A multi-gene expression profile panel for predicting liver metastasis: An algorithmic approach.

ABSTRACT:

Background & aim

Liver metastasis has been found to affect outcome in prostate, pancreatic and colorectal cancers, but its role in lung cancer is unclear. The 5 year survival rate remains extensively low owing to intrinsic resistance to conventional therapy which can be attributed to the genetic modulators involved in the pathogenesis of the disease. Thus, this study aims to generate a model for early diagnosis and timely treatment of liver metastasis in lung cancer patients.

Methods

mRNA expression of 15 genes was quantified by real time PCR on lung cancer specimens with (n = 32) and without (n = 30) liver metastasis and their normal counterparts. Principal Component analysis, linear discriminant analysis and hierarchical clustering were conducted to obtain a predictive mod

SUBMITTER: Shah K 

PROVIDER: S-EPMC6211708 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature