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Deciphering tissue-based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors.

ABSTRACT: Thymic epithelial tumors (TETs) belong to a group of tumors that rarely occur, but have unresolved mechanisms and heterogeneous clinical behaviors. Current care of TET patients demands biomarkers of high sensitivity and specificity for accurate histological classification and prognosis management. In this study, 134 fresh-frozen tissue samples (84 tumor, 40 tumor adjacent, and 10 normal thymus) were recruited to generate a quantitative and systematic view of proteomic landscape of TETs. Among them, 90 samples were analyzed by data-independent acquisition mass spectrometry (DIA-MS) leading to discovery of novel classifying molecules among different TET subtypes. The correlation between clinical outcome and the identified molecules was probed, and the prioritized proteins of interest were further validated on the remaining samples (n = 44) via parallel reaction monitoring (PRM) as well as immunohistochemical and confocal imaging analysis. In particular, two proteins, the cellular mRNA deadenylase CCR4 (carbon catabolite repressor 4)-NOT (negative on TATA) complex subunit 2/9 (CNOT2/9) and the serine hydroxymethyltransferase that catalyzes the reversible interconversions of serine and glycine (SHMT1), were found at dramatic low levels in the thymic epithelia of more malignant subtype, thymic squamous cell carcinoma (TSCC). Interestingly, the mRNA levels of these two genes were shown to be closely correlated with prognosis of the TET patients. These results extended the existing human tissue proteome atlas and allowed us to identify several new protein classifiers for TET subtyping. Newly identified subtyping and prognosis markers, CNOT2/9 and SHMT1, will expand current diagnostic arsenal in terms of higher specificity and prognostic insights for TET diagnosis and management.

SUBMITTER: Ku X

PROVIDER: S-EPMC7138395 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Deciphering tissue-based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors.

Ku Xin X Sun Qiangling Q Zhu Lei L Gu Zhitao Z Han Yuchen Y Xu Ning N Meng Chen C Yang Xiaohua X Yan Wei W Fang Wentao W

Molecular oncology 20200206 4

Thymic epithelial tumors (TETs) belong to a group of tumors that rarely occur, but have unresolved mechanisms and heterogeneous clinical behaviors. Current care of TET patients demands biomarkers of high sensitivity and specificity for accurate histological classification and prognosis management. In this study, 134 fresh-frozen tissue samples (84 tumor, 40 tumor adjacent, and 10 normal thymus) were recruited to generate a quantitative and systematic view of proteomic landscape of TETs. Among th ...[more]

PMID: 31967407

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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.

Project description:BACKGROUND:The current prognosis of thymic epithelial tumors (TETs) is according to the World Health Organization (WHO) histologic classification and the Masaoka staging system. These methods of prognosis have certain limitations in clinical application and there is a need to seek new method for determining the prognosis of patients with TETs. To date, there have been no studies done on the use of DNA methylation biomarkers for prognosis of TETs. The present study was therefore carried out to identify DNA methylation biomarkers that can determine the overall survival in patients with TETs. METHODS:Bioinformatic analysis of TCGA 450 K methylation array data, transcriptome sequencing data, WHO histologic classification and Masaoka staging system was performed to identify differentially expressed methylation sites between thymoma and thymic carcinoma as well as the different DNA methylation sites associated with the overall survival in patients with TETs. Using pyrosequencing, 4 different methylation sites (cg05784862, cg07154254, cg02543462, and cg06288355) were sequenced from tumor tissues of 100 Chinese patients with TETs. A prognostic model for TETs was constructed using these four methylation sites. RESULTS:The TCGA dataset showed 5155 and 6967 hyper- and hypomethylated CpG sites in type A-B3 group and type C group, respectively, of which 3600 were located within the gene promoter regions. One hundred thirty-four genes were silenced by promoter hypermethylation and 174 mRNAs were upregulated. Analysis of univariate and multivariate Cox regression showed significant association between the methylation levels of 187 sites and the overall survival in patients with TETs. cg05784862(KSR1), cg07154254(ELF3), cg02543462(ILRN), and cg06288355(RAG1) were identified as independent prognostic factors for overall survival in patients with TETs after adjusting for Masaoka staging in 100 Chinese patients. The prognostic model which consists of the four abovementioned genes had higher accuracy for predicting the 5-year overall survival in patients with TETs as compared to the Masaoka clinical staging. (Time-dependent ROC analysis AUC 1.000 vs 0.742, P = 2.7 × 10-6). CONCLUSIONS:The methylation levels of cg05784862(KSR1), cg07154254(ELF3), cg02543462(ILRN), and cg06288355(RAG1) sites are associated with the progression of TETs and may serve as new biomarkers for predicting the overall survival in patients with TETs.

Dataset Information

Deciphering tissue-based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors.

Publications

Deciphering tissue-based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors.

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