scholarly journals Molecular Characteristics, Clinical Implication, and Cancer Immunity Interactions of Pyroptosis-Related Genes in Breast Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Dandan Xu ◽  
Zhipeng Ji ◽  
Ling Qiang
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Signature ◽  
Immune Checkpoints ◽  
Molecular Characteristics ◽  
Predictive Index ◽  
Cox Regression Analysis ◽  
Cancer Immunity ◽  
Tcga Dataset

Objective: Pyroptosis represents an emerging inflammatory form of programmed cell death. Herein, specific functions and clinical implications of pyroptosis-related genes were systematically characterized in breast cancer.Methods: Expression, somatic mutation and copy number variation of 33 pyroptosis-related genes were assessed in breast cancer from TCGA dataset. Their interactions, biological functions and prognostic values were then observed. By stepwise Cox regression analysis, a pyroptosis-related gene signature was generated. The predictive efficacy in survival was examined by survival analyses, ROCs, univariate and multivariate analyses and subgroup analyses. Associations between risk score (RS) and cancer immunity cycle, HLA, immune cell infiltrations, and immune checkpoints were analyzed.Results: Most of pyroptosis-related genes were abnormally expressed in breast cancer. CASP8, NLRC4, NLRP3, NLRP2, PLCG1, NLRP1, NLRP7, SCAF11, GSDMC, and NOD1 occurred somatic mutations as well as most of them had high frequency of CNV. There were closely interactions between them. These genes were distinctly enriched in immune-related processes. A three-gene signature was generated, containing IL-18, GSDMC, and TIRAP. High RS predicted poorer overall survival, progression, and recurrence. After verification, this RS was an independent and sensitive predictive index. This RS was negatively correlated to cancer immunity cycle. Also, low RS was characterized by high HLA, immune cell infiltrations and immune checkpoints. A nomogram including age and RS was generated for accurately predicting 5-, 8-, and 10-year survival probabilities.Conclusion: Pyroptosis-related genes exert key roles in cancer immunity and might be applied as a prognostic factor of breast cancer.

scholarly journals An Immune-Related Gene Prognostic Index for Triple-Negative Breast Cancer Integrates Multiple Aspects of Tumor-Immune Microenvironment

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5342
Author(s):  
Xiaowei Wang ◽  
Wenjia Su ◽  
Dabei Tang ◽  
Jing Jing ◽  
Jing Xiong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Molecular Taxonomy ◽  
Prognostic Index ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Data Set ◽  
Cox Regression Analysis

Tumor-immune cell compositions and immune checkpoints comprehensively affect TNBC outcomes. With the significantly improved survival rate of TNBC patients treated with ICI therapies, a biomarker integrating multiple aspects of TIME may have prognostic value for improving the efficacy of ICI therapy. Immune-related hub genes were identified with weighted gene co-expression network analysis and differential gene expression assay using The Cancer Genome Atlas TNBC data set (n = 115). IRGPI was constructed with Cox regression analysis. Immune cell compositions and TIL status were analyzed with CIBERSORT and TIDE. The discovery was validated with the Molecular Taxonomy of Breast Cancer International Consortium data set (n = 196) and a patient cohort from our hospital. Tumor expression or serum concentrations of CCL5, CCL25, or PD-L1 were determined with immunohistochemistry or ELISA. The constructed IRGPI was composed of CCL5 and CCL25 genes and was negatively associated with the patient’s survival. IRGPI also predicts the compositions of M0 and M2 macrophages, memory B cells, CD8+ T cells, activated memory CD4 T cells, and the exclusion and dysfunction of TILs, as well as PD-1 and PD-L1 expression of TNBC. IRGPI is a promising biomarker for predicting the prognosis and multiple immune characteristics of TNBC.

scholarly journals Development and Verification of a Hypoxic Gene Signature for Predicting Prognosis, Immune Microenvironment, and Chemosensitivity for Osteosarcoma

2022 ◽  
Vol 8 ◽  
Author(s):  
Fengfeng Wu ◽  
Juntao Xu ◽  
Mingchao Jin ◽  
Xuesheng Jiang ◽  
Jianyou Li ◽  
...  
Keyword(s):  
Risk Score ◽  
Immune Cell ◽  
Cox Regression ◽  
External Validation ◽  
Gene Signature ◽  
Low Risk ◽  
Immune Checkpoints ◽  
Survival Duration ◽  
Cox Regression Analysis ◽  
Chemotherapy Drugs

