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Ma Z, Men Y, Liu Y, Bao Y, Liu Q, Yang X, Wang J, Deng L, Zhai Y, Bi N, Wang L, Hui Z. Preoperative CT-based radiomic prognostic index to predict the benefit of postoperative radiotherapy in patients with non-small cell lung cancer: a multicenter study. Cancer Imaging 2024; 24:61. [PMID: 38741207 DOI: 10.1186/s40644-024-00707-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 04/29/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND The value of postoperative radiotherapy (PORT) for patients with non-small cell lung cancer (NSCLC) remains controversial. A subset of patients may benefit from PORT. We aimed to identify patients with NSCLC who could benefit from PORT. METHODS Patients from cohorts 1 and 2 with pathological Tany N2 M0 NSCLC were included, as well as patients with non-metastatic NSCLC from cohorts 3 to 6. The radiomic prognostic index (RPI) was developed using radiomic texture features extracted from the primary lung nodule in preoperative chest CT scans in cohort 1 and validated in other cohorts. We employed a least absolute shrinkage and selection operator-Cox regularisation model for data dimension reduction, feature selection, and the construction of the RPI. We created a lymph-radiomic prognostic index (LRPI) by combining RPI and positive lymph node number (PLN). We compared the outcomes of patients who received PORT against those who did not in the subgroups determined by the LRPI. RESULTS In total, 228, 1003, 144, 422, 19, and 21 patients were eligible in cohorts 1-6. RPI predicted overall survival (OS) in all six cohorts: cohort 1 (HR = 2.31, 95% CI: 1.18-4.52), cohort 2 (HR = 1.64, 95% CI: 1.26-2.14), cohort 3 (HR = 2.53, 95% CI: 1.45-4.3), cohort 4 (HR = 1.24, 95% CI: 1.01-1.52), cohort 5 (HR = 2.56, 95% CI: 0.73-9.02), cohort 6 (HR = 2.30, 95% CI: 0.53-10.03). LRPI predicted OS (C-index: 0.68, 95% CI: 0.60-0.75) better than the pT stage (C-index: 0.57, 95% CI: 0.50-0.63), pT + PLN (C-index: 0.58, 95% CI: 0.46-0.70), and RPI (C-index: 0.65, 95% CI: 0.54-0.75). The LRPI was used to categorize individuals into three risk groups; patients in the moderate-risk group benefited from PORT (HR = 0.60, 95% CI: 0.40-0.91; p = 0.02), while patients in the low-risk and high-risk groups did not. CONCLUSIONS We developed preoperative CT-based radiomic and lymph-radiomic prognostic indexes capable of predicting OS and the benefits of PORT for patients with NSCLC.
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Affiliation(s)
- Zeliang Ma
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Men
- Department of VIP Medical Services, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yunsong Liu
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yongxing Bao
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qian Liu
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xu Yang
- Department of Medical Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianyang Wang
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lei Deng
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yirui Zhai
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Nan Bi
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Luhua Wang
- Department of Radiation Oncology, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhouguang Hui
- Department of VIP Medical Services, National Clinical Research Center for Cancer/Cancer Hospital/National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Lu J, Yang J, Ma C, Wang X, Luo J, Ma X, Fu X, Zheng S. Model construction and risk analysis of the lncRNA genes associated with the prognosis of esophageal adenocarcinoma with immune infiltration. J Gastrointest Oncol 2023; 14:22-28. [PMID: 36915426 PMCID: PMC10007919 DOI: 10.21037/jgo-22-1279] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 02/02/2023] [Indexed: 03/03/2023] Open
Abstract
Background Our study analyzed the immune infiltration of esophageal adenocarcinoma (EAC) tumor cells and identified long non-coding ribonucleic acid (lncRNA) genes to construct a prognostic model of EAC to evaluate the survival prognosis of patients and explore potential therapeutic targets. Methods The data of 89 patients with EAC, including 11 normal tissue samples and 78 EAC of tumor tissue samples, were downloaded from The Cancer Genome Atlas public database. Perl script and R software were used to run the code, conduct the statistical analysis, calculate the risk coefficients of the patients, and conduct the Cox regression analysis, immune-related lncRNA survival analysis, risk analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) curve analysis. Results We screened and identified 19 prognostic biomarkers, including LINC01612, AC008443.2, and LINC02582, allocated the patients into high- and low-risk groups, and found significant differences in the prognosis between the high- and low-risk groups using the Kaplan-Meier survival analysis (P<0.001). A ROC curve was used to evaluate the feasibility of the prognostic model for EAC, and we found that the model had high predictability (area under the curve =0.964). A PCA analysis was performed of the complex transcriptome sequencing data and other cubes to transform the data into a 3-dimensional space constructed by feature vectors. Conclusions Our study effectively screened and identified the lncRNA genes related to the immune infiltration of EAC and successfully constructed a prognostic model. In total, 19 potential diagnostic and therapeutic target genes, including LINC01612, AC008443.2, and LINC02582, were identified that have certain significance in guiding the clinical treatment of EAC patients.
