Abstract
In recent years, the use of gene expression analysis to predict the occurrence and development of cancer has become a hot research field. However, existing gene expression prediction models face some limitations, such as complex sample processing and high cost, which limit their clinical application. There is currently a lack of ideal markers for colorectal cancer. Although some tumor markers have been used for clinical prediction, diagnosis and treatment of colorectal cancer, their sensitivity is low and often can not meet the needs of early clinical tumor prediction. This study aims to explore a new, low-cost cancer prediction method that uses optical imaging technology combined with gene expression analysis to predict the association between tumor marker LINC01207 and cancer, providing a new strategy for the early diagnosis of cancer. The study used an advanced optical imaging system combined with gene expression data analysis methods to study the expression patterns of LINC01207 in cancer. The findings show that LINC01207 has been shown to promote the aggressiveness and migration of CRC cells, suggesting that it may play a key role in the metastasis of the disease, making it a potential marker for predicting the progression and prognosis of the disease. The identification of LINC01207 as a potential biomarker for CRC has important implications for the diagnosis and treatment of the disease. By utilizing LINC01207 as a predictive marker, it may be possible to identify patients at high risk for colorectal cancer and initiate early intervention to prevent or delay disease progression.
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This study was supported by Reserve outstanding talents of Shanghai University of traditional Chinese Medicine (RCPY0037).
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GH has done the first version, WC, WP and YC has done the simulations. All authors have contributed to the paper’s analysis, discussion, writing, and revision.
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Hu, G., Chen, W., Peng, W. et al. Application of optical imaging technology for prediction of rectal cancer using tumor marker LINC01207 based on gene expression. Opt Quant Electron 56, 438 (2024). https://doi.org/10.1007/s11082-023-06140-6
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DOI: https://doi.org/10.1007/s11082-023-06140-6