Predicting cancer type from tumour DNA signatures.

ABSTRACT:

Background

Establishing the cancer type and site of origin is important in determining the most appropriate course of treatment for cancer patients. Patients with cancer of unknown primary, where the site of origin cannot be established from an examination of the metastatic cancer cells, typically have poor survival. Here, we evaluate the potential and limitations of utilising gene alteration data from tumour DNA to identify cancer types.

Methods

Using sequenced tumour DNA downloaded via the cBioPortal for Cancer Genomics, we collected the presence or absence of calls for gene alterations for 6640 tumour samples spanning 28 cancer types, as predictive features. We employed three machine-learning techniques, namely linear support vector machines with recursive feature selecti

SUBMITTER: Soh KP 

PROVIDER: S-EPMC5706302 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature