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Kong R, Wang N, Zhou CL, Lu J. Prognostic Value of an Immune Long Non-Coding RNA Signature in Liver Hepatocellular Carcinoma. J Microbiol Biotechnol 2024; 34:958-968. [PMID: 38494878 DOI: 10.4014/jmb.2308.08022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/28/2023] [Accepted: 01/18/2024] [Indexed: 03/19/2024]
Abstract
In recent years, there has been a growing recognition of the important role that long non-coding RNAs (lncRNAs) play in the immunological process of hepatocellular carcinoma (LIHC). An increasing number of studies have shown that certain lncRNAs hold great potential as viable options for diagnosis and treatment in clinical practice. The primary objective of our investigation was to devise an immune lncRNA profile to explore the significance of immune-associated lncRNAs in the accurate diagnosis and prognosis of LIHC. Gene expression profiles of LIHC samples obtained from TCGA database were screened for immune-related genes. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate Cox analysis. Then, the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were performed to evaluate the capability of the immune lncRNA signature as a prognostic indicator. Six long non-coding RNAs were identified via correlation analysis and Cox regression analysis considering their interactions with immune genes. Subsequently, tumor samples were categorized into two distinct risk groups based on different clinical outcomes. Stratification analysis indicated that the prognostic ability of this signature acted as an independent factor. The Kaplan-Meier method was employed to conduct survival analysis, results showed a significant difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Additionally, data obtained from gene set enrichment analysis (GSEA) revealed several potential biological processes in which these biomarkers may be involved. To summarize, this study demonstrated that this six-lncRNA signature could be identified as a potential factor that can independently predict the prognosis of LIHC patients.
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Affiliation(s)
- Rui Kong
- Department of Gastroenterology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, P.R. China
| | - Nan Wang
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, P.R. China
| | - Chun Li Zhou
- Department of Gastroenterology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, P.R. China
| | - Jie Lu
- Department of Gastroenterology, Pu Dong Area Gongli Hospital, School of Medicine, Shanghai University, Shanghai 200135, P.R. China
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, P.R. China
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Zhang Y, Gao Y, Li F, Qi Q, Li Q, Gu Y, Zheng Z, Hu B, Wang T, Zhang E, Xu H, Liu L, Tian T, Jin G, Yan C. Long non-coding RNA NRAV in the 12q24.31 risk locus drives gastric cancer development through glucose metabolism reprogramming. Carcinogenesis 2024; 45:23-34. [PMID: 37950445 DOI: 10.1093/carcin/bgad080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 10/24/2023] [Accepted: 11/08/2023] [Indexed: 11/12/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) serve as vital candidates to mediate cancer risk. Here, we aimed to identify the risk single-nucleotide polymorphisms (SNPs)-induced lncRNAs and to investigate their roles in gastric cancer (GC) development. Through integrating the differential expression analysis of lncRNAs in GC tissues and expression quantitative trait loci analysis in normal stomach tissues and GC tissues, as well as genetic association analysis based on GC genome-wide association studies and an independent validation study, we identified four lncRNA-related SNPs consistently associated with GC risk, including SNHG7 [odds ratio (OR) = 1.16, 95% confidence interval (CI): 1.09-1.23], NRAV (OR = 1.11, 95% CI: 1.05-1.17), LINC01082 (OR = 1.16, 95% CI: 1.08-1.22) and FENDRR (OR = 1.16, 95% CI: 1.07-1.25). We further found that a functional SNP rs6489786 at 12q24.31 increases binding of MEOX1 or MEOX2 at a distal enhancer and results in up-regulation of NRAV. The functional assays revealed that NRAV accelerates GC cell proliferation while inhibits GC cell apoptosis. Mechanistically, NRAV decreases the expression of key subunit genes through the electron transport chain, thereby driving the glucose metabolism reprogramming from aerobic respiration to glycolysis. These findings suggest that regulating lncRNA expression is a crucial mechanism for risk-associated variants in promoting GC development.
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Affiliation(s)
- Yan Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Yun Gao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Fengyuan Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qi Qi
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qian Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuanliang Gu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhonghua Zheng
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Beiping Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Public Health Institute of Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Erbao Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Hao Xu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Li Liu
- Institute of Digestive Endoscopy, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Tian Tian
- Department of Epidemiology, School of Public Health, Nantong University, Nantong, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
- Public Health Institute of Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Immunology, Key Laboratory of Immunological Environment and Disease, Nanjing Medical University, Nanjing, China
- The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Wuxi, China
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3
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Chen C, Xie Z, Ni Y, He Y. Screening immune-related blood biomarkers for DKD-related HCC using machine learning. Front Immunol 2024; 15:1339373. [PMID: 38318171 PMCID: PMC10838782 DOI: 10.3389/fimmu.2024.1339373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/05/2024] [Indexed: 02/07/2024] Open
Abstract
Background Diabetes mellitus is a significant health problem worldwide, often leading to diabetic kidney disease (DKD), which may also influence the occurrence of hepatocellular carcinoma (HCC). However, the relationship and diagnostic biomarkers between DKD and HCC are unclear. Methods Using public database data, we screened DKD secretory RNAs and HCC essential genes by limma and WGCNA. Potential mechanisms, drugs, and biomarkers for DKD-associated HCC were identified using PPI, functional enrichment, cMAP, and machine learning algorithms, and a diagnostic nomogram was constructed. Then, ROC, calibration, and decision curves were used to evaluate the diagnostic performance of the nomograms. In addition, immune cell infiltration in HCC was explored using CIBERSORT. Finally, the detectability of critical genes in blood was verified by qPCR. Results 104 DEGs associated with HCC using WGCNA were identified. 101 DEGs from DKD were predicated on secreting into the bloodstream with Exorbase datasets. PPI analysis identified three critical modules considered causative genes for DKD-associated HCC, primarily involved in inflammation and immune regulation. Using lasso and RM, four hub genes associated with DKD-associated HCC were identified, and a diagnostic nomogram confirmed by DCA curves was established. The results of immune cell infiltration showed immune dysregulation in HCC, which was associated with the expression of four essential genes. PLVAP was validated by qPCR as a possible blood-based diagnostic marker for DKD-related HCC. Conclusion We revealed the inflammatory immune pathways of DKD-related HCC and developed a diagnostic nomogram for HCC based on PLVAP, C7, COL15A1, and MS4A6A. We confirmed with qPCR that PLVAP can be used as a blood marker to assess the risk of HCC in DKD patients.
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Affiliation(s)
- Chao Chen
- Engineering Research Center of Natural Medicine, Ministry of Education, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, China
- Instrumentation and Service Center for Science and Technology, Beijing Normal University at Zhuhai, Zhuhai, China
| | - Zhinan Xie
- Medical Engineering Department, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Ying Ni
- Engineering Research Center of Natural Medicine, Ministry of Education, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, China
| | - Yuxi He
- Department of Pediatrics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China
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Shen X, Wu S, Yang Z, Zhu C. Establishment of an endoplasmic reticulum stress-associated lncRNAs model to predict prognosis and immunological characteristics in hepatocellular carcinoma. PLoS One 2023; 18:e0287724. [PMID: 37647290 PMCID: PMC10468045 DOI: 10.1371/journal.pone.0287724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 06/01/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND The endoplasmic reticulum stress (ERS) and unfolded protein response (UPR) pathways play an essential role in the pathophysiology of hepatocellular carcinoma (HCC), and activation of the UPR pathway is strongly associated with tumor growth. However, the function of ERS-associated long non-coding RNAs (lncRNAs) in HCC is less recognized. METHODS We have used TCGA (The Cancer Genome Atlas) to obtain clinical and transcriptome data for HCC patients and the GSEA (Gene Set Enrichment Analysis) molecular signature database to get the ERS gene. ERS-associated prognostic lncRNA was determined using univariate Cox regression study. Then, least absolute shrinkage and selection operator and multivariate Cox regression study were used to construct ERS-associated lncRNAs risk model. Next, we use Kaplan-Meier (KM) survival study, time-dependent receiver operating characteristic (ROC) curve, univariate and multivariate Cox regression study to validate and evaluate the risk model. GSEA reveals the underlying molecular mechanism of the risk model. In addition, differences in Immune cell Infiltration Study, half-maximal inhibitory concentration (IC50) and immune checkpoints blockade (ICB) treatment between high and low risk groups were analyzed. RESULTS We constructed a risk model consisting of 6 ERS-associated lncRNAS (containingMKLN1-AS, LINC01224, AL590705.3, AC008622.2, AC145207.5, and AC026412.3). The KM survival study showed that the prognosis of HCC patients in low-risk group was better than that in high-risk group. ROC study, univariate and multivariate Cox regression study showed that the risk model had good predictive power for HCC patients. Our verification sample verified the aforesaid findings. GSEA suggests that several tumor- and metabolism-related signaling pathways are associated with risk groups. Simultaneously, we discovered that the risk models may help in the treatment of ICB and the selection of chemotherapeutic drugs. CONCLUSIONS In this article, we created an ERS-associated lncRNAs risk model to help prognostic diagnosis and personalized therapy in HCC.
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Affiliation(s)
- Xingyuan Shen
- School of Graduate, Dalian Medical University, Dalian, Liaoning, China
| | - Siyuan Wu
- Department of General Surgery, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Zhen Yang
- School of Graduate, Dalian Medical University, Dalian, Liaoning, China
| | - Chunfu Zhu
- Department of General Surgery, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, China
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Qu J, Tao D, Huang W, Lu L, Fan J, Zhang S, Huang F. Assessment of prognostic role of a novel 7-lncRNA signature in HCC patients. Heliyon 2023; 9:e18493. [PMID: 37520979 PMCID: PMC10382640 DOI: 10.1016/j.heliyon.2023.e18493] [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: 01/15/2023] [Revised: 07/07/2023] [Accepted: 07/19/2023] [Indexed: 08/01/2023] Open
Abstract
Background Hepatocellular carcinoma (HCC) is characterized by extensive risk factors, high morbidity and mortality. Clinical prognostic evaluation assay assumes a nonspecific quality. Better HCC prognostics are urgently needed. Long noncoding RNAs (lncRNAs) exerts a crucial role in tumorigenesis and development. Excavating specific lncRNAs signature to ameliorate the high-risk survival prediction in HCC patients is worthwhile. Methods Differentially expressed lncRNAs (DElncRNAs) profile was acquired from The Cancer Genome Atlas database (TCGA). Then, the lncRNAs high-risk survival prognostic model was established using the least absolute shrinkage and selection operator (LASSO)-Cox regression algorithm. The lncRNAs were evaluated in clinical specimen by PCR. The receiver operating characteristic curve (ROC) analysis was further conducted to assess the potential prognostic value of the model. Moreover, a visible nomogram containing clinicopathological features and prognostic model was developed for prediction of survival property. Potential molecular mechanism was assessed by GO, KEGG, GSEA enrichment analysis and CIBERSORT immune infiltration analysis. Results A novel 7-lncRNA risk model (AL161937.2, LINC01063, AC145207.5, POLH-AS1, LNCSRLR, MKLN1-AS, AC105345.1) was constructed and validated for HCC prognosis prediction. Kaplan-Meier analysis revealed that patients in the high-risk group suffered a poor prognosis (p = 1.813 × 10-8). These genes were detected by PCR, and the expression trend was in accordance with TCGA database. Interestingly, the risk score served as an independent risk factor for HCC patients (HR: 1.166, 95% CI:1.119-1.214, p < 0.001). The nomogram was established, and the predictive accuracy in the nomogram was prior to the TNM stage according to the ROC curve analysis. Cell proliferation related pathway, decreased CD4+ T cell, CD8+ T cell, NK cell and elevated Neutrophil, Macrophage M0 were observed in high-risk group. Besides, suppression of MKLN1-AS expression inhibited cell proliferation of HCC cells by CCK8 assay in vitro. Conclusion The 7-lncRNA signature may exert a particular prognostic prediction role in HCC and provide new insight in HCC carcinogenesis.
