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Lin Y, Wu W, Lin H, Chen S, Lv H, Chen S, Li C, Wang X, Chen Y. KM04416 suppressed lung adenocarcinoma progression by promoting immune infiltration. J Cardiothorac Surg 2024; 19:465. [PMID: 39054490 PMCID: PMC11270931 DOI: 10.1186/s13019-024-02971-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 07/12/2024] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVES Lung adenocarcinoma (LUAD) is a malignant tumor originating from the bronchial mucosa or glands of the lung, with the fastest increasing morbidity and mortality. Therefore, the prognosis of lung cancer remains poor. Glycerol-3-phosphate dehydrogenase 2 (GPD2) is a widely existing protein pattern sequence in biology and is closely related to tumor progression. The therapy values of GPD2 inhibitor in LUAD were unclear. Therefore, we aimed to analyze the therapy values of GPD2 inhibitor in LUAD. MATERIALS AND METHODS The Cancer Genome Atlas (TCGA)-LUAD database was used to analyze the expression levels of GPD2 in LUAD tissues. The relationship between GPD2 expression and LUAD patient survival was analyzed by Kaplan-Meier method. Moreover, KM04416 as a target inhibitor of GPD2 was used to further investigate the therapy value of GPD2 inhibitor in LUAD cells lines (A549 cell and H1299 cell). The TISIDB website was used to investigate the associations between GPD2 expression and immune cell infiltration in LUAD. RESULTS The results showed that GPD2 is overexpressed in LUAD tissues and significantly associated with poor survival. KM04416 can suppress the progression of LUAD cells by targeting GPD2. Low expression of GPD2 is related to high infiltration of immune cells. CONCLUSIONS In summary, our present study found that targeting inhibition of GPD2 by KM04416 can suppress LUAD progression via adjusting immune cell infiltration.
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Affiliation(s)
- Yalan Lin
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Weijing Wu
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Huihuang Lin
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Shiyuan Chen
- Department of Oncology, Dongguan People 's Hospital, Dongguan, China
| | - Huiying Lv
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Shuchao Chen
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Chuzhao Li
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Xinwen Wang
- Department of Orthopedics, Sanming First Hospital Affiliated to Fujian Medical University, Sanming, Fujian, China.
| | - Yunfeng Chen
- Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
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Shen Y, Gong L, Xu F, Wang S, Liu H, Wang Y, Hu L, Zhu L. Insight into the lncRNA-mRNA Co-Expression Profile and ceRNA Network in Lipopolysaccharide-Induced Acute Lung Injury. Curr Issues Mol Biol 2023; 45:6170-6189. [PMID: 37504305 PMCID: PMC10378513 DOI: 10.3390/cimb45070389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/16/2023] [Accepted: 07/20/2023] [Indexed: 07/29/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) participate in acute lung injury (ALI). However, their latent biological function and molecular mechanism have not been fully understood. In the present study, the global expression profiles of lncRNAs and mRNAs between the control and lipopolysaccharide (LPS)-stimulated groups of human normal lung epithelial cells (BEAS-2B) were determined using high-throughput sequencing. Overall, a total of 433 lncRNAs and 183 mRNAs were differentially expressed. A lncRNA-mRNA co-expression network was established, and then the top 10 lncRNAs were screened using topological methods. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis results showed that the key lncRNAs targeting mRNAs were mostly enriched in the inflammatory-related biological processes. Gene set variation analysis and Pearson's correlation coefficients confirmed the close correlation for the top 10 lncRNAs with inflammatory responses. A protein-protein interaction network analysis was conducted based on the key lncRNAs targeting mRNAs, where IL-1β, IL-6, and CXCL8 were regarded as the hub genes. A competing endogenous RNA (ceRNA) modulatory network was created with five lncRNAs, thirteen microRNAs, and twelve mRNAs. Finally, real-time quantitative reverse transcription-polymerase chain reaction was employed to verify the expression levels of several key lncRNAs in BEAS-2B cells and human serum samples.
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Affiliation(s)
- Yue Shen
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Linjing Gong
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Fan Xu
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Sijiao Wang
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Hanhan Liu
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yali Wang
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lijuan Hu
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lei Zhu
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Department of Pulmonary and Critical Care Medicine, Huadong Hospital, Fudan University, Shanghai 200040, China
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Xu QS, Shen ZZ, Yuan LQ. Identification and validation of a novel cuproptosis-related lncRNA signature for prognosis and immunotherapy of head and neck squamous cell carcinoma. Front Cell Dev Biol 2022; 10:968590. [DOI: 10.3389/fcell.2022.968590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 10/28/2022] [Indexed: 11/18/2022] Open
Abstract
Head and neck squamous cell carcinoma (HNSCC) is a highly prevalent and heterogeneous malignancy with a dismal overall survival rate. Nevertheless, the effective biomarkers remain ambiguous and merit further investigation. Cuproptosis is a novel defined pathway of programmed cell death that contributes to the progression of cancers. Meanwhile, long non-coding RNAs (lncRNAs) play a crucial role in the biological process of tumors. Nevertheless, the prognostic value of cuproptosis-related lncRNAs in HNSCC is still obscure. This study aimed to develop a new cuproptosis-related lncRNAs (CRLs) signature to estimate survival and tumor immunity in patients with HNSCC. Herein, 620 cuproptosis-related lncRNAs were identified from The Cancer Genome Atlas database through the co-expression method. To construct a risk model and validate the accuracy of the results, the samples were divided into two cohorts randomly and equally. Subsequently, a prognostic model based on five CRLs was constructed by the Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm. In addition, the prognostic potential of the five-CRL signature was verified via Cox regression, survival analysis, the receiver operating characteristic (ROC) curve, nomogram, and clinicopathologic characteristics correlation analysis. Furthermore, we explored the associations between the signature risk score (RS) and immune landscape, somatic gene mutation, and drug sensitivity. Finally, we gathered six clinical samples and different HNSCC cell lines to validate our bioinformatics results. Overall, the proposed novel five-CRL signature can predict prognosis and assess the efficacy of immunotherapy and targeted therapies to prolong the survival of patients with HNSCC.
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Liu R, Guo Z, Huang J, Li J, Tan Q, Luo Q. Identification of a 7-miRNA signature for predicting the prognosis of patients with lung adenocarcinoma. Exp Biol Med (Maywood) 2022; 247:641-657. [PMID: 35068222 DOI: 10.1177/15353702211067450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The role of microRNAs (miRNAs) in tumor diagnosis and patients’ prognosis has recently gained extensive research attention. This study was designed to analyze miRNA in lung adenocarcinoma (LUAD) using bioinformatics analysis and to identify novel biomarkers to predict overall survival (OS) for LUAD patients. Differential miRNA expression analysis was performed on LUAD, and normal tissues were extracted from The Cancer Genome Atlas (TCGA). Univariate Cox risk regression and least absolute shrinkage and selection operator (LASSO) Cox analysis were used to screen prognostic miRNAs and develop a risk score model. The prognostic performance of the system was examined utilizing the Kaplan–Meier and receiver operating characteristic (ROC) curves. Independent prognostic factors of LUAD were determined by multivariate Cox regression analysis. Nomogram was constructed according to the independent prognostic factors to evaluate the patients’ one-, three- and five-year OS. A 7-miRNA signature based on miR-584-5p, miR-31-3p, miR-490-3, miR-4661-5p, miR-30e-5p, miR-582-5p, and miR-148a-3p was established. To categorize patients into high- and low-risk groups, the risk score was computed. The OS of the low-risk group was significantly longer than the high-risk group, and the signature showed high sensitivity and specificity in anticipating the one-, three- and five-year OS. The system was an independent factor in predicting the OS of LUAD patients and performed better when combined with the N stage in nomogram. A 7-miRNA signature developed in this study could accurately predict LUAD survival.
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Affiliation(s)
- Ruijun Liu
- Lung Tumor Clinical Medicine Center, Shanghai Chest Hospital, Shanghai Jiao tong University, Shanghai 200030, China
| | - Zhiyi Guo
- Lung Tumor Clinical Medicine Center, Shanghai Chest Hospital, Shanghai Jiao tong University, Shanghai 200030, China
| | - Jia Huang
- Lung Tumor Clinical Medicine Center, Shanghai Chest Hospital, Shanghai Jiao tong University, Shanghai 200030, China
| | - Jiantao Li
- Lung Tumor Clinical Medicine Center, Shanghai Chest Hospital, Shanghai Jiao tong University, Shanghai 200030, China
| | - Qiang Tan
- Lung Tumor Clinical Medicine Center, Shanghai Chest Hospital, Shanghai Jiao tong University, Shanghai 200030, China
| | - Qingquan Luo
- Lung Tumor Clinical Medicine Center, Shanghai Chest Hospital, Shanghai Jiao tong University, Shanghai 200030, China
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Construction of an immune-related lncRNA signature as a novel prognosis biomarker for LUAD. Aging (Albany NY) 2021; 13:20684-20697. [PMID: 34438369 PMCID: PMC8436904 DOI: 10.18632/aging.203455] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 08/11/2021] [Indexed: 12/23/2022]
Abstract
The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.
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Huang Z, Wang S, Zhang HJ, Zhou YL, Shi JH. SMOX expression predicts the prognosis of non-small cell lung cancer. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1048. [PMID: 34422960 PMCID: PMC8339854 DOI: 10.21037/atm-21-998] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 05/21/2021] [Indexed: 12/16/2022]
Abstract
Background The development of non-small cell lung cancer (NSCLC) is very rapid, and the effect of its treatment is often closely related to the diagnosis time of the disease. Therefore, simple and convenient tumor biomarkers are helpful for the timely diagnosis and prevention of NSCLC. Methods Through univariate and multivariate Cox regression analyses, SMOX was determined as an independent prognostic factor of GSE42127, GSE41271, GSE68465, and TCGA datasets. Furthermore, western blot, reverse transcription-polymerase chain reaction (RT-PCR), and immunohistochemical analysis were performed to confirm the predictive efficiency of SMOX expression in NSCLC. Results Patients were divided into high and low expression groups according to the median value of SMOX expression, and Kaplan-Meier curves of multiple datasets indicated that patients with low SMOX expression had a better survival rate. According to the analysis of immune infiltration, the immune microenvironment, and immune checkpoints, SMOX expression of the high and low groups showed differences in immunity in NSCLC. By comparing cancer and adjacent tissues using western blot analysis, RT-PCR and immunohistochemical analysis, we found that SMOX was highly expressed in tumor tissues and had low expression in adjacent tissues. Simultaneously, the Kaplan-Meier curve suggested that among the 155 NSCLC patients, those with low SMOX expression had better survival. Conclusions SMOX can be used as an effective predictive target for NSCLC.
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Affiliation(s)
- Zhanghao Huang
- Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Nantong, China.,Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China.,Medical College of Nantong University, Nantong, China
| | - Shuo Wang
- Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Nantong, China.,Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China.,Medical College of Nantong University, Nantong, China
| | - Hai-Jian Zhang
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China
| | - You Lang Zhou
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China
| | - Jia-Hai Shi
- Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Nantong, China.,Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China
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