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Lu W, Wang Q, Liu L, Luo W. Exploring the mystery of colon cancer from the perspective of molecular subtypes and treatment. Sci Rep 2024; 14:10883. [PMID: 38740818 DOI: 10.1038/s41598-024-60495-8] [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: 11/30/2023] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
The molecular categorization of colon cancer patients remains elusive. Gene set enrichment analysis (GSEA), which investigates the dysregulated genes among tumor and normal samples, has revealed the pivotal role of epithelial-to-mesenchymal transition (EMT) in colon cancer pathogenesis. In this study, we employed multi-clustering method for grouping data, resulting in the identification of two clusters characterized by varying prognostic outcomes. These two subgroups not only displayed disparities in overall survival (OS) but also manifested variations in clinical variables, genetic mutation, and gene expression profiles. Using the nearest template prediction (NTP) method, we were able to replicate the molecular classification effectively within the original dataset and validated it across multiple independent datasets, underscoring its robust repeatability. Furthermore, we constructed two prognostic signatures tailored to each of these subgroups. Our molecular classification, centered on EMT, hold promise in offering fresh insights into the therapy strategies and prognosis assessment for colon cancer.
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Affiliation(s)
- Wenhong Lu
- The Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, Hunan, People's Republic of China
| | - Qiwei Wang
- Hunan Provincial Rehabilitation Hospital, Changsha, 410007, Hunan, People's Republic of China
| | - Lifang Liu
- The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410007, Hunan, People's Republic of China
| | - Wenpeng Luo
- The Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, Hunan, People's Republic of China.
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2
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Holubekova V, Loderer D, Grendar M, Mikolajcik P, Kolkova Z, Turyova E, Kudelova E, Kalman M, Marcinek J, Miklusica J, Laca L, Lasabova Z. Differential gene expression of immunity and inflammation genes in colorectal cancer using targeted RNA sequencing. Front Oncol 2023; 13:1206482. [PMID: 37869102 PMCID: PMC10586664 DOI: 10.3389/fonc.2023.1206482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 08/24/2023] [Indexed: 10/24/2023] Open
Abstract
Introduction Colorectal cancer (CRC) is a heterogeneous disease caused by molecular changes, as driver mutations, gene methylations, etc., and influenced by tumor microenvironment (TME) pervaded with immune cells with both pro- and anti-tumor effects. The studying of interactions between the immune system (IS) and the TME is important for developing effective immunotherapeutic strategies for CRC. In our study, we focused on the analysis of expression profiles of inflammatory and immune-relevant genes to identify aberrant signaling pathways included in carcinogenesis, metastatic potential of tumors, and association of Kirsten rat sarcoma virus (KRAS) gene mutation. Methods A total of 91 patients were enrolled in the study. Using NGS, differential gene expression analysis of 11 tumor samples and 11 matching non-tumor controls was carried out by applying a targeted RNA panel for inflammation and immunity genes containing 475 target genes. The obtained data were evaluated by the CLC Genomics Workbench and R library. The significantly differentially expressed genes (DEGs) were analyzed in Reactome GSA software, and some selected DEGs were used for real-time PCR validation. Results After prioritization, the most significant differences in gene expression were shown by the genes TNFRSF4, IRF7, IL6R, NR3CI, EIF2AK2, MIF, CCL5, TNFSF10, CCL20, CXCL11, RIPK2, and BLNK. Validation analyses on 91 samples showed a correlation between RNA-seq data and qPCR for TNFSF10, RIPK2, and BLNK gene expression. The top differently regulated signaling pathways between the studied groups (cancer vs. control, metastatic vs. primary CRC and KRAS positive and negative CRC) belong to immune system, signal transduction, disease, gene expression, DNA repair, and programmed cell death. Conclusion Analyzed data suggest the changes at more levels of CRC carcinogenesis, including surface receptors of epithelial or immune cells, its signal transduction pathways, programmed cell death modifications, alterations in DNA repair machinery, and cell cycle control leading to uncontrolled proliferation. This study indicates only basic molecular pathways that enabled the formation of metastatic cancer stem cells and may contribute to clarifying the function of the IS in the TME of CRC. A precise identification of signaling pathways responsible for CRC may help in the selection of personalized pharmacological treatment.
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Affiliation(s)
- Veronika Holubekova
- Laboratory of Genomics and Prenatal Diagnostics, Biomedical Center in Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Dusan Loderer
- Laboratory of Genomics and Prenatal Diagnostics, Biomedical Center in Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Marian Grendar
- Laboratory of Bioinformatics and Biostatistics, Biomedical Center in Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Peter Mikolajcik
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin University Hospital, Martin, Slovakia
| | - Zuzana Kolkova
- Laboratory of Genomics and Prenatal Diagnostics, Biomedical Center in Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Eva Turyova
- Department of Molecular Biology and Genomics, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Eva Kudelova
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin University Hospital, Martin, Slovakia
| | - Michal Kalman
- Department of Pathological Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin University Hospital, Martin, Slovakia
| | - Juraj Marcinek
- Department of Pathological Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin University Hospital, Martin, Slovakia
| | - Juraj Miklusica
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin University Hospital, Martin, Slovakia
| | - Ludovit Laca
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin University Hospital, Martin, Slovakia
| | - Zora Lasabova
- Department of Molecular Biology and Genomics, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
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Li J, Yu T, Sun J, Zeng Z, Liu Z, Ma M, Zheng Z, He Y, Kang W. Comprehensive analysis of cuproptosis-related immune biomarker signature to enhance prognostic accuracy in gastric cancer. Aging (Albany NY) 2023; 15:2772-2796. [PMID: 37036489 PMCID: PMC10120894 DOI: 10.18632/aging.204646] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 03/24/2023] [Indexed: 04/11/2023]
Abstract
BACKGROUND Gastric cancer (GC) is a malignant tumor with high prevalence and fatality. Cuproptosis is a recently identified copper-dependent programmed cell death mechanism. Multiple studies have demonstrated the profound impact of the immune microenvironment on tumor development. Hence, we decided to excavate the potential functional roles of cuproptosis-related immune genes (CRIGs) in GC and their values as biomarkers. METHODS Cuproptosis- and immune-related genes were curated from top published studies on cell cuproptosis and cellular immunity. Transcriptome data and clinical information were obtained from TCGA, GTEx, and GEO databases. Cox and LASSO analyses were used to establish a prognostic signature for GC. Long-term prognosis, immune infiltration, immune checkpoint, and drug response were compared between signature groups. CRIG expression in GC scRNA-seq was analyzed. Immunohistochemistry was used to evaluate CRIG and cuproptosis regulator FDX1 in GC tissues. RESULTS Seven CRIGs (ANOS1, CTLA4, ITGAV, CXCR4, NRP1, FABP3, and LGR6) were selected to establish a potent signature to forecast the long-term prognosis of patients. GC patients had worse prognosis and poor responses to chemotherapeutic drugs (5-Fluorouracil and paclitaxel) in the high-risk group. scRNA-seq revealed that CTLA4, ITGAV, CXCR4, and NRP1 enrichment in specific cell types regulated the progression of GC. Moreover, NRP1, CXCR4, LGR6, CTLA4, and FDX1 were elevated in GC tissues, with a positive correlation between their expression and FDX1. CONCLUSIONS To conclude, this study first provides insights into the functions of CRIGs in GC. Furthermore, a robust cuproptosis-related immune biomarker signature was established to forecast the long-term survival of GC patients accurately.
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Affiliation(s)
- Jie Li
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Tian Yu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Juan Sun
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Ziyang Zeng
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Zhen Liu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Mingwei Ma
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Zicheng Zheng
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Yixuan He
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
| | - Weiming Kang
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, People’s Republic of China
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Zhang C, Huang Y, Fang C, Liang Y, Jiang D, Li J, Ma H, Jiang W, Feng Y. Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma. Cancer Biomark 2023; 36:313-326. [PMID: 36938730 DOI: 10.3233/cbm-220227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
BACKGROUND We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC). METHODS From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression. RESULTS Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue. CONCLUSION Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.
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Affiliation(s)
- Chengpeng Zhang
- Department of Thoracic Surgery, Suzhou Ninth People's Hospital, Suzhou, Jiangsu, China.,Department of Thoracic Surgery, Suzhou Ninth People's Hospital, Suzhou, Jiangsu, China
| | - Yong Huang
- Department of Thoracic Surgery, Haimen People's Hospital, Nantong, Jiangsu, China.,Department of Thoracic Surgery, Suzhou Ninth People's Hospital, Suzhou, Jiangsu, China
| | - Chen Fang
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.,Department of Thoracic Surgery, Suzhou Ninth People's Hospital, Suzhou, Jiangsu, China
| | - Yingkuan Liang
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Dong Jiang
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Jiaxi Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Haitao Ma
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Wei Jiang
- Department of Thoracic Surgery, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, China
| | - Yu Feng
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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Zamani-Ahmadmahmudi M, Jajarmi M, Talebipour S. Molecular phenotyping of malignant canine mammary tumours: Detection of high-risk group and its relationship with clinicomolecular characteristics. Vet Comp Oncol 2023; 21:73-81. [PMID: 36251017 DOI: 10.1111/vco.12863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 10/09/2022] [Accepted: 10/10/2022] [Indexed: 11/27/2022]
Abstract
Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high-throughput technologies such as microarray and next-generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA-sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) (n = 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high-risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2-C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates (ps <.05). The high-risk subtype (C5) was further characterized through the development of a cell cycle-based gene signature, which comprised 37 proliferation-related genes according to the support vector machine algorithm. This signature identified the high-risk group in both training and validation datasets (ps <.001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.
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Affiliation(s)
- Mohamad Zamani-Ahmadmahmudi
- Department of Clinical Science, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Maziar Jajarmi
- Department of Pathobiology, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Saeedeh Talebipour
- Department of Clinical Science, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
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Cui Y, Wang X, Zhang L, Liu W, Ning J, Gu R, Cui Y, Cai L, Xing Y. A novel epithelial-mesenchymal transition (EMT)-related gene signature of predictive value for the survival outcomes in lung adenocarcinoma. Front Oncol 2022; 12:974614. [PMID: 36185284 PMCID: PMC9521574 DOI: 10.3389/fonc.2022.974614] [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: 06/21/2022] [Accepted: 08/30/2022] [Indexed: 11/24/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is a remarkably heterogeneous and aggressive disease with dismal prognosis of patients. The identification of promising prognostic biomarkers might enable effective diagnosis and treatment of LUAD. Aberrant activation of epithelial-mesenchymal transition (EMT) is required for LUAD initiation, progression and metastasis. With the purpose of identifying a robust EMT-related gene signature (E-signature) to monitor the survival outcomes of LUAD patients. In The Cancer Genome Atlas (TCGA) database, least absolute shrinkage and selection operator (LASSO) analysis and cox regression analysis were conducted to acquire prognostic and EMT-related genes. A 4 EMT-related and prognostic gene signature, comprising dickkopf-like protein 1 (DKK1), lysyl oxidase-like 2 (LOXL2), matrix Gla protein (MGP) and slit guidance ligand 3 (SLIT3), was identified. By the usage of datum derived from TCGA database and Western blotting analysis, compared with adjacent tissue samples, DKK1 and LOXL2 protein expression in LUAD tissue samples were significantly higher, whereas the trend of MGP and SLIT3 expression were opposite. Concurrent with upregulation of epithelial markers and downregulation of mesenchymal markers, knockdown of DKK1 and LOXL2 impeded the migration and invasion of LUAD cells. Simultaneously, MGP and SLIT3 silencing promoted metastasis and induce EMT of LUAD cells. In the TCGA-LUAD set, receiver operating characteristic (ROC) analysis indicated that our risk model based on the identified E-signature was superior to those reported in literatures. Additionally, the E-signature carried robust prognostic significance. The validity of prediction in the E-signature was validated by the three independent datasets obtained from Gene Expression Omnibus (GEO) database. The probabilistic nomogram including the E-signature, pathological T stage and N stage was constructed and the nomogram demonstrated satisfactory discrimination and calibration. In LUAD patients, the E-signature risk score was associated with T stage, N stage, M stage and TNM stage. GSEA (gene set enrichment analysis) analysis indicated that the E-signature might be linked to the pathways including GLYCOLYSIS, MYC TARGETS, DNA REPAIR and so on. In conclusion, our study explored an innovative EMT based prognostic signature that might serve as a potential target for personalized and precision medicine.
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Affiliation(s)
- Yimeng Cui
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xin Wang
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Lei Zhang
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Wei Liu
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Jinfeng Ning
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ruixue Gu
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yaowen Cui
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Li Cai
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
- *Correspondence: Ying Xing, ; Li Cai,
| | - Ying Xing
- The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China
- *Correspondence: Ying Xing, ; Li Cai,
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Liu L, He H, Peng Y, Yang Z, Gao S. A four-gene prognostic signature for predicting the overall survival of patients with lung adenocarcinoma. PeerJ 2021; 9:e11911. [PMID: 34631307 PMCID: PMC8465999 DOI: 10.7717/peerj.11911] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 07/14/2021] [Indexed: 01/12/2023] Open
Abstract
Background The prognosis of patients for lung adenocarcinoma (LUAD) is known to vary widely; the 5-year overall survival rate is just 63% even for the pathological IA stage. Thus, in order to identify high-risk patients and facilitate clinical decision making, it is vital that we identify new prognostic markers that can be used alongside TNM staging to facilitate risk stratification. Methods We used mRNA expression from The Cancer Genome Atlas (TCGA) cohort to identify a prognostic gene signature and combined this with clinical data to develop a predictive model for the prognosis of patients for lung adenocarcinoma. Kaplan-Meier curves, Lasso regression, and Cox regression, were used to identify specific prognostic genes. The model was assessed via the area under the receiver operating characteristic curve (AUC-ROC) and validated in an independent dataset (GSE50081) from the Gene Expression Omnibus (GEO). Results Our analyses identified a four-gene prognostic signature (CENPH, MYLIP, PITX3, and TRAF3IP3) that was associated with the overall survival of patients with T1-4N0-2M0 in the TCGA dataset. Multivariate regression suggested that the total risk score for the four genes represented an independent prognostic factor for the TCGA and GEO cohorts; the hazard ratio (HR) (high risk group vs low risk group) were 2.34 (p < 0.001) and 2.10 (p = 0.017). Immune infiltration estimations, as determined by an online tool (TIMER2.0) showed that CD4+ T cells were in relative abundance in the high risk group compared to the low risk group in both of the two cohorts (both p < 0.001). We established a composite prognostic model for predicting OS, combined with risk-grouping and clinical factors. The AUCs for 1-, 3-, 5- year OS in the training set were 0.750, 0.737, and 0.719; and were 0.645, 0.766, and 0.725 in the validation set. The calibration curves showed a good match between the predicted probabilities and the actual probabilities. Conclusions We identified a four-gene predictive signature which represents an independent prognostic factor and can be used to identify high-risk patients from different TNM stages of LUAD. A new prognostic model that combines a prognostic gene signature with clinical features exhibited better discriminatory ability for OS than traditional TNM staging.
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Affiliation(s)
- Lei Liu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Huayu He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yue Peng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhenlin Yang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shugeng Gao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Zhang Z, Chen J, Tang W, Feng Q, Xu J, Ren L. Comprehensive Analysis Reveals the Potential Regulatory Mechanism Between Ub-Proteasome System and Cell Cycle in Colorectal Cancer. Front Cell Dev Biol 2021; 9:653528. [PMID: 34195188 PMCID: PMC8238047 DOI: 10.3389/fcell.2021.653528] [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: 01/14/2021] [Accepted: 03/18/2021] [Indexed: 11/24/2022] Open
Abstract
The ubiquitin (Ub)–proteasome system (UPS) is an important regulatory component in colorectal cancer (CRC), and the cell cycle is also characterized to play a significant role in CRC. In this present study, we firstly identified UPS-associated differentially expressed genes and all the differentially expressed protein-coding genes in CRC through three differential analyses. UPS-associated genes were also further analyzed via survival analysis. A weighted gene co-expression network analysis (WGCNA) was used to identify the cell cycle-associated genes. We used protein–protein interaction (PPI) network to comprehensively mine the potential mechanism of the UPS–cell cycle regulatory axis. Moreover, we constructed a signature based on UPS-associated genes to predict the overall survival of CRC patients. Our research provides a novel insight view of the UPS and cell cycle system in CRC.
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Affiliation(s)
- Zhiyuan Zhang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jingwen Chen
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wentao Tang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qingyang Feng
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jianmin Xu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Li Ren
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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Zhang Z, Ji M, Li J, Wu Q, Huang Y, He G, Xu J. Molecular Classification Based on Prognostic and Cell Cycle-Associated Genes in Patients With Colon Cancer. Front Oncol 2021; 11:636591. [PMID: 33898311 PMCID: PMC8059408 DOI: 10.3389/fonc.2021.636591] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/11/2021] [Indexed: 01/27/2023] Open
Abstract
The molecular classification of patients with colon cancer is inconclusive. The gene set enrichment analysis (GSEA) of dysregulated genes among normal and tumor tissues indicated that the cell cycle played a crucial role in colon cancer. We performed univariate Cox regression analysis to find out the prognostic-related genes, and these genes were then intersected with cell cycle-associated genes and were further recognized as prognostic and cell cycle-associated genes. Unsupervised non-negative matrix factorization (NMF) clustering was performed based on cell cycle-associated genes. Two subgroups were identified with different overall survival, clinical features, cell cycle enrichment profile, and mutation profile. Through nearest template prediction (NTP), the molecular classification could be effectively repeated in the original data set and validated in several independent data sets indicating that the classification is highly repeatable. Furthermore, we constructed two prognostic signatures in two subgroups, respectively. Our molecular classification based on cell cycle may provide novel insight into the treatment and the prognosis of colon cancer.
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Affiliation(s)
- Zhiyuan Zhang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Meiling Ji
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jie Li
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qi Wu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuanjian Huang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guodong He
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jianmin Xu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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