1
|
Chen K, Dai P, Gu L. Building endoplasmic reticulum stress-related LncRNAs signatures of lung adenocarcinoma. J Gene Med 2024; 26:e3731. [PMID: 39146558 DOI: 10.1002/jgm.3731] [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: 03/21/2024] [Revised: 06/29/2024] [Accepted: 07/29/2024] [Indexed: 08/17/2024] Open
Abstract
BACKGROUND Endoplasmic reticulum stress (ERS) could be a strategy for treating malignant tumors. Moreover, long noncoding RNAs (lncRNAs) can promote tumorigenesis and progression, and forecast the prognosis of cancers. Nevertheless, the prognostic value of ERS-related lncRNAs has not been reported in lung adenocarcinoma (LUAD). METHODS The messenger RNA (mRNA), microRNA (miRNA) and lncRNA expression data related to LUAD were obtained in public databases (TCGA and GEO databases). Prognostic ERS-related differentially expressed lncRNAs (ERS-DELs) were obtained and used to build an ERS-related model by Cox regression analysis. Moreover, we further screened independent prognostic elements and built a nomogram. Furthermore, enrichment analysis of genes was conducted to investigate the functions. A lncRNA-miRNA-mRNA network was built to explore mechanism of lncRNAs. Finally, qRT-PCR was utilized to examine the expression levels of lncRNAs. RESULTS 30 ERS-DELs were identified, and an ERS-related signature was built based on AF131215.2, LINC00472, LINC01352, RP1-78O14.1, RP11-253E3.3, RP11-98D18.9, and SNHG12. Gene set enrichment analysis indicated that genes in the high-risk group were chiefly focused on the regulation of mRNA binding, and genes in the low-risk group were significantly focused on protein localization to cilia. A lncRNA-miRNA-mRNA network, containing 7 signature lncRNAs, 23 miRNAs, and 128 mRNAs, was also established. Eventually, quantitative real-time polymerase chain reaction was used to confirm that seven prognostic lncRNAs had a consistent expression with the analysis. CONCLUSIONS An ERS-related signature containing seven prognostic lncRNAs was built, which offered new thinking concerning the role of ERS-related lncRNAs in LUAD.
Collapse
Affiliation(s)
- Kai Chen
- The Department of Cardiovascular and Thoracic Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Peiling Dai
- The Department of Radiotherapy, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lizhong Gu
- The Department of Cardiovascular and Thoracic Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| |
Collapse
|
2
|
Xie B, Wu T, Hong D, Lu Z. Comprehensive landscape of junctional genes and their association with overall survival of patients with lung adenocarcinoma. Front Mol Biosci 2024; 11:1380384. [PMID: 38841188 PMCID: PMC11150628 DOI: 10.3389/fmolb.2024.1380384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/22/2024] [Indexed: 06/07/2024] Open
Abstract
Objectives Junctional proteins are involved in tumorigenesis. Therefore, this study aimed to investigate the association between junctional genes and the prognosis of patients with lung adenocarcinoma (LUAD). Methods Transcriptome, mutation, and clinical data were retrieved from The Cancer Genome Atlas (TCGA). "Limma" was used to screen differentially expressed genes. Moreover, Kaplan-Meier survival analysis was used to identify junctional genes associated with LUAD prognosis. The junctional gene-related risk score (JGRS) was generated based on multivariate Cox regression analysis. An overall survival (OS) prediction model combining the JGRS and clinicopathological properties was proposed using a nomogram and further validated in the Gene Expression Omnibus (GEO) LUAD cohort. Results To our knowledge, this study is the first to demonstrate the correlation between the mRNA levels of 14 junctional genes (CDH15, CDH17, CDH24, CLDN6, CLDN12, CLDN18, CTNND2, DSG2, ITGA2, ITGA8, ITGA11, ITGAL, ITGB4, and PKP3) and clinical outcomes of patients with LUAD. The JGRS was generated based on these 14 genes, and a higher JGRS was associated with older age, higher stage levels, and lower immune scores. Thus, a prognostic prediction nomogram was proposed based on the JGRS. Internal and external validation showed the good performance of the prediction model. Mechanistically, JGRS was associated with cell proliferation and immune regulatory pathways. Mutational analysis revealed that more somatic mutations occurred in the high-JGRS group than in the low-JGRS group. Conclusion The association between junctional genes and OS in patients with LUAD demonstrated by our "TCGA filtrating and GEO validating" model revealed a new function of junctional genes.
Collapse
Affiliation(s)
- Bin Xie
- School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China
| | - Ting Wu
- School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China
| | - Duiguo Hong
- Jincheng Community Health Service Center, Hangzhou, China
| | - Zhe Lu
- Key Laboratory of Aging and Cancer Biology of Zhejiang Province, Hangzhou Normal University, Hangzhou, China
- School of Basic Medicine, Hangzhou Normal University, Hangzhou, China
| |
Collapse
|
3
|
Sun C, Cheng X, Xu J, Chen H, Tao J, Dong Y, Wei S, Chen R, Meng X, Ma Y, Tian H, Guo X, Bi S, Zhang C, Kang J, Zhang M, Lv H, Shang Z, Lv W, Zhang R, Jiang Y. A review of disease risk prediction methods and applications in the omics era. Proteomics 2024:e2300359. [PMID: 38522029 DOI: 10.1002/pmic.202300359] [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: 09/15/2023] [Revised: 03/08/2024] [Accepted: 03/12/2024] [Indexed: 03/25/2024]
Abstract
Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.
