Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer
Abstract The current staging method is inadequate to identify high-risk recurrence patients with stage II colon cancer (CC). Using a systematic and comprehensive-biomarker discovery and validation method, we aimed to construct a lncRNA-based signature to improve the prognostic prediction of stage II...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-25852-5 |
| _version_ | 1811175947861229568 |
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| author | Ailin Qu Qian Wang Qing Chang Jingkang Liu Yongmei Yang Xin Zhang Yanli Zhang Xiaoshi Zhang Hongchun Wang Yi Zhang |
| author_facet | Ailin Qu Qian Wang Qing Chang Jingkang Liu Yongmei Yang Xin Zhang Yanli Zhang Xiaoshi Zhang Hongchun Wang Yi Zhang |
| author_sort | Ailin Qu |
| collection | DOAJ |
| description | Abstract The current staging method is inadequate to identify high-risk recurrence patients with stage II colon cancer (CC). Using a systematic and comprehensive-biomarker discovery and validation method, we aimed to construct a lncRNA-based signature to improve the prognostic prediction of stage II CC. We identified 1,377 differently expressed lncRNAs by analyzing 16 paired stage II CC tumor tissue and adjacent normal mucosal tissue from the TCGA dataset. Subsequently, using a univariable and step multivariable Cox regression model, we trained an 11-lncRNA signature in the training cohort (n = 141), which could divide patients into high-risk and low-risk groups (AUC at 3 years = 0.801, 95% CI: 0.724–0.877; AUC at 5 years = 0.801, 95% CI: 0.718–0.885). Significantly, patients in the high-risk group had poorer recurrence-free survival (RFS) compared with the low-risk group (log-rank test, P < 0.001 in the training cohort). This lncRNA-based signature was further confirmed in the validation cohort (P < 0.001). Multivariate Cox regression and stratified survival analyses showed that the prognostic value of this signature was independent of other clinicopathological risk factors (CEA, T stage, and chemotherapy). Time-dependent receiver operating characteristic (ROC) analysis demonstrated that this signature had better prognostic ability than any other clinical risk factors or single lncRNAs (all P < 0.05). A nomogram was constructed for clinical use, which integrated both the lncRNA-based signature and clinical risk factors (CEA and T stage) and performed well in the calibration plots. Altogether, our lncRNA-based signature was an independent prognostic factor and possessed a stronger predictive power compared with the currently used clinicopathological risk factors when predicting the recurrence of patients with stage II CC. Collectively, this lncRNA-based signature might facilitate individualized treatment decisions and postoperative counseling, ultimately contributing to improved survival. |
| first_indexed | 2024-04-10T19:44:16Z |
| format | Article |
| id | doaj.art-8b45de38deaa48ac9098fbb556f278ea |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-10T19:44:16Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-8b45de38deaa48ac9098fbb556f278ea2023-01-29T12:08:32ZengNature PortfolioScientific Reports2045-23222023-01-0113111110.1038/s41598-022-25852-5Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancerAilin Qu0Qian Wang1Qing Chang2Jingkang Liu3Yongmei Yang4Xin Zhang5Yanli Zhang6Xiaoshi Zhang7Hongchun Wang8Yi Zhang9Department of Clinical Laboratory, Qilu Hospital, Shandong UniversityDepartment of Gastroenterology, Central Hospital, Shandong First Medical UniversityDepartment of Clinical Laboratory, Qilu Hospital, Shandong UniversityDepartment of Gynecology, Qilu Hospital, Shandong UniversityDepartment of Clinical Laboratory, Qilu Hospital, Shandong UniversityDepartment of Clinical Laboratory, Qilu Hospital, Shandong UniversityDepartment of Clinical Laboratory, Shandong Provincial Third HospitalDepartment of Clinical Laboratory, Qilu Hospital, Shandong UniversityDepartment of Clinical Laboratory, Qilu Hospital, Shandong UniversityDepartment of Clinical Laboratory, Qilu Hospital, Shandong UniversityAbstract The current staging method is inadequate to identify high-risk recurrence patients with stage II colon cancer (CC). Using a systematic and comprehensive-biomarker discovery and validation method, we aimed to construct a lncRNA-based signature to improve the prognostic prediction of stage II CC. We identified 1,377 differently expressed lncRNAs by analyzing 16 paired stage II CC tumor tissue and adjacent normal mucosal tissue from the TCGA dataset. Subsequently, using a univariable and step multivariable Cox regression model, we trained an 11-lncRNA signature in the training cohort (n = 141), which could divide patients into high-risk and low-risk groups (AUC at 3 years = 0.801, 95% CI: 0.724–0.877; AUC at 5 years = 0.801, 95% CI: 0.718–0.885). Significantly, patients in the high-risk group had poorer recurrence-free survival (RFS) compared with the low-risk group (log-rank test, P < 0.001 in the training cohort). This lncRNA-based signature was further confirmed in the validation cohort (P < 0.001). Multivariate Cox regression and stratified survival analyses showed that the prognostic value of this signature was independent of other clinicopathological risk factors (CEA, T stage, and chemotherapy). Time-dependent receiver operating characteristic (ROC) analysis demonstrated that this signature had better prognostic ability than any other clinical risk factors or single lncRNAs (all P < 0.05). A nomogram was constructed for clinical use, which integrated both the lncRNA-based signature and clinical risk factors (CEA and T stage) and performed well in the calibration plots. Altogether, our lncRNA-based signature was an independent prognostic factor and possessed a stronger predictive power compared with the currently used clinicopathological risk factors when predicting the recurrence of patients with stage II CC. Collectively, this lncRNA-based signature might facilitate individualized treatment decisions and postoperative counseling, ultimately contributing to improved survival.https://doi.org/10.1038/s41598-022-25852-5 |
| spellingShingle | Ailin Qu Qian Wang Qing Chang Jingkang Liu Yongmei Yang Xin Zhang Yanli Zhang Xiaoshi Zhang Hongchun Wang Yi Zhang Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer Scientific Reports |
| title | Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer |
| title_full | Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer |
| title_fullStr | Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer |
| title_full_unstemmed | Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer |
| title_short | Prognostic and predictive value of a lncRNA signature in patients with stage II colon cancer |
| title_sort | prognostic and predictive value of a lncrna signature in patients with stage ii colon cancer |
| url | https://doi.org/10.1038/s41598-022-25852-5 |
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