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Identification of prognostic immune-related lncRNA signature predicting the overall survival for colorectal cancer. Sci Rep 2023; 13:1333. [PMID: 36693898 PMCID: PMC9873726 DOI: 10.1038/s41598-023-28305-9] [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: 08/13/2022] [Accepted: 01/17/2023] [Indexed: 01/25/2023] Open
Abstract
Long non-coding RNA (lncRNA) is an important regulator of gene expression and serves a fundamental role in immune regulation. The present study aimed to develop a novel immune-related lncRNA signature to assess the prognosis of patients with colorectal cancer (CRC). Transcriptome data and clinical information of patients with CRC were downloaded from The Cancer Genome Atlas (TCGA) and UCSC Xena platforms. Immune-related mRNAs were extracted from the Molecular Signatures Database (MSigDB), and the immune-related lncRNAs were identified based on correlation analysis. Then, univariate, Lasso and multivariate Cox regression were applied to construct an immune-related lncRNA signature, and CRC patients were divided into high- and low-risk groups according to the median risk score. Finally, we evaluated the signature from the perspectives of clinical outcome, clinicopathological parameters, tumor-infiltrating immune cells (TIICs), immune status, tumor mutation burden (TMB) and immunotherapy responsiveness. In total, 272 immune-related lncRNAs were identified, five of which were applied to construct an immune-related lncRNA signature. The signature divided patients with CRC into low- and high-risk groups, the prognosis of patients in the high-risk group were significantly poorer than those in low-risk group, and the results were further confirmed in external validation cohort. Furthermore, the high-risk group showed aggressive clinicopathological characteristics, specific TIIC and immune function status, and low sensitivity to immunotherapy. The immune-related lncRNA signature could be exploited as a promising biomarker for predicting the prognosis and immune status of patients with CRC.
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Ma B, Cao L, Li Y. A novel 10-gene immune-related lncRNA signature model for the prognosis of colorectal cancer. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:9743-9760. [PMID: 34814366 DOI: 10.3934/mbe.2021477] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND The tumor immune microenvironment of colorectal cancer (CRC) affects tumor development, prognosis and immunotherapy strategies. Recently, immune-related lncRNA were shown to play vital roles in the tumor immune microenvironment. The objective of this study was to identify lncRNAs involved in the immune response, tumorigenesis and progression of CRC and to establish an immune-related lncRNA signature for predicting the prognosis of CRC. METHODS We used data retrieved from the cancer genome atlas (TCGA) dataset to construct a 10-gene immune-related lncRNA pair (IRLP) signature model using a method based on the ranking and comparison of paired gene expression in CRC. The clinical prognosis, immune checkpoints and lncRNA-protein networks were analyzed to evaluate the signature. RESULTS The signature was closely associated with overall survival of CRC patients (p < 0.001 in both of the training and validating cohorts) and the 3-year AUC values for the training and validating cohorts were 0.884 and 0.739, respectively. And, there were positive correlations between the signature and age (p = 0.048), clinical stage (p < 0.01), T stage (p < 0.01), N stage (p < 0.001) and M stage (p < 0.01). In addition, the signature model appeared to be highly relevant to some checkpoints, including CD160, TNFSF15, HHLA2, IDO2 and KIR3DL1. Further, molecular functional analysis and lncRNA-protein networks were applied to understand the molecular mechanisms underlying the carcinogenic effect and progression. CONCLUSION The 10-gene IRLP signature model is an independent prognostic factor for CRC patient and can be utilized for the development of immunotherapy.