Objective: Hypoxic tumors contribute to local failure and distant metastases. Nevertheless, the molecular hallmarks of hypoxia remain ill-defined in osteosarcoma. Here, we developed a hypoxic gene signature in osteosarcoma prognoses.Methods: With the random survival forest algorithm, a prognostic hypoxia-related gene signature was constructed for osteosarcoma in the TARGET cohort. Overall survival (OS) analysis, receiver operating characteristic (ROC) curve, multivariate cox regression analysis, and subgroup analysis were utilized for assessing the predictive efficacy of this signature. Also, external validation was presented in the GSE21257 cohort. GSEA was applied for signaling pathways involved in the high- and low-risk samples. Correlation analyses between risk score and immune cells, stromal/immune score, immune checkpoints, and sensitivity of chemotherapy drugs were performed in osteosarcoma. Then, a nomogram was built by integrating risk score, age, and gender.Results: A five-hypoxic gene signature was developed for predicting survival outcomes of osteosarcoma patients. ROC curves confirmed that this signature possessed the well predictive performance on osteosarcoma prognosis. Furthermore, it could be independently predictive of prognosis. Metabolism of xenobiotics by cytochrome P450 and nitrogen metabolism were activated in the high-risk samples while cell adhesion molecules cams and intestinal immune network for IgA production were enriched in the low-risk samples. The low-risk samples were characterized by elevated immune cell infiltrations, stromal/immune scores, TNFRSF4 expression, and sensitivity to cisplatin. The nomogram accurately predicted 1-, 3-, and 5-years survival duration.Conclusion: These findings might offer an insight into the optimization of prognosis risk stratification and individualized therapy for osteosarcoma patients.

scholarly journals An Immune-Related Prognostic Signature for Predicting Clinical Outcomes and Immune Landscape in IDH-Mutant Lower-Grade Gliomas

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Gang Xiao ◽  
Xuan Gao ◽  
Lifeng Li ◽  
Chao Liu ◽  
Zhiyuan Liu ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Outcomes ◽  
Immune Cell ◽  
Cox Regression ◽  
Immune Escape ◽  
Gene Signature ◽  
Individual Therapy ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Cox Regression Analysis

Background. IDH mutation is the most common in diffuse LGGs, correlated with a favorable prognosis. However, the IDH-mutant LGGs patients with poor prognoses need to be identified, and the potential mechanism leading to a worse outcome and treatment options needs to be investigated. Methods. A six-gene immune-related prognostic signature in IDH-mutant LGGs was constructed based on two public datasets and univariate, multivariate, and LASSO Cox regression analysis. Patients were divided into low- and high-risk groups based on the median risk score in the training and validation sets. We analyzed enriched pathways and immune cell infiltration, applying the GSEA and the immune evaluation algorithms. Results. Stratification and multivariate Cox analysis unveiled that the six-gene signature was an independent prognostic factor. The signature (0.806/0.795/0.822) showed a remarkable prognostic performance, with 1-, 3-, and 5-year time-dependent AUC, higher than for grade (0.612/0.638/0.649) and 1p19q codeletion status (0.606/0.658/0.676). High-risk patients had higher infiltrating immune cells. However, the specific immune escape was observed in the high-risk group after immune activation, owing to increasing immunosuppressive cells, inhibitory cytokines, and immune checkpoint molecules. Moreover, a novel nomogram model was developed to evaluate the survival in IDH-mutant LGGs patients. Conclusion. The six-gene signature could be a promising prognostic biomarker, which is promising to promote individual therapy and improve the clinical outcomes of IDH-mutant gliomas. The study also refined the current classification system of IDH-mutant gliomas, classifying patients into two subtypes with distinct immunophenotypes and overall survival.

scholarly journals Identification of a Novel Glycolysis-Related Signature to Predict the Prognosis of Patients with Breast Cancer

2021 ◽  
Author(s):  
Menglin He ◽  
Cheng Hu ◽  
Jian Deng ◽  
Hui Ji ◽  
Weiqian Tian
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
High Risk Group ◽  
Low Risk ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Incidence And Mortality