Collapse
Affiliation(s)
- Chen Sun
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Xiangshu Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Jing Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Haiyan Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Junxian Tao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Yu Dong
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Siyu Wei
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Rui Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xin Meng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yingnan Ma
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Hongsheng Tian
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xuying Guo
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Shuo Bi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Chen Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jingxuan Kang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Mingming Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Hongchao Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Zhenwei Shang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Wenhua Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Ruijie Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yongshuai Jiang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| |
Collapse
|
4
|
Jiang W, Zhu X, Bo J, Ma J. Screening of Immune-related lncRNAs in Lung Adenocarcinoma and Establishing a Survival Prognostic Risk Prediction Model. Comb Chem High Throughput Screen 2024; 27:1175-1190. [PMID: 37711103 DOI: 10.2174/1386207326666230913120523] [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: 03/27/2023] [Revised: 06/12/2023] [Accepted: 07/26/2023] [Indexed: 09/16/2023]
Abstract
OBJECTIVE This study aimed to improve lung adenocarcinoma (LUAD) prognosis prediction based on a signature of immune-related long non-coding RNAs (lncRNAs). METHODS LUAD samples from the TCGA database were divided into the immunity_H group and the immunity_L group. Differentially expressed RNAs (DERs) between the two groups were identified. Optimized immune-related lncRNAs combination was obtained using LASSO Cox regression. A prognostic risk prediction (RS) model was built and further validated in the training and validation datasets. A network among lncRNAs in the RS model, their co-expressed DERs, and the related KEGG pathways were established. Critical lncRNAs were validated in LUAD tissue samples. RESULTS In total, 255 DERs were obtained, and 11 immune-related lncRNAs were significantly related to prognosis. Six lncRNAs were demonstrated as an optimal combination for building the RS model, including LINC00944, LINC00930, LINC00607, LINC00582, LINC00543, and LINC00319. The KM curve and ROC curve revealed the RS model to be a reliable indicator for LUAD prognosis. LINC00944 and LINC00582 showed a co-expression relationship with the MS4A1. LINC00944, LINC00582, and MS4A1 were successfully validated in LUAD samples. CONCLUSION We have established a promising LUAD patient survival prediction model based on six immune-related lncRNAs. For LUAD patients, this prognostic model could guide personalized treatment.
Collapse
Affiliation(s)
- Wenxia Jiang
- School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China
| | - Xuyou Zhu
- Department of Pathology, Tongji Hospital of Tongji University, Shanghai, 20065, China
| | - Jiaqi Bo
- Department of Pathology, Tongji Hospital of Tongji University, Shanghai, 20065, China
| | - Jun Ma
- Department of Nephrology, Jing'an District Center Hospital of Shanghai, Fudan University, Shanghai, 200040, China
| |
Collapse
|
5
|
Xiang C, Zhang M, Shang Z, Chen S, Zhao J, Ding B, Jiang D, Zhu Q, Teng H, Zhu L, Shao J, Zhao R, Ye M, Yu Y, Han Y. Single-cell profiling reveals the trajectory of FOLR2-expressing tumor-associated macrophages to regulatory T cells in the progression of lung adenocarcinoma. Cell Death Dis 2023; 14:493. [PMID: 37532692 PMCID: PMC10397223 DOI: 10.1038/s41419-023-06021-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 07/17/2023] [Accepted: 07/25/2023] [Indexed: 08/04/2023]
Abstract
An immunosuppressive microenvironment enriched with regulatory CD4+ T lymphocytes (Tregs) facilitates the progression of lung adenocarcinoma (LUAD). This study aims to investigate the cellular mechanism underlying the formation of the immunosuppressive microenvironment in LUAD. LUAD samples (n = 12) and normal lung samples (n = 3) were obtained from patients with different pathological stages of LUAD. Single-cell RNA sequencing was performed to classify cellular components and analyze the transcriptomes, including transcription factors/targets and chemokine ligands/receptors, followed by bioinformatics study such as pseudotime analysis. Myeloid cells and T cells were the most abundant cell types in tumors and normal lung tissues, while tumor-associated macrophage-folate receptor 2 (TAM-FOLR2) and CD4+ nuclear receptor subfamily 4 group A member 3 (NR4A3) exhibited sharp increases in invasive adenocarcinoma (IA). The enrichment of TAM-FOLR2 in IA might result from alveolar resident macrophage-resistin (ARM-RETN) transformation and recruitment of dendritic cells (DCs) and other TAMs, as evidenced by temporal trajectories and differential expression profiles of chemokine ligands/receptors versus those in the early stages of tumors. High expression of CCL17/19/22 was observed in IA as well as in DCs, along with the strong interaction of TAM-FOLR2 with DCs. The results of pseudotime analysis suggested that CD4+NR4A3 might potentially convert to CD4+FOXP3, further supported by the high expression of NR4A3 target genes in CD4+FOXP3 cells. This study provides a single-cell transcriptome atlas from preinvasive to invasive LUAD and reveals a potential ARM-RETN/TAM-FOLR2/DCs/CD4+NR4A3/CD4+FOXP3 trajectory in shaping the immune suppressive microenvironment along the pathogenesis of LUAD.
Collapse
Affiliation(s)
- Chan Xiang
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Min Zhang
- Novogene Co., Ltd., Beijing, 100015, China
| | - Zhanxian Shang
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Shengnan Chen
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Jikai Zhao
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Bowen Ding
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Dong Jiang
- Novogene Co., Ltd., Beijing, 100015, China
| | - Qian Zhu
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Haohua Teng
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Lei Zhu
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Jinchen Shao
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Ruiying Zhao
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Min Ye
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Yang Yu
- Novogene Co., Ltd., Beijing, 100015, China.
| | - Yuchen Han
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
| |
Collapse
|
6
|
He X, Su Y, Liu P, Chen C, Chen C, Guan H, Lv X, Guo W. Machine learning-based immune prognostic model and ceRNA network construction for lung adenocarcinoma. J Cancer Res Clin Oncol 2023; 149:7379-7392. [PMID: 36939925 DOI: 10.1007/s00432-023-04609-1] [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: 10/20/2022] [Accepted: 01/27/2023] [Indexed: 03/21/2023]
Abstract
PURPOSE Lung adenocarcinoma (LUAD) is a malignant tumor with a high lethality rate. Immunotherapy has become a breakthrough in cancer treatment and improves patient survival and prognosis. Therefore, it is necessary to find new immune-related markers. However, the current research on immune-related markers in LUAD is not sufficient. Therefore, there is a need to find new immune-related biomarkers to help treat LUAD patients. METHODS In this study, a bioinformatics approach combined with a machine learning approach screened reliable immune-related markers to construct a prognostic model to predict the overall survival (OS) of LUAD patients, thus promoting the clinical application of immunotherapy in LUAD. The experimental data were obtained from The Cancer Genome Atlas (TCGA) database, including 535 LUAD and 59 healthy control samples. Firstly, the Hub gene was screened using a bioinformatics approach combined with the Support Vector Machine Recursive Feature Elimination algorithm; then, a multifactorial Cox regression analysis by constructing an immune prognostic model for LUAD and a nomogram to predict the OS rate of LUAD patients. Finally, the regulatory mechanism of Hub genes in LUAD was analyzed by ceRNA. RESULTS Five genes, ADM2, CDH17, DKK1, PTX3, and AC145343.1, were screened as potential immune-related genes in LUAD. Among them, ADM2 and AC145343.1 had a good prognosis in LUAD patients (HR < 1) and were novel markers. The remaining three genes screened were associated with poor prognosis in LUAD patients (HR > 1). In addition, the experimental results showed that patients in the low-risk group had better OS rates than those in the high-risk group (P < 0.001). CONCLUSION In this paper, we propose an immune prognostic model to predict OS rate in LUAD patients and show the correlation between five immune genes and the level of immune-related cell infiltration. It provides new markers and additional ideas for immunotherapy in patients with LUAD.
Collapse
Affiliation(s)
- Xiaoqian He
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Ying Su
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Pei Liu
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Cheng Chen
- College of Software, Xinjiang University, Urumqi, 830046, China.
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Haoqin Guan
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Xiaoyi Lv
- College of Software, Xinjiang University, Urumqi, 830046, China.
| | - Wenjia Guo
- Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, 830011, China.
| |
Collapse
|
7
|
Mao Y, Cai F, Jiang T, Zhu X. Identification Invasion-Related Long Non-Coding RNAs in Lung Adenocarcinoma and Analysis of Competitive Endogenous RNA Regulatory Networks. Int J Gen Med 2023; 16:1817-1831. [PMID: 37213476 PMCID: PMC10198273 DOI: 10.2147/ijgm.s407266] [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: 02/18/2023] [Accepted: 05/01/2023] [Indexed: 05/23/2023] Open
Abstract
Background Cell invasion plays a vital role in cancer development and progression. Aberrant expression of long non-coding RNAs (lncRNAs) is also critical in carcinogenesis. However, the prognostic value of invasion-related lncRNAs in lung adenocarcinoma (LUAD) remains unknown. Methods Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and microRNAs (DEmiRNAs) were between LUAD and control samples. Pearson correlation analyses were performed to screen for invasion-related DElncRNAs (DEIRLs). Univariate and multivariate Cox regression algorithms were applied to identify key genes and construct the risk score model, which was evaluated using receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA) was used to explore the underlying pathways of the risk model. Moreover, an invasion-related competitive endogenous RNA (ceRNA) regulatory network was constructed. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to detect the expression of prognostic lncRNAs in the LUAD and control samples. Results A total of 45 DElncRNAs were identified as DEIRLs. RP3-525N10.2, LINC00857, EP300-AS1, PDZRN3-AS1, and RP5-1102E8.3 were potential prognostic lncRNAs, the expression of which was verified by RT-qPCR in LUAD samples. Both the risk score model and nomogram used the prognostic lncRNAs. ROC curves showed the risk score model had moderate accuracy and the nomogram had high accuracy in predicting patient prognosis. GSEA results indicated that the risk score model was associated with many biological processes and pathways relevant to cell proliferation. A ceRNA regulatory network was constructed in which PDZRN3-miR-96-5p-CPEB1, EP300-AS1-miR-93-5p-CORO2B, and RP3-525N10.2-miR-130a-5p-GHR may be key invasion-related regulatory pathways in LUAD. Conclusion Our study identified five novel invasion-related prognostic lncRNAs (RP3-525N10.2, LINC00857, EP300-AS1, PDZRN3-AS1, and RP5-1102E8.3) and established an accurate model for predicting the prognosis of patients with LUAD. These findings enrich our understanding of the relationships between cell invasion, lncRNAs, and LUAD and may provide novel treatment directions.
Collapse
Affiliation(s)
- Yuze Mao
- Department of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People’s Republic of China
| | - Fangyu Cai
- Department of Thoracic Surgery, Beidahuang Industry Group General Hospital, Harbin, Heilongjiang, 150088, People’s Republic of China
| | - Tengjiao Jiang
- Department of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People’s Republic of China
| | - Xiaofeng Zhu
- Department of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People’s Republic of China
- Correspondence: Xiaofeng Zhu, Department of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People’s Republic of China, Tel +86-13845456700, Email
| |
Collapse
|
8
|
Zhao J, Li G, Zhao G, Wang W, Shen Z, Yang Y, Huang Y, Ye L. Prognostic signature of lipid metabolism associated LncRNAs predict prognosis and treatment of lung adenocarcinoma. Front Oncol 2022; 12:986367. [PMID: 36387240 PMCID: PMC9664164 DOI: 10.3389/fonc.2022.986367] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 10/17/2022] [Indexed: 07/25/2023] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) is the most predominant histological subtype of lung cancer. Abnormal lipid metabolism is closely related to the development of LUAD. LncRNAs are involved in the regulation of various lipid metabolism-related genes in various cancer cells including LUAD. Here, we aimed to identify lipid metabolism-related lncRNAs associated with LUAD prognosis and to propose a new prognostic signature. METHODS First, differentially expressed lncRNAs (DE-lncRNAs) from the TCGA-LUAD and the GSE31210 dataset were identified. Then the correlation analysis between DE-lncRNAs and lipid metabolism genes was performed to screen lipid metabolism-related lncRNAs. Cox regression analyses were performed in the training set to establish a prognostic model and the model was validated in the testing set and the validation set. Moreover, The role of this model in the underlying molecular mechanisms, immunotherapy, and chemotherapeutic drug sensitivity analysis was predicted by methods such as Gene Set Enrichment Analysis, immune infiltration, tumor mutational burden (TMB), neoantigen, Tumor Immune Dysfunction and Exclusion, chemosensitivity analysis between the high- and low-risk groups. The diagnostic ability of prognostic lncRNAs has also been validated. Finally, we validated the expression levels of selected prognostic lncRNAs by quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS The prognostic model was constructed based on four prognostic lncRNAs (LINC00857, EP300-AS1, TBX5-AS1, SNHG3) related to lipid metabolism. The receiver operating characteristic curve (ROC) and Kaplan Meier (KM) curves of the risk model showed their validity. The results of Gene Set Enrichment Analysis suggested that differentially expressed genes in high- and low-risk groups were mainly enriched in immune response and cell cycle. There statistical differences in TMB and neoantigen between high- and low-risk groups. Drug sensitivity analysis suggested that patients with low risk scores may have better chemotherapy outcomes. The results of qRT-PCR were suggesting that compared with the normal group, the expressions of EP300-AS1 and TBX5-AS1 were down-regulated in the tumor group, while the expressions of LINC00857 and SNHG3 were up-regulated. The four prognostic lncRNAs had good diagnostic capabilities, and the overall diagnostic model of the four prognostic lncRNAs was more effective. CONCLUSION A total of 4 prognostic lncRNAs related to lipid metabolism were obtained and an effective risk model was constructed.
Collapse
Affiliation(s)
- Jie Zhao
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| | - Guangjian Li
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| | - Guangqiang Zhao
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| | - Wei Wang
- Department of Thoracic Surgery, Taihe Hospital (Hubei University of Medicine), Shiyan, China
| | - Zhenghai Shen
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| | - Yantao Yang
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| | - Yunchao Huang
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| | - Lianhua Ye
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University (Yunnan Cancer Hospital), Kunming, China
| |
Collapse
|
9
|
Zhan X, Feng S, Zhou X, Liao W, Zhao B, Yang Q, Tan Q, Shen J. Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma. Front Genet 2022; 13:1047435. [PMID: 36386793 PMCID: PMC9640754 DOI: 10.3389/fgene.2022.1047435] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 10/17/2022] [Indexed: 11/30/2022] Open
Abstract
Background: Immunotherapy has been a promising approach option for lung cancer. Method: All the open-accessed data was obtained from the Cancer Genome Atlas (TCGA) database. All the analysis was conducted using the R software analysis. Results: Firstly, the genes differentially expressed in lung cancer immunotherapy responders and non-responders were identified. Then, the lung adenocarcinoma immunotherapy-related genes were determined by LASSO logistic regression and SVM-RFE, respectively. A total of 18 immunotherapy response-related genes were included in our investigation. Subsequently, we constructed the logistics score model. Patients with high logistics score had a better clinical effect on immunotherapy, with 63.2% of patients responding to immunotherapy, while only 12.1% of patients in the low logistics score group responded to immunotherapy. Moreover, we found that pathways related to immunotherapy were mainly enriched in metabolic pathways such as fatty acid metabolism, bile acid metabolism, oxidative phosphorylation, and carcinogenic pathways such as KRAS signaling. Logistics score was positively correlated with NK cells activated, Mast cells resting, Monocytes, Macrophages M2, dendritic cells resting, dendritic cells activated and eosinophils, while was negatively related to Tregs, macrophages M0, macrophages M1, and mast cells activated. In addition, ERVH48-1 was screened for single-cell exploration. The expression of ERVH48-1 increased in patients with distant metastasis, and ERVH48-1 was associated with pathways such as pancreas beta cells, spermatogenesis, G2M checkpoints and KRAS signaling. The result of quantitative real-time PCR showed that ERVH48-1 was upregulated in lung cancer cells. Conclusion: Our study developed an effective signature to predict the immunotherapy response of lung cancer patients.
Collapse
Affiliation(s)
- Xue Zhan
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Shihan Feng
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Xutao Zhou
- Department of Oncology, Jiulongpo Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Wei Liao
- Department of Oncology, Jiulongpo Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Bin Zhao
- Department of Oncology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Qian Yang
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Qi Tan
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Jian Shen
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
- *Correspondence: Jian Shen,
| |
Collapse
|
10
|
Wang Y, Chen X, Jiang F, Shen Y, Fang F, Li Q, Yang C, Dong Y, Shen X. A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity. Front Genet 2022; 13:939439. [PMID: 36147488 PMCID: PMC9485603 DOI: 10.3389/fgene.2022.939439] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Pyroptosis is a recently identified mode of programmed inflammatory cell death that has remarkable implications for cancer development. lncRNAs can be involved in cellular regulation through various pathways and play a critical role in gastric cancer (GC). However, pyroptosis -related lncRNAs (PRlncRNAs) have been rarely studied in GC. Methods: Pyroptosis-related gene were abstracted from the literature and GSEA Molecular Signatures data resource. PRlncRNAs were obtained using co-expression analysis. LASSO Cox regression assessment was employed to build a risk model. Kaplan-Meier (KM), univariate along with multivariate Cox regression analysis were adopted to verify the predictive efficiency of the risk model in terms of prognosis. qRT-PCR was adopted to validate the expression of PRlncRNAs in GC tissues. In addition, immune cell infiltration assessment and ESTIMATE score evaluation were adopted for assessing the relationship of the risk model with the tumor immune microenvironment (TME). Finally, immune checkpoint gene association analysis and chemotherapy drug sensitivity analysis were implemented to assess the worthiness of our risk model in immunotherapy and chemotherapy of GC. Results: We identified 3 key PRlncRNAs (PVT1, CYMP-AS1 and AC017076.1) and testified the difference of their expression levels in GC tumor tissues and neighboring non-malignant tissues (p < 0.05). PRlncRNAs risk model was able to successfully estimate the prognosis of GC patients, and lower rate of survival was seen in the high-GC risk group relative to the low-GC risk group (p < 0.001). Other digestive system tumors such as pancreatic cancer further validated our risk model. There was a dramatic difference in TMB level between high-GC and low-GC risk groups (p < 0.001). Immune cell infiltration analysis and ESTIMATE score evaluation demonstrated that the risk model can be adopted as an indicator of TME status. Besides, the expressions of immunodetection site genes in different risk groups were remarkably different (CTLA-4 (r = −0.14, p = 0.010), VISTA (r = 0.15, p = 0.005), and B7-H3 (r = 0.14, p = 0.009)). PRlncRNAs risk model was able to effectively establish a connection with the sensitivity of chemotherapeutic agents. Conclusion: The 3 PRlncRNAs identified in this study could be utilized to predict disease outcome in GC patients. It may also be a potential therapeutic target in GC therapy, including immunotherapy and chemotherapy.
Collapse
|
11
|
Liu C, Wang Y. Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs. Front Public Health 2022; 10:902445. [PMID: 35801241 PMCID: PMC9253426 DOI: 10.3389/fpubh.2022.902445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 05/25/2022] [Indexed: 12/24/2022] Open
Abstract
This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.
