Gene Signature Determines Metastatic Behavior in Thymomas

Thymoma is a rare cancer of the thymus gland, and a molecular classifier would be useful to improve the assessment of metastatic behavior and optimize patient management.

Scientists at the Indiana University School of Medicine (Indianapolis, IN, USA) analyzed 111 cases of thymomas with follow up and archival blocks requested from multiple institutions. Thirty-six samples were selected for the training set based upon shortest and longest time to metastasis. The remaining samples were included in the validation set. The blocks were entirely composed of tumor in all but three cases and ribonucleic acid (RNA) was extracted from five 10-µm-thick sections.

Prediction Analysis of Microarrays (PAM) identified 10 genes associated with metastases and 9 genes associated with the stage of neoplasm. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to analyze the 19 discriminant genes, both metastases and stage related, and 4 control genes from formalin-fixed, paraffin-embedded (FFPE) primary thymomas. The gene test is called DecisionDx-Thymoma (Castle Biosciences; Phoenix, AZ, USA; www.castlebiosciences.com) and it was carried out at St. Joseph's Hospital and Medical Center (Phoenix, AZ, USA; www.stjosephs-phx.org). In the training set, five year and 10 year metastasis-free survival rates were 77% for the predicted Class 1 low risk for metastasis and 26% for Class 2 high risk for metastasis.


Sunil Badve, MD, FRCPath, a professor of pathology and laboratory medicine and lead author said, “Our studies established and validated a nine-gene signature which predicts the likelihood of metastasis more accurately than traditional staging methods, including Masaoka and extent of surgical resection. Since current guidelines recommend adjuvant radiation and chemotherapy for all resected patients with Stage II/III thymoma tumors, it can lead to under treatment of patients with aggressive tumors diagnosed at an early stage, and overtreatment of slow-growing tumors diagnosed at a later stage."


The authors concluded that the development and validation of a nine-gene prognostic assay serves as an independent predictor of metastasis-free survival and appears superior to currently used prognosticators such as Masaoka stage and histology. The current study provides a useful template for the efficient application of genetic expression data for the patient's benefit, especially in rare diseases. The study was published on July 24, 2013, in the journal Public Library of Science ONE.

Related Links:

Indiana University School of Medicine

St. Joseph's Hospital and Medical Center

Castle Biosciences