Abstract Background: Breast cancer (BC) is a kind of cancer with high incidence and mortality in female. Conventional clinical characteristics are far from accurate to predict individual outcomes. Therefore, we aimed to develop a novel signature to predict the survival of patients with BC. Methods: We analyzed the data of a training cohort from the TCGA database and a validation cohort from GEO database. After the applications of GSEA and Cox regression analyses, a glycolysis-related signature for predicting the survival of patients with BC was developed. The signature contains AK3, CACNA1H, IL13RA1, NUP43, PGK1, and SDC1. Then, we constructed a risk score formula to classify the patients into high and low-risk groups based on the expression levels of six-gene in patients. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to assess the predicted capacity of the model. Next, a nomogram was developed to predict the outcomes of patients with risk score and clinical features in 1, 3, and 5 years. We further used Human Protein Atlas (HPA) database to validate the expressions of the six biomarkers in tumor and sample tissues.Results: We constructed a six-gene signature to predict the outcomes of patients with BC. The patients in high-risk group showed poor prognosis than that in low-risk group. The AUC values were 0.719 and 0.702, showing that the prediction performance of the signature is acceptable. Additionally, Cox regression analysis revealed that these biomarkers could independently predict the prognosis of BC patients without being affected by clinical factors. The expression levels of all six biomarkers in BC tissues were higher than that in normal tissues except AK3. Conclusion: We developed a six-gene signature to predict the prognosis of patients with BC. Our signature has been proved to have the ability to make an accurate and obvious prediction and might be used to expand the prediction methods in clinical.

scholarly journals Elevated expression of IL-10RB acts as an independent unfavorable prognostic marker and predicts the polarization of tumor-associated macrophages in glioma

2021 ◽  
Author(s):  
Yaqiong Fan ◽  
Yichen Peng ◽  
Feng Chen ◽  
Wenbin Li
Keyword(s):  
Immune Responses ◽  
Prognostic Marker ◽  
Poor Prognosis ◽  
Immune Cell ◽  
Cox Regression ◽  
Interleukin 10 ◽  
Immune Checkpoints ◽  
Marker Genes ◽  
Tumor Associated Macrophages ◽  
Cox Regression Analysis

Abstract Background: Interleukin-10 receptor B (IL10RB) is a subunit of the interleukin-10 receptor. As an important part of the interleukin-10 signaling pathway, IL10RB plays an essential role in the regulation of the immune response. However, studies of IL10RB in glioma are rare. The present study aimed to investigate the potential role of IL10RB in glioma.Methods: 611 glioma samples in TCGA dataset and 310 glioma samples in CGGA dataset were download and organized, then analyzed the clinical expression characteristics and prognostic value of IL10RB as well as its correlation with immune cell infiltration in these samples using R. Results: IL10RB expression was significantly higher in the glioma tissues than in the normal tissues and increased in gliomas, especially with malignant phenotype. The Kaplan-Meier survival analysis and Cox regression analysis indicated that IL10RB was significantly associated with poor prognosis in patients with glioma and could be used as an independent prognostic marker. Further functional analysis suggested that IL10RB was involved in immune responses, and high expression of IL10RB in the glioma tissue resulted in more infiltrated immune cells, especially macrophages. Moreover, IL10RB was found to be strongly correlated with marker genes of tumor-associated macrophages (TAMs) and M2 macrophages, but low or even no correlation with marker genes of M1 macrophages. In addition, there was also a significant association between IL10RB and immune checkpoints that suppress effective antitumor immune responses.Conclusions: Our results demonstrated that high expressed IL10RB was associated with the malignant progression of gliomas and poor prognosis, and it might be involved in the polarization of macrophages which play a crucial role in the immunosuppressive response of gliomas.

scholarly journals A Novel Immune Checkpoint-Related Gene Signature to Predict Overall Survival and Immunotherapy Response in Triple-Negative Breast Cancer

2021 ◽  
Author(s):  
Jingyi Liu ◽  
Siyuan Tian ◽  
Yuwei Ling ◽  
Xinyi Zhang ◽  
Yan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Immune Checkpoint ◽  
Triple Negative ◽  
Cox Regression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Molecular Taxonomy ◽  
Gene Signature ◽  
Cox Regression Analysis

Abstract Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that lacks effective therapeutic targets. Immunotherapy is considered as a novel treatment strategy for TNBC. However, only some patients could benefit from the treatment. Limited studies have comprehensively explored expression patterns and prognostic value of immune checkpoint genes (ICGs) in TNBC. In this study, we downloaded relevant ICGs expression profiles and clinical TNBC data from the Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to develop a multi-gene signature for predicting the prognostic outcome. PDCD1, PDCD1LG2 and KIR3DL2 were identified as hub genes and incorporated into the model. This gene signature could stratify patients into two prognostic subgroups, and unfavorable clinical outcomes were observed in high-risk patients. The predictive performance was assessed by the receiver operating characteristic curves. Moreover, we also analyzed differences in immune status and therapeutic response between both groups. This novel gene signature may be served as a robust prognostic marker, but also an indicator reflecting immunotherapy response.

scholarly journals Androgen Receptor Highjacks ErbB-2 Nuclear Function to Induce Triple Negative Breast Cancer Growth

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A804-A804
Author(s):  
Agustina Roldán Deamicis ◽  
Robert H Oakley ◽  
Sergio Andonegui Helguera ◽  
Mariela B Lenze ◽  
Santiago Madera ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Androgen Receptor ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Nuclear Migration ◽  
Subcellular Fractionation ◽  
Gene Signature ◽  
Dominant Negative ◽  
Cox Regression Analysis

Abstract Triple negative breast cancer (TNBC) has poor prognosis and neither established biomarkers nor therapeutic targets. On the one hand the androgen receptor (AR), a steroid hormone receptor (SR) which is expressed in 10-53% of TNBC and proved to be critical for BC proliferation, has been proposed as a new target in TNBC. On the other hand, we and others have shown that membrane ErbB-2 migrates to the nucleus (nuclear ErbB-2, NErbB-2) where it binds DNA at HER-2 associated sequences (HAS) to regulate BC proliferation and migration. Since we have previously shown a functional interplay between growth factors and SR signaling pathways in BC, we propose the existence of an interaction between AR and ErbB-2 which is involved in NErbB-2+/AR+ BC growth. The experimental model used was the human TNBC cell line MDA-MB-453 which displays high expression levels of AR and NErbB-2. By Western Blot (WB) we found that dihydrotestosterone (DHT) treatment for short times (minutes) did not regulate ErbB-2 phosphorylation status at residues Tyr1221/1222 and 1248 which were constitutively activated. However, DHT led to an increase in ErbB-2 phosphorylation at residue Tyr877 which we have proved to be required for ErbB-2 nuclear migration. The latter effect was blocked by the AR antagonist enzalutamide (enza). Blockage of Src activity with dasatinib inhibited DHT-induced ErbB-2 phosphorylation at Tyr877. By Immunofluorescence and confocal microscopy analyses and subcellular fractionation studies we demonstrated that DHT induced ErbB-2 nuclear migration which was inhibited by enza. By chIP we found that DHT induced ErbB-2 recruitment to a HAS site in ERK5, a gene involved in BC proliferation, and to a HAS site in FKBP5, a classical AR responsive gene. By WB we demonstrated that transfection with an ErbB-2 mutant which is unable to translocate to the nucleus and functions as a dominant negative inhibitor of ErbB-2 nuclear migration (hErbB-2ΔNLS), inhibited FKBP51 up-regulation by DHT. Finally, by microarray and bioinformatics analysis we identified 315 differentially expressed genes (DEGs) in the presence of DHT and NErbB-2 eviction. Enrichment analyses showed that the DEGs belonged to the immune response and interferon pathways. Kaplan-Meier analysis revealed that the expression of 6 genes was significantly associated with overall survival in TNBC patients from the METABRIC cohort: CXCL10, TAP1, STAT1, NMI, HLA-A and NLRC5. Multivariate Cox regression analysis identified the combined expression of the 6 genes as an independent predictor of better clinical outcome in TNBC (HR: 0.56, 95% CI 0.38-0.82, P = 0.003). In conclusion, our findings evidence that DHT-activated AR induces Src-mediated ErbB-2 rapid activation and its migration to the nucleus where it binds to HAS sites in the DNA. Moreover, based on the DEGs of NErbB-2 eviction in presence of DHT we identified a gene signature associated with favorable outcome in TNBC.

scholarly journals Identification of a Novel Glycolysis-Related Gene Signature for Predicting Breast Cancer Survival

2021 ◽  
Vol 10 ◽  
Author(s):  
Dai Zhang ◽  
Yi Zheng ◽  
Si Yang ◽  
Yiche Li ◽  
Meng Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Survival ◽  
Cox Regression ◽  
Gene Signature ◽  
Breast Cancer Survival ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Kaplan Meier

To identify a glycolysis-related gene signature for the evaluation of prognosis in patients with breast cancer, we analyzed the data of a training set from TCGA database and four validation cohorts from the GEO and ICGC databases which included 1,632 patients with breast cancer. We conducted GSEA, univariate Cox regression, LASSO, and multiple Cox regression analysis. Finally, an 11-gene signature related to glycolysis for predicting survival in patients with breast cancer was developed. And Kaplan–Meier analysis and ROC analyses suggested that the signature showed a good prognostic ability for BC in the TCGA, ICGC, and GEO datasets. The analyses of univariate Cox regression and multivariate Cox regression revealed that it’s an important prognostic factor independent of multiple clinical features. Moreover, a prognostic nomogram, combining the gene signature and clinical characteristics of patients, was constructed. These findings provide insights into the identification of breast cancer patients with a poor prognosis.

Comprehensive Analysis of the Immune Effect of TGFβ1 in Colorectal Adenocarcinoma:A TGFβ1-related Prognostic Model of Tumor Microenvironment

2021 ◽  
Author(s):  
Yucheng Qian ◽  
Lina Zhang ◽  
Jihang Wen ◽  
Yanxia Mei ◽  
Jingsun Wei ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Survival Data ◽  
Prognostic Model ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Immune Checkpoints ◽  
Cox Regression Analysis

Abstract ColorColorectal cancer is one of the most common cancer worldwide. Recently, tumor microenvironment (TME), especially its remoulding , is thought to control the colorectal cancer genesis and progression. In this study, we use ESTIMATEscore to make out the proportion of immune and stromal components in colorectal adenocarcinoma (CRA) samples from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were found by COX regression analysis and protein-protein interaction (PPI) network, among which TGFβ1 was supposed to be a prognosis factor and tumor environment indicator. Continuous analysis showed that TGFβ1 expression is positively correlated with lymph node metastasis (N stage) but negatively correlated with survival. Gene Set Enrichment Analysis (GSEA) revealed that the genes of the high-expression TGFβ1 group were mainly enriched in immune-related activities. Cluster analysis divided the samples into 2 subgroups. 24 HLA-related genes and 8 immune checkpoint genes were found upregulated in the high immunity group as well as TGFβ1, which suggests the possibility of novel therapies targeting immune checkpoints combined with TGFβ1. Tumor-infiltrating immune cell (TIC) profile of CRA patients was described by CIBERSORT analysis. Further analysis showed that the infiltration of Tregs and Neutrophils were positively correlated with TGFβ1 high expression. Then 3 TGFβ1-related genes were picked out to construct a prognostic model, which matches the survival data well.

scholarly journals Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Huiling Wang ◽  
Shuo You ◽  
Meng Fang ◽  
Qian Fang
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Regression Analysis ◽  
Clustering Algorithm ◽  
Immune Cell ◽  
Cox Regression ◽  
Therapeutic Potential ◽  
Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Immune Infiltration

Background. Breast cancer (BC) is the most common malignant tumor in women. The immunophenotype of tumor microenvironment (TME) has shown great therapeutic potential in tumor. Method. The transcriptome was obtained from TCGA and GEO data. Immune infiltration was analyzed by single-sample gene set enrichment (ssGSEA). The immune feature was constructed by Cox regression analysis. In addition, the coexpression of differential expression genes (DEGs) was identified. Through enrichment analysis, the function and pathway of module genes were identified. The somatic mutations related to immune characteristics were analyzed by Maftools. By using the consistency clustering algorithm, the molecular subtypes were constructed, and the overall survival time (OS) was predicted. Results. Immune landscape can be divided into low immune infiltration and high immune infiltration. Cox regression analysis identified seven immune cells as protective factors of BC. In the coexpression modules for DEGs of high and low immune infiltration, module 1 was related to T cells and high immune infiltration. In particular, the area under the curve (AUC) value of hub gene SASH3 was the highest, and the correlation with T cells was stronger in the high immune infiltration. Enrichment analysis found that oxidative stress, T cell aggregation, and apoptosis were observed in high immune infiltration. In addition, TP53 was identified as the most important somatic gene mutation related to immune characteristics. Importantly, we also constructed seven immune cell-based breast cancer subtypes to predict OS. Conclusion. We evaluated the immune landscape of BC and constructed the gene characteristics related to the immune landscape. The potential of T cells and SASH3 in immunotherapy of BC was revealed, which may guide the development of new clinical treatment strategies.

Sign in / Sign up

Export Citation Format

Share Document