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Affiliation(s)
- Junchi Qu
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
- Department of Gastroenterology, The First People's Hospital of PingJiang, Yueyang 410400, China
| | - Di Tao
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Wei Huang
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Liting Lu
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Junming Fan
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Shineng Zhang
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Fengting Huang
- Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
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Integrated Analysis of N1-Methyladenosine Methylation Regulators-Related lncRNAs in Hepatocellular Carcinoma. Cancers (Basel) 2023; 15:cancers15061800. [PMID: 36980686 PMCID: PMC10046959 DOI: 10.3390/cancers15061800] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/07/2023] [Accepted: 03/14/2023] [Indexed: 03/19/2023] Open
Abstract
N1-methyladenosine (m1A) and long non-coding RNAs (lncRNAs) play significant roles in tumor progression in hepatocellular carcinoma (HCC). However, their association with HCC is still unclear. In this study, lncRNAs related to m1A were extracted from the mRNA expression matrix in The Cancer Genome Atlas (TCGA) database. Five m1A-related lncRNAs (AL031985.3, NRAV, WAC-AS1, AC026412.3, and AC099850.4) were identified based on lasso Cox regression and they generated a prognostic signature of HCC. The prognostic signature was identified as an independent prognosis factor in HCC patients. Moreover, the prognostic signature achieved better performance than TP53 mutation status or tumor mutational burden (TMB) scores in the stratification of patient survival. The immune landscape indicated that most immune checkpoint genes and immune cells were distributed differently between both risk groups. A higher IC50 of chemotherapeutics (sorafenib, nilotinib, sunitinib, and gefitinib) was observed in the high-risk group, and a lower IC50 of gemcitabine in the low-risk group, suggesting the potential of the prognostic signature in chemosensitivity. In addition, fifty-five potential small molecular drugs were found based on drug sensitivity and NRAV expression. Together, five m1A-related lncRNAs generated a prognostic signature that could be a promising prognostic prediction approach and therapeutic response assessment tool for HCC patients.
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7
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Xiao H, Feng X, Liu M, Gong H, Zhou X. SnoRNA and lncSNHG: Advances of nucleolar small RNA host gene transcripts in anti-tumor immunity. Front Immunol 2023; 14:1143980. [PMID: 37006268 PMCID: PMC10050728 DOI: 10.3389/fimmu.2023.1143980] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 03/03/2023] [Indexed: 03/17/2023] Open
Abstract
The small nucleolar RNA host genes (SNHGs) are a group of genes that can be transcript into long non-coding RNA SNHG (lncSNHG) and further processed into small nucleolar RNAs (snoRNAs). Although lncSNHGs and snoRNAs are well established to play pivotal roles in tumorigenesis, how lncSNHGs and snoRNAs regulate the immune cell behavior and function to mediate anti-tumor immunity remains further illustrated. Certain immune cell types carry out distinct roles to participate in each step of tumorigenesis. It is particularly important to understand how lncSNHGs and snoRNAs regulate the immune cell function to manipulate anti-tumor immunity. Here, we discuss the expression, mechanism of action, and potential clinical relevance of lncSNHGs and snoRNAs in regulating different types of immune cells that are closely related to anti-tumor immunity. By uncovering the changes and roles of lncSNHGs and snoRNAs in different immune cells, we aim to provide a better understanding of how the transcripts of SNHGs participate in tumorigenesis from an immune perspective.
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Affiliation(s)
- Hao Xiao
- Department of Clinical Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Clinical Laboratory Medicine, Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Xin Feng
- Department of Clinical Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Clinical Laboratory Medicine, Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Mengjun Liu
- Department of Clinical Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Clinical Laboratory Medicine, Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Hanwen Gong
- Department of Clinical Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Clinical Laboratory Medicine, Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Xiao Zhou
- Department of Clinical Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Clinical Laboratory Medicine, Xiangya School of Medicine, Central South University, Changsha, Hunan, China
- *Correspondence: Xiao Zhou,
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Yang Y, Zhang W, Wang X, Yang J, Cui Y, Song H, Li W, Li W, Wu L, Du Y, He Z, Shi J, Zhang J. A passage-dependent network for estimating the in vitro senescence of mesenchymal stromal/stem cells using microarray, bulk and single cell RNA sequencing. Front Cell Dev Biol 2023; 11:998666. [PMID: 36824368 PMCID: PMC9941187 DOI: 10.3389/fcell.2023.998666] [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: 07/20/2022] [Accepted: 01/26/2023] [Indexed: 02/10/2023] Open
Abstract
Long-term in vitro culture of human mesenchymal stem cells (MSCs) leads to cell lifespan shortening and growth stagnation due to cell senescence. Here, using sequencing data generated in the public domain, we have established a specific regulatory network of "transcription factor (TF)-microRNA (miRNA)-Target" to provide key molecules for evaluating the passage-dependent replicative senescence of mesenchymal stem cells for the quality control and status evaluation of mesenchymal stem cells prepared by different procedures. Short time-series expression miner (STEM) analysis was performed on the RNA-seq and miRNA-seq databases of mesenchymal stem cells from various passages to reveal the dynamic passage-related changes of miRNAs and mRNAs. Potential miRNA targets were predicted using seven miRNA target prediction databases, including TargetScan, miRTarBase, miRDB, miRWalk, RNA22, RNAinter, and TargetMiner. Then use the TransmiR v2.0 database to obtain experimental-supported transcription factor for regulating the selected miRNA. More than ten sequencing data related to mesenchymal stem cells or mesenchymal stem cells reprogramming were used to validate key miRNAs and mRNAs. And gene set variation analysis (GSVA) was performed to calculate the passage-dependent signature. The results showed that during the passage of mesenchymal stem cells, a total of 29 miRNAs were gradually downregulated and 210 mRNA were gradually upregulated. Enrichment analysis showed that the 29 miRNAs acted as multipotent regulatory factors of stem cells and participated in a variety of signaling pathways, including TGF-beta, HIPPO and oxygen related pathways. 210 mRNAs were involved in cell senescence. According to the target prediction results, the targets of these key miRNAs and mRNAs intersect to form a regulatory network of "TF-miRNA-Target" related to replicative senescence of cultured mesenchymal stem cells, across 35 transcription factor, 7 miRNAs (has-mir-454-3p, has-mir-196b-5p, has-mir-130b-5p, has-mir-1271-5p, has-let-7i-5p, has-let-7a-5p, and has-let-7b-5p) and 7 predicted targets (PRUNE2, DIO2, CPA4, PRKAA2, DMD, DDAH1, and GATA6). This network was further validated by analyzing datasets from a variety of mesenchymal stem cells subculture and lineage reprogramming studies, as well as qPCR analysis of early passages mesenchymal stem cells versus mesenchymal stem cells with senescence morphologies (SA-β-Gal+). The "TF-miRNA-Target" regulatory network constructed in this study reveals the functional mechanism of miRNAs in promoting the senescence of MSCs during in vitro expansion and provides indicators for monitoring the quality of functional mesenchymal stem cells during the preparation and clinical application.
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Affiliation(s)
- Yong Yang
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Wencheng Zhang
- Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China,Shanghai Engineering Research Center of Stem Cells Translational Medicine, Shanghai, China,Shanghai Institute of Stem Cell Research and Clinical Translation, Shanghai, China
| | - Xicheng Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China,Shanghai Engineering Research Center of Stem Cells Translational Medicine, Shanghai, China,Shanghai Institute of Stem Cell Research and Clinical Translation, Shanghai, China
| | - Jingxian Yang
- Department of Anesthesiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Yangyang Cui
- Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China,Shanghai Engineering Research Center of Stem Cells Translational Medicine, Shanghai, China,Shanghai Institute of Stem Cell Research and Clinical Translation, Shanghai, China,Postgraduate Training Base of Shanghai East Hospital, Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Haimeng Song
- Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China,Shanghai Engineering Research Center of Stem Cells Translational Medicine, Shanghai, China,Shanghai Institute of Stem Cell Research and Clinical Translation, Shanghai, China
| | - Weiping Li
- Department of Gastrointestinal Surgery, The First People’s Hospital of Taicang City, Taicang Affiliated Hospital of Soochow University, Taicang, Jiangsu, China
| | - Wei Li
- Department of General Surgery, Fuzhou Dongxiang District People’s Hospital, Fuzhou, Jiangxi, China
| | - Le Wu
- Department of General Surgery, Fuzhou Dongxiang District People’s Hospital, Fuzhou, Jiangxi, China
| | - Yao Du
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Zhiying He
- Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China,Shanghai Engineering Research Center of Stem Cells Translational Medicine, Shanghai, China,Shanghai Institute of Stem Cell Research and Clinical Translation, Shanghai, China,*Correspondence: Zhiying He, ; Jun Shi, ; Jiangnan Zhang,
| | - Jun Shi
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China,*Correspondence: Zhiying He, ; Jun Shi, ; Jiangnan Zhang,
| | - Jiangnan Zhang
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China,*Correspondence: Zhiying He, ; Jun Shi, ; Jiangnan Zhang,
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Revealing Prognostic and Immunotherapy-Sensitive Characteristics of a Novel Cuproptosis-Related LncRNA Model in Hepatocellular Carcinoma Patients by Genomic Analysis. Cancers (Basel) 2023; 15:cancers15020544. [PMID: 36672493 PMCID: PMC9857215 DOI: 10.3390/cancers15020544] [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: 11/29/2022] [Revised: 01/05/2023] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
Immunotherapy has shown strong anti-tumor activity in a subset of patients. However, many patients do not benefit from the treatment, and there is no effective method to identify sensitive immunotherapy patients. Cuproptosis as a non-apoptotic programmed cell death caused by excess copper, whether it is related to tumor immunity has attracted our attention. In the study, we constructed the prognostic model of 9 cuproptosis-related LncRNAs (crLncRNAs) and assessed its predictive capability, preliminarily explored the potential mechanism causing treatment sensitivity difference between the high-/low-risk group. Our results revealed that the risk score was more effective than traditional clinical features in predicting the survival of HCC patients (AUC = 0.828). The low-risk group had more infiltration of immune cells (B cells, CD8+ T cells, CD4+ T cells), mainly with anti-tumor immune function (p < 0.05). It showed higher sensitivity to immune checkpoint inhibitors (ICIs) treatment (p < 0.001) which may exert the effect through the AL365361.1/hsa-miR-17-5p/NLRP3 axis. In addition, NLRP3 mutation-sensitive drugs (VNLG/124, sunitinib, linifanib) may have better clinical benefits in the high-risk group. All in all, the crLncRNAs model has excellent specificity and sensitivity, which can be used for classifying the therapy-sensitive population and predicting the prognosis of HCC patients.
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Wu S, Cheng C, Zhu W, Yang J, He BB, Li S, Wang X, Guo H, Chen D, Guo YM. Whole transcriptome analysis reveals that immune infiltration- lncRNAs are related to cellular apoptosis in liver transplantation. Front Immunol 2023; 14:1152742. [PMID: 37081883 PMCID: PMC10110847 DOI: 10.3389/fimmu.2023.1152742] [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: 01/31/2023] [Accepted: 03/20/2023] [Indexed: 04/22/2023] Open
Abstract
Introduction In most instances, liver transplantation (LT) is the only available treatment for end-stage liver diseases. However, LT could also induce serious liver diseases or injury, and the underlying mechanisms of LT-induced complications remain largely unknown, especially the mechanisms of the dysfunction of the immune system mediated by long noncoding RNAs (lncRNAs). Methods In this study, we globally analyzed the proportion of immune cells by using the transcriptome sequencing data (RNA-seq) of needle-core liver biopsies from pre- and post-transplantation recipients. Dysregulated lncRNAs were found to be correlated with the altered fractions of immune cells. We finally explored the potential targets of dysregulated lncRNAs and analyzed their functions in LT. Results We found that in the samples, some immune cells changed significantly after LT, including CD4 T cells, NK cells and mast cells. The proportion of macrophages in different polarization states also changed significantly, with M0 macrophages increasing and M2 macrophages decreasing. Through weighted gene co-expression network analysis (WGCNA), 7 gene expression modules related to LT were identified. These modules were related to changes in the proportion of different immune cells. The functions of these modules represent the response modes of different functional genes after LT. Among these modules, MEtan and MEyellow modules were primarily enriched in apoptosis and inflammatory pathways. Twelve immunity-related lncRNAs were identified for the first time, and the regulatory network co-changing with immune cells was also identified. The co-expressed genes of these lncRNAs were highly enriched in apoptosis-related pathways. Many apoptosis-related genes were found to be up-regulated after LT. Discussion In summary, we speculated that the expression and regulation of these apoptotic genes may be related to the changes in the proportion of immune cells. Some of these lncRNAs and apoptosis-related genes have been reported to be related to cell proliferation and apoptosis. They are also potential biomarkers or therapeutic targets.
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Affiliation(s)
- Shile Wu
- Soochow University, Suzhou, Jiangsu, China
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Chao Cheng
- Center for Genome Analysis, Wuhan Ruixing Biotechnology Co., Ltd, Wuhan, China
| | - Wenjun Zhu
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Jinyu Yang
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Bei-bei He
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Song Li
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Xinsheng Wang
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Hao Guo
- Center for Genome Analysis, Wuhan Ruixing Biotechnology Co., Ltd, Wuhan, China
| | - Dong Chen
- Center for Genome Analysis, Wuhan Ruixing Biotechnology Co., Ltd, Wuhan, China
- *Correspondence: Ya-min Guo, ; Dong Chen,
| | - Ya-min Guo
- General Surgery Department, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
- *Correspondence: Ya-min Guo, ; Dong Chen,
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Hsa_circ_0015278 Regulates FLT3-ITD AML Progression via Ferroptosis-Related Genes. Cancers (Basel) 2022; 15:cancers15010071. [PMID: 36612069 PMCID: PMC9817690 DOI: 10.3390/cancers15010071] [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: 11/11/2022] [Revised: 12/14/2022] [Accepted: 12/19/2022] [Indexed: 12/25/2022] Open
Abstract
AML with the FLT3-ITD mutation seriously threatens human health. The mechanism by which circRNAs regulate the pathogenesis of FLT3-ITD mutant-type AML through ferroptosis-related genes (FerRGs) remains unclear. Differentially expressed circRNAs and mRNAs were identified from multiple integrated data sources. The target miRNAs and mRNAs of the circRNAs were predicted using various databases. The PPI network, ceRNA regulatory network, GO, and KEGG enrichment analyses were performed. The "survival" and the "pROC" R packages were used for K-M and ROC analysis, respectively. GSEA, immune infiltration analysis, and clinical subgroup analysis were performed. Finally, circRNAs were validated by Sanger sequencing and qRT-PCR. In our study, 77 DECircs-1 and 690 DECircs-2 were identified. Subsequently, 11 co-up-regulated DECircs were obtained by intersecting DECircs-1 and DECircs-2. The target miRNAs of the circRNAs were screened by CircInteractome, circbank, and circAtlas. Utilizing TargetScan, ENCORI, and miRWalk, the target mRNAs of the miRNAs were uncovered. Ultimately, 73 FerRGs were obtained, and the ceRNA regulatory network was constructed. Furthermore, MAPK3 and CD44 were significantly associated with prognosis. qRT-PCR results confirmed that has_circ_0015278 was significantly overexpressed in FLT3-ITD mutant-type AML. In summary, we constructed the hsa_circ_0015278/miRNAs/FerRGs signaling axis, which provides new insight into the pathogenesis and therapeutic targets of AML with FLT3-ITD mutation.
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Li D, Fan X, Zuo L, Wu X, Wu Y, Zhang Y, Zou F, Sun Z, Zhang W. Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:1356. [PMID: 36660710 PMCID: PMC9843414 DOI: 10.21037/atm-22-5827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 12/13/2022] [Indexed: 01/01/2023]
Abstract
Background Liver hepatocellular carcinoma (LIHC), whose incidence is increasing globally, is one of the most prevalent malignant cancers. RAS-related pathways are involved in the cell proliferation, migration, apoptosis, and metabolism in LIHC. Long noncoding RNAs (lncRNAs) also play important roles in the progression and prognosis of LIHC. However, the clinical role, prognostic significance, and immune regulation of RAS-related lncRNAs in LIHC remains unclear. Our study aims to construct and validate a RAS-related lncRNA prognostic risk signature that can estimate the prognosis and response to immunotherapy in LIHC. Methods The clinical information and corresponding messenger RNA (mRNA)/lncRNA expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and 502 RAS-related lncRNAs were identified by Pearson correlation analysis. A prognostic risk signature with 5 RAS-related lncRNAs was then developed based on the Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm analyses. Subsequently, Kaplan-Meier survival curve, receiver operating characteristic (ROC) curve, and the nomogram were established to evaluate the predictive accuracy of the signature. In addition, the immune microenvironment, tumor mutation burden, and drug sensitivity associated with the signature were also analyzed in LIHC. Results Compared with the low-risk groups, the high-risk groups had an unfavorable outcome. Multivariate regression analysis revealed that the risk score signature was the independent prognostic factor superior to the other clinical variables. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses demonstrated that the risk score was highly associated with the nuclear division, DNA replication, and immune response. The group with high risk tended to hold a lower immune escape rate and better immunotherapy efficacy, while the group with low risk was more sensitive to some small molecular targeted drugs. Conclusions We developed a RAS-related lncRNA risk signature that was highly associated with the prognosis and response to immunotherapy and targeted drugs and which provided novel mechanistic insights into the personalized treatment and potential drug selection for patients with LIHC.
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Affiliation(s)
- Ding Li
- Department of Pharmacy, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China;,Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, Zhengzhou, China;,Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, Zhengzhou, China
| | - Xinxin Fan
- Department of Hematology, Zhengzhou Third People's Hospital, Zhengzhou, China
| | - Lihua Zuo
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xuan Wu
- Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Yingxi Wu
- Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China
| | - Yuanyuan Zhang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Fanmei Zou
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhi Sun
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenzhou Zhang
- Department of Pharmacy, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, China;,Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, Zhengzhou, China;,Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, Zhengzhou, China
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13
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Li R, Jin C, Zhao W, Liang R, Xiong H. Development of a novel immune-related lncRNA prognostic signature for patients with hepatocellular carcinoma. BMC Gastroenterol 2022; 22:450. [PMID: 36344926 PMCID: PMC9639314 DOI: 10.1186/s12876-022-02540-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 10/14/2022] [Indexed: 11/09/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common neoplasm and the major cause of cancer-associated death worldwide. The high mortality rate of HCC is mainly attributed to its widespread prevalence and the lack of effective treatment. Immunotherapy as a promising, innovative approach has revolutionised the treatment of solid tumours. However, owing to the heterogeneity and complex tumour microenvironment of HCC, an efficient biomarker for immunotherapy has yet to be identified. We investigated the role of immune-related long non-coding RNAs (lncRNAs) as prognostic biomarkers in patients with HCC from The Cancer Genome Atlas (TCGA) database. Spearman correlation, univariate and multivariate Cox, and lasso regression analyses were utilised to screen lncRNAs associated with prognosis. Four lncRNAs were filtered out to develop an immune-associated lncRNA prognostic signature in TCGA training as well as validation cohorts. Patients with HCC were then categorised into low- and high-risk groups according to the median value of the risk scores to evaluate the ability of the prognostic model between training and validation cohorts. A nomogram (based on risk score and stage) was constructed to appraise the general overall survival (OS) of patients with HCC. Differences in immune cell infiltration, immune checkpoint inhibitor (ICI) treatment response, gene mutation, and drug sensitivity were observed between the two groups. Thus, the lncRNA prognostic signature can serve as a sensitive prognostic biomarker with potential in individualised immunotherapy for HCC patients.
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Affiliation(s)
- Rui Li
- grid.33199.310000 0004 0368 7223Department of Oncology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei China
| | - Chen Jin
- grid.268099.c0000 0001 0348 3990Department of Epidemiology and Biostatistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang China
| | - Weiheng Zhao
- grid.33199.310000 0004 0368 7223Department of Oncology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei China
| | - Rui Liang
- grid.190737.b0000 0001 0154 0904Biological Engineering Academy, Chongqing University, Chongqing, China
| | - Huihua Xiong
- grid.33199.310000 0004 0368 7223Department of Oncology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei China
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Gao C, Zhou G, Cheng M, Feng L, Cao P, Zhou G. Identification of senescence-associated long non-coding RNAs to predict prognosis and immune microenvironment in patients with hepatocellular carcinoma. Front Genet 2022; 13:956094. [PMID: 36330438 PMCID: PMC9624069 DOI: 10.3389/fgene.2022.956094] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 09/30/2022] [Indexed: 02/17/2024] Open
Abstract
Background: Cellular senescence plays a complicated and vital role in cancer development because of its divergent effects on tumorigenicity. However, the long non-coding RNAs (lncRNAs) associated with tumor senescence and their prognostic value in hepatocellular carcinoma (HCC) remain unexplored. Methods: The trans-cancer oncogene-induced senescence (OIS) signature was determined by gene set variation analysis (GSVA) in the cancer genome atlas (TCGA) dataset. The OIS-related lncRNAs were identified by correlation analyses. Cox regression analyses were used to screen lncRNAs associated with prognosis, and an optimal predictive model was created by regression analysis of the least absolute shrinkage and selection operator (LASSO). The performance of the model was evaluated by Kaplan-Meier survival analyses, nomograms, stratified survival analyses, and receiver operating characteristic curve (ROC) analyses. Gene set enrichment analysis (GSEA) and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) were carried out to explore the functional relevance and immune cell infiltration, respectively. Results: Firstly, we examined the pan-cancer OIS signature, and found several types of cancer with OIS strongly associated with the survival of patients, including HCC. Subsequently, based on the OIS signature, we identified 76 OIS-related lncRNAs with prognostic values in HCC. We then established an optimal prognostic model based on 11 (including NRAV, AC015908.3, MIR100HG, AL365203.2, AC009005.1, SNHG3, LINC01138, AC090192.2, AC008622.2, AL139423.1, and AC026356.1) of these lncRNAs by LASSO-Cox regression analysis. It was then confirmed that the risk score was an independent and potential risk indicator for overall survival (OS) (HR [95% CI] = 4.90 [2.74-8.70], p < 0.001), which outperforms those traditional clinicopathological factors. Furthermore, patients with higher risk scores also showed more advanced levels of a proinflammatory senescence-associated secretory phenotype (SASP), higher infiltration of regulatory T (Treg) cells and lower infiltration of naïve B cells, suggesting the regulatory effects of OIS on immune microenvironment. Additionally, we identified NRAV as a representative OIS-related lncRNA, which is over-expressed in HCC tumors mainly driven by DNA hypomethylation. Conclusion: Based on 11 OIS-related lncRNAs, we established a promising prognostic predictor for HCC patients, and highlighted the potential immune microenvironment-modulatory roles of OIS in HCC, providing a broad molecular perspective of tumor senescence.
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Affiliation(s)
- Chengzhi Gao
- State Key Laboratory of Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, Beijing, China
| | - Guangming Zhou
- State Key Laboratory of Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, Beijing, China
| | - Min Cheng
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lan Feng
- State Key Laboratory of Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, Beijing, China
| | - Pengbo Cao
- State Key Laboratory of Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, Beijing, China
| | - Gangqiao Zhou
- State Key Laboratory of Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, Beijing, China
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Hebei University, Baoding, China
- Anhui Medical University, Hefei, China
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15
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Identification of Prognostic Fatty Acid Metabolism lncRNAs and Potential Molecular Targeting Drugs in Uveal Melanoma. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:3726351. [PMID: 36267302 PMCID: PMC9578887 DOI: 10.1155/2022/3726351] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 09/17/2022] [Accepted: 09/24/2022] [Indexed: 11/25/2022]
Abstract
Background The aim of this study was to identify prognostic fatty acid metabolism lncRNAs and potential molecular targeting drugs in uveal melanoma through integrated bioinformatics analysis. Methods In the present study, we obtained the expression matrix of 309 FAM-mRNAs and identified 225 FAM-lncRNAs by coexpression network analysis. We then performed univariate Cox analysis, LASSO regression analysis, and cross-validation and finally obtained an optimized UVM prognosis prediction model composed of four PFAM-lncRNAs (AC104129.1, SOS1-IT1, IDI2-AS1, and DLGAP1-AS2). Results The survival curves showed that the survival time of UVM patients in the high-risk group was significantly lower than that in the low-risk group in the train cohort, test cohort, and all patients in the prognostic prediction model (P < 0.05). We further performed risk prognostic assessment, and the results showed that the risk scores of the high-risk group in the train cohort, test cohort, and all patients were significantly higher than those of the low-risk group (P < 0.05), patient survival decreased and the number of deaths increased with increasing risk scores, and AC104129.1, SOS1-IT1, and DLGAP1-AS2 were high-risk PFAM-lncRNAs, while IDI2-AS1 were low-risk PFAM-lncRNAs. Afterwards, we further verified the accuracy and the prognostic value of our model in predicting prognosis by PCA analysis and ROC curves. Conclusion We identified 24 potential molecularly targeted drugs with significant sensitivity differences between high- and low-risk UVM patients, of which 13 may be potential targeted drugs for high-risk patients. Our findings have important implications for early prediction and early clinical intervention in high-risk UVM patients.
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Chen M, Wu GB, Hua S, Zhao ZF, Li HJ, Luo M. Identification and validation of a prognostic model of necroptosis-related lncRNAs in hepatocellular carcinoma. Front Genet 2022; 13:907859. [PMID: 36246594 PMCID: PMC9557293 DOI: 10.3389/fgene.2022.907859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/05/2022] [Indexed: 11/27/2022] Open
Abstract
Background: The study focused on establishing a prognostic survival model with six necroptosis-related lncRNAs to predict overall survival (OS) in patients with hepatocellular carcinoma (HCC). Methods: The data of gene expression and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA). Cox regression with LASSO was used for constructing a necroptosis-related lncRNA survival model, which we further validated with qRT-PCR in vitro. The relative bioinformatics analysis and consensus cluster analysis were performed based on six differentially expressed lncRNAs. Results: The survival prognostic model was constructed by using data from TCGA. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. GSEA showed that several signaling pathways were related to HCC progression. Immune-related functional analysis showed that aDCs, macrophages, Th2 cells, and Tregs have stronger correlation with the high-risk group. The consensus cluster analysis further validated the 6-lncRNA prognostic model. Conclusion: A novel 6-lncRNA (AL606489.1, NRAV, LINC02870, DUXAP8, “ZFPM2-AS1,” and AL031985.3) prognostic model had an accurately predictive power in HCC prognosis, which might be worthy of clinical application.
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Affiliation(s)
- Min Chen
- Department of General Surgery, Shanghai Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang-Bo Wu
- Department of General Surgery, Shanghai Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shan Hua
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhi-Feng Zhao
- Department of General Surgery, Shanghai Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong-Jie Li
- Department of General Surgery, Shanghai Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Hong-Jie Li, ; Meng Luo,
| | - Meng Luo
- Department of General Surgery, Shanghai Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Hong-Jie Li, ; Meng Luo,
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Pallozzi M, Di Tommaso N, Maccauro V, Santopaolo F, Gasbarrini A, Ponziani FR, Pompili M. Non-Invasive Biomarkers for Immunotherapy in Patients with Hepatocellular Carcinoma: Current Knowledge and Future Perspectives. Cancers (Basel) 2022; 14:cancers14194631. [PMID: 36230554 PMCID: PMC9559710 DOI: 10.3390/cancers14194631] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 09/18/2022] [Accepted: 09/20/2022] [Indexed: 12/16/2022] Open
Abstract
Simple Summary The search for non-invasive biomarkers is a hot topic in modern oncology, since a tissue biopsy has significant limitations in terms of cost and invasiveness. The treatment perspectives have been significantly improved after the approval of immunotherapy for patients with hepatocellular carcinoma; therefore, the quick identification of responders is crucial to define the best therapeutic strategy. In this review, the current knowledge on the available non-invasive biomarkers of the response to immunotherapy is described. Abstract The treatment perspectives of advanced hepatocellular carcinoma (HCC) have deeply changed after the introduction of immunotherapy. The results in responders show improved survival compared with Sorafenib, but only one-third of patients achieve a significant benefit from treatment. As the tumor microenvironment exerts a central role in shaping the response to immunotherapy, the future goal of HCC treatment should be to identify a proxy of the hepatic tissue condition that is easy to use in clinical practice. Therefore, the search for biomarkers that are accurate in predicting prognosis will be the hot topic in the therapeutic management of HCC in the near future. Understanding the mechanisms of resistance to immunotherapy may expand the patient population that will benefit from it, and help researchers to find new combination regimens to improve patients’ outcomes. In this review, we describe the current knowledge on the prognostic non-invasive biomarkers related to treatment with immune checkpoint inhibitors, focusing on serological markers and gut microbiota.
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Affiliation(s)
- Maria Pallozzi
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
| | - Natalia Di Tommaso
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
| | - Valeria Maccauro
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
| | - Francesco Santopaolo
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
| | - Antonio Gasbarrini
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
- Translational Medicine and Surgery Department, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Francesca Romana Ponziani
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
- Translational Medicine and Surgery Department, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
- Correspondence: (F.R.P.); (M.P.)
| | - Maurizio Pompili
- Internal Medicine and Gastroenterology-Hepatology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
- Translational Medicine and Surgery Department, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
- Correspondence: (F.R.P.); (M.P.)
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Liu Y, Yu M, Cheng X, Zhang X, Luo Q, Liao S, Chen Z, Zheng J, Long K, Wu X, Qu W, Gong M, Song Y. A novel LUAD prognosis prediction model based on immune checkpoint-related lncRNAs. Front Genet 2022; 13:1016449. [PMID: 36212122 PMCID: PMC9533213 DOI: 10.3389/fgene.2022.1016449] [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: 08/11/2022] [Accepted: 09/05/2022] [Indexed: 12/24/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is a malignant disease with an extremely poor prognosis, and there is currently a lack of clinical methods for early diagnosis and precise treatment and management. With the deepening of tumor research, more and more attention has been paid to the role of immune checkpoints (ICP) and long non-coding RNAs (lncRNAs) regulation in tumor development. Therefore, this study downloaded LUAD patient data from the TCGA database, and finally screened 14 key ICP-related lncRNAs based on ICP-related genes using univariate/multivariate COX regression analysis and LASSO regression analysis to construct a risk prediction model and corresponding nomogram. After multi-dimensional testing of the model, the model showed good prognostic prediction ability. In addition, to further elucidate how ICP plays a role in LUAD, we jointly analyzed the immune microenvironmental changes in LAUD patients and performed a functional enrichment analysis. Furthermore, to enhance the clinical significance of this study, we performed a sensitivity analysis of common antitumor drugs. All the above works aim to point to new directions for the treatment of LUAD.
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Sun R, Wang X, Chen J, Teng D, Chan S, Tu X, Wang Z, Zuo X, Wei X, Lin L, Zhang Q, Zhang X, Tang K, Zhang H, Chen W. Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma. Front Genet 2022; 13:949110. [PMID: 36147502 PMCID: PMC9485671 DOI: 10.3389/fgene.2022.949110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 08/09/2022] [Indexed: 01/19/2023] Open
Abstract
Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predicting the survival of patients with hepatocellular carcinoma (HCC) and the associated immune landscape based on senescence-related (sr) lncRNAs. Method: Expression profiles of srlncRNAs in 424 patients with HCC were retrieved from The Cancer Genome Atlas database. Lasso and Cox regression analyses were performed to identify differentially expressed lncRNAs related to senescence. The prediction efficiency of the signature was checked using a receiver operating characteristic (ROC) curve, Kaplan–Meier analysis, Cox regression analyses, nomogram, and calibration. The risk groups of the gene set enrichment analysis, immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) were also analyzed. Quantitative real-time polymerase chain reaction (qPCR) was used to confirm the levels of AC026412.3, AL451069.3, and AL031985.3 in normal hepatic and HCC cell lines. Results: We identified 3 srlncRNAs (AC026412.3, AL451069.3, and AL031985.3) and constructed a new risk model. The results of the ROC curve and Kaplan–Meier analysis suggested that it was concordant with the prediction. Furthermore, a nomogram model was constructed to accurately predict patient prognosis. The risk score also correlated with immune cell infiltration status, immune checkpoint expression, and chemosensitivity. The results of qPCR revealed that AC026412.3 and AL451069.3 were significantly upregulated in hepatoma cell lines. Conclusion: The novel srlncRNA (AC026412.3, AL451069.3, and AL031985.3) signatures may provide insights into new therapies and prognosis predictions for patients with HCC.
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Affiliation(s)
- Rui Sun
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xu Wang
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jiajie Chen
- Department of Dermatology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Da Teng
- Department of Hepatopancreatobiliary Surgery, Affiliated Chuzhou Hospital of Anhui Medical University, First People’s Hospital of Chuzhou, Chuzhou, China
| | - Shixin Chan
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xucan Tu
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhenglin Wang
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiaomin Zuo
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiang Wei
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China
| | - Li Lin
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China
| | - Qing Zhang
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China
| | - Xiaomin Zhang
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China
| | - Kechao Tang
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China
| | - Huabing Zhang
- Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China
- Affiliated Chuzhou Hospital of Anhui Medical University, First People’s Hospital of Chuzhou, Chuzhou, China
- *Correspondence: Huabing Zhang, ; Wei Chen, ,
| | - Wei Chen
- Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Huabing Zhang, ; Wei Chen, ,
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Xu Y, Liu R. Analysis of the role of m6A and lncRNAs in prognosis and immunotherapy of hepatocellular carcinoma. Heliyon 2022; 8:e10612. [PMID: 36158075 PMCID: PMC9489786 DOI: 10.1016/j.heliyon.2022.e10612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 05/14/2022] [Accepted: 09/07/2022] [Indexed: 12/24/2022] Open
Abstract
Objective To study the role of m6A and lncRNAs in the prognosis and immunotherapy of hepatocellular carcinoma, construct the risk score of overall survival of hepatocellular carcinoma, and search for new therapeutic targets and drugs. Methods The data used in this study are obtained from The Cancer Genome Atlas (TCGA) database. A total of 424 HCC samples were included. The co-expression of lncRNAs and M6A-related genes in HCC was analyzed, COX regression analysis was conducted to construct the risk score for HCC prognosis, and the model's validity was further verified in different clinical trials subtypes and principal component analysis. GO enrichment analysis and immune function analysis were performed for the differential genes in the high-risk group and the low-risk group divided by risk score and analyzed the prognostic effect of TMB on the two groups. Based on the results, potential therapeutic agents for HCC were screened. Results The risk score can better predict the prognosis of HCC, the area under the ROC curve is 0.727. Differential genes were mainly located in the extracellular matrix and chromosomal regions and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation of cells. Type Ⅱ IFN response, type Ⅰ IFN response and MHC class Ⅰ were the three most different functions in terms of immune function between the high-risk group and the low-risk group. Type II IFN response, type I IFN response was significantly down-regulated in the high-risk group, while MHC class I was up-regulated. 14 potential therapeutic drugs were screened out. Conclusions The risk score constructed with NRAV and AL031985.3 had a good predictive effect on the prognosis of HCC. Differences in genes and immune function between high-risk and low-risk groups promoted the occurrence and progression of HCC.
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Affiliation(s)
- Yan Xu
- Department of Hepatopancreatobiliary Surgical Oncology, Chinese People's Liberation Army (PLA) General Hospital, Beijing, 100853, China
| | - Rong Liu
- Department of Hepatopancreatobiliary Surgical Oncology, Chinese People's Liberation Army (PLA) General Hospital, Beijing, 100853, China
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21
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Peng Y, Wu G, Qiu X, Luo Y, Zou Y, Wei X, Li A. Construction and validation of a necroptosis-related lncRNAs prognosis signature of hepatocellular carcinoma. Front Genet 2022; 13:916024. [PMID: 36110223 PMCID: PMC9468751 DOI: 10.3389/fgene.2022.916024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Immunotherapy has achieved remarkable success in treating advanced liver cancer. Current evidence shows that most of the available immune checkpoint inhibitor (ICB) treatments are suboptimal, and specific markers are needed for patients regarded as good candidates for immunotherapy. Necroptosis, a type of programmed cell death, plays an important role in hepatocellular carcinoma (HCC) progression and outcome. However, studies on the necroptosis-related lncRNA in HCC are scarce. In this view, the present study investigates the link among necroptosis-related lncRNA, prognosis, immune microenvironment, and immunotherapy response.Methods: Gene transcriptome and clinical data were retrieved from The Cancer Genome Atlas database. Pearson correlation analysis of necroptosis-related genes was performed to identify necroptosis-related lncRNAs. The Wilcoxon method was used to detect differentially expressed genes, and prognostic relevant lncRNAs were obtained by univariate Cox regression analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were utilized to perform functional enrichment analysis. Lasso–Cox stepwise regression analysis was employed to calculate risk score, which was involved in analyzing immune cells infiltration, immune checkpoints expression, and predicting immunotherapeutic efficacy. Quantitative RT-PCR (qRT-PCR) was performed to detect the expression pattern of lncRNA in cell lines.Results: The 10 lncRNAs generated in this study were used to create a prognostic risk model for HCC and group patients into groups based on risk. High-risk patients with HCC have a significantly lower OS rate than low-risk patients. Multivariate Cox regression analysis showed that risk score is an independent risk factor for HCC with high accuracy. Patients in the high-risk group exhibited a weaker immune surveillance and higher expression level of immune checkpoint molecules. In terms of drug resistance, patients in the low-risk group were more sensitive to sorafenib. The OS-related nomogram was constructed to verify the accuracy of our model. Finally, quantitative RT-PCR experiments were used to verify the expression patterns of candidate genes.Conclusion: The lncRNA signature established herein, encompassing 10 necroptosis-related lncRNAs, is valuable for survival prediction and holds promise as prognostic markers for HCC.
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Affiliation(s)
- YunZhen Peng
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - GuoJing Wu
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Xin Qiu
- Department of Urology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, China
| | - Yue Luo
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - YiShu Zou
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - XueYan Wei
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Aimin Li
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
- *Correspondence: Aimin Li, mailto:
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22
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Zhang G, Lv X, Yang Q, Liu H. Identification of HM13 as a prognostic indicator and a predictive biomarker for immunotherapy in hepatocellular carcinoma. BMC Cancer 2022; 22:888. [PMID: 35964022 PMCID: PMC9375928 DOI: 10.1186/s12885-022-09987-2] [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: 03/30/2022] [Accepted: 08/02/2022] [Indexed: 12/12/2022] Open
Abstract
Background Histocompatibility minor 13 (HM13) is a signal sequence stubbed intramembrane cleavage catalytic protein that is essential for cell signaling, intracellular communication, and cancer. However, the expression of HM13 and its prognostic value, association with tumor-infiltrating immune cells (TIICs) in the microenvironment, and potential to predict immunotherapeutic response in HCC are unknown. Methods The HM13 expression, clinicopathology analysis, and its influence on survival were analyzed in multiple public databases and further verified in collected HCC and normal tissues by qRT-PCR and immunohistochemistry staining assay (IHC). Furthermore, the lentivirus vector encoding HM13-shRNA to manipulate HM13 expression was selected to investigate whether HM13 could influence the malignant growth and metastasis potential of HCC cells. Finally, significant impacts of HM13 on the HCC tumor microenvironment (TME) and reaction to immune checkpoint inhibitors were analyzed. Results Upregulated HM13 was substantially correlated with poor prognosis in patients with HCC, and could facilitate the proliferation and migratory potential of HCC cells. Additionally, patients with high HM13 expression might be more sensitive to immunotherapy. Conclusions HM13 might be a prognostic biomarker and potential molecular therapeutic target for HCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09987-2.
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Affiliation(s)
- Genhao Zhang
- Department of Blood transfusion, Zhengzhou University First Affiliated Hospital, Zhengzhou, China
| | - Xianping Lv
- Department of Blood transfusion, Zhengzhou University First Affiliated Hospital, Zhengzhou, China
| | - Qiankun Yang
- Department of Blood transfusion, Zhengzhou University First Affiliated Hospital, Zhengzhou, China
| | - Hongchun Liu
- Department of Medical Laboratory, Zhengzhou University First Affiliated Hospital, Zhengzhou, China.
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23
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Wang T, Yang Y, Sun T, Qiu H, Wang J, Ding C, Lan R, He Q, Wang W. The Pyroptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Immunotherapeutic Efficiency in Hepatocellular Carcinoma. Front Cell Dev Biol 2022; 10:779269. [PMID: 35712653 PMCID: PMC9195296 DOI: 10.3389/fcell.2022.779269] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 01/28/2022] [Indexed: 02/05/2023] Open
Abstract
Pyroptosis was recently demonstrated to be an inflammatory form of gasdermin-regulated programmed cell death characterized by cellular lysis and the release of several proinflammatory factors and participates in tumorigenesis. However, the effects of pyroptosis-related long noncoding RNAs (lncRNAs) on hepatocellular carcinoma (HCC) have not yet been completely elucidated. Based on the regression coefficients of ZFPM2-AS1, KDM4A-AS1, LUCAT1, NRAV, CRYZL2P-SEC16B, AL031985.3, SNHG4, AL049840.5, AC008549.1, MKLN1-AS, AC099850.3, and LINC01224, HCC patients were classified into a low- or high-risk group. The high-risk score according to pyroptosis-related lncRNA signature was significantly associated with poor overall survival even after adjusting for age and clinical stage. Receiver operating characteristic curves and principal component analysis further supported the accuracy of the model. Our study revealed that a higher pyroptosis-related lncRNA risk score was significantly associated with tumor staging, pathological grade, and tumor-node-metastasis stages. The nomogram incorporating the pyroptosis-related lncRNA risk score and clinicopathological factors demonstrated good accuracy. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. Notably, based on the risk model, we found that the risk score is closely related to the expression of immune checkpoint genes, immune subtypes of tumors, and the sensitivity of HCC to chemotherapy drugs and immunotherapy. In conclusion, our novel risk score of pyroptosis-related lncRNA can serve as a promising prognostic biomarker for HCC patients and provide help for HCC patients to guide precision drug treatment and immunotherapy.
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Affiliation(s)
- Tao Wang
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, China.,State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Yang
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Ting Sun
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Haizhou Qiu
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jian Wang
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Cheng Ding
- Department of Hepatobiliary Surgery, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China
| | - Ren Lan
- Department of Hepatobiliary Surgery, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China
| | - Qiang He
- Department of Hepatobiliary Surgery, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China
| | - Wentao Wang
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, China
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24
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Wang Q, Fang Q, Huang Y, Zhou J, Liu M. Identification of a novel prognostic signature for HCC and analysis of costimulatory molecule-related lncRNA AC099850.3. Sci Rep 2022; 12:9954. [PMID: 35705628 PMCID: PMC9200812 DOI: 10.1038/s41598-022-13792-z] [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: 11/11/2021] [Accepted: 05/27/2022] [Indexed: 12/04/2022] Open
Abstract
Costimulatory molecules are involved in initiation of anti-tumor immune responses while long non‐coding RNAs (lncRNAs) regulate the development of various cancers. However, the roles of lncRNA in hepatocellular carcinoma (HCC) have not been fully established. In this study, we aimed at identifying lncRNAs-related costimulatory molecules in HCC and to construct a prognostic signature for predicting the clinical outcomes for HCC patients. Data were downloaded from The Cancer Genome Atlas database for bioinformatics analyses. Costimulatory molecules were obtained from published literature. The R software, SPSS, and GraphPad Prism were used for statistical analyses. A risk model that is based on five costimulatory molecule-related lncRNAs was constructed using lasso and Cox regression analyses. Multivariate regression analysis revealed that the risk score could predict the prognostic outcomes for HCC. Samples in high- and low-risk groups exhibited significant differences in gene set enrichment and immune infiltration levels. Through colony formation and CCK8 assays, we found that AC099850.3 was strongly associated with HCC cell proliferation. We identified and validated a novel costimulatory molecule-related survival model. In addition, AC099850.3 was found to be closely associated with clinical stages and proliferation of HCC cells, making it a potential target for HCC treatment.
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Affiliation(s)
- Qi Wang
- Department of Histology and Embryology, Anhui Medical College, Hefei, 230601, Anhui, China
| | - Qiong Fang
- Department of Histology and Embryology, Anhui Medical College, Hefei, 230601, Anhui, China
| | - Yanping Huang
- Department of Histology and Embryology, Anhui Medical College, Hefei, 230601, Anhui, China
| | - Jin Zhou
- Department of Histology and Embryology, Anhui Medical College, Hefei, 230601, Anhui, China
| | - Meimei Liu
- Department of Histology and Embryology, Anhui Medical College, Hefei, 230601, Anhui, China.
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25
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Peng B, Lou H, Chen C, Wang L, Li H, Lu T, Na R, Xu R, Xin T, Yao L, Xu H, Wang K, Liu X, Zhang L. Mitochondrial Homeostasis–Related lncRNAs are Potential Biomarkers for Predicting Prognosis and Immune Response in Lung Adenocarcinoma. Front Genet 2022; 13:870302. [PMID: 35769997 PMCID: PMC9234294 DOI: 10.3389/fgene.2022.870302] [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: 02/11/2022] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
The prognosis of the most common histological subtype of lung cancer, lung adenocarcinoma (LUAD), is relatively poor. Mitochondrial homeostasis depends to a great extent on the coordination between mitophagy and mitochondrial biogenesis, the deregulation of which causes various human diseases, including cancer. There is accumulating evidence that long noncoding RNAs (lncRNAs) are critical in predicting the prognosis and immune response in carcinoma. Therefore, it is critical to discern lncRNAs related to mitochondrial homeostasis in LUAD patients. In this study, we identified mitochondrial homeostasis–related lncRNAs (MHRlncRNAs) by coexpression analysis. In order to construct a prognostic signature composed of three MHRlncRNAs, univariate and multivariate Cox regression analyses were performed. Kaplan–Meier analysis, stratification analysis, principal component analysis (PCA), receiver operating characteristic (ROC) curve, gene set enrichment analysis (GSEA), and nomogram were applied to evaluate and optimize the risk model. Subsequently, we identified the mitochondrial homeostasis–related lncRNA signature (MHLncSig) as an independent predictive factor of prognosis. Based on the LUAD subtypes regrouped by this risk model, we further investigated the underlying tumor microenvironment, tumor mutation burden, and immune landscape behind different risk groups. Likewise, individualized immunotherapeutic strategies and candidate compounds were screened to aim at different risk subtypes of LUAD patients. Finally, we validated the expression trends of lncRNAs included in the risk model using quantitative real-time polymerase chain reaction (qRT-PCR) assays. The established MHLncSig may be a promising tool for predicting the prognosis and guiding individualized treatment in LUAD.
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Affiliation(s)
- Bo Peng
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Han Lou
- Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China and Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, China
| | - Chen Chen
- Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China and Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, China
| | - Lei Wang
- Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China and Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, China
| | - Huawei Li
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tong Lu
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Ruisi Na
- Department of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ran Xu
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tong Xin
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Lingqi Yao
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Henghui Xu
- Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China and Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, China
| | - Kaiyu Wang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xin Liu
- Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China and Key Laboratory of Cardiovascular Medicine Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, China
- *Correspondence: Xin Liu, ; Linyou Zhang,
| | - Linyou Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- *Correspondence: Xin Liu, ; Linyou Zhang,
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Wu Z, Ju Q. Non-Coding RNAs Implicated in the Tumor Microenvironment of Colorectal Cancer: Roles, Mechanisms and Clinical Study. Front Oncol 2022; 12:888276. [PMID: 35574420 PMCID: PMC9096125 DOI: 10.3389/fonc.2022.888276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 04/04/2022] [Indexed: 11/21/2022] Open
Abstract
Colorectal cancer (CRC) is one of the most common malignant tumors. The morbidity and mortality rates have been increasing all over the world. It is critical to elucidate the mechanism of CRC occurrence and development. However, tumor microenvironment (TME) includes immune cells, fibroblasts, endothelial cells, cytokines, chemokines and other components that affect the progression of CRC and patients’ prognosis. Non-coding RNAs (ncRNAs) including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) without protein-coding ability have been shown to engage in tumor microenvironment-mediated angiogenesis and metastasis. Therefore, clarifying the mechanism of ncRNAs regulating the microenvironment is very important to develop the therapeutic target of CRC and improve the survival time of patients. This review focuses on the role and mechanism of ncRNAs in the CRC microenvironment and puts forward possible clinical treatment strategies.
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Affiliation(s)
- Zhaoxu Wu
- Department of Blood Transfusion, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Qiang Ju
- Department of Blood Transfusion, The Affiliated Hospital of Qingdao University, Qingdao, China
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27
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Zheng G, Liu M, Chang X, Cao X, Dong A, Zhu H, Hu W, Xie J, Zhao Y, Hu D, Jia X, Yang Y, Shi X, Lu J. Comprehensive Analysis of N6-Methyladenosine-Related Long Noncoding RNA Prognosis of Acute Myeloid Leukemia and Immune Cell Infiltration. Front Genet 2022; 13:888173. [PMID: 35601490 PMCID: PMC9115802 DOI: 10.3389/fgene.2022.888173] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 04/07/2022] [Indexed: 12/12/2022] Open
Abstract
N6-Methyladenosine-related long noncoding RNAs play an essential role in many cancers’ development. However, the relationship between m6A-related lncRNAs and acute myelogenous leukemia (AML) prognosis remains unclear. We systematically analyzed the association of m6A-related lncRNAs with the prognosis and tumor immune microenvironment (TME) features using the therapeutically applicable research to generate effective treatment (TARGET) database. We screened 315 lncRNAs associated with AML prognosis and identified nine key lncRNAs associated with m6A by the LASSO Cox analysis. A model was established based on these nine lncRNAs and the predictive power was explored in The Cancer Genome Atlas (TCGA) database. The areas under the ROC curve of TARGET and TCGA databases for ROC at 1, 3, and 5 years are 0.701, 0.704, and 0.696, and 0.587, 0.639, and 0.685, respectively. The nomogram and decision curve analysis (DCA) showed that the risk score was more accurate than other clinical indicators in evaluating patients’ prognoses. The clusters with a better prognosis enrich the AML pathways and immune-related pathways. We also found a close correlation between prognostic m6A-related lncRNAs and tumor immune cell infiltration. LAG3 expression at the immune checkpoint was lower in the worse prognostic cluster. In conclusion, m6A-related lncRNAs partly affected AML prognosis by remodeling the TME and affecting the anticarcinogenic ability of immune checkpoints, especially LAG3 inhibitors. The prognostic model constructed with nine key m6A-related lncRNAs can provide a method to assess the prognosis of AML patients in both adults and children.
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Affiliation(s)
- Guowei Zheng
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Mengying Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xinyu Chang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiting Cao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ani Dong
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Huili Zhu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wanli Hu
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Junna Xie
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yang Zhao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Dongsheng Hu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xuezhong Shi
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- *Correspondence: Jie Lu, ; Xuezhong Shi,
| | - Jie Lu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- *Correspondence: Jie Lu, ; Xuezhong Shi,
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Chen H, Zhou C, Hu Z, Sang M, Ni S, Wu J, Pan Q, Tong J, Liu K, Li N, Zhu L, Xu G. Construction of an algorithm based on oncosis-related LncRNAs comprising the molecular subtypes and a risk assessment model in lung adenocarcinoma. J Clin Lab Anal 2022; 36:e24461. [PMID: 35476781 PMCID: PMC9169186 DOI: 10.1002/jcla.24461] [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: 03/26/2022] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 12/12/2022] Open
Abstract
Background As an important non‐apoptotic cell death method, oncosis has been reported to be closely associated with tumors in recent years. However, few research reported the relationship between oncosis and lung cancer. Methods In this study, we established an oncosis‐based algorithm comprised of cluster grouping and a risk assessment model to predict the survival outcomes and related tumor immunity of patients with lung adenocarcinomas (LUAD). We selected 11 oncosis‐related lncRNAs associated with the prognosis (CARD8‐AS1, LINC00941, LINC01137, LINC01116, AC010980.2, LINC00324, AL365203.2, AL606489.1, AC004687.1, HLA‐DQB1‐AS1, and AL590226.1) to divide the LUAD patients into different clusters and different risk groups. Compared with patients in clsuter1, patients in cluster2 had a survival advantage and had a relatively more active tumor immunity. Subsequently, we constructed a risk assessment model to distinguish between patients into different risk groups, in which low‐risk patients tend to have a better prognosis. GO enrichment analysis revealed that the risk assessment model was closely related to immune activities. In addition, low‐risk patients tended to have a higher content of immune cells and stromal cells in tumor microenvironment, higher expression of PD‐1, CTLA‐4, HAVCR2, and were more sensitive to immune checkpoint inhibitors (ICIs), including PD‐1/CTLA‐4 inhibitors. The risk score had a significantly positive correlation with tumor mutation burden (TMB). The survival curve of the novel oncosis‐based algorithm suggested that low‐risk patients in cluster2 have the most obvious survival advantage. Conclusion The novel oncosis‐based algorithm investigated the prognosis and the related tumor immunity of patients with LUAD, which could provide theoretical support for customized individual treatment for LUAD patients.
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Affiliation(s)
- Hang Chen
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Chongchang Zhou
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Zeyang Hu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Menglu Sang
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Saiqi Ni
- Department of Urology, Ningbo City First Hospital, Ningbo, China
| | - Jiacheng Wu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Qiaoling Pan
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Jingtao Tong
- Department of Radiation Oncology, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Kaitai Liu
- Department of Radiation Oncology, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Ni Li
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Linwen Zhu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Guodong Xu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
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29
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Inflammatory Response-Related Long Non-Coding RNA Signature Predicts the Prognosis of Hepatocellular Carcinoma. JOURNAL OF ONCOLOGY 2022; 2022:9917244. [PMID: 35342418 PMCID: PMC8947866 DOI: 10.1155/2022/9917244] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 02/22/2022] [Indexed: 01/08/2023]
Abstract
Background Hepatocellular carcinoma (HCC) is a high mortality malignant tumor with genetic and phenotypic heterogeneity, making predicting prognosis challenging. Meanwhile, the inflammatory response is an indispensable player in the tumorigenesis process and regulates the tumor microenvironment, which can affect the prognosis of tumor patients. Methods Using HCC samples in the TCGA-LIHC dataset, we explored lncRNA expression profiles associated with the inflammatory response. The inflammatory response-related lncRNA signature was constructed by univariate Cox regression, LASSO regression, and multivariate Cox regression methods based on inflammatory response-related differentially expressed lncRNAs in HCC. Results Seven inflammatory response-related lncRNA signatures were identified in predicting HCC prognosis. Kaplan–Meier (K-M) survival analysis indicated that high-risk group HCC patients were associated with poor prognosis. The utility of the inflammatory response-related lncRNA signatures was proved by the AUC and DCA analysis. The nomogram further confirmed the accuracy of the novel signature in predicting HCC patients' prognoses. In validation, our novel signature is more accurate than traditional clinicopathological performance for prognosis prediction of HCC patients. GSEA analysis further elucidated the underlying mechanisms and pathways of HCC progression in the low- and high-risk groups. Moreover, immune cells infiltration responses and immune function analyses revealed a significant difference between high- and low-risk groups in cytolytic activity, MHC class I, type I INF response, type II INF response, inflammation-promoting, and T cell coinhibition. Finally, HHLA2, NRP1, CD276, TNFRSF9, TNFSF4, CD80, and VTCN1 were expressed higher in high-risk groups in the immune checkpoint analysis. Conclusions A novel inflammatory response-related lncRNA signature (AC145207.5, POLHAS1, AL928654.1, MKLN1AS, AL031985.3, PRRT3AS1, and AC023157.2) is capable of predicting the prognosis of HCC patients and providing new immune targeted therapies insight.
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Liu ZK, Wu KF, Zhang RY, Kong LM, Shang RZ, Lv JJ, Li C, Lu M, Yong YL, Zhang C, Zheng NS, Li YH, Chen ZN, Bian H, Wei D. Pyroptosis-Related LncRNA Signature Predicts Prognosis and Is Associated With Immune Infiltration in Hepatocellular Carcinoma. Front Oncol 2022; 12:794034. [PMID: 35311105 PMCID: PMC8927701 DOI: 10.3389/fonc.2022.794034] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 02/11/2022] [Indexed: 12/15/2022] Open
Abstract
Pyroptosis is an inflammatory form of programmed cell death that is involved in various cancers, including hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) were recently verified as crucial mediators in the regulation of pyroptosis. However, the role of pyroptosis-related lncRNAs in HCC and their associations with prognosis have not been reported. In this study, we constructed a prognostic signature based on pyroptosis-related differentially expressed lncRNAs in HCC. A co-expression network of pyroptosis-related mRNAs-lncRNAs was constructed based on HCC data from The Cancer Genome Atlas. Cox regression analyses were performed to construct a pyroptosis-related lncRNA signature (PRlncSig) in a training cohort, which was subsequently validated in a testing cohort and a combination of the two cohorts. Kaplan-Meier analyses revealed that patients in the high-risk group had poorer survival times. Receiver operating characteristic curve and principal component analyses further verified the accuracy of the PRlncSig model. Besides, the external cohort validation confirmed the robustness of PRlncSig. Furthermore, a nomogram based on the PRlncSig score and clinical characteristics was established and shown to have robust prediction ability. In addition, gene set enrichment analysis revealed that the RNA degradation, the cell cycle, the WNT signaling pathway, and numerous immune processes were significantly enriched in the high-risk group compared to the low-risk group. Moreover, the immune cell subpopulations, the expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. Finally, the expression levels of the five lncRNAs in the signature were validated by quantitative real-time PCR. In summary, our PRlncSig model shows significant predictive value with respect to prognosis of HCC patients and could provide clinical guidance for individualized immunotherapy.
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Affiliation(s)
- Ze-Kun Liu
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Ke-Fei Wu
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Ren-Yu Zhang
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Ling-Min Kong
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Run-Ze Shang
- Department of General Surgery, Affiliated Haixia Hospital of Huaqiao University (The 910 Hospital of the Joint Logistics Team), Quanzhou, China
| | - Jian-Jun Lv
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Can Li
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Meng Lu
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Yu-Le Yong
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Cong Zhang
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Nai-Shan Zheng
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Yan-Hong Li
- Department of Gynaecology and Obstetrics, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhi-Nan Chen
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Huijie Bian
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
| | - Ding Wei
- National Translational Science Center for Molecular Medicine, Department of Cell Biology, State Key Laboratory of Cancer Biology, Fourth Military Medical University, Xi'an, China
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Li Y, Sun X. An Effective Hypoxia-Related Long Non-Coding RNA Assessment Model for Prognosis of Lung Adenocarcinoma. Front Genet 2022; 13:768971. [PMID: 35368654 PMCID: PMC8966506 DOI: 10.3389/fgene.2022.768971] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 02/03/2022] [Indexed: 12/23/2022] Open
Abstract
Background: Lung adenocarcinoma (LUAD) represents one of the highest incidence rates worldwide. Hypoxia is a significant biomarker associated with poor prognosis of LUAD. However, there are no definitive markers of hypoxia-related long non-coding RNAs (lncRNAs) in LUAD. Methods: From The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB), we acquired the expression of hypoxia-related lncRNAs and corresponding clinical information of LUAD patients. The hypoxia-related prognostic model was constructed by univariable COX regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariable Cox regression analysis. To assess the performance of the model, the Kaplan–Meier (KM) survival and receiver operating characteristic (ROC) curve analyses were performed. Results: We found seven lncRNAs, AC022613.1, AC026355.1, GSEC, LINC00941, NKILA, HSPC324, and MYO16-AS1, as biomarkers of the potential hypoxia-related prognostic signature. In the low-risk group, patients had a better overall survival (OS). In addition, the results of ROC analysis indicated that the risk score predicted LUAD prognosis exactly. Furthermore, combining the expression of lncRNAs with clinical features, two predictive nomograms were constructed, which could accurately predict OS and had high clinical application value. Conclusion: In summary, the seven-lncRNA prognostic signature related to hypoxia might be useful in predicting clinical outcomes and provided new molecular targets for the research of LUAD patients.
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Affiliation(s)
- Yuanshuai Li
- Department of Obstetrics and Gynecology, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Guangzhou, China
| | - Xiaofang Sun
- Department of Obstetrics and Gynecology, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, Guangzhou, China
- *Correspondence: Xiaofang Sun,
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Gan Y, Fang W, Zeng Y, Wang P, Shan R, Zhang L. Identification of a Novel Survival-Related circRNA–miRNA–mRNA Regulatory Network Related to Immune Infiltration in Liver Hepatocellular Carcinoma. Front Genet 2022; 13:800537. [PMID: 35309118 PMCID: PMC8924452 DOI: 10.3389/fgene.2022.800537] [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: 11/18/2021] [Accepted: 02/03/2022] [Indexed: 11/29/2022] Open
Abstract
Increasing studies have reported that circular RNAs (circRNAs) play critical roles in tumorigenesis and cancer progression. However, the underlying regulatory mechanisms of circRNA-related competing endogenous RNA (ceRNA) in liver hepatocellular carcinoma (LIHC) are still unclear. In the present study, we discovered dysregulated circRNAs through Gene Expression Omnibus (GEO) analysis and validated the expression of the top seven circRNAs with upregulated expression by qRT–PCR and Sanger sequencing. Then, the Cancer-Specific CircRNA Database (CSCD) was used to predict the downstream miRNAs of seven circRNAs, and expression and survival analyses through The Cancer Genome Atlas (TCGA) were performed to identify the key miRNA in LIHC. Thereafter, the hsa_circ_0017264-hsa-miR-195–5p subnetwork was successfully constructed. Subsequently, we predicted downstream target genes of hsa-miR-195–5p with TargetScan, miRDB, and mirtarbase and overlapped them with differentially expressed mRNAs to obtain 21 target genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to predict the biological and functional roles of these target genes. Finally, with Pearson correlation and prognostic value analysis, a survival-related hsa_circ_0017264-hsa-miR-195-5p-CHEK1/CDC25A/FOXK1 axis was established. Gene set enrichment analysis (GSEA) was performed to determine the function of CHEK1/CDC25A/FOXK1 in the ceRNA network. Moreover, immune infiltration analysis revealed that the ceRNA network was markedly associated with the levels of multiple immune cell infiltrates, immune cell biomarkers and immune checkpoints. Overall, the hsa_circ_0017264-hsa-miR-195-5p-CHEK1/CDC25A/FOXK1 network might provide novel insights into the potential mechanisms underlying LIHC onset and progression.
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Affiliation(s)
- Yu Gan
- Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Weidan Fang
- Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yan Zeng
- Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Peijun Wang
- Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Renfeng Shan
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Ling Zhang
- Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Human Genetic Resources Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
- *Correspondence: Ling Zhang,
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Wang B, Liu L, Wu J, Mao X, Fang Z, Chen Y, Li W. Construction and Verification of a Combined Hypoxia and Immune Index for Clear Cell Renal Cell Carcinoma. Front Genet 2022; 13:711142. [PMID: 35222525 PMCID: PMC8863964 DOI: 10.3389/fgene.2022.711142] [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: 05/18/2021] [Accepted: 01/21/2022] [Indexed: 11/13/2022] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive malignancies in humans. Hypoxia-related genes are now recognized as a reflection of poor prognosis in cancer patients with cancer. Meanwhile, immune-related genes play an important role in the occurrence and progression of ccRCC. Nevertheless, reliable prognostic indicators based on hypoxia and immune status have not been well established in ccRCC. The aims of this study were to develop a new gene signature model using bioinformatics and open databases and to validate its prognostic value in ccRCC. The data used for the model structure can be accessed from The Cancer Genome Atlas database. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the hypoxia- and immune-related genes associated with prognostic risk, which were used to develop a characteristic model of prognostic risk. Kaplan-Meier and receiver-operating characteristic curve analyses were performed as well as independent prognostic factor analyses and correlation analyses of clinical characteristics in both the training and validation cohorts. In addition, differences in tumor immune cell infiltrates were compared between the high and low risk groups. Overall, 30 hypoxia- and immune-related genes were identified, and five hypoxia- and immune-related genes (EPO, PLAUR, TEK, TGFA, TGFB1) were ultimately selected. Survival analysis showed that the high-risk score on the hypoxia- and immune-related gene signature was significantly associated with adverse survival outcomes. Furthermore, clinical ccRCC samples from our medical center were used to validate the differential expression of the five genes in tumor tissue compared to normal tissue through quantitative real-time polymerase chain reaction (qRT-PCR). However, more clinical trials are needed to confirm these results, and future experimental studies must verify the potential mechanism behind the predictive value of the hypoxia- and immune-related gene signature.
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Affiliation(s)
- Bin Wang
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lixiao Liu
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jinting Wu
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaolu Mao
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhen Fang
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yingyu Chen
- Department of Neurosurgery, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Wenfeng Li
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- *Correspondence: Wenfeng Li,
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Zhu Y, Shan D, Guo L, Chen S, Li X. Immune-Related lncRNA Pairs Clinical Prognosis Model Construction for Hepatocellular Carcinoma. Int J Gen Med 2022; 15:1919-1931. [PMID: 35237066 PMCID: PMC8882675 DOI: 10.2147/ijgm.s343350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/02/2022] [Indexed: 11/26/2022] Open
Abstract
Background Long non-coding RNA (lncRNA) plays an essential regulatory role in the occurrence and development of hepatocellular carcinoma (HCC). This paper aims to establish an immune-related lncRNA (irlncRNA) pairs model independent of expression level for risk assessment and prognosis prediction of HCC. Methods Transcriptome data and corresponding clinical data were downloaded from TCGA. HCC patients were randomly divided into training group and test group. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multiple Cox regression analysis were used to establish a prognostic model. The prediction ability of the model was verified by ROC curves. Next, the patients were divided into low-risk and high-risk groups. We compared the differences between the two groups in survival rate, clinicopathological characteristics, tumor immune cell infiltration status, chemotherapeutic drug sensitivity and immunosuppressive molecules. Results A prognosis prediction model was established based on 7 irlncRNA pairs, namely irlncRNA pairs (IRLP). ROC curves of the training group and test group showed that the IRLP model had high sensitivity and specificity for survival prediction. Kaplan–Meier analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Immune cell infiltration analysis showed that the high-risk group was significantly correlated with various immune cell infiltration. Finally, there were statistically significant differences in chemosensitivity and molecular marker expression between the two groups. Conclusion The prognosis prediction model established by irlncRNA pairs has a certain guiding significance for the prognosis prediction of HCC. It may provide valuable clinical applications in antitumor immunotherapy.
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Affiliation(s)
- Yinghui Zhu
- Department of Digestology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, People’s Republic of China
| | - Dezhi Shan
- Graduate School of Peking Union Medical College, Beijing, People’s Republic of China
| | - Lianyi Guo
- Department of Digestology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, People’s Republic of China
| | - Shujia Chen
- Department of Digestology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, People’s Republic of China
| | - Xiaofei Li
- Department of Digestology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, People’s Republic of China
- Correspondence: Xiaofei Li, Jinzhou, Liaoning, 121000, People’s Republic of China, Email
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Huang S, Zhang J, Lai X, Zhuang L, Wu J. Identification of Novel Tumor Microenvironment-Related Long Noncoding RNAs to Determine the Prognosis and Response to Immunotherapy of Hepatocellular Carcinoma Patients. Front Mol Biosci 2022; 8:781307. [PMID: 35004851 PMCID: PMC8739902 DOI: 10.3389/fmolb.2021.781307] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/25/2021] [Indexed: 12/12/2022] Open
Abstract
Introduction: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. The tumor microenvironment (TME) plays a vital role in HCC progression. Thus, this research was designed to analyze the correlation between the TME and the prognosis of HCC patients and to construct a TME-related long noncoding RNA (lncRNA) signature to determine HCC patients’ prognosis and response to immunotherapy. Methods: We assessed the stromal–immune–estimate scores within the HCC microenvironment using the ESTIMATE (Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data) algorithm based on The Cancer Genome Atlas database, and their associations with survival and clinicopathological parameters were also analyzed. Thereafter, differentially expressed lncRNAs were filtered out according to the immune and stromal scores. Cox regression analysis was performed to build a TME-related lncRNA risk signature. Kaplan–Meier analysis was used to explore the prognostic value of the risk signature. Furthermore, we explored the biological functions and immune microenvironment features in the high- and low-risk groups. Lastly, we probed the association of the risk model with treatment responses to immune checkpoint inhibitors (ICIs) in HCC. Results: The stromal, immune, and estimate scores were obtained utilizing the ESTIMATE algorithm for patients with HCC. Kaplan–Meier analysis showed that high scores were significantly correlated with better prognosis in HCC patients. Six TME-related lncRNAs were screened to construct the prognostic model. The Kaplan–Meier curves suggested that HCC patients with low risk had better prognosis than those with high risk. Receiver operating characteristic (ROC) curve and Cox regression analyses indicated that the risk model could predict HCC survival exactly and independently. Functional enrichment analysis revealed that some tumor- and immune-related pathways were activated in the high-risk group. We also revealed that some immune cells, which were important in enhancing immune responses toward cancer, were significantly increased in the low-risk group. In addition, there was a close correlation between ICIs and the risk signature, which can be used to predict the treatment responses of HCC patients. Conclusion: We analyzed the influence of the stromal, immune, and estimate scores on the prognosis of HCC patients. A novel TME-related lncRNA risk model was established, which could be effectively applied as an independent prognostic biomarker and predictor of ICIs for HCC patients.
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Affiliation(s)
- Shenglan Huang
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
| | - Jian Zhang
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
| | - Xiaolan Lai
- Ningde Municipal Hospital Affiliated to Ningde Normal University, Ningde, China
| | - Lingling Zhuang
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
| | - Jianbing Wu
- The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Jiangxi Key Laboratory of Clinical and Translational Cancer Research, Nanchang, China
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Deng M, Lin JB, Zhao RC, Li SH, Lin WP, Zou JW, Wei W, Guo RP. Construction of a novel immune-related lncRNA signature and its potential to predict the immune status of patients with hepatocellular carcinoma. BMC Cancer 2021; 21:1347. [PMID: 34923955 PMCID: PMC8684648 DOI: 10.1186/s12885-021-09059-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 11/28/2021] [Indexed: 12/24/2022] Open
Abstract
Background The accuracy of existing biomarkers for predicting the prognosis of hepatocellular carcinoma (HCC) is not satisfactory. It is necessary to explore biomarkers that can accurately predict the prognosis of HCC. Methods In this study, original transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related long noncoding ribonucleic acids (irlncRNAs) were identified by coexpression analysis, and differentially expressed irlncRNA (DEirlncRNA) pairs were distinguished by univariate analysis. In addition, the least absolute shrinkage and selection operator (LASSO) penalized regression was modified. Next, the cutoff point was determined based on the area under the curve (AUC) and Akaike information criterion (AIC) values of the 5-year receiver operating characteristic (ROC) curve to establish an optimal model for identifying high-risk and low-risk groups of HCC patients. The model was then reassessed in terms of clinicopathological features, survival rate, tumor-infiltrating immune cells, immunosuppressive markers, and chemotherapy efficacy. Results A total of 1009 pairs of DEirlncRNAs were recognized in this study, 30 of these pairs were included in the Cox regression model for subsequent analysis. After regrouping according to the cutoff point, we could more effectively identify factors such as aggressive clinicopathological features, poor survival outcomes, specific immune cell infiltration status of tumors, high expression level of immunosuppressive biomarkers, and low sensitivity to chemotherapy drugs in HCC patients. Conclusions The nonspecific expression level signature involved with irlncRNAs shows promising clinical value in predicting the prognosis of HCC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-09059-x.
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Affiliation(s)
- Min Deng
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China
| | - Jia-Bao Lin
- Department of Health Management Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Rong-Ce Zhao
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China
| | - Shao-Hua Li
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China
| | - Wen-Ping Lin
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China
| | - Jing-Wen Zou
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China
| | - Wei Wei
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.,State Key Laboratory of Oncology in South China, Guangzhou, China.,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China
| | - Rong-Ping Guo
- Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China. .,State Key Laboratory of Oncology in South China, Guangzhou, China. .,Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, China.
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Wang X, Chen K, Wang Z, Xu Y, Dai L, Bai T, Chen B, Yang W, Chen W. Using Immune-Related Long Non-coding Ribonucleic Acids to Develop a Novel Prognosis Signature and Predict the Immune Landscape of Colon Cancer. Front Cell Dev Biol 2021; 9:750709. [PMID: 34660608 PMCID: PMC8514752 DOI: 10.3389/fcell.2021.750709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 09/08/2021] [Indexed: 12/24/2022] Open
Abstract
Purpose: This study aimed to construct a novel signature to predict the survival of patients with colon cancer and the associated immune landscape, based on immune-related long noncoding ribonucleic acids (irlncRNAs). Methods: Expression profiles of irlncRNAs in 457 patients with colon cancer were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed (DE) irlncRNAs were identified and irlncRNA pairs were recognized using Lasso regression and Cox regression analyses. Akaike information criterion (AIC) values of receiver operating characteristic (ROC) curve were calculated to identify the ideal cut-off point for dividing patients into two groups and constructing the prognosis signature. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the expression of LINC02195 and SCARNA9 in colon cancer. Results: We identified 22 irlncRNA pairs and patients were divided into high-risk and low-risk groups based on the calculated risk score using these 22 irlncRNA pairs. The irlncRNA pairs were significantly related to patient survival. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). The area under the curve of the signature to predict 5-year survival was 0.951. The risk score correlated with tumor stage, infiltration depth, lymph node metastasis, and distant metastasis. The risk score remained significant after univariate and multivariate Cox regression analyses. A nomogram model to predict patient survival was developed based on the results of Cox regression analysis. Immune cell infiltration status, expression of some immune checkpoint genes, and sensitivity to chemotherapeutics were also related to the risk score. The results of qRT-PCR revealed that LINC02195 and SCARNA9 were significantly upregulated in colon cancer tissues. Conclusion: The constructed prognosis signature showed remarkable efficiency in predicting patient survival, immune cell infiltration status, expression of immune checkpoint genes, and sensitivity to chemotherapeutics.
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Affiliation(s)
- Xu Wang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ke Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhenglin Wang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yuanmin Xu
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Longfei Dai
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Tao Bai
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Bo Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wenqi Yang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wei Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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Zhou Q, Li D, Zheng H, He Z, Qian F, Wu X, Yin Z, Bao PT, Jin M. A novel lncRNA-miRNA-mRNA competing endogenous RNA regulatory network in lung adenocarcinoma and kidney renal papillary cell carcinoma. Thorac Cancer 2021; 12:2526-2536. [PMID: 34453499 PMCID: PMC8487820 DOI: 10.1111/1759-7714.14129] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 12/15/2022] Open
Abstract
Background GPRIN1 may be a novel tumor regulator, but its role and mechanism in tumors are still unclear. Methods First, a pan‐cancer correlation analysis was conducted on the expression and prognosis of GPRIN1 based on the data downloaded from The Cancer Genome Atlas (TCGA) database. Second, the Starbase database was used to predict the upstream miRNAs and lncRNAs of GPRIN1, and the expression analysis, survival analysis, and correlation analysis were performed to screen the microRNA (miRNAs)/long non‐coding RNAs (lncRNAs) that had a correlation with kidney renal papillary cell carcinoma (KIRP) or lung adenocarcinoma (LUAD). Third, the CIBERSORT algorithm was employed to calculate the proportion of various types of immune cells, and then the R packages were used for evaluating the relation between GPRIN1 expression and tumor immune cell infiltration as well as between GPRIN1 and the immune cell biomarker. Finally, the correlation analysis was made on GPRIN1 and immune checkpoints (CD274, CTLA4, and PDCD1). Results The pan‐cancer analysis suggested that GPRIN1 was up‐expressed in KIRP and LUAD, and it correlated with poor prognosis. LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG‐miR‐140‐3p was likely to be the most promising upstream regulation pathway of GPRIN1. Upexpression of LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG and downexpression of miR‐140‐3p were found relevant with poor outcomes of KIRP and LUAD. GPRIN1 expression was significantly correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoints. Conclusions The competitive endogenous (ceRNA) of miR‐140‐3p‐GPRIN1 axis and its upstream lncRNAs are closely related to KIRP and LUAD, and might affect the prognosis and therapeutic effect of KIRP and LUAD.
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Affiliation(s)
- Qiwei Zhou
- Department of Urology, Chinese People's Liberation Army General Hospital/PLA Medical School, Beijing, China.,Department of Urology, Chinese People's Liberation Army No.92493 Hospital, Huludao, China
| | - Diangeng Li
- Department of Scientific Research, Beijing-Chaoyang Hospital, Beijing, China
| | | | - Zheng He
- Department of Laboratory, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Feng Qian
- Department of Emergency Medicine, Chinese People's Liberation Army No. 92493 Hospital, Huludao, China
| | - Xiaotian Wu
- College of Integration Science, Yanbian University, Yanbian, China
| | - Zhiwei Yin
- Department of Nephrology, Chinese People's Liberation Army General Hospital, Chinese People's Liberation Army Institute of Nephrology, State Key Laboratory of Kidney Diseases (2011DAV00088), National Clinical Research Center for Kidney Diseases, Beijing, China
| | - Peng Tao Bao
- Department of Respiratory Medicine, The Eighth Medical Center of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Meiling Jin
- Department of Nephrology, Chinese People's Liberation Army General Hospital, Chinese People's Liberation Army Institute of Nephrology, State Key Laboratory of Kidney Diseases (2011DAV00088), National Clinical Research Center for Kidney Diseases, Beijing, China.,Department of Nephrology, Beijing-Chaoyang Hospital, Beijing, China
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