Development of Genome-Derived Tumor Type Prediction to Inform Clinical Cancer Care.

ABSTRACT:

Importance

Diagnosing the site of origin for cancer is a pillar of disease classification that has directed clinical care for more than a century. Even in an era of precision oncologic practice, in which treatment is increasingly informed by the presence or absence of mutant genes responsible for cancer growth and progression, tumor origin remains a critical factor in tumor biologic characteristics and therapeutic sensitivity.

Objective

To evaluate whether data derived from routine clinical DNA sequencing of tumors could complement conventional approaches to enable improved diagnostic accuracy.

Design, setting, and participants

A machine learning approach was developed to predict tumor type from targeted panel DNA sequence data obtained at the point of care, incorpora

SUBMITTER: Penson A 

PROVIDER: S-EPMC6865333 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature