{"title":"长链非编码RNA AP000695.2作为胃癌新的预后生物标志物","authors":"Yun Cheng, Xiaoqing Yi, Shuang Fu, Junchi Cheng, Wei Li, Hongliang Xu","doi":"10.24976/Discov.Med.202335174.4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Long non-coding RNA (lncRNA) AP000695.2 (ENSG00000248538) expresses abnormally in various malignancies, what shows its role as oncogene. However, it has not been extensively studied in gastric cancer. The aim of the current study was to explore the clinical value of AP000695.2 to prognose gastric cancer.</p><p><strong>Methods: </strong>The cancer genome atlas (TCGA) and the gene expression profiling interactive analysis (GEPIA) online tool were used to analyze AP000695.2 expression pattern, diagnostic and prognostic role in gastric cancer. Kaplan-Meier and Cox regression analyses were used to assess survival in patients with gastric cancer. Receiver operating curve (ROC) analysis was used to assess AP000695.2 diagnostic capacity. Nomograms were created to predict overall survival (OS) and progression free survival (PFS).</p><p><strong>Results: </strong>LncRNA AP000695.2 was abnormally upregulated in 19 types of malignancy, including gastric cancer. Survival analysis indicated that high expression of AP000695.2 was associated with poor survival of gastric cancer. Multivariate Cox regression analysis verified the independent prognostic value of AP000695.2 to predict OS (HR (hazard ratio): 1.104, 95% CI (confidence interval): 1.035-1.178, <i>p</i> = 0.003) and PFS (HR: 1.170, 95% CI: 1.090-1.256, <i>p</i> < 0.001). ROC analysis indicated a favorable AP000695.2 diagnostic capacity (area under the curve (AUC) = 0.890). Nomograms were also constructed for OS and PFS based on AP000695.2 expression-related risk score. Additionally, AP000695.2 was found to be positively associated with tumor-infiltrating immune cells, including classically activated (M1) macrophages, neutrophils, alternatively activated (M2) macrophages, and natural killer (NK) cells.</p><p><strong>Conclusions: </strong>It was observed that AP000695.2 can be used as a novel biomarker to diagnose or predict survival of gastric patient.</p>","PeriodicalId":11379,"journal":{"name":"Discovery medicine","volume":"35 174","pages":"28-35"},"PeriodicalIF":2.0000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Long Noncoding RNA AP000695.2 as a Novel Prognostic Biomarker for Gastric Cancer.\",\"authors\":\"Yun Cheng, Xiaoqing Yi, Shuang Fu, Junchi Cheng, Wei Li, Hongliang Xu\",\"doi\":\"10.24976/Discov.Med.202335174.4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Long non-coding RNA (lncRNA) AP000695.2 (ENSG00000248538) expresses abnormally in various malignancies, what shows its role as oncogene. However, it has not been extensively studied in gastric cancer. The aim of the current study was to explore the clinical value of AP000695.2 to prognose gastric cancer.</p><p><strong>Methods: </strong>The cancer genome atlas (TCGA) and the gene expression profiling interactive analysis (GEPIA) online tool were used to analyze AP000695.2 expression pattern, diagnostic and prognostic role in gastric cancer. Kaplan-Meier and Cox regression analyses were used to assess survival in patients with gastric cancer. Receiver operating curve (ROC) analysis was used to assess AP000695.2 diagnostic capacity. Nomograms were created to predict overall survival (OS) and progression free survival (PFS).</p><p><strong>Results: </strong>LncRNA AP000695.2 was abnormally upregulated in 19 types of malignancy, including gastric cancer. Survival analysis indicated that high expression of AP000695.2 was associated with poor survival of gastric cancer. Multivariate Cox regression analysis verified the independent prognostic value of AP000695.2 to predict OS (HR (hazard ratio): 1.104, 95% CI (confidence interval): 1.035-1.178, <i>p</i> = 0.003) and PFS (HR: 1.170, 95% CI: 1.090-1.256, <i>p</i> < 0.001). ROC analysis indicated a favorable AP000695.2 diagnostic capacity (area under the curve (AUC) = 0.890). Nomograms were also constructed for OS and PFS based on AP000695.2 expression-related risk score. Additionally, AP000695.2 was found to be positively associated with tumor-infiltrating immune cells, including classically activated (M1) macrophages, neutrophils, alternatively activated (M2) macrophages, and natural killer (NK) cells.</p><p><strong>Conclusions: </strong>It was observed that AP000695.2 can be used as a novel biomarker to diagnose or predict survival of gastric patient.</p>\",\"PeriodicalId\":11379,\"journal\":{\"name\":\"Discovery medicine\",\"volume\":\"35 174\",\"pages\":\"28-35\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discovery medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.24976/Discov.Med.202335174.4\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discovery medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.24976/Discov.Med.202335174.4","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Long Noncoding RNA AP000695.2 as a Novel Prognostic Biomarker for Gastric Cancer.
Background: Long non-coding RNA (lncRNA) AP000695.2 (ENSG00000248538) expresses abnormally in various malignancies, what shows its role as oncogene. However, it has not been extensively studied in gastric cancer. The aim of the current study was to explore the clinical value of AP000695.2 to prognose gastric cancer.
Methods: The cancer genome atlas (TCGA) and the gene expression profiling interactive analysis (GEPIA) online tool were used to analyze AP000695.2 expression pattern, diagnostic and prognostic role in gastric cancer. Kaplan-Meier and Cox regression analyses were used to assess survival in patients with gastric cancer. Receiver operating curve (ROC) analysis was used to assess AP000695.2 diagnostic capacity. Nomograms were created to predict overall survival (OS) and progression free survival (PFS).
Results: LncRNA AP000695.2 was abnormally upregulated in 19 types of malignancy, including gastric cancer. Survival analysis indicated that high expression of AP000695.2 was associated with poor survival of gastric cancer. Multivariate Cox regression analysis verified the independent prognostic value of AP000695.2 to predict OS (HR (hazard ratio): 1.104, 95% CI (confidence interval): 1.035-1.178, p = 0.003) and PFS (HR: 1.170, 95% CI: 1.090-1.256, p < 0.001). ROC analysis indicated a favorable AP000695.2 diagnostic capacity (area under the curve (AUC) = 0.890). Nomograms were also constructed for OS and PFS based on AP000695.2 expression-related risk score. Additionally, AP000695.2 was found to be positively associated with tumor-infiltrating immune cells, including classically activated (M1) macrophages, neutrophils, alternatively activated (M2) macrophages, and natural killer (NK) cells.
Conclusions: It was observed that AP000695.2 can be used as a novel biomarker to diagnose or predict survival of gastric patient.
期刊介绍：
Discovery Medicine publishes novel, provocative ideas and research findings that challenge conventional notions about disease mechanisms, diagnosis, treatment, or any of the life sciences subjects. It publishes cutting-edge, reliable, and authoritative information in all branches of life sciences but primarily in the following areas: Novel therapies and diagnostics (approved or experimental); innovative ideas, research technologies, and translational research that will give rise to the next generation of new drugs and therapies; breakthrough understanding of mechanism of disease, biology, and physiology; and commercialization of biomedical discoveries pertaining to the development of new drugs, therapies, medical devices, and research technology.
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