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Affiliation(s)
- Jun Lu
- Intensive Care Unit, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Juan Yang
- Department of Gastroenterology, The Third People's Hospital of Yunnan Province, Kunming, China
| | - Chi Ma
- Graduate School of Clinical Medicine, Dali University, Dali, China
| | - Xinxin Wang
- Graduate School of Clinical Medicine, Dali University, Dali, China
| | - Jiangyan Luo
- Graduate School of Clinical Medicine, Dali University, Dali, China
| | - Xiaoying Ma
- Graduate School of Clinical Medicine, Dali University, Dali, China
| | - Xinnian Fu
- Graduate School of Clinical Medicine, Dali University, Dali, China
| | - Sheng Zheng
- Department of Gastroenterology, The Third People's Hospital of Yunnan Province, Kunming, China
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Bispo IMC, Granger HP, Almeida PP, Nishiyama PB, de Freitas LM. Systems biology and OMIC data integration to understand gastrointestinal cancers. World J Clin Oncol 2022; 13:762-778. [PMID: 36337313 PMCID: PMC9630993 DOI: 10.5306/wjco.v13.i10.762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 05/22/2021] [Accepted: 10/03/2022] [Indexed: 02/06/2023] Open
Abstract
Gastrointestinal (GI) cancers are a set of diverse diseases affecting many parts/ organs. The five most frequent GI cancer types are esophageal, gastric cancer (GC), liver cancer, pancreatic cancer, and colorectal cancer (CRC); together, they give rise to 5 million new cases and cause the death of 3.5 million people annually. We provide information about molecular changes crucial to tumorigenesis and the behavior and prognosis. During the formation of cancer cells, the genomic changes are microsatellite instability with multiple chromosomal arrangements in GC and CRC. The genomically stable subtype is observed in GC and pancreatic cancer. Besides these genomic subtypes, CRC has epigenetic modification (hypermethylation) associated with a poor prognosis. The pathway information highlights the functions shared by GI cancers such as apoptosis; focal adhesion; and the p21-activated kinase, phosphoinositide 3-kinase/Akt, transforming growth factor beta, and Toll-like receptor signaling pathways. These pathways show survival, cell proliferation, and cell motility. In addition, the immune response and inflammation are also essential elements in the shared functions. We also retrieved information on protein-protein interaction from the STRING database, and found that proteins Akt1, catenin beta 1 (CTNNB1), E1A binding protein P300, tumor protein p53 (TP53), and TP53 binding protein 1 (TP53BP1) are central nodes in the network. The protein expression of these genes is associated with overall survival in some GI cancers. The low TP53BP1 expression in CRC, high EP300 expression in esophageal cancer, and increased expression of Akt1/TP53 or low CTNNB1 expression in GC are associated with a poor prognosis. The Kaplan Meier plotter database also confirmed the association between expression of the five central genes and GC survival rates. In conclusion, GI cancers are very diverse at the molecular level. However, the shared mutations and protein pathways might be used to understand better and reveal diagnostic/prognostic or drug targets.
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Affiliation(s)
- Iasmin Moreira Costa Bispo
- Núcleo de Biointegração, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45.029-094, Bahia, Brazil
| | - Henry Paul Granger
- Núcleo de Biointegração, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45.029-094, Bahia, Brazil
| | - Palloma Porto Almeida
- Division of Experimental and Translational Research, Brazilian National Cancer Institute, Rio de Janeiro 20231-050, Brazil
| | - Patricia Belini Nishiyama
- Núcleo de Biointegração, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45.029-094, Bahia, Brazil
| | - Leandro Martins de Freitas
- Núcleo de Biointegração, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45.029-094, Bahia, Brazil
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Chen F, Gong E, Ma J, Lin J, Wu C, Chen S, Hu S. Prognostic score model based on six m6A-related autophagy genes for predicting survival in esophageal squamous cell carcinoma. J Clin Lab Anal 2022; 36:e24507. [PMID: 35611939 PMCID: PMC9279981 DOI: 10.1002/jcla.24507] [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: 09/28/2021] [Revised: 05/06/2022] [Accepted: 05/09/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Prognostic signatures based on autophagy genes have been proposed for esophageal squamous cell carcinoma (ESCC). Autophagy genes are closely associated with m6A genes. Our purpose is to identify m6A-related autophagy genes in ESCC and develop a survival prediction model. METHODS Differential expression analyses for m6A genes and autophagy genes were performed based on TCGA and HADd databases followed by constructing a co-expression network. Uni-variable Cox regression analysis was performed for m6A-related autophagy genes. Using the optimal combination of feature genes by LASSO Cox regression model, a prognostic score (PS) model was developed and subsequently validated in an independent dataset. RESULTS The differential expression of 13 m6A genes and 107 autophagy genes was observed between ESCC and normal samples. The co-expression network contained 13 m6A genes and 96 autophagy genes. Of the 12 m6A-related autophagy genes that were significantly related to survival, DAPK2, DIRAS3, EIF2AK3, ITPR1, MAP1LC3C, and TP53 were used to construct a PS model, which split the training set into two risk groups with significant different survival ratios (p = 0.015, 1-year, 3-year, and 5-year AUC = 0.873, 0.840, and 0.829). Consistent results of GSE53625 dataset confirmed predictive ability of the model (p = 0.024, 1-year, 3-year, and 5-year AUC = 0.793, 0.751, and 0.744). The six-gene PS score was an independent prognostic factor from clinical factors (HR, 2.362; 95% CI, 1.390-7.064; p-value = 0.012). CONCLUSION Our study recommends 6 m6A-related autophagy genes as promising prognostic biomarkers and develops a PS model to predict survival in ESCC.
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Affiliation(s)
- Funan Chen
- Department of Cardiothoracic Surgery, Longyan First Hospital, Longyan City, China
| | - Erxiu Gong
- Department of Cardiothoracic Surgery, Longyan First Hospital, Longyan City, China
| | - Jun Ma
- Department of Cardiothoracic Surgery, Longyan First Hospital, Longyan City, China
| | - Jiehuan Lin
- Department of Cardiothoracic Surgery, Longyan First Hospital, Longyan City, China
| | - Canxing Wu
- Department of Cardiothoracic Surgery, Longyan First Hospital, Longyan City, China
| | - Shanshan Chen
- Priority Ward, Longyan First Hospital, Longyan City, China
| | - Shuqiao Hu
- Department of Cardiothoracic Surgery, Longyan First Hospital, Longyan City, China
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Zheng W, Bai X, Zhou Y, Yu L, Ji D, Zheng Y, Meng N, Wang H, Huang Z, Chen W, Yam JWP, Xu Y, Cui Y. Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer. Aging (Albany NY) 2022; 14:4425-4444. [PMID: 35580861 PMCID: PMC9186782 DOI: 10.18632/aging.204080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 05/02/2022] [Indexed: 11/26/2022]
Abstract
Inositol 1,4,5-Triphosphate Receptor Family (ITPRs) are necessary intracellular Ca2+-release channel encoders and participate in mammalian cell physiological and pathological processes. Previous studies have suggested that ITPRs participate in tumorigenesis of multiple cancers. Nevertheless, the diverse expression profiles and prognostic significance of three ITPRs in pancreatic cancer have yet to be uncovered. In this work, we examined the expression levels and survival dates of ITPRs in patients with pancreatic cancer. As a result, we identified that ITPR1 and ITPR3 expression levels are significantly elevated in cancerous specimens. Survival data revealed that over-expression of ITPR2 and ITPR3 resulted in unfavourable overall survival and pathological stage. The multivariate Cox logistic regression analysis showed that ITPR3 could be an independent risk factor for PAAD patient survival. Moreover, to investigate how ITPRs work, co-expressed genes, alterations, protein-protein interaction, immune infiltration, methylation, and functional enrichment of ITPRs were also analyzed. Then, we evaluated these findings in clinical samples. Moreover, the gain and loss of function of ITPR3 were also conducted. The electron microscope assay was employed to explore the role of ITPR3 in pancreatic cancer cell lines' endoplasmic reticulum stress. In summary, our findings demonstrated that ITPR3 has the potential to be drug targets and biomarkers for human pancreatic cancer.
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Affiliation(s)
- Wangyang Zheng
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin 150086, China
- Department II of Gastroenterology, Third Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Xue Bai
- Department of Clinic of Internal Medicine I, Ulm University, Ulm 89081, Germany
| | - Yongxu Zhou
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin 150086, China
| | - Liang Yu
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin 150086, China
| | - Daolin Ji
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin 150086, China
- Department of Hepatopancreatobiliary Surgery, Fourth Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Yuling Zheng
- Department of Pediatric, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Nanfeng Meng
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Hang Wang
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Ziyue Huang
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Wangming Chen
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
| | - Judy Wai Ping Yam
- Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China
| | - Yi Xu
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin 150086, China
- Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China
| | - Yunfu Cui
- Department of Hepatopancreatobiliary Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
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Yu L, Zheng Y, Gao L. MiRNA-disease association prediction based on meta-paths. Brief Bioinform 2022; 23:6501422. [PMID: 35018405 DOI: 10.1093/bib/bbab571] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/02/2021] [Accepted: 12/11/2021] [Indexed: 01/09/2023] Open
Abstract
Since miRNAs can participate in the posttranscriptional regulation of gene expression, they may provide ideas for the development of new drugs or become new biomarkers for drug targets or disease diagnosis. In this work, we propose an miRNA-disease association prediction method based on meta-paths (MDPBMP). First, an miRNA-disease-gene heterogeneous information network was constructed, and seven symmetrical meta-paths were defined according to different semantics. After constructing the initial feature vector for the node, the vector information carried by all nodes on the meta-path instance is extracted and aggregated to update the feature vector of the starting node. Then, the vector information obtained by the nodes on different meta-paths is aggregated. Finally, miRNA and disease embedding feature vectors are used to calculate their associated scores. Compared with the other methods, MDPBMP obtained the highest AUC value of 0.9214. Among the top 50 predicted miRNAs for lung neoplasms, esophageal neoplasms, colon neoplasms and breast neoplasms, 49, 48, 49 and 50 have been verified. Furthermore, for breast neoplasms, we deleted all the known associations between breast neoplasms and miRNAs from the training set. These results also show that for new diseases without known related miRNA information, our model can predict their potential miRNAs. Code and data are available at https://github.com/LiangYu-Xidian/MDPBMP.
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Affiliation(s)
- Liang Yu
- School of Computer Science and Technology, Xidian University, Xi'an 710071, P.R. China
| | - Yujia Zheng
- School of Computer Science and Technology, Xidian University, Xi'an 710071, P.R. China
| | - Lin Gao
- School of Computer Science and Technology, Xidian University, Xi'an 710071, P.R. China
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Chen N, Wang Z, Yang X, Geng D, Fu J, Zhang Y. Integrated analysis of competing endogenous RNA in esophageal carcinoma. J Gastrointest Oncol 2021; 12:11-27. [PMID: 33708421 DOI: 10.21037/jgo-20-615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Background The Competing endogenous RNA (CeRNA) network plays important roles in the development and progression of multiple human cancers. Increasing attention has been paid to CeRNA in esophageal carcinoma (ESCA). Methods We explored The Cancer Genome Atlas (TCGA) database and then analyzed the RNAs of 142 samples to obtain long non-coding RNAs (lncRNAs), micro RNAs (miRNAs), and messenger RNAs (mRNAs) with different expression trends alongside the progress of ESCA. A series test of cluster (STC) analysis was carried out to identify a set of unique model expression tendencies. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to validate the function of key genes that were obtained from the STC analysis. Results Through our analysis, 272 lncRNAs, 87 miRNAs, and 692 mRNAs showed upward expression or downward expression trends, and these molecules were tightly involved in cell cycle, pathways in cancer, metabolic processes, and protein phosphorylation, among others. Ultimately, we constructed a CeRNA network containing a total of 71 lncRNAs, 56 miRNAs, and 125 mRNAs. The overall survival (OS) was analyzed using univariate Cox regression analysis to clarify the relationship between these key molecules from the CeRNA network and the prognosis of ESCA patients. Through survival analysis, we finally screened out two lncRNAs (DLEU2, RP11-890B15.3), three miRNAs (miR-26b-3p, miR-92a-3p, miR-324-5p), and one mRNA (SIK2) as crucial prognostic factors for ESCA. Conclusions The novel CeRNA network that we constructed will provide new novel prognostic biomarkers and therapeutic targets for patients with ESCA.
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Affiliation(s)
- Nanzheng Chen
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zhi Wang
- Nursing Department, Xi'an Chest Hospital, Xi'an, China
| | - Xiaomei Yang
- Hospital 521 of China's Ordnance Industry Group, Xi'an, China
| | - Donghong Geng
- School of Continuing Education of Xi'an Jiaotong University, Xi'an, China
| | - Junke Fu
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yong Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Zhuang W, Ben X, Zhou Z, Ding Y, Tang Y, Huang S, Deng C, Liao Y, Zhou Q, Zhao J, Wang G, Xu Y, Wen X, Zhang Y, Cai S, Chen R, Qiao G. Identification of a Ten-Gene Signature of DNA Damage Response Pathways with Prognostic Value in Esophageal Squamous Cell Carcinoma. JOURNAL OF ONCOLOGY 2021; 2021:3726058. [PMID: 34976055 PMCID: PMC8716225 DOI: 10.1155/2021/3726058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 11/27/2021] [Indexed: 02/06/2023]
Abstract
Molecular prognostic signatures are critical for treatment decision-making in esophageal squamous cell cancer (ESCC), but the robustness of these signatures is limited. The aberrant DNA damage response (DDR) pathway may lead to the accumulation of mutations and thus accelerate tumor progression in ESCC. Given this, we applied the LASSO Cox regression to the transcriptomic data of DDR genes, and a prognostic DDR-related gene expression signature (DRGS) consisting of ten genes was constructed, including PARP3, POLB, XRCC5, MLH1, DMC1, GTF2H3, PER1, SMC5, TCEA1, and HERC2. The DRGS was independently associated with overall survival in both training and validation cohorts. The DRGS achieved higher accuracy than six previously reported multigene signatures for the prediction of prognosis in comparable cohorts. Furtherly, a nomogram incorporating DRGS and clinicopathological features showed improved predicting performance. Taken together, the DRGS was identified as a novel, robust, and effective prognostic indicator, which may refine the scheme of risk stratification and management in ESCC patients.
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Affiliation(s)
- Weitao Zhuang
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Shantou University Medical College, Shantou 515041, China
| | - Xiaosong Ben
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Zihao Zhou
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Yu Ding
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Yong Tang
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Shujie Huang
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Shantou University Medical College, Shantou 515041, China
| | - Cheng Deng
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Yuchen Liao
- Burning Rock Biotech, Guangzhou 510300, China
| | | | - Jing Zhao
- Burning Rock Biotech, Guangzhou 510300, China
| | | | - Yu Xu
- Burning Rock Biotech, Guangzhou 510300, China
| | | | - Yuzi Zhang
- Burning Rock Biotech, Guangzhou 510300, China
| | - Shangli Cai
- Burning Rock Biotech, Guangzhou 510300, China
| | - Rixin Chen
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Research Center of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Guibin Qiao
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
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