Development and Clinical Validation of a 90-Gene Expression Assay for Identifying Tumor Tissue Origin

J Mol Diagn. 2020 Sep;22(9):1139-1150. doi: 10.1016/j.jmoldx.2020.06.005. Epub 2020 Jun 28.

Abstract

The accurate identification of tissue origin in patients with metastatic cancer is critical for effective treatment selection but remains a challenge. The aim of this study is to develop a gene expression assay for tumor molecular classification and integrate it with clinicopathologic evaluations to identify the tissue origin for cancer of uncertain primary (CUP). A 90-gene expression signature, covering 21 tumor types, was identified and validated with an overall accuracy of 89.8% (95% CI, 0.87-0.92) in 609 tumor samples. More specifically, the classification accuracy reached 90.4% (95% CI, 0.87-0.93) for 323 primary tumors and 89.2% (95% CI, 0.85-0.92) for 286 metastatic tumors, with no statistically significant difference (P = 0.71). Furthermore, in a real-life cohort of 141 CUP patients, predictions by the 90-gene expression signature were consistent or compatible with the clinicopathologic features in 71.6% of patients (101/141). Findings suggest that this novel gene expression assay could efficiently predict the primary origin for a broad spectrum of tumor types and support its diagnostic utility of molecular classification in difficult-to-diagnose metastatic cancer. Additional studies are ongoing to further evaluate the clinical utility of this novel gene expression assay in predicting primary site and directing therapy for CUP patients.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers, Tumor / genetics
  • Child
  • Data Accuracy
  • Female
  • Gene Expression Profiling / methods*
  • Genetic Association Studies / methods*
  • Humans
  • Male
  • Middle Aged
  • Neoplasms, Unknown Primary / genetics*
  • Neoplasms, Unknown Primary / pathology
  • Real-Time Polymerase Chain Reaction / methods*
  • Sensitivity and Specificity
  • Transcriptome*
  • Young Adult

Substances

  • Biomarkers, Tumor