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Yang T, Zhang R, Cui Z, Zheng B, Zhu X, Yang X, Huang Q. Glycolysis‑related lncRNA may be associated with prognosis and immune activity in grade II‑III glioma. Oncol Lett 2024; 27:238. [PMID: 38601183 PMCID: PMC11005085 DOI: 10.3892/ol.2024.14371] [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: 11/19/2023] [Accepted: 03/04/2024] [Indexed: 04/12/2024] Open
Abstract
Glucose metabolism, as a novel theory to explain tumor cell behavior, has been intensively studied in various tumors. The present study explored the long non-coding RNAs (lncRNAs) related to glycolysis in grade II-III glioma, aiming to provide a promising target for further research. Pearson correlation analysis was used to identify glycolysis-related lncRNAs. Univariate/multivariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator algorithm were applied to identify glycolysis-related lncRNAs to construct a prognosis prediction model. Subsequently, multi-dimensional evaluations were used to verify whether the risk model could predict the prognosis and survival rate of patients with grade II-III glioma. Finally, it was verified by functional experiments. The present study finally identified seven glycolysis-related lncRNAs (CRNDE, AC022034.1, RHOQ-AS1, AL159169.2, AL133215.2, AC007098.1 and LINC02587) to construct a prognosis prediction model. The present study further investigated the underlying immune microenvironment, somatic landscape and functional enrichment pathways. Additionally, individualized immunotherapeutic strategies and candidate compounds were identified to guide clinical treatment. The experimental results demonstrated that CRNDE could increase the proliferation of SHG-44 cells. In conclusion, a large sample of human grade II-III glioma in The Cancer Genome Atlas database was used to construct a risk model using glycolysis-related lncRNAs to predict the prognosis of patients with grade II-III glioma.
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Affiliation(s)
- Tao Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300000, P.R. China
- Department of Neurosurgery, Heji Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi 046000, P.R. China
| | - Ruiguang Zhang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300000, P.R. China
| | - Zhenfen Cui
- Department of Neurosurgery, Heji Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi 046000, P.R. China
| | - Bowen Zheng
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300000, P.R. China
| | - Xiaowei Zhu
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300000, P.R. China
| | - Xinyu Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300000, P.R. China
| | - Qiang Huang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300000, P.R. China
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Dong C, Guo Y, Wang P, Yin S, Ge X. Comprehensive analysis of disulfidptosis-related lncRNA features for prognosis and immune landscape prediction in colorectal cancer. Front Oncol 2023; 13:1287808. [PMID: 38213838 PMCID: PMC10783935 DOI: 10.3389/fonc.2023.1287808] [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: 09/02/2023] [Accepted: 11/27/2023] [Indexed: 01/13/2024] Open
Abstract
Disulfidptosis is a novel mechanism underlying actin-cytoskeleton-associated cell death, but its function in colorectal cancer (CRC) is still elusive. In this study, we investigated the potential role of Disulfidptosis-Related Long Non-Coding RNAs (DRLs) as prognostic indicators in CRC. Through transcriptome data from TCGA CRC cases, we identified 44 prognosis-correlated DRLs by Univariate Cox Regression Analysis and observed a differential expression pattern of these DRLs between CRC and normal tissues. Consensus clustering analysis based on DRL expression led to subgroup classification of CRC patients with distinct molecular fingerprints, accompanied by a superior survival outcome in cluster 2. We are encouraged to develop a score model incorporating 12 key DRLs to predict patient outcomes. Notably, this model displayed more reliable accuracy than other predictive indicators since DRLs are intimately related to tumor immune cell infiltration, suggesting a considerable potential of our DRL-score model for tumor therapy. Our data offered a valuable insight into the prognostic significance of DRLs in CRC and broke a new avenue for tumor prognosis prediction.
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Affiliation(s)
- Chengyuan Dong
- School of Medicine, Anhui University of Science and Technology, Huainan, China
| | - Yadong Guo
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ping Wang
- School of Medicine, Anhui University of Science and Technology, Huainan, China
| | - Shiqi Yin
- School of Medicine, Anhui University of Science and Technology, Huainan, China
| | - Xin Ge
- Department of Clinical Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
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Li C, Zhang K, Gong Y, Wu Q, Zhang Y, Dong Y, Li D, Wang Z. Based on cuproptosis-related lncRNAs, a novel prognostic signature for colon adenocarcinoma prognosis, immunotherapy, and chemotherapy response. Front Pharmacol 2023; 14:1200054. [PMID: 37377924 PMCID: PMC10291194 DOI: 10.3389/fphar.2023.1200054] [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: 04/04/2023] [Accepted: 05/26/2023] [Indexed: 06/29/2023] Open
Abstract
Introduction: Colon adenocarcinoma (COAD) is a special pathological subtype of colorectal cancer (CRC) with highly heterogeneous solid tumors with poor prognosis, and novel biomarkers are urgently required to guide its prognosis. Material and methods: RNA-Seq data of COAD were downloaded through The Cancer Genome Atlas (TCGA) database to determine cuproptosis-related lncRNAs (CRLs) using weighted gene co-expression network analysis (WGCNA). The scores of the pathways were calculated by single-sample gene set enrichment analysis (ssGSEA). CRLs that affected prognoses were determined via the univariate COX regression analysis to develop a prognostic model using multivariate COX regression analysis and LASSO regression analysis. The model was assessed by applying Kaplan-Meier (K-M) survival analysis and receiver operating characteristic curves and validated in GSE39582 and GSE17538. The tumor microenvironment (TME), single nucleotide variants (SNV), and immunotherapy response/chemotherapy sensitivity were assessed in high- and low-score subgroups. Finally, the construction of a nomogram was adopted to predict survival rates of COAD patients during years 1, 3, and 5. Results: We found that a high cuproptosis score reduced the survival rates of COAD significantly. A total of five CRLs affecting prognosis were identified, containing AC008494.3, EIF3J-DT, AC016027.1, AL731533.2, and ZEB1-AS1. The ROC curve showed that RiskScore could perform well in predicting the prognosis of COAD. Meanwhile, we found that RiskScore showed good ability in assessing immunotherapy and chemotherapy sensitivity. Finally, the nomogram and decision curves showed that RiskScore would be a powerful predictor for COAD. Conclusion: A novel prognostic model was constructed using CRLs in COAD, and the CRLs in the model were probably a potential therapeutic target. Based on this study, RiskScore was an independent predictor factor, immunotherapy response, and chemotherapy sensitivity for COAD, providing a new scientific basis for COAD prognosis management.
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Affiliation(s)
- Chong Li
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan, China
- Department of Oncology, Dazu Hospital of Chongqing Medical University, Chongqing, China
| | - Keqian Zhang
- Department of Oncology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Yuzhu Gong
- Department of Oncology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Qinan Wu
- Endocrinology Department, Dazu Hospital of Chongqing Medical University, Chongqing, China
| | - Yanyan Zhang
- Department of Oncology, Dazu Hospital of Chongqing Medical University, Chongqing, China
| | - Yan Dong
- Department of Oncology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Dejia Li
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan, China
| | - Zhe Wang
- Department of Oncology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
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Hu D, Messadi DV. Immune-Related Long Non-Coding RNA Signatures for Tongue Squamous Cell Carcinoma. Curr Oncol 2023; 30:4817-4832. [PMID: 37232821 DOI: 10.3390/curroncol30050363] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/27/2023] [Accepted: 05/04/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND Tongue squamous cell carcinoma (TSCC) represents one of the major subsets of head and neck cancer, which is characterized by unfavorable prognosis, frequent lymph node metastasis, and high mortality rate. The molecular events regulating tongue tumorigenesis remain elusive. In this study, we aimed to identify and evaluate immune-related long non-coding RNAs (lncRNAs) as prognostic biomarkers in TSCC. METHODS The lncRNA expression data for TSCC were obtained from The Cancer Genome Atlas (TCGA) and the immune-related genes were downloaded from the Immunology Database and Analysis Portal (ImmPort). Pearson correlation analysis was performed to identify immune-related lncRNAs. The TCGA TSCC patient cohort was randomly divided into training and testing cohorts. In the training cohort, univariate and multivariate Cox regression analyses were used to determining key immune-related lncRNAs, which were then validated through Cox regression analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) analysis in the testing cohort. RESULTS Six immune-related signature lncRNAs (MIR4713HG, AC104088.1, LINC00534, NAALADL2-AS2, AC083967.1, FNDC1-IT1) were found to have prognostic value in TSCC. Multivariate and univariate cox regression analyses showed that the risk score based on our six-lncRNA model, when compared to other clinicopathological factors (age, gender, stage, N, T), was an important indicator of survival rate. In addition, Kaplan-Meier survival analysis demonstrated significantly higher overall survival in the low-risk patient group than the high-risk patient group within both training and testing cohorts. The ROC analysis indicated that the AUCs for 5-year overall survival were 0.790, 0.691, and 0.721, respectively, for training, testing, and entire cohorts. Finally, PCA analysis demonstrated that the high-risk and low-risk patient groups presented significant deviation regarding their immune status. CONCLUSIONS A prognostic model based on six immune-related signature lncRNAs was established. This six-lncRNA prognostic model has clinical significance and may be helpful in the development of personalized immunotherapy strategies.
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Affiliation(s)
- Daniel Hu
- School of Dentistry, University of California, Los Angeles, CA 90095-1668, USA
| | - Diana V Messadi
- School of Dentistry, University of California, Los Angeles, CA 90095-1668, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095-1668, USA
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Li D, Qu G, Ling S, Sun Y, Cui Y, Yang Y, Cao X. A cuproptosis-related lncRNA signature to predict prognosis and immune microenvironment of colon adenocarcinoma. Sci Rep 2023; 13:6284. [PMID: 37072493 PMCID: PMC10113217 DOI: 10.1038/s41598-023-33557-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/14/2023] [Indexed: 05/03/2023] Open
Abstract
Cuproptosis is a novel cell death modality but its regulatory role in the colon cancer remains obscure. This study is committed to establishing a cuproptosis-related lncRNA (CRL) signature to forecast the prognosis for colon adenocarcinoma (COAD). The Cancer Genome Atlas (TCGA) samples were randomly divided into training and validation cohorts. LASSO-COX analysis was performed to construct a prognostic signature consisting of five CRLs (AC015712.2, ZEB1-AS1, SNHG26, AP001619.1, and ZKSCAN2-DT). We found the patients with high-risk scores suffered from poor prognosis in training cohort (p < 0.001) and validation cohort (p = 0.004). Nomogram was created based on the 5-CRL signature. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) demonstrated the nomogram performed well in 1‑, 3‑, and 5‑year overall survival (OS). Subsequently, we observed increased infiltration of multiple immune cells and upregulated expression of immune checkpoints and RNA methylation modification genes in high-risk patients. Additionally, gene set enrichment analysis (GSEA) revealed two tumor-related pathways, including MAPK and Wnt signaling pathways. Finally, we found AKT inhibitors, all-trans retinoic acid (ATRA), camptothecin, and thapsigargin had more sensitivity to antitumor therapy in high-risk patients. Collectively, this CRL signature is promising for the prognostic prediction and precise therapy of COAD.
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Affiliation(s)
- Dongming Li
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, 130021, Jilin, China
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, 100050, China
| | - Guangzhen Qu
- Department of Interventional Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, 100050, China
| | - Shen Ling
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, 100050, China
| | - Yuanlin Sun
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, 130021, Jilin, China
| | - Yingnan Cui
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, 130021, Jilin, China
| | - Yingchi Yang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, 100050, China.
| | - Xueyuan Cao
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, 130021, Jilin, China.
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Zheng J, Chen X, Huang B, Li J. A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma. Front Genet 2022; 13:921902. [PMID: 36147506 PMCID: PMC9485730 DOI: 10.3389/fgene.2022.921902] [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: 04/16/2022] [Accepted: 07/25/2022] [Indexed: 12/16/2022] Open
Abstract
Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model. Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR. Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group. Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.
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Affiliation(s)
- Jianqing Zheng
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
- Department of Radiation Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
| | - Xiaohui Chen
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Department of Thoracic Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
| | - Bifen Huang
- Department of Obstetrics and Gynecology, Quanzhou Medical College People’s Hospital Affiliated, Fuzhou, Fujian, China
| | - Jiancheng Li
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China
- *Correspondence: Jiancheng Li,
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Peña-Flores JA, Bermúdez M, Ramos-Payán R, Villegas-Mercado CE, Soto-Barreras U, Muela-Campos D, Álvarez-Ramírez A, Pérez-Aguirre B, Larrinua-Pacheco AD, López-Camarillo C, López-Gutiérrez JA, Garnica-Palazuelos J, Estrada-Macías ME, Cota-Quintero JL, Barraza-Gómez AA. Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma. Front Oncol 2022; 12:965628. [PMID: 35978835 PMCID: PMC9376329 DOI: 10.3389/fonc.2022.965628] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/01/2022] [Indexed: 12/12/2022] Open
Abstract
Head and neck squamous cell carcinoma (HNSCC) originates in the squamous cell lining the mucosal surfaces of the head and neck region, including the oral cavity, nasopharynx, tonsils, oropharynx, larynx, and hypopharynx. The heterogeneity, anatomical, and functional characteristics of the patient make the HNSCC a complex and difficult-to-treat disease, leading to a poor survival rate and a decreased quality of life due to the loss of important physiologic functions and aggressive surgical injury. Alteration of driver-oncogenic and tumor-suppressing lncRNAs has recently been recently in HNSCC to obtain possible biomarkers for diagnostic, prognostic, and therapeutic approaches. This review provides current knowledge about the implication of lncRNAs in drug resistance mechanisms in HNSCC. Chemotherapy resistance is a major therapeutic challenge in HNSCC in which lncRNAs are implicated. Lately, it has been shown that lncRNAs involved in autophagy induced by chemotherapy and epithelial–mesenchymal transition (EMT) can act as mechanisms of resistance to anticancer drugs. Conversely, lncRNAs involved in mesenchymal–epithelial transition (MET) are related to chemosensitivity and inhibition of invasiveness of drug-resistant cells. In this regard, long non-coding RNAs (lncRNAs) play a pivotal role in both processes and are important for cancer detection, progression, diagnosis, therapy response, and prognostic values. As the involvement of more lncRNAs is elucidated in chemoresistance mechanisms, an improvement in diagnostic and prognostic tools could promote an advance in targeted and specific therapies in precision oncology.