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Affiliation(s)
- Bin Ma
- Department of Colorectal Surgery, Liaoning Cancer Hospital & Institute (Cancer Hospital of China Medical University), Shenyang, China
| | - Lianqun Cao
- Department of Colorectal Surgery, Liaoning Cancer Hospital & Institute (Cancer Hospital of China Medical University), Shenyang, China
| | - Yongmin Li
- Department of Colorectal Surgery, Liaoning Cancer Hospital & Institute (Cancer Hospital of China Medical University), Shenyang, China
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Ma C, Zhang X, Zhao X, Zhang N, Zhou S, Zhang Y, Li P. Predicting the Survival and Immune Landscape of Colorectal Cancer Patients Using an Immune-Related lncRNA Pair Model. Front Genet 2021; 12:690530. [PMID: 34552614 PMCID: PMC8451271 DOI: 10.3389/fgene.2021.690530] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/29/2021] [Indexed: 12/12/2022] Open
Abstract
Background Accumulating evidence has demonstrated that immune-related long non-coding ribonucleic acids (irlncRNAs) can be used as prognostic indicators of overall survival (OS) in patients with colorectal cancer (CRC). Our aim in this research, therefore, was to construct a risk model using irlncRNA pairs with no requirement for a specific expression level, in hope of reliably predicting the prognosis and immune landscape of CRC patients. Methods Clinical and transcriptome profiling data of CRC patients downloaded from the Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed (DE) irlncRNAs. The irlncRNA pairs significantly correlated with the prognosis of patients were screened out by univariable Cox regression analysis and a prognostic model was constructed by Lasso and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was then plotted, with the area under the curve calculated to confirm the reliability of the model. Based on the optimal cutoff value, CRC patients in the high- or low-risk groups were distinguished, laying the ground for evaluating the risk model from the following perspectives: survival, clinicopathological traits, tumor-infiltrating immune cells (TIICs), antitumor drug efficacy, kinase inhibitor efficacy, and molecules related to immune checkpoints. Results A prognostic model consisting of 15 irlncRNA pairs was constructed, which was found to have a high correlation with patient prognosis in a cohort from the TCGA (p < 0.001, HR = 1.089, 95% CI [1.067-1.112]). According to both univariate and multivariate Cox analyses, this model could be used as an independent prognostic indicator in the TCGA cohort (p < 0.001). Effective differentiation between high- and low-risk patients was also accomplished, on the basis of aggressive clinicopathological characteristics, sensitivity to antitumor drugs, and kinase inhibitors, the tumor immune infiltration status, and the expression levels of specific molecules related to immune checkpoints. Conclusion The prognostic model established with irlncRNA pairs is a promising indicator for prognosis prediction in CRC patients.
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Affiliation(s)
- Chao Ma
- Medical School of Chinese PLA, Beijing, China.,Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xin Zhang
- State Key Laboratory of Proteomics Beijing Proteome Research Center National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China
| | - Xudong Zhao
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Nan Zhang
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Sixin Zhou
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yonghui Zhang
- Medical School of Chinese PLA, Beijing, China.,Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Peiyu Li
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
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Peng Y, Xu C, Wen J, Zhang Y, Wang M, Liu X, Zhao K, Wang Z, Liu Y, Zhang T. Fatty Acid Metabolism-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Patients With Colorectal Cancer. Front Oncol 2021; 11:704038. [PMID: 34458145 PMCID: PMC8386021 DOI: 10.3389/fonc.2021.704038] [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: 05/01/2021] [Accepted: 07/22/2021] [Indexed: 12/22/2022] Open
Abstract
Abnormal metabolism, including abnormal fatty acid metabolism, is an emerging hallmark of cancer. The current study sought to investigate the potential prognostic value of fatty acid metabolism-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC). To this end, we obtained the gene expression data and clinical data of patients with CRC from The Cancer Genome Atlas (TCGA) database. Through gene set variation analysis (GSVA), we found that the fatty acid metabolism pathway was related to the clinical stage and prognosis of patients with CRC. After screening differentially expressed RNAs, we constructed a fatty acid metabolism-related competing endogenous RNA (ceRNA) network based on the miRTarBase, miRDB, TargetScan, and StarBase databases. Next, eight fatty acid metabolism-related lncRNAs included in the ceRNA network were identified to build a prognostic signature with Cox and least absolute shrinkage and selection operator (LASSO) regression analyses, and a nomogram was established based on the lncRNA signature and clinical variables. The signature and nomogram were further validated by Kaplan–Meier survival analysis, Cox regression analysis, calibration plots, receiver operating characteristic (ROC) curves, decision curve analysis (DCA). Besides, the TCGA internal and the quantitative real-time polymerase chain reaction (qRT-PCR) external cohorts were applied to successfully validate the robustness of the signature and nomogram. Finally, in vitro assays showed that knockdown of prognostic lncRNA TSPEAR-AS2 decreased the triglyceride (TG) content and the expressions of fatty acid synthase (FASN) and acetyl-CoA carboxylase 1 (ACC1) in CRC cells, which indicated the important role of lncRNA TSPEAR-AS2 in modulating fatty acid metabolism of CRC. The result of Oil Red O staining showed that the lipid content in lncRNA TSPEAR-AS2 high expression group was higher than that in lncRNA TSPEAR-AS2 low expression group. Our study may provide helpful information for fatty acid metabolism targeting therapies in CRC.
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Affiliation(s)
- Yurui Peng
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Chenxin Xu
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Jun Wen
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Yuanchuan Zhang
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Meng Wang
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Xiaoxiao Liu
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Kang Zhao
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Zheng Wang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanjun Liu
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
| | - Tongtong Zhang
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China.,Medical Research Center, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China
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Lu Y, Wang W, Liu Z, Ma J, Zhou X, Fu W. Long non-coding RNA profile study identifies a metabolism-related signature for colorectal cancer. Mol Med 2021; 27:83. [PMID: 34344319 PMCID: PMC8336290 DOI: 10.1186/s10020-021-00343-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 07/15/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Heterogeneity in colorectal cancer (CRC) patients provides novel strategies in clinical decision-making. Identifying distinctive subgroups in patients can improve the screening of CRC and reduce the cost of tests. Metabolism-related long non-coding RNA (lncRNA) can help detection of tumorigenesis and development for CRC patients. METHODS RNA sequencing and clinical data of CRC patients which extracted and integrated from public databases including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were set as training cohort and validation cohort. Metabolism-related genes were acquired from Kyoto Encyclopedia of Genes and Genomes (KEGG) and the metabolism-related lncRNAs were filtered using correlation analysis. The risk score was calculated based on lncRNAs with prognostic value and verified through survival curve, receiver operating characteristic (ROC) curve and risk curve. Prognostic factors of CRC patients were also analyzed. Nomogram was constructed based on the results of cox regression analyses. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). RESULTS The training cohort and the validation cohort enrolled 432 and 547 CRC patients respectively. A total of 23 metabolism-related lncRNAs with prognostic value were screened out and 10 of which were significantly differentially expressed between tumour and normal tissues. Finally, 8 lncRNAs were used to establish a risk score (DICER1-AS1, PCAT6, GAS5, PRR7-AS1, MCM3AP-AS1, GAS6-AS1, LINC01082 and ADIRF-AS1). Patients were divided into high-risk and low-risk groups according to the median of risk scores in training cohort and the survival curves indicated that the survival prognosis was significantly different. The area under curve (AUC) of the ROC curve in two cohorts were both greater than 0.6. The age, tumour stage and risk score were selected as independent factors and used to construct a nomogram to predict CRC patients' survival rate with the c-index of 0.806. The ssGSEA indicated that the risk score was associated with immune cells and functions. CONCLUSIONS Our systematic study established a metabolism-related lncRNA signature to predict outcomes of CRC patients which may contribute to individual prevention and treatment.
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Affiliation(s)
- Yongqu Lu
- Department of General Surgery, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China
| | - Wendong Wang
- Department of General Surgery, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China
| | - Zhenzhen Liu
- Department of General Surgery, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China
| | - Junren Ma
- Department of General Surgery, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China
| | - Xin Zhou
- Department of General Surgery, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
| | - Wei Fu
- Department of General Surgery, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
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Mao R, Yang F, Wang Z, Xu C, Liu Q, Liu Y, Zhang T. Clinical Significance of a Novel Tumor Progression-Associated Immune Signature in Colorectal Adenocarcinoma. Front Cell Dev Biol 2021; 9:625212. [PMID: 33732694 PMCID: PMC7959763 DOI: 10.3389/fcell.2021.625212] [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: 11/02/2020] [Accepted: 01/13/2021] [Indexed: 12/13/2022] Open
Abstract
Background Some colorectal adenocarcinoma (CRC) patients are susceptible to recurrence, and they rapidly progress to advanced cancer stages and have a poor prognosis. There is an urgent need for efficient screening criteria to identify patients who tend to relapse in order to treat them earlier and more systematically. Methods We identified two groups of patients with significantly different outcomes by unsupervised cluster analysis of GSE39582 based on 101 significantly differentially expressed immune genes. To develop an accurate and specific signature based on immune-related genes to predict the recurrence of CRC, a multivariate Cox risk regression model was constructed with a training cohort composed of 519 CRC samples. The model was then validated using 129, 292, and 446 samples in the real-time quantitative reverse transcription PCR (qRT-PCR), test, and validation cohorts, respectively. Results This classification system can also be used to predict the prognosis in clinical subgroups and patients with different mutation states. Four independent datasets, including qRT-PCR and The Cancer Genome Atlas (TCGA), demonstrated that they can also be used to accurately predict the overall survival of CRC patients. Further analysis suggested that high-risk patients were characterized by worse effects of chemotherapy and immunotherapy, as well as lower immune scores. Ultimately, the signature was identified as an independent prognostic factor. Conclusion The signature can accurately predict recurrence and overall survival in patients with CRC and may serve as a powerful prognostic tool to further optimize cancer immunotherapy.
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Affiliation(s)
- Rui Mao
- The Center of Gastrointestinal and Minimally Invasive Surgery, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Fan Yang
- Emergency Department, Peking University Third Hospital, School of Medicine, Peking University, Beijing, China
| | - Zheng Wang
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chenxin Xu
- The Center of Gastrointestinal and Minimally Invasive Surgery, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Qian Liu
- Department of Colorectal Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanjun Liu
- The Center of Gastrointestinal and Minimally Invasive Surgery, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China.,The Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, China
| | - Tongtong Zhang
- The Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, China.,Medical Research Center, The Third People's Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, The Second Chengdu Hospital Affiliated to Chongqing Medical University, Chengdu, China
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