The highlight of this study lies in the acquisition of a set of characteristic genes associated with CRC through multi-omics research and machine learning methods. By leveraging the features extracted from IHC images, we have developed a highly robust diagnostic model using machine learning techniques, which significantly contributes to the diagnosis of CRC and advances precision medicine.
Multi-omics analysis refers to the comprehensive utilization of diverse biological data types including genomics, transcriptomics, proteomics, metabolomics, etc., aiming to gain a holistic understanding of tumor diseases. Its advantage lies in its ability to simultaneously consider multiple levels of biological information ranging from genes, RNA molecules, proteins to metabolites thus enabling a more comprehensive and profound understanding of tumor diseases. In this study, potential characteristic markers for CRC were identified through comprehensive analysis and cross-validation across different datasets. These markers may be implicated in tumor initiation, progression as well as treatment response; thereby facilitating improved diagnosis and treatment outcomes for this disease.
After conducting comprehensive validation of differential analysis, employing SVM-RFE and Random Forest algorithm, assessing protein expression levels, and performing IHC analysis, we ultimately identified four specific markers for CRC, namely AKR1B10, CA2, DHRS9, and
How do you envision these gene markers being used in clinical practice, and what precautions would need to be taken to avoid potential overdiagnosis or unnecessary treatment? [[1](https://www.nature.com/articles/s41379-018-0136-1)]
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**Interviewer:** Joining us today is Dr. [Guest Name], lead author of a groundbreaking new study on colorectal cancer. Dr. [Guest Name], your research identified four specific genes as potential markers for CRC. Can you elaborate on the significance of this finding?
**Dr. [Guest Name]:** Absolutely. This study used a multi-omics approach, meaning we combined data from genomics, transcriptomics, proteomics, and other fields to get a complete picture of the disease. We believe these four genes, AKR1B10, CA2, DHRS9, and [Fourth Gene Name], could be key players in the development and progression of CRC.
**Interviewer:** This could revolutionize diagnosis and treatment. But some might say relying on genetic markers alone could lead to overdiagnosis or unnecessary treatment. What’s your response to that?
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