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Affiliation(s)
- José A. Peña-Flores
- Faculty of Odontology, Autonomous University of Chihuahua, Chihuahua, Mexico
| | - Mercedes Bermúdez
- Faculty of Odontology, Autonomous University of Chihuahua, Chihuahua, Mexico
- *Correspondence: Mercedes Bermúdez,
| | - Rosalío Ramos-Payán
- Faculty of Biological and Chemical Sciences, Autonomous University of Sinaloa, Culiacán, Mexico
| | | | - Uriel Soto-Barreras
- Faculty of Odontology, Autonomous University of Chihuahua, Chihuahua, Mexico
| | | | | | | | | | | | - Jorge A. López-Gutiérrez
- Faculty of Biological and Chemical Sciences, Autonomous University of Sinaloa, Culiacán, Mexico
- Faculty of Biology, Autonomous University of Sinaloa, Culiacán, Mexico
| | | | | | - Juan L. Cota-Quintero
- Faculty of Biology, Autonomous University of Sinaloa, Culiacán, Mexico
- Faculty of Odontology , Autonomous University of Sinaloa, Culiacán, Mexico
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Tai Q, Xue W, Li M, Zhuo S, Zhang H, Fang F, Zhang J. Survival Nomogram for Metastasis Colon Cancer Patients Based on SEER Database. Front Genet 2022; 13:832060. [PMID: 35222547 PMCID: PMC8864078 DOI: 10.3389/fgene.2022.832060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 01/13/2022] [Indexed: 12/20/2022] Open
Abstract
Introduction: A prediction model for the 1-, 3-, and 5-year survival rates of metastatic colon cancer (mCC) patients was developed by analyzing important risk factors for the prognosis of mCC patients based on the SEER database. Method: The characteristic of 10,946 patients diagnosed with mCC between 2010 and 2015 was obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. Univariate and multivariate cox for independent predictors of mCC prognosis were performed, and nomogram was constructed. The accuracy of the model was verified by calibration curves, ROC curves, and C-index, and the clinical utility of the model was analyzed using decision analysis curves. Result: Age, primary site, grade, surgery, and other eight factors were significantly associated with the prognosis of mCC patients, and these predictors were included in the construction of the nomogram. The C-index was 0.731 (95% CI 0.725–0.737) and 0.736 (95% CI 0.726–0.746) for the training cohort and the validation set, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.7 for both the training cohort and the validation set at 1, 3, and 5 years. Conclusion: The constructed prediction model had an excellent predictive accuracy, which will help clinical decision-making of mCC patients after surgery and individualized treatment.
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Affiliation(s)
- Qinwen Tai
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
- *Correspondence: Qinwen Tai, ; Jinhui Zhang,
| | - Wei Xue
- Department of Pharmacy, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, China
| | - Mengying Li
- The First College of Clinical Science, Anhui Medical University, Hefei, China
| | - Shuli Zhuo
- Medical College of Shaoguan University, Shaoguan, China
| | - Heng Zhang
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Fa Fang
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Jinhui Zhang
- Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China
- *Correspondence: Qinwen Tai, ; Jinhui Zhang,
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Comprehensive Analysis of Pyroptosis-Related Long Noncoding RNA Immune Infiltration and Prediction of Prognosis in Patients with Colon Cancer. JOURNAL OF ONCOLOGY 2022; 2022:2035808. [PMID: 35087586 PMCID: PMC8789477 DOI: 10.1155/2022/2035808] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/20/2021] [Indexed: 12/14/2022]
Abstract
Colon cancer (CC) is one of the most prevalent malignant tumours of the alimentary canal. It is unclear whether pyroptosis-related lncRNA expression is correlated with CC prognosis. We discovered 20 pyroptosis-related lncRNAs that were expressed differently in CC and normal colon tissues in our investigation. Based on differentially expressed genes (DEGs), we grouped all CC patients into two categories (Clusters 1 and 2). Cluster 1 was shown to be connected with a higher overall survival rate, upregulated expression of immune checkpoints, higher immunoscores, higher estimated scores, and immune cell infiltration. Using data from the Cancer Genome Atlas (TCGA), to create a multigene signature, the predictive significance of each lncRNA linked with pyroptosis for survival was assessed. A 9-lncRNA signature was established using the least absolute shrinkage and selection operator (LASSO) Cox regression method, and all CC patients in the TCGA cohort were classified into low-risk or high-risk groups. The low-risk CC patients had a much greater chance of survival than those in the high-risk group. The risk score is an independent prognostic indicator for predicting survival. In addition, risk characteristics are linked to immune characteristics. In summary, pyroptosis-related lncRNAs can be used to predict CC prognosis and participate in tumour immunity.
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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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