Computational pan-cancer characterization of model-based quantitative transcription regulations dysregulated in regional lymph node metastasis

Cancer is one of the major causes of mortality worldwide. Regional lymph node metastasis is an important mechanism during the spread of human cancers, in which transcription regulation plays an essential role. This study formulated a regression-model-based quantitative transcription regulation (mqTrans) between one mRNA gene and multiple transcription factors (TFs). Computational pan-cancer screening was carried out to detect the quantitative dysregulation of transcription regulation in the regional lymph node metastasis of 18 cancer types. Only a few metastasis-dysregulated mqTrans models were shared among the cancer types. The mRNA genes of the metastasis-dysregulated mqTrans models were not differentially expressed in regional lymph node metastasis. The experimental data suggested that mqTrans technology provided a complementary approach to the evaluation of transcription regulation mechanisms and may facilitate its quantitative investigation in other phenotypes.

Automated summary

This study developed a quantitative transcription regulation model based on regression analysis to analyze dysregulation in regional lymph node metastasis across 18 cancer types. Results revealed a few shared dysregulated models among cancer types, with mRNA genes in these models not showing differential expression during metastasis. The experimental data suggested that the mqTrans technology could complement the evaluation of transcription regulation mechanisms and aid in quantitative investigation of other phenotypes.