Abstract 2525: Comprehensive analysis of thymic epithelial tumors using an integrated bioinformatics platform reveals novel biological characteristics

• Published in: Cancer research (Chicago, Ill.) Vol. 79; no. 13_Supplement; p. 2525
• Main Authors: Radovich, Milan, Solzak, Jeffrey P., Webster, Wade, Paquette, Jesse
• Format: Journal Article
• Language: English
• Published: 01.07.2019
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2019-2525

Abstract Introduction:Thymic epithelial tumors (TETs) are rare malignancies. Among TETs, thymoma is the most predominant, characterized by a unique association with myasthenia gravis, followed by thymic carcinoma which is less common but more clinically aggressive. The TCGA recently published a comprehensive analysis of 117 TETs using molecular profiling by exome-seq, RNA-seq, RPPA, and methylation. Using an integrated informatics platform we re-analyzed the TCGA TET data to identify novel biological characteristics of these rare tumors. Methods: Molecular and clinical data from the TCGA TET project was downloaded from the cbioportal database and imported into the tag.bio informatics platform. Tag.bio is a commercial cloud-based analysis platform that combines data, algorithms and question-based analysis protocols. It is used to for the rapid and reproducible statistical comparison of cohorts.Statistical analysis for differential expression, methylation, RPPA and mutational enrichment was performed using the Mann-Whitney test with multiple correction testing. Pathway and upstream regulator analysis were performed using Ingenuity Pathway Analysis. Results: Differential expression analysis of myasthenia gravis (MG) patients (N=32) compared to those with no history of MG (N=85), revealed the most significant gene as PPARGC1A (overexpressed, p<1e-8). This gene has not been previously associated with MG. PPARGC1A is highly expressed in skeletal muscle and mediates mitochondrial biogenesis. Supporting this observation, upstream regulator analysis was performed which identifies regulators that can explain the observed gene expression changes in a dataset. The results demonstrated that PPARGC1A as the most activated transcriptional regulator in MG+ tumors and may represent a novel autoantigen for MG. TETs are relatively indolent tumors, and only a small subset metastasizes. Differential expression in a subset of Stage IV tumors (N=6) identified overexpressed FGFR3. Of note, a previous study identified two patients with activating mutations in FGFR3. A genomic hallmark of Thymic Carcinoma (TC) is Chr16q loss. Several tumor suppressors reside on 16q, including:CYLD, CBFB, CDH1, CDH11, CTCF, ZFHX3, but the exact causative candidate is unknown. Analysis of the mutational data identified 2 of 10 patients with concurrent 16q loss and deleterious mutations in CYLD, congruent with previous reports of recurrent mutations in CYLD in TC. CYLD has been previously demonstrated to regulate STAT3. Differential expression followed by upstream regulator analysis of TC vs Thymoma demonstrated activated STAT3 in TC. Conclusion:Re-analysis of the TCGA TET dataset using a novel integrated bioinformatics platform identified novel biology of TETs including: PPARGC1A association with MG; FGFR3 expression in TET metastasis; and CYLD/STAT3 axis in TC. Citation Format: Milan Radovich, Jeffrey P. Solzak, Wade Webster, Jesse Paquette. Comprehensive analysis of thymic epithelial tumors using an integrated bioinformatics platform reveals novel biological characteristics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2525.