Development and validation of a prediction model for metastasis in colorectal cancer based on LncRNA CRNDE and radiomics. Issue 1 (17th July 2022)
- Record Type:
- Journal Article
- Title:
- Development and validation of a prediction model for metastasis in colorectal cancer based on LncRNA CRNDE and radiomics. Issue 1 (17th July 2022)
- Main Title:
- Development and validation of a prediction model for metastasis in colorectal cancer based on LncRNA CRNDE and radiomics
- Authors:
- Zhao, Jiaojiao
Jiang, Ou
Chen, Xiao
Liu, Qin
Li, Xue
Wu, Min
Zhang, Yan
Zeng, Fanxin - Abstract:
- Abstract: Accurate prediction of metastasis is an important determinant for selecting appropriate treatment for advanced colorectal cancer (CRC). In this study, 1250 patients in two hospitals from 2014 to 2019 histologically diagnosed with CRC were enrolled. We performed the transcriptome analysis on 141 CRC patients. RNA‐seq analysis revealed that long noncoding RNA (LncRNA) colorectal neoplasia differentially expressed (CRNDE) played an important role in CRC metastasis. The least absolute shrinkage and selection operator regression was used to select features and develop radiomics model. Multivariate logistic regression analysis was used to develop combined model. The radiomics model with 13 filtered radiomics features had good discrimination in predicting expression level of LncRNA CRNDE in training set (receiver operating characteristic [AUC] = 0.809) and testing set (AUC = 0.755). Furthermore, the radiomics model could predict the metastasis of CRC in internal validation set (AUC, 0.665) and in external validation set (AUC = 0.690). The combined model developed with radiomics score and carcinoembryonic antigen had better performance, and the AUC was 0.708, 0.700 in internal validation set and in external validation set, respectively. In conclusion, we proposed a radiomics model and combined model, which could predict the expression level of LncRNA CRNDE and further predict CRC metastasis, thereby helping clinician make treatment decisions. Abstract : The gene setAbstract: Accurate prediction of metastasis is an important determinant for selecting appropriate treatment for advanced colorectal cancer (CRC). In this study, 1250 patients in two hospitals from 2014 to 2019 histologically diagnosed with CRC were enrolled. We performed the transcriptome analysis on 141 CRC patients. RNA‐seq analysis revealed that long noncoding RNA (LncRNA) colorectal neoplasia differentially expressed (CRNDE) played an important role in CRC metastasis. The least absolute shrinkage and selection operator regression was used to select features and develop radiomics model. Multivariate logistic regression analysis was used to develop combined model. The radiomics model with 13 filtered radiomics features had good discrimination in predicting expression level of LncRNA CRNDE in training set (receiver operating characteristic [AUC] = 0.809) and testing set (AUC = 0.755). Furthermore, the radiomics model could predict the metastasis of CRC in internal validation set (AUC, 0.665) and in external validation set (AUC = 0.690). The combined model developed with radiomics score and carcinoembryonic antigen had better performance, and the AUC was 0.708, 0.700 in internal validation set and in external validation set, respectively. In conclusion, we proposed a radiomics model and combined model, which could predict the expression level of LncRNA CRNDE and further predict CRC metastasis, thereby helping clinician make treatment decisions. Abstract : The gene set enrichment analysis results based on the group of different expression level of long noncoding RNA (LncRNA) colorectal neoplasia differentially expressed (CRNDE) illustrated that CRNDE played an important role in tumor metastasis. The radiomics model with 13 radiomics features which had good discrimination in predicting expression level of LncRNA CRNDE in training set (AUC, 0.809) and testing set (AUC = 0.755). The combined model with radiomics score and carcinoembryonic antigen could help clinician make treatment decisions. … (more)
- Is Part Of:
- MedComm. Volume 1:Issue 1(2022)
- Journal:
- MedComm
- Issue:
- Volume 1:Issue 1(2022)
- Issue Display:
- Volume 1, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 1
- Issue:
- 1
- Issue Sort Value:
- 2022-0001-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-07-17
- Subjects:
- colorectal cancer -- LncRNA CRNDE -- prediction model -- radiomics -- transcriptome
Medical innovations -- Periodicals
Medicine -- Research -- Periodicals
Biology -- Research
Medicine -- Research
Periodicals
610.72 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/27696456 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mef2.6 ↗
- Languages:
- English
- ISSNs:
- 2769-6456
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23927.xml