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Diagnostic Roles of Immunohistochemistry in Thymic Tumors: Differentiation between Thymic Carcinoma and Thymoma.

ABSTRACT: Background: The present study aims to evaluate the diagnostic roles of various immunohistochemical (IHC) markers in thymic tumors, including thymic carcinoma (TC) and thymoma (TM). Methods: Eligible studies were obtained by searching the PubMed databases and screening the searched articles. Thirty-eight articles were used in the present meta-analysis and included 636 TCs and 1861 TMs. Besides, for IHC markers with statistical significance, a diagnostic test accuracy review was performed. Results: The comparison of various IHC expressions between TC and TM was performed for 32 IHC markers. Among these IHC markers, there were significant differences between TC and TM for beta-5t, B-cell lymphoma 2 (Bcl-2), calretinin, CD1a, CD5, carcinoembryonic antigen (CEA), cytokeratin19 (CK19), CD117, glucose transporter 1 (Glut-1), insulin-like growth factor 1 receptor (IGF-1R), mesothelin, MOC31, mucin1 (MUC1), p21, and terminal deoxynucleotidyl transferase (TdT). Markers with higher expressions in TCs were Bcl-2, calretinin, CD5, CEA, CD117, Glut-1, IGF-1R, mesothelin, MOC31, MUC1, and p21. Among these markers, there were no significant differences between TC and TM type B3 in immunohistochemistries for Bcl-2 and CK19. On the other hand, ?-catenin and CD205 showed a considerable difference in IHC expressions between TC and TM type B3, but not between TC and overall TM. In diagnostic test accuracy review, MUC1 and beta-5t were the most useful markers for TC and TM, respectively. Conclusions: Taken together, our results showed that the expression rates for various IHC markers significantly differed between TC and TM. The IHC panel can be useful for differentiation from limited biopsied specimens in daily practice.

SUBMITTER: Jeong JH

PROVIDER: S-EPMC7399973 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Diagnostic Roles of Immunohistochemistry in Thymic Tumors: Differentiation between Thymic Carcinoma and Thymoma.

Jeong Jae-Han JH Pyo Jung-Soo JS Kim Nae-Yu NY Kang Dong-Wook DW

Diagnostics (Basel, Switzerland) 20200706 7

<i>Background:</i> The present study aims to evaluate the diagnostic roles of various immunohistochemical (IHC) markers in thymic tumors, including thymic carcinoma (TC) and thymoma (TM). <i>Methods:</i> Eligible studies were obtained by searching the PubMed databases and screening the searched articles. Thirty-eight articles were used in the present meta-analysis and included 636 TCs and 1861 TMs. Besides, for IHC markers with statistical significance, a diagnostic test accuracy review was perf ...[more]

PMID: 32640732

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Project description:BackgroundThe purpose of our study was to differentiate between thymoma and thymic carcinoma using a radiomics analysis based on the computed tomography (CT) image features.MethodsThe CT images of 61 patients with thymic epithelial tumors (TETs) who underwent contrast-enhanced CT with slice thickness <1 mm were analyzed. Pathological examination of the surgical specimens revealed thymoma in 45 and thymic carcinoma in 16. Tumor volume and the ratio of major axis to minor axis were calculated using a computer-aided diagnostic software. Sixty-one different radiomics features in the segmented CT images were extracted, then filtered and minimized by least absolute shrinkage and selection operator (LASSO) regression to select the optimal radiomics features for predicting thymic carcinoma. The association between the quantitative values and a diagnosis of thymic carcinoma were analyzed with logistic regression models. Parameters identified as significant in univariate analysis were included in multiple analyses. Receiver-operating characteristic (ROC) curves were assessed to evaluate the diagnostic performance.ResultsThymic carcinoma was significantly predominant in men (P=0.001). Optimal radiomics features for predicting thymic carcinoma were as follows: gray-level co-occurrence matrix (GLCM)-homogeneity, GLCM-energy, compactness, large zone high gray-level emphasis (LZHGE), solidity, size of minor axis, and kurtosis. Multiple logistic regression analysis of these features revealed solidity and GLCM-energy as independent indicators associated with thymic carcinoma [odds ratio, 14.7 and 14.3; 95% confidence interval (CI): 1.6-139.0 and 3.0-68.7; and P=0.045 and 0.002, respectively]. Area under the curve (AUC) for diagnosing thymic carcinoma was 0.882 (sensitivity, 81.2%; specificity, 91.1%). Multivariate analysis adjusted for sex similarly revealed two features (solidity and GLCM-energy) as independent indicators associated with thymic carcinoma (odds ratio, 14.6 and 23.9; 95% CI: 2.4-89.2 and 1.9-302.8; P=0.004 and 0.014, respectively). Adjusted AUC for diagnosing thymic carcinoma was 0.921 (95% CI: 0.82-0.97): sensitivity, 62.5% and specificity, 100%.ConclusionsTwo texture features (GLCM-energy and solidity) were significant predictors of thymic carcinoma.

Project description:BackgroundNo standard treatments are available for advanced thymic epithelial tumours after failure of platinum-based chemotherapy. We investigated the activity of sunitinib, an orally administered tyrosine kinase inhibitor.MethodsBetween May 15, 2012, and Oct 2, 2013, we did an open-label phase 2 trial in patients with histologically confirmed chemotherapy-refractory thymic epithelial tumours. Patients were eligible if they had disease progression after at least one previous regimen of platinum-containing chemotherapy, an Eastern Cooperative Oncology Group performance status of two or lower, measurable disease, and adequate organ function. Patients received 50 mg of sunitinib orally once a day, in 6-week cycles (ie, 4 weeks of treatment followed by 2 weeks without treatment), until tumour progression or unacceptable toxic effects arose. The primary endpoint was investigator-assessed best tumour response at any point, which we analysed separately in thymoma and thymic carcinoma cohorts. Patients who had received at least one cycle of treatment and had their disease reassessed were included in the analyses of response. The trial was registered with ClinicalTrials.gov, number NCT01621568.Findings41 patients were enrolled, 25 with thymic carcinoma and 16 with thymoma. One patient with thymic carcinoma was deemed ineligible after enrolment and did not receive protocol treatment. Of patients who received treatment, one individual with thymic carcinoma was not assessable because she died. Median follow-up on trial was 17 months (IQR 14.0-18.4). Of 23 assessable patients with thymic carcinoma, six (26%, 90% CI 12.1-45.3, 95% CI 10.2-48.4) had partial responses, 15 (65%, 95% CI 42.7-83.6) achieved stable disease, and two (9%, 1.1-28.0) had progressive disease. Of 16 patients with thymoma, one (6%, 95% CI 0.2-30.2) had a partial response, 12 (75%, 47.6-92.7) had stable disease, and three (19%, 4.1-45.7) had progressive disease. The most common grade 3 and 4 treatment-related adverse events were lymphocytopenia (eight [20%] of 40 patients), fatigue (eight [20%]), and oral mucositis (eight [20%]). Five (13%) patients had decreases in left-ventricular ejection fraction, of which three (8%) were grade 3 events. Three (8%) patients died during treatment, including one individual who died of cardiac arrest that was possibly treatment-related.InterpretationSunitinib is active in previously treated patients with thymic carcinoma. Further studies are needed to identify potential biomarkers of activity.FundingNational Cancer Institute (Cancer Therapy Evaluation Program).

Dataset Information

Diagnostic Roles of Immunohistochemistry in Thymic Tumors: Differentiation between Thymic Carcinoma and Thymoma.

Publications

Diagnostic Roles of Immunohistochemistry in Thymic Tumors: Differentiation between Thymic Carcinoma and Thymoma.

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