Supervised hierarchical clustering of the fresh-frozen thymomas based on the histologic groups.

<p>The figure comprises of 34 tumors (GI = group I (type AB), GII = group II (types B1–B2), and GIII = group III (type B3) and one duplicate.</p

Unsupervised hierarchical clustering of the 34 fresh-frozen thymomas showing four distinct clusters (C1–C4).

<p>One sample is included as the duplicate.</p

Biological processes and canonical pathways associated with metastasis and stage using Ingenuity Pathways Analysis.

<p>The top ten significant biological functions. (A) Metastasis, (B) stage, and canonical pathways. (C) Metastasis and (D) stage were grouped based on the <i>P</i> values using right tailed Fisher exact test and with threshold less than 0.05.</p

Heat map representing the mRNA levels of <i>AKR1B10</i>, <i>JPH1</i>, and <i>COL11A1</i> genes using TaqMan qPCR system.

<p>Data is normalized to the geometric mean of the reference genes <i>IPO8 and TFRC</i>. The heat map is generated using the Applied Biosystems DataAssist™ v3.0 software. M, tumors associated with metastasis, N, tumors with no metastasis.</p

Clinical characteristics of the patients included in the gene expression analysis.

<p>Clinical characteristics of the patients included in the gene expression analysis.</p

A Gene Signature to Determine Metastatic Behavior in Thymomas

<div><p>Purpose</p><p>Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management.</p><p>Methods</p><p>qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (<i>n</i> = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (<i>n</i> = 75).</p><p>Results</p><p>A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (<i>P</i> = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (<i>P</i> = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (<i>P</i> = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (<i>P</i> = 0.036).</p><p>Conclusion</p><p>A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.</p></div

Kaplan-Meier curves for metastasis-free survival (MFS) in the validation set cohort of samples.

<p>MFS is grouped according to Masaoka staging (A), WHO classification (B), extent of resection (C), or predicted nine-gene signature class 1 (low metastatic potential) or class 2 (high metastatic potential) as determined by radial basis machine predictive modeling algorithm (D). Numbers of cases at risk at two-year time points are shown below each graph, and 5- and 10-year MFS is presented. <i>P</i> values for each classification system were calculated by log-rank method. <i>GEP, gene expression profile; NED, no evidence of disease; RD, residual disease, WHO, World Health Organization</i>.</p

Kaplan-Meier curves for metastasis-free survival (MFS) in the training set cohort of samples.

<p>MFS is grouped according to Masaoka staging (A), WHO classification (B), extent of resection (C), or predicted nine-gene signature class 1 (low metastatic potential) or class 2 (high metastatic potential) as determined by radial basis machine predictive modeling algorithm (D). Numbers of cases at risk at two-year time points are shown below each graph, and 5- and 10-year MFS is presented. <i>P</i> values for each classification system were calculated by log-rank method. <i>GEP, gene expression profile; NED, no evidence of disease; RD, residual disease, WHO, World Health Organization</i>.</p

Univariate and multivariate analysis of the independent 75-sample validation set.

<p><i>CI, confidence interval; HR, hazard ratio</i>.</p>*<p><b><i>P≤0.05 is considered as statistically significant</i></b>.</p

Baseline demographics of training set and independent validation set.

<p><i>CT, chemotherapy; MFS, metastasis-free survival; RT, radiation therapy</i>.</p