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Guo Y, Wu Z, Cen K, Bai Y, Dai Y, Mai Y, Hong K, Qu L. Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma. Front Immunol 2023; 14:1171811. [PMID: 37359528 PMCID: PMC10289160 DOI: 10.3389/fimmu.2023.1171811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 05/26/2023] [Indexed: 06/28/2023] Open
Abstract
Background Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients' prognoses. Methods The URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool. Results The URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes. Conclusion The URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.
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Affiliation(s)
- Yangyang Guo
- Department of General Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
- Department of Emergency, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, Zhejiang, China
| | - Zhixuan Wu
- Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kenan Cen
- Department of General Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - Yongheng Bai
- National Key Clinical Specialty (General Surgery), The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ying Dai
- Department of General Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - Yifeng Mai
- Department of General Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - Kai Hong
- Department of General Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - Liangchen Qu
- Department of Emergency, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, Zhejiang, China
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Li N, Jia X, Wang Z, Wang K, Qu Z, Chi D, Sun Z, Jiang J, Cui Y, Wang C. Characterization of anoikis-based molecular heterogeneity in pancreatic cancer and pancreatic neuroendocrine tumor and its association with tumor immune microenvironment and metabolic remodeling. Front Endocrinol (Lausanne) 2023; 14:1153909. [PMID: 37234801 PMCID: PMC10206226 DOI: 10.3389/fendo.2023.1153909] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 03/21/2023] [Indexed: 05/28/2023] Open
Abstract
Background Accumulating evidence suggests that anoikis plays a crucial role in the onset and progression of pancreatic cancer (PC) and pancreatic neuroendocrine tumors (PNETs); nevertheless, the prognostic value and molecular characteristics of anoikis in cancers are yet to be determined. Materials and methods We gathered and collated the multi-omics data of several human malignancies using the TCGA pan-cancer cohorts. We thoroughly investigated the genomics and transcriptomics features of anoikis in pan-cancer. We then categorized a total of 930 patients with PC and 226 patients with PNETs into distinct clusters based on the anoikis scores computed through single-sample gene set enrichment analysis. We then delved deeper into the variations in drug sensitivity and immunological microenvironment between the various clusters. We constructed and validated a prognostic model founded on anoikis-related genes (ARGs). Finally, we conducted PCR experiments to explore and verify the expression levels of the model genes. Results Initially, we identified 40 differentially expressed anoikis-related genes (DE-ARGs) between pancreatic cancer (PC) and adjacent normal tissues based on the TCGA, GSE28735, and GSE62452 datasets. We systematically explored the pan-cancer landscape of DE-ARGs. Most DE-ARGs also displayed differential expression trends in various tumors, which were strongly linked to favorable or unfavorable prognoses of patients with cancer, especially PC. Cluster analysis successfully identified three anoikis-associated subtypes for PC patients and two anoikis-associated subtypes for PNETs patients. The C1 subtype of PC patients showed a higher anoikis score, poorer prognosis, elevated expression of oncogenes, and lower level of immune cell infiltration, whereas the C2 subtype of PC patients had the exact opposite characteristics. We developed and validated a novel and accurate prognostic model for PC patients based on the expression traits of 13 DE-ARGs. In both training and test cohorts, the low-risk subpopulations had significantly longer overall survival than the high-risk subpopulations. Dysregulation of the tumor immune microenvironment could be responsible for the differences in clinical outcomes between low- and high-risk groups. Conclusions These findings provide fresh insights into the significance of anoikis in PC and PNETs. The identification of subtypes and construction of models have accelerated the progress of precision oncology.
