Scholarlink

<p>Messenger RNA (mRNA) stool based biomarkers represent a promising approach for the diagnosis of colorectal cancer (CRC) and advanced adenoma (AA). But it is unclear which mRNA biomarkers have the most clinical utility. This study aims to partially fill this gap by performing an analysis which first ranks genes based on their expression profile in publicly available RNA-seq tissue datasets. Each gene was ranked based on observed differential expression across the majority of tumors as well as the level of expression in tumor tissue. Those genes with strong differential expression across the majority of tumors that were also highly expressed would have a higher ranking. The top 20 genes as ranked in the bioinformatic analysis of tumor and normal colon tissue gene expression were then tested on 114 clinical stool samples (CRC <i>N</i> = 33, AA <i>N</i> = 28, Controls <i>N</i> = 53). Fourteen of the genes had significant differential expression in the stool of CRC patients compared to controls (false discovery rate or FDR &lt; 0.05). The Pearson correlation coefficient between tissue and stool expression was 0.57 (p-value = 0.007). The combined performance of the 20 genes in clinical stool samples had an area under the receiver operator curve (AUC) of 0.94 for CRC detection (sensitivity 75.5%, specificity 95%) and an AUC of 0.83 (sensitivity 55.8%, specificity 92.6%) for AA detection. The ability to use existing public transcriptomic datasets to identify promising candidate genes can substantially reduce the cost and effort required to screen for clinically useful mRNA biomarkers.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Bioinformatic screen with clinical validation for the identification of novel stool based mRNA biomarkers for the detection of colorectal lesions including advanced adenoma

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月11日

查看全文
  • Houcong Liu,
  • Loren Hansen,
  • Changpu Song,
  • Haijiu Lin,
  • Dan Chen,
  • Zhufang Chen,
  • Hekai Zhou,
  • Xiao Yang,
  • Wenying Pan,
  • Jihui Du

摘要

Messenger RNA (mRNA) stool based biomarkers represent a promising approach for the diagnosis of colorectal cancer (CRC) and advanced adenoma (AA). But it is unclear which mRNA biomarkers have the most clinical utility. This study aims to partially fill this gap by performing an analysis which first ranks genes based on their expression profile in publicly available RNA-seq tissue datasets. Each gene was ranked based on observed differential expression across the majority of tumors as well as the level of expression in tumor tissue. Those genes with strong differential expression across the majority of tumors that were also highly expressed would have a higher ranking. The top 20 genes as ranked in the bioinformatic analysis of tumor and normal colon tissue gene expression were then tested on 114 clinical stool samples (CRC N = 33, AA N = 28, Controls N = 53). Fourteen of the genes had significant differential expression in the stool of CRC patients compared to controls (false discovery rate or FDR < 0.05). The Pearson correlation coefficient between tissue and stool expression was 0.57 (p-value = 0.007). The combined performance of the 20 genes in clinical stool samples had an area under the receiver operator curve (AUC) of 0.94 for CRC detection (sensitivity 75.5%, specificity 95%) and an AUC of 0.83 (sensitivity 55.8%, specificity 92.6%) for AA detection. The ability to use existing public transcriptomic datasets to identify promising candidate genes can substantially reduce the cost and effort required to screen for clinically useful mRNA biomarkers.