Weihong Chen, Dongqin Huang, Xiaoping Su, Yuchao Su, Shaobin Li
{"title":"生物信息学分析和鉴定结直肠癌中与杯突症相关的长非编码 RNA。","authors":"Weihong Chen, Dongqin Huang, Xiaoping Su, Yuchao Su, Shaobin Li","doi":"10.1177/03000605241274563","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs).</p><p><strong>Methods: </strong>In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR).</p><p><strong>Results: </strong>Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m<sup>6</sup>A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated.</p><p><strong>Conclusion: </strong>Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.</p>","PeriodicalId":16129,"journal":{"name":"Journal of International Medical Research","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11350552/pdf/","citationCount":"0","resultStr":"{\"title\":\"Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer.\",\"authors\":\"Weihong Chen, Dongqin Huang, Xiaoping Su, Yuchao Su, Shaobin Li\",\"doi\":\"10.1177/03000605241274563\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs).</p><p><strong>Methods: </strong>In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR).</p><p><strong>Results: </strong>Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m<sup>6</sup>A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated.</p><p><strong>Conclusion: </strong>Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.</p>\",\"PeriodicalId\":16129,\"journal\":{\"name\":\"Journal of International Medical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11350552/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of International Medical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/03000605241274563\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of International Medical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/03000605241274563","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer.
Objective: Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs).
Methods: In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR).
Results: Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m6A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated.
Conclusion: Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.
期刊介绍：
_Journal of International Medical Research_ is a leading international journal for rapid publication of original medical, pre-clinical and clinical research, reviews, preliminary and pilot studies on a page charge basis.
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