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Xie Y, Li J, Tao Q, Wu Y, Liu Z, Zeng C, Chen Y. Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis. J Cancer 2024; 15:3199-3214. [PMID: 38706895 PMCID: PMC11064262 DOI: 10.7150/jca.91687] [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: 10/30/2023] [Accepted: 03/16/2024] [Indexed: 05/07/2024] Open
Abstract
Backgrounds: Colorectal cancer (CRC) is a highly malignant gastrointestinal malignancy with a poor prognosis, which imposes a significant burden on patients and healthcare providers globally. Previous studies have established that genes related to glutamine metabolism play a crucial role in the development of CRC. However, no studies have yet explored the prognostic significance of these genes in CRC. Methods: CRC patient data were downloaded from The Cancer Genome Atlas (TCGA), while glutamine metabolism-related genes were obtained from the Molecular Signatures Database (MSigDB) database. Univariate COX regression analysis and LASSO Cox regression were utilized to identify 15 glutamine metabolism-related genes associated with CRC prognosis. The risk scores were calculated and stratified into high-risk and low-risk groups based on the median risk score. The model's efficacy was assessed using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curve analysis. Cox regression analysis was employed to determine the risk score as an independent prognostic factor for CRC. Differential immune cell infiltration between the high-risk and low-risk groups was assessed using the ssGSEA method. The clinical applicability of the model was validated by constructing nomograms based on age, gender, clinical staging, and risk scores. Immunohistochemistry (IHC) was used to detect the expression levels of core genes. Results: We identified 15 genes related to glutamine metabolism in CRC: NLGN1, RIMKLB, UCN, CALB1, SYT4, WNT3A, NRCAM, LRFN4, PHGDH, GRM1, CBLN1, NRG1, GLYATL1, CBLN2, and VWC2. Compared to the high-risk group, the low-risk group demonstrated longer overall survival (OS) for CRC. Clinical correlation analysis revealed a positive correlation between the risk score and the clinical stage and TNM stage of CRC. Immune correlation analysis indicated a predominance of Th2 cells in the low-risk group. The nomogram exhibited excellent discriminatory ability for OS in CRC. Immunohistochemistry revealed that the core gene CBLN1 was expressed at a lower level in CRC, while GLYATL1 was expressed at a higher level. Conclusions: In summary, we have successfully identified and comprehensively analyzed a gene signature associated with glutamine metabolism in CRC for the first time. This gene signature consistently and reliably predicts the prognosis of CRC patients, indicating its potential as a metabolic target for individuals with CRC.
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Affiliation(s)
- Yang Xie
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
| | - Jun Li
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
| | - Qing Tao
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
| | - Yonghui Wu
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
| | - Zide Liu
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
| | - Chunyan Zeng
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
- Jiangxi Clinical Research Center for Gastroenterology, Nanchang, Jiangxi, China
| | - Youxiang Chen
- Department of Gastroenterology, digestive disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang China
- Jiangxi Clinical Research Center for Gastroenterology, Nanchang, Jiangxi, China
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Wang F, Wang C, Li B, Wang G, Meng Z, Han J, Guo G, Yu B, Wang G. Identification of angiogenesis-related subtypes, the development of a prognosis model, and features of tumor microenvironment in colon cancer. Biotechnol Appl Biochem 2024; 71:45-60. [PMID: 37881150 DOI: 10.1002/bab.2520] [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: 03/20/2023] [Accepted: 09/26/2023] [Indexed: 10/27/2023]
Abstract
Angiogenesis is associated with tumor progression, prognosis, and treatment effect. However, the angiogenesis' underlying mechanisms in the tumor microenvironment (TME) still remain unclear. Understanding the dynamic interactions between angiogenesis and TME in colon adenocarcinoma (COAD) is necessary. We downloaded the transcriptome data and corresponding clinical data of colon cancer patients from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, respectively. We identified two distinct angiogenesis-related molecular subtypes (subtype A and subtype B) and assessed the clinical features, prognosis, and infiltrating immune cells of patients in the two subtypes. According to the prognostic differential genes, we defined two different gene clusters to further explore the correlation between angiogenesis and tumor heterogeneity. Then, we construct the prognostic risk scoring model angiogenesis-related gene (ARG-score) including seven genes (ARMCX2, latent transforming growth factor β binding protein 1, ADAM8, FABP4, CCL11, CXCL11, ITLN1) using Lasso-multivariate cox method. We analyzed the correlation between ARG-score and prognosis, clinicopathological features, TME, molecular feature, cancer stem cells (CSCs), and microsatellite instability (MSI) status. To assess the application value of ARG-score in clinical treatment, immunophenotype score was used to predict patients' immunotherapy response in colon cancer. We found the mutations of ARGs in TCGA-COAD dataset from genetic levels and discussed their expression patterns based on TCGA and GEO datasets. We observed important differences in clinicopathological features, prognosis, immune feature, molecular feature between the two molecular subgroups. Then, we established an ARG-score for predicting OS and validated its predictive capability. A high ARG-score characterized by higher transcription level of ARGs, suggested lower MSI-high (MSI-H), lower immune score, and worse clinical stage and survival outcome. Additionally, the ARG-score was remarkably related to the CSCs index and immunotherapy sensitivity. We found two new molecular subtypes and two gene clusters based on ARGs and established an ARG-score. Multilayered analysis revealed that ARGs were remarkably correlated to the heterogeneity of colon cancer patients and explained the process of tumorigenesis and progression better. The ARG-score can help us better assess patients' survival outcomes and provide guidance for individualized treatment.
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Affiliation(s)
- Feifei Wang
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Changjing Wang
- Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Baokun Li
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Guanglin Wang
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Zesong Meng
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Jiachao Han
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Ganlin Guo
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Bin Yu
- The Second Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Guiying Wang
- Department of Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
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Lu J, Tan J, Yu X. A prognostic model based on tumor microenvironment-related lncRNAs predicts therapy response in pancreatic cancer. Funct Integr Genomics 2023; 23:32. [PMID: 36625842 DOI: 10.1007/s10142-023-00964-x] [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: 10/08/2022] [Revised: 12/21/2022] [Accepted: 01/02/2023] [Indexed: 01/11/2023]
Abstract
Pancreatic cancer is an aggressive malignant tumor with high mortality and a low survival rate. The immune and stromal cells that infiltrate in the tumor microenvironment (TME) significantly impact immunotherapy and drug responses. Therefore, we identify the TME-related lncRNAs to develop a prognostic model for predicting the therapy efficacy in pancreatic cancer patients. Firstly, we identified differentially expressed genes (DEGs) for weighted gene co-expression network analysis (WGCNA) to identify the TME-related module eigengenes. According to the module eigengenes, the TME-related prognostic lncRNAs were screened through the univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses to construct a prognostic risk score (RS) model. Next, the predictive power of this model was evaluated by the time-dependent receiver operating characteristic (ROC) curve and Kaplan-Meier analyses. In addition, functional enrichment, immune cell infiltration, and somatic mutation analyses were performed. Finally, tumor immune dysfunction and exclusion (TIDE) score and drug sensitivity analyses were applied to predict therapy response. In this study, 11 TME-related prognostic lncRNAs were identified to develop the prognostic RS model. According to the RS, the low-risk patients had a better prognosis, lower rates of somatic mutation, lower TIDE scores, and higher sensitivity to gemcitabine and paclitaxel compared to high-risk patients. The findings above suggested that low-risk patients may benefit more from immunotherapy, and high-risk patients may benefit more from chemotherapy. Within this study, we established a prognostic RS model based on 11 TME-related lncRNAs, which may help improve clinical decision-making.
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Affiliation(s)
- Jianzhong Lu
- School of Sciences, Shanghai Institute of Technology, Shanghai, 201418, China
| | - Jinhua Tan
- School of Sciences, Shanghai Institute of Technology, Shanghai, 201418, China
| | - Xiaoqing Yu
- School of Sciences, Shanghai Institute of Technology, Shanghai, 201418, China.
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The Prediction of Necroptosis-Related lncRNAs in Prognosis and Anticancer Therapy of Colorectal Cancer. Anal Cell Pathol 2022; 2022:7158684. [PMID: 36199434 PMCID: PMC9527116 DOI: 10.1155/2022/7158684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 08/21/2022] [Accepted: 09/01/2022] [Indexed: 12/04/2022] Open
Abstract
Background Colorectal cancer is one of the most common gastrointestinal malignancies globally. Necroptosis has been proved to play a role in the occurrence and development of the tumor, which makes it a new target for molecular therapy. However, the role of necroptosis in colorectal cancer remains unknown yet. Our study aims to build a prognostic signature of necroptosis-related lncRNAs (nrlncRNAs) to predict the outcomes of patients with colorectal cancer and facilitate in anticancer therapy. Method We obtained RNA-seq and clinical data of colorectal adenocarcinoma from the TCGA database and got prognosis-related nrlncRNAs by univariate regression analysis. Then, we carried out the LASSO regression and multivariate regression analysis to build the prognostic signature, whose predictive ability was tested by the Kaplan-Meier as well as ROC curves and verified by the internal cohort. Moreover, we divided the cohort into 2 groups based on median of risk scores: high- and low-risk groups. By analyzing the difference in the tumor microenvironment, microsatellite instability, and tumor mutation burden between the two groups, we explored the potential chemotherapy and immunotherapy drugs. Results We screened out 9 nrlncRNAs and built a prognostic signature based on them. With its good prognostic ability, the risk scores can act as an independent prognostic factor for patients with colorectal cancer. The overall survival rate of patients in high-risk group was significantly higher than the low-risk one. Furthermore, risk scores can also give us hints about the tumor microenvironment and facilitate in predicting the response to the CTLA-4 blocker treatment and other chemotherapeutic agents with potential efficacy such as cisplatin and staurosporine. Conclusions In conclusion, our prognostic signature of necroptosis-related lncRNAs can facilitate in predicting the prognosis and response to the anticancer therapy of colorectal cancer patients.
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