Links

Tools

Export citation

Search in Google Scholar

Wading through the noise of "multi-omics" to identify prognostic biomarkers in hepatocellular carcinoma.

Journal article published in 2015 by Karen Pineda-Solis, Vivian C. McAlister
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Question mark in circle
Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

Multi-omics, the molecular analysis of genes, transcriptional RNA and proteins, allows researchers document the mechanism of action of a target gene. However multi-omics may result in an avalanche of information when used to screen a population. It is very difficult to discern a pattern or signal related to a disease or its progression. Differential multi-omics exploits our ability to see differences between subjects who are similar in all respects except for the outcome being tested. Twin studies are an example of this. Miao and colleagues compared two patients who had diverse outcomes following treatment of multi-focal hepatocellular carcinoma (HCC) to identify seven candidates as the responsible genes. In a larger cohort of patients with HCC they narrowed the field down to a single target down. By looking at progression of HCC, they isolated TTK, a protein kinase which disrupts the interaction of the tumour suppressor p53 with the oncogene MDM2. TTK-high tumours recurred 3 times faster than TTK-low tumours.