Collapse
|
12
|
Xue Q, Wang Y, Zheng Q, Chen L, Jin Y, Shen X, Li Y. Construction of a prognostic immune-related lncRNA model and identification of the immune microenvironment in middle- or advanced-stage lung squamous carcinoma patients. Heliyon 2022; 8:e09521. [PMID: 35663751 PMCID: PMC9157204 DOI: 10.1016/j.heliyon.2022.e09521] [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: 01/11/2022] [Revised: 03/09/2022] [Accepted: 05/18/2022] [Indexed: 11/29/2022] Open
Abstract
Background Methods Results Conclusion
Collapse
Affiliation(s)
- Qianqian Xue
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
| | - Yue Wang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
| | - Qiang Zheng
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
| | - Lijun Chen
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
| | - Yan Jin
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
| | - Xuxia Shen
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
| | - Yuan Li
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Thoracic Oncology, Fudan University, Shanghai, China
- Corresponding author.
| |
Collapse
|
13
|
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.
Collapse
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,
| |
Collapse
|
14
|
Dang R, Jin M, Nan J, Jiang X, He Z, Su F, Li D. A Novel Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Patients with Papillary Renal Cell Carcinoma. Int J Gen Med 2022; 15:207-222. [PMID: 35023959 PMCID: PMC8747765 DOI: 10.2147/ijgm.s341034] [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: 10/15/2021] [Accepted: 12/15/2021] [Indexed: 12/12/2022] Open
Abstract
Purpose Papillary renal cell carcinoma (PRCC) is a common renal cell carcinoma. Recent studies have reported that ferroptosis is involved in the occurrence and development of tumors. Long non-coding RNAs can be used as independent biomarkers for the diagnosis and prognosis of a variety of tumors. Methods Gene expression profile and clinical information of patients with PRCC were obtained from The Cancer Genome Atlas (TCGA) database. Lasso penalized Cox regression and univariate Cox regression analysis were utilized for model construction. The Kaplan–Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Immune cell infiltration and immune function were compared between the high-risk and low-risk groups. Chemotherapy sensitivity analysis was also performed. Results We constructed a prognostic signature consisting of 15 ferroptosis-related lncRNAs. The K-M curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the lncRNA signature was 0.930, exhibiting robust prognostic capacity. The high-risk group had a greater degree of immune cell infiltration than the low-risk group. Significant differences in inflammation promotion, parainflammation, and type I IFN response were noted between the low-risk and high-risk groups (p < 0.01). The expression levels of immune checkpoints including CD80, IDO1, and LAG3 were significantly higher in the high-risk group than in the low-risk group (p < 0.05). Chemotherapy sensitivity analysis showed that MNX1-AS1, ZFAS1, MIR4435-2HG, and ADAMTS9-AS1 were significantly correlated with the sensitivity of some chemotherapy drugs (p < 0.05). Conclusion We demonstrated that a ferroptosis-related lncRNA prognostic signature could be a novel biomarker for PRCC.
Collapse
Affiliation(s)
- Ruijie Dang
- Department of Oncology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Meiling Jin
- Department of Nephrology, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People's Republic of China
| | - Jingzhu Nan
- Department of Clinical Laboratory, the First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Xuege Jiang
- Respiratory Diseases Department, Second Medical Center of PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Zheng He
- Department of Clinical Laboratory, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Fang Su
- Aeronautical Physiological Identification Training Laboratory, Air Force Medical Center, PLA, Beijing, 100142, People's Republic of China
| | - Diangeng Li
- Department of Scientific Research, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People's Republic of China
| |
Collapse
|
15
|
Jin L, Chen C, Huang L, Sun Q, Bu L. Long noncoding RNA NR2F1-AS1 stimulates the tumorigenic behavior of non-small cell lung cancer cells by sponging miR-363-3p to increase SOX4. Open Med (Wars) 2022; 17:87-95. [PMID: 34993348 PMCID: PMC8678621 DOI: 10.1515/med-2021-0403] [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: 07/13/2021] [Revised: 11/10/2021] [Accepted: 11/12/2021] [Indexed: 11/23/2022] Open
Abstract
Long noncoding RNA (lncRNA), specifically the upregulation of lncRNA NR2F1 antisense RNA 1 (NR2F1-AS1), has been involved in the progression of non-small cell lung cancer (NSCLC), but the mechanisms that underlie this remain unclear. In this study, the expression of NR2F1-AS1, miR-363-3p, and SOX4 was assessed in NSCLC cells. A loss-of-function assay was used to measure the tumorigenicity of NSCLC cells. The glycolysis and glutamine metabolism of NSCLC cells was also measured via extracellular acidification rate, consumption of glucose and glutamine, and production of lactate and ATP. The relationships among NR2F1-AS1, miR-363-3p, and SOX4 were detected via dual-luciferase reporter assay. HK-2, GLS1, and SOX4 levels were also analyzed. We found that both NSCLC tissues and cells had higher levels of NR2F1-AS1. Silencing of NR2F1-AS1 inhibited the tumorigenicity of cells in vitro and reduced the glycolysis and glutamine metabolism of NSCLC cells. Regarding its mechanism, NR2F1-AS1 positively regulated the SOX4 level by sponging miR-363-3p. Furthermore, miR-363-3p inhibition or SOX4 overexpression reversed the repressing role of sh-NR2F1-AS1 in the tumorigenicity of NSCLC cells. In summary, NR2F1-AS1 promotes the tumorigenicity of NSCLC cells by regulating miR-363-3p/SOX4.
Collapse
Affiliation(s)
- Luming Jin
- Department of Thoracic Surgery, Xiamen University Institute of Chest and Lung Disease, Xiang'an Hospital of Xiamen University, Xiamen, China
| | - Chaoyang Chen
- Department of Thoracic Surgery, Xiamen University Institute of Chest and Lung Disease, Xiang'an Hospital of Xiamen University, Xiamen, China
| | - Lipeng Huang
- Department of Thoracic Surgery, Xiamen University Institute of Chest and Lung Disease, Xiang'an Hospital of Xiamen University, Xiamen, China
| | - Qingyu Sun
- Department of Thoracic Surgery, Xiamen University Institute of Chest and Lung Disease, Xiang'an Hospital of Xiamen University, Xiamen, China
| | - Liang Bu
- Department of Thoracic Surgery, Xiamen University Institute of Chest and Lung Disease, Xiang'an Hospital of Xiamen University, Xiamen, China
| |
Collapse
|
16
|
Chen H, Hu Z, Sang M, Ni S, Lin Y, Wu C, Mu Y, Liu K, Wu S, Li N, Xu G. Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma. Front Genet 2021; 12:767694. [PMID: 34956321 PMCID: PMC8692741 DOI: 10.3389/fgene.2021.767694] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/26/2021] [Indexed: 12/25/2022] Open
Abstract
Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature on the basis of long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of patients with LUAD. We selected ARlncRNAs associated with prognosis to construct a model and divided each sample into different groups on the basis of risk score. The ARlncRNA signature could be recognized as an independent prognostic factor for patients with LUAD, and patients in the low-risk group had a greater survival advantage. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden. Low-risk patients had a higher PD-1, CTLA-4, and HAVCR2 expression and had a better efficacy of immune checkpoint inhibitors, including PD-1/CTLA-4 inhibitor. A reliable signature on the basis of ARlncRNAs was constructed to explore the TIME and prognosis of patients with LUAD, which could provide valuable information for individualized LUAD treatment.
Collapse
Affiliation(s)
- Hang Chen
- Medical School, Ningbo University, Ningbo, China
| | - Zeyang Hu
- Medical School, 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
| | - Yao Lin
- Medical School, Ningbo University, Ningbo, China
| | - Chengfang Wu
- Medical School, Ningbo University, Ningbo, China
| | - Yinyu Mu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Kaitai Liu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Shibo Wu
- Department of Cardiothoracic Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, China
| | - Ni Li
- 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
| |
Collapse
|
17
|
Xu S, Tang L, Liu Z, Luo C, Cheng Q. Hypoxia-Related lncRNA Correlates With Prognosis and Immune Microenvironment in Lower-Grade Glioma. Front Immunol 2021; 12:731048. [PMID: 34659218 PMCID: PMC8514865 DOI: 10.3389/fimmu.2021.731048] [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: 06/26/2021] [Accepted: 09/09/2021] [Indexed: 01/12/2023] Open
Abstract
Background Hypoxia-related genes are demonstrated to correlate with the prognosis of various cancers. However, the role of hypoxia-related long non-coding RNAs (HRLs) in lower-grade glioma (LGG) remains unclear. Methods A total of 700 LGG samples were extracted from TCGA and CGGA databases. Pearson correlation analysis was used to identify HRLs. Lasso analysis was adopted to construct the HRL signature. TIDE algorithm was used to predict responses to immune checkpoint inhibitors. Cell proliferation was estimated by cell counting kit-8 assay, colony formation assay, and EdU assay. Results We identified 340 HRLs and constructed a novel risk signature composed of 19 HRLs. The risk score exhibited potent value in predicting the prognosis of LGG patients and was significantly associated with the prognosis of LGG patients. Moreover, HRL signature could distinguish patients with similar expression levels of immune checkpoints and might predict the efficacy of immune checkpoint inhibitors. Additionally, hypoxia-related pathways and immune pathways were enriched in high-risk group, and high risk score indicated low tumor purity and high immune infiltration. Two major HRLs, LINC00941 and BASP1-AS1, could significantly affect the proliferation of glioma cells. Conclusions Our study constructed a novel HRL signature that could predict the prognosis and immunotherapy response of LGG patients. HRLs could be novel biomarkers to predict the prognosis of LGG patients and potential targets for LGG treatment.
Collapse
Affiliation(s)
- Shengchao Xu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Tang
- Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Chengke Luo
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| |
Collapse
|
18
|
Man G, Duan A, Liu W, Cheng J, Liu Y, Song J, Zhou H, Shen K. Circular RNA-Related CeRNA Network and Prognostic Signature for Patients with Osteosarcoma. Cancer Manag Res 2021; 13:7527-7541. [PMID: 34629900 PMCID: PMC8494289 DOI: 10.2147/cmar.s328559] [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: 07/09/2021] [Accepted: 09/26/2021] [Indexed: 12/21/2022] Open
Abstract
Introduction Osteosarcoma (OSA) is characterized by its relatively high morbidity in children and adolescents. Patients usually have advanced disease at the time of diagnosis, resulting in poor outcomes. This study focused on building a circular RNA-based ceRNA network to develop a reliable model for OSA risk prediction. Methods We used the Gene Expression Omnibus (GEO) datasets to explore the expression patterns of circRNA, miRNA, and mRNA in OSA. The prognostic value of circRNA host genes was assessed with data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database using Kaplan–Meier survival analysis. We established a circRNA-related ceRNA network and annotated its biological functions. Next, we developed a prognostic risk signature based on mRNAs extracted from the ceRNA network. We also developed a prognostic model and constructed a nomogram to enhance the prediction of OSA prognosis. Results We identified 166 DEcircRNAs, 233 DEmiRNAs, and 1317 DEmRNAs and used them to create a circRNA-related ceRNA network. We then established a prognostic risk model consisting of four genes (MLLT11, TNFRSF11B, SLC7A7, and PARVA). Moreover, we found that inhibition of MLLT11 and SLC7A7 blocked OSA cell proliferation and migration in in vitro experiments. Conclusion Our study identifies crucial prognostic genes and provides a circRNA-related ceRNA network for OSA, which will contribute to the elucidation of the molecular mechanisms underlying the oncogenesis and development of OSA.
Collapse
Affiliation(s)
- Gu Man
- Department of Orthopedics, Nanjing Lishui District Traditional Chinese Medicine Hospital, Nanjing, Jiangsu, People's Republic of China
| | - Ao Duan
- Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Wanshun Liu
- Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Jiangqi Cheng
- Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Yu Liu
- Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Jiahang Song
- Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Haisen Zhou
- Department of Pathology, Nanjing Lishui District Traditional Chinese Medicine Hospital, Nanjing, Jiangsu, People's Republic of China
| | - Kai Shen
- Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| |
Collapse
|
19
|
Qi X, Chen G, Chen Z, Li J, Chen W, Lin J, Lin L. Construction of a Novel Lung Adenocarcinoma Immune-Related lncRNA Pair Signature. Int J Gen Med 2021; 14:4279-4289. [PMID: 34421308 PMCID: PMC8371455 DOI: 10.2147/ijgm.s325240] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 07/29/2021] [Indexed: 12/22/2022] Open
Abstract
Background A growing number of studies have demonstrated that immune-related long noncoding ribonucleic acids (irlncRNAs) are potential prognostic factors for lung adenocarcinoma. Two-gene combination patterns could improve the sensitivity of prognostic models, providing us a novel signature construction concept that we applied to lung adenocarcinoma. Methods Gene expression and clinical data were downloaded from the Lung Adenocarcinoma project of The Cancer Genome Atlas (TCGA) database. We applied a co-expression analysis with immune genes obtained from the ImmPort database to recognize irlncRNA. The matrix of irlncRNA pairs was established by a cyclic comparison of each lncRNA pair expression level. Univariate and multivariate Cox regressions and Lasso penalized regression analysis were applied to construct the risk model. Patients with lung adenocarcinoma were divided into high- and low-risk groups, according to the Akaike Information Criterion (AIC) values of the receiver operating characteristic (ROC) curve. Then, we evaluated our signature under various clinical settings: clinical-pathological characteristics, tumor-infiltrating immune cells, checkpoint-related biomarkers, targeted therapy, and chemotherapy. Results Based on the 239 differently expressed irlncRNAs, we constructed an 11-irlncRNA pair signature. The area under the curve (AUC) of the ROC curve for the signature to predict the 4-year survival rate was 0.819, and the cut-off point was recognized as 1.003. Subsequent analysis showed that our signature can effectively distinguish unfavorable survival outcomes, prognostic clinic-pathological characteristics, and specify tumor infiltration status. Highly expressed immune checkpoint-related genes, as well as higher chemosensitivity, were correlated to the low-risk group. Conclusion We constructed a novel lung adenocarcinoma irlncRNA signature with promising prognostic value using the TCGA database, based on paired irlncRNAs and not relying on lncRNAs special expression levels.
Collapse
Affiliation(s)
- Xiangjun Qi
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Guoming Chen
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Zhuangzhong Chen
- Department of Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Jing Li
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.,Department of Oncology, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, People's Republic of China
| | - Wenmin Chen
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Jietao Lin
- Department of Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Lizhu Lin
- Department of Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.,Cancer Project Team of China Center for Evidence Based Traditional Chinese Medicine, Guangzhou, People's Republic of China
| |
Collapse
|