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Genomic Analysis of Thymic Epithelial Tumors Identifies Novel Subtypes Associated with Distinct Clinical Features.

ABSTRACT: Purpose: To reconcile the heterogeneity of thymic epithelial tumors (TET) and gain deeper understanding of the molecular determinants of TETs, we set out to establish a clinically relevant molecular classification system for these tumors.Experimental Design: Molecular subgrouping of TETs was performed in 120 patients from The Cancer Genome Atlas using a multidimensional approach incorporating analyses of DNA mutations, mRNA expression, and somatic copy number alterations (SCNA), and validated in two independent cohorts.Results: Four distinct molecular subtypes of TETs were identified. The most commonly identified gene mutation was a missense mutation in General Transcription Factor II-I (GTF2I group), which was present in 38% of patients. The next group was identified by unsupervised mRNA clustering of GTF2I wild-type tumors and represented TETs enriched in expression of genes associated with T-cell signaling (TS group; 33%). The remaining two groups were distinguished by their degree of chromosomal stability (CS group; 8%) or instability (CIN group; 21%) based upon SCNA analyses. Disease-free survival and overall survival were favorable in the GTF2I group and unfavorable in the CIN group. These molecular subgroups were associated with TET histology and clinical features including disease-free survival. Finally, we demonstrate high expression of PD1 mRNA and correlation of PD1 and CD8A in the TS subgroup.Conclusions: Molecular subtyping of TETs is associated with disease-free and overall survival. Classification of TETs by a molecular framework could aid in the refinement of staging and in the discovery and development of rational treatment options for patients with TETs. Clin Cancer Res; 23(16); 4855-64. ©2017 AACR.

SUBMITTER: Lee HS

PROVIDER: S-EPMC5559309 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Genomic Analysis of Thymic Epithelial Tumors Identifies Novel Subtypes Associated with Distinct Clinical Features.

Lee Hyun-Sung HS Jang Hee-Jin HJ Shah Rohan R Yoon David D Hamaji Masatsugu M Wald Ori O Lee Ju-Seog JS Sugarbaker David J DJ Burt Bryan M BM

Clinical cancer research : an official journal of the American Association for Cancer Research 20170411 16

<b>Purpose:</b> To reconcile the heterogeneity of thymic epithelial tumors (TET) and gain deeper understanding of the molecular determinants of TETs, we set out to establish a clinically relevant molecular classification system for these tumors.<b>Experimental Design:</b> Molecular subgrouping of TETs was performed in 120 patients from The Cancer Genome Atlas using a multidimensional approach incorporating analyses of DNA mutations, mRNA expression, and somatic copy number alterations (SCNA), an ...[more]

PMID: 28400429

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Project description:To determine the prognostic CT features in patients with untreated thymic epithelial tumors (TETs). Clinical data and CT imaging features of 194 patients with pathologically confirmed TETs were retrospectively reviewed. The subjects included 113 male and 81 female patients between 15 and 78 years of age, with a mean age of 53.8 years. Clinical outcomes were categorized according to whether relapse, metastasis or death occurred within 3 years after the first diagnosis. Associations between clinical outcomes and CT imaging features were determined using univariate and multivariate logistic regression analyses, while the survival status was analyzed by Cox regression. In this study, we analyzed 110 thymic carcinomas, 52 high-risk thymomas and 32 low-risk thymomas. Percentages of poor outcome and patient death in thymic carcinomas were much higher than those in patients with high-risk and low-risk thymomas. In the thymic carcinomas groups, 46 patients (41.8%) experienced tumor progression, local relapse or metastasis and were categorized as having poor outcomes; vessel invasion and pericardial mass were confirmed to be independent predictors by logistic regression analysis (p < 0.01). In the high-risk thymoma group, 11 patients (21.2%) were categorized as having poor outcomes, and the CT feature pericardial mass was confirmed to be an independent predictor (p < 0.01). In survival analysis, Cox regression showed that CT features of lung invasion, great vessel invasion, lung metastasis and distant organ metastasis were independent predictors for worse survival in the thymic carcinoma group (p < 0.01), while lung invasion and pericardial mass were independent predictors for worse survival in high-risk thymoma group. No CT features were related to poor outcome and worse survival in the low-risk thymoma group. Patients with thymic carcinoma had poorer prognosis and worse survival than those with high-risk or low-risk thymoma. CT can serve as an important tool for predicting the prognosis and survival of patients with TETs. In this cohort, CT features of vessel invasion and pericardial mass were related to poorer outcomes in those with thymic carcinoma and pericardial mass in those with high-risk thymoma. Features including lung invasion, great vessel invasion, lung metastasis and distant organ metastasis indicate worse survival in thymic carcinoma, whereas lung invasion and pericardial mass indicate worse survival in high-risk thymoma.

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Genomic Analysis of Thymic Epithelial Tumors Identifies Novel Subtypes Associated with Distinct Clinical Features.

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Genomic Analysis of Thymic Epithelial Tumors Identifies Novel Subtypes Associated with Distinct Clinical Features.

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