Identification of biomarkers predictive of metastasis development in early-stage colorectal cancer using network-based regularization.

ABSTRACT: Colorectal cancer (CRC) is the third most common cancer and the second most deathly worldwide. It is a very heterogeneous disease that can develop via distinct pathways where metastasis is the primary cause of death. Therefore, it is crucial to understand the molecular mechanisms underlying metastasis. RNA-sequencing is an essential tool used for studying the transcriptional landscape. However, the high-dimensionality of gene expression data makes selecting novel metastatic biomarkers problematic. To distinguish early-stage CRC patients at risk of developing metastasis from those that are not, three types of binary classification approaches were used: (1) classification methods (decision trees, linear and radial kernel support vector machines, logistic regression, and random forest) using

SUBMITTER: Peixoto C 

PROVIDER: S-EPMC9841719 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature