivariate analyses. Several biological processes, including TGF-β and EMT signaling pathways, were enriched in the high-risk group. T cells CD4 memory resting and Macrophage M2 were significantly higher in the high-risk risk group compared with the low-risk group.ConclusionIn short, we developed a prognostic IRGS for estimating prognosis in GC, including stage I&II disease, providing new insights into the identification of patients with GC with a high risk of mortality.
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