Increased Expression of VANGL1 is Predictive of Lymph Node Metastasis in Colorectal Cancer: Results from a 20-Gene Expression Signature
This study aimed at building a prognostic signature based on a candidate gene panel whose expression may be associated with lymph node metastasis (LNM), thus potentially able to predict colorectal cancer (CRC) progression and patient survival. The mRNA expression levels of 20 candidate genes were ev...
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Published in | Journal of personalized medicine Vol. 11; no. 2; p. 126 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI
14.02.2021
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Subjects | |
Online Access | Get full text |
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Summary: | This study aimed at building a prognostic signature based on a candidate gene panel whose expression may be associated with lymph node metastasis (LNM), thus potentially able to predict colorectal cancer (CRC) progression and patient survival. The mRNA expression levels of 20 candidate genes were evaluated by RT-qPCR in cancer and normal mucosa formalin-fixed paraffin-embedded (FFPE) tissues of CRC patients. Receiver operating characteristic curves were used to evaluate the prognosis performance of our model by calculating the area under the curve (AUC) values corresponding to stage and metastasis. A total of 100 FFPE primary tumor tissues from stage I-IV CRC patients were collected and analyzed. Among the 20 candidate genes we studied, only the expression levels of
significantly varied between patients with and without LNMs (
= 0.02). Additionally, the AUC value of the 20-gene panel was found to have the highest predictive performance (i.e., AUC = 79.84%) for LNMs compared with that of two subpanels including 5 and 10 genes. According to our results,
gene expression levels are able to estimate LNMs in different stages of CRC. After a proper validation in a wider case series, the evaluation of
gene expression and that of the 20-gene panel signature could help in the future in the prediction of CRC progression. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2075-4426 2075-4426 |
DOI: | 10.3390/jpm11020126 |