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<p>Colorectal cancer (CRC) is the third most commonly diagnosed malignant tumour in worldwide populations. Although colon cancer (CC) and rectal cancer (RC) are often discussed together, there is a global trend towards considering them as two separate disease entities. It is necessary to choice the appropriate treatment for CC and RC based on their own characteristics. Hence, it is a great importance to find effective biomarkers to distinguish CC from RC. In the present study, a total of 343 participants were recruited, including 132 healthy individuals, 101 patients with CC, and 110 patients with RC. The concentrations of 93 metabolites were determined by using a combination of dried blood spot sampling and direct infusion mass spectrometry technology. Multiple algorithms were applied to characterize altered metabolic profiles in CC and RC. Significantly altered metabolites were screened for distinguishing RC from CC in training set. A biomarker panel including Glu, C0, C8, C20, Gly/Ala, and C10:1 was tested with tenfold cross-validation and an independent test set, and showed the potential to distinguish between RC and CC. The metabolomics analysis makes contribution to summarize the metabolic differences in RC and CC, which might provide further guidance on novel clinical designs for the two diseases.</p>

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Altered metabolic profiles in colon and rectal cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月2日

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  • Xue Wu,
  • Qi Yang,
  • Li Leng,
  • Peng Yang,
  • Zhitu Zhu

摘要

Colorectal cancer (CRC) is the third most commonly diagnosed malignant tumour in worldwide populations. Although colon cancer (CC) and rectal cancer (RC) are often discussed together, there is a global trend towards considering them as two separate disease entities. It is necessary to choice the appropriate treatment for CC and RC based on their own characteristics. Hence, it is a great importance to find effective biomarkers to distinguish CC from RC. In the present study, a total of 343 participants were recruited, including 132 healthy individuals, 101 patients with CC, and 110 patients with RC. The concentrations of 93 metabolites were determined by using a combination of dried blood spot sampling and direct infusion mass spectrometry technology. Multiple algorithms were applied to characterize altered metabolic profiles in CC and RC. Significantly altered metabolites were screened for distinguishing RC from CC in training set. A biomarker panel including Glu, C0, C8, C20, Gly/Ala, and C10:1 was tested with tenfold cross-validation and an independent test set, and showed the potential to distinguish between RC and CC. The metabolomics analysis makes contribution to summarize the metabolic differences in RC and CC, which might provide further guidance on novel clinical designs for the two diseases.