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Affiliation(s)
- Ning Li
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Department of General Surgery, Wafangdian Central Hospital, Dalian, Liaoning, China
- Graduate School of Dalian Medical University, Dalian, Liaoning, China
| | - Xingqing Jia
- Department of Digestive, Jinan City People’s Hospital, Jinan, Shandong, China
| | - Zhong Wang
- Department of General Surgery, Wafangdian Central Hospital, Dalian, Liaoning, China
| | - Kaige Wang
- Graduate School of Dalian Medical University, Dalian, Liaoning, China
| | - Zumin Qu
- Department of Pathology, Wafangdian Central Hospital, Dalian, Liaoning, China
| | - Dong Chi
- Department of General Surgery, Wafangdian Central Hospital, Dalian, Liaoning, China
| | - Zhubo Sun
- Department of General Surgery, Wafangdian Central Hospital, Dalian, Liaoning, China
| | - Jian Jiang
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yougang Cui
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Department of General Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China
| | - Changmiao Wang
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
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Ye S, Yang B, Zhang T, Wei W, Li Z, Chen J, Li X. Identification of an Immune-Related Prognostic Signature for Glioblastoma by Comprehensive Bioinformatics and Experimental Analyses. Cells 2022; 11:cells11193000. [PMID: 36230961 PMCID: PMC9562700 DOI: 10.3390/cells11193000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/13/2022] [Accepted: 09/22/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Glioblastoma (GBM), which has a poor prognosis, accounts for 31% of all cancers in the brain and central nervous system. There is a paucity of research on prognostic indicators associated with the tumor immune microenvironment in GBM patients. Accurate tools for risk assessment of GBM patients are urgently needed. Methods: In this study, we used weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) methods to screen out GBM-related genes among immune-related genes (IRGs). Then, we used survival analysis and Cox regression analysis to identify prognostic genes among the GBM-related genes to further establish a risk signature, which was validated using methods including ROC analysis, stratification analysis, protein expression level validation (HPA), gene expression level validation based on public cohorts, and RT-qPCR. In order to provide clinicians with a useful tool to predict survival, a nomogram based on an assessment of IRGs and clinicopathological features was constructed and further validated using DCA, time-dependent ROC curve, etc. Results: Three immune-related genes were found: PPP4C (p < 0.001, HR = 0.514), C5AR1 (p < 0.001, HR = 1.215), and IL-10 (p < 0.001, HR = 1.047). An immune-related prognostic signature (IPS) was built to calculate risk scores for GBM patients; patients classified into different risk groups had significant differences in survival (p = 0.006). Then, we constructed a nomogram based on an assessment of the IRG-based signature, which was validated as a potential prediction tool for GBM survival rates, showing greater accuracy than the nomogram without the IPS when predicting 1-year (0.35 < Pt < 0.50), 3-year (0.65 < Pt < 0.80), and 5-year (0.65 < Pt < 0.80) survival. Conclusions: In conclusion, we integrated bioinformatics and experimental approaches to construct an IPS and a nomogram based on IPS for predicting GBM prognosis. The signature showed strong potential for prognostic prediction and could help in developing more precise diagnostic approaches and treatments for GBM.
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He S, Qiao J, Wang L, Yu L. A novel immune-related gene signature predicts the prognosis of hepatocellular carcinoma. Front Oncol 2022; 12:955192. [PMID: 36185203 PMCID: PMC9520462 DOI: 10.3389/fonc.2022.955192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/24/2022] [Indexed: 11/21/2022] Open
Abstract
Immune-related genes play a key role in regulating the cancer immune microenvironment, influencing the overall survival of patients with hepatocellular carcinoma (HCC). Along with the rapid development of immunotherapy, identifying immune-related genes with prognostic value in HCC has attracted increasing attention. Here, we aimed to develop a prognostic signature based on immune-related genes. By investigating the transcriptome landscape of 374 HCC and 160 non-HCC samples in silico, a total of 2251 differentially expressed genes were identified. Among which, 183 differentially expressed immune-related genes were subjected to a univariate Cox proportional hazard model to screen for genes with possible prognostic significance. A 10-gene prognostic signature, including HLA-G, S100A9, S100A10, DCK, CCL14, NRAS, EPO, IL1RN, GHR and RHOA, was generated employing a multivariate Cox proportional hazard model. Kaplan–Meier and Receiver Operator Characteristic (ROC) curves were used to evaluate the prognostic utility of the 10-gene signature. Moreover, the underlying mechanisms of these genes were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. According to the Tumor Immune Estimation Resource (TIMER) database, our prognostic signature was significantly associated with tumor-infiltrating B cells, CD4 T cells, dendritic cells, macrophages and neutrophils. Our study provides a novel prognostic signature based on immune-related genes associated with clinical outco mes of HCC.
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Su Y, Qi R, Li L, Wang X, Li S, Zhao X, Hou R, Ma W, Liu D, Zheng J, Shi M. An immune-related gene prognostic risk index for pancreatic adenocarcinoma. Front Immunol 2022; 13:945878. [PMID: 35958614 PMCID: PMC9360334 DOI: 10.3389/fimmu.2022.945878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/04/2022] [Indexed: 11/19/2022] Open
Abstract
Objective Our goal is to construct an immune-related gene prognostic risk index (IRGPRI) for pancreatic adenocarcinoma (PAAD), and to clarify the immune and molecular features in IRGPRI-defined PAAD subgroups and the benefit of immune checkpoint inhibitors (ICIs) therapy. Method Through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and univariate Cox regression analysis, 16 immune-related hub genes were identified using the Cancer Genome Atlas (TCGA) PAAD dataset (n = 182) and immune gene set. From these genes, we constructed an IRGPRI with the Cox regression method and the IRGPRI was verified based on the Gene Expression Omnibus (GEO) dataset (n = 45). Then, we analyzed the immune and molecular features and the benefit of ICI therapy in IRGPRI-defined subgroups. Results Five genes, including S100A16, CD40, VCAM1, TNFRSF4 and TRAF1 were used to construct IRGPRI. As with the results of the GEO cohort, the overall survival (OS) was more favorable in low IRGPRI patients versus high IRGPRI patients. The composite results pointed out that low IRGPRI was associated with immune response-related pathways, high level of CTLA4, low KRAS and TP53 mutation rate, more infiltration of activated memory CD4+ T cells, CD8+ T cells, and more benefits from ICIs therapy. In comparison, high IRGPRI was associated with cancer-related pathways, low expression of CTLA4, high KRAS and TP53 mutation rate, more infiltration of M2 macrophages, and less benefit from ICIs therapies. Conclusion This IRGPRI is an encouraging biomarker to define the prognosis, immune and molecular features, and benefits from ICIs treatments in PAAD.
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Affiliation(s)
- Yang Su
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Ruoshan Qi
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Lanying Li
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Xu Wang
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Sijin Li
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Xuan Zhao
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Rui Hou
- College of Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Wen Ma
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Dan Liu
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
- *Correspondence: Ming Shi, ; Junnian Zheng, ; Dan Liu,
| | - Junnian Zheng
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
- *Correspondence: Ming Shi, ; Junnian Zheng, ; Dan Liu,
| | - Ming Shi
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
- *Correspondence: Ming Shi, ; Junnian Zheng, ; Dan Liu,
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Xu Y, Zheng Q, Zhou T, Ye B, Xu Q, Meng X. Necroptosis-Related LncRNAs Signature and Subtypes for Predicting Prognosis and Revealing the Immune Microenvironment in Breast Cancer. Front Oncol 2022; 12:887318. [PMID: 35686108 PMCID: PMC9171493 DOI: 10.3389/fonc.2022.887318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 04/15/2022] [Indexed: 12/14/2022] Open
Abstract
Purpose Necroptosis is a mode of programmed cell death that overcomes apoptotic resistance. We aimed to construct a steady necroptosis-related signature and identify subtypes for prognostic and immunotherapy sensitivity prediction. Methods Necroptosis-related prognostic lncRNAs were selected by co-expression analysis, and were used to construct a linear stepwise regression model via univariate and multivariate Cox regression, along with least absolute shrinkage and selection operator (LASSO). Quantitative reverse transcription polymerase chain reaction (RT-PCR) was used to measure the gene expression levels of lncRNAs included in the model. Based on the riskScore calculated, we separated patients into high- and low-risk groups. Afterwards, we performed CIBERSORT and the single-sample gene set enrichment analysis (ssGSEA) method to explore immune infiltration status. Furthermore, we investigated the relationships between the signature and immune landscape, genomic integrity, clinical characteristics, drug sensitivity, and immunotherapy efficacy. Results We constructed a robust necroptosis-related 22-lncRNA model, serving as an independent prognostic factor for breast cancer (BRCA). The low-risk group seemed to be the immune-activated type. Meanwhile, it showed that the higher the tumor mutation burden (TMB), the higher the riskScore. PD-L1-CTLA4 combined immunotherapy seemed to be a promising treatment strategy. Lastly, patients were assigned to 4 clusters to better discern the heterogeneity among patients. Conclusions The necroptosis-related lncRNA signature and molecular clusters indicated superior predictive performance in prognosis and the immune microenvironment, which may also provide guidance to drug regimens for immunotherapy and provide novel insights into precision medicine.
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Affiliation(s)
- Yuhao Xu
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Qinghui Zheng
- General Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Tao Zhou
- Hangzhou Medical College, Hangzhou, China
| | - Buyun Ye
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Qiuran Xu
- Laboratory of Tumor Molecular Diagnosis and Individualized Medicine of Zhejiang Province, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
| | - Xuli Meng
- General Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China
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