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Evaluation of 12 antibodies for distinguishing epithelioid mesothelioma from adenocarcinoma: identification of a three-antibody immunohistochemical panel with maximal sensitivity and specificity | Mod

diverse tumors with epithelioid histology can affect the peripheral lung, pleura, and chest wall. These include epithelioid mesothelioma, AdCAs, epithelioid nerve cocktail dress tumors, melanoma, and pseudomesotheliomatous angiosarcoma. 45 By far, the most common tumors in this category are AdCA and mesothelioma. therefore, our study focused on the most common differential diagnostic return in this fructify, namely, the eminence between epithelioid mesothelioma and AdCA involving serous surfaces. There have been some excellent reviews of the immunohistochemical approaches to this problem 1, 11, 12, 46, 47, 48, 49, 50, 51, 52 The importance of using a gore of markers preferably than a single one was well recognized in the early years of IHC. 53, 54, 55 late studies identified some antibodies with acceptable rates of specificity and sensitivity in distinguishing MEM from AdCA 3, 4, 10, 16, 22, 35, 56, 57, 58, 59 although other antibodies have yielded suboptimal results. 60, 61, 62, 63 Two major strengths of our study were the utilization of a broad empanel of antibodies to the most common markers of mesothelioma and AdCAs, and the large number of cases evaluated. choice of the specific antibodies was based on both evaluation of the literature 17, 48, 64, 65, 66, 67, 68 and on clinical experience in our laboratories. A few potentially utilitarian markers, such as E-cadherin and N-cadherin, were omitted because of conflicting reports about their performance in distinguishing mesothelioma from AdCA. 57, 69, 70, 71, 72 A one-third strength of our study was the detailed statistical analysis, which distinguishes this report from most previous studies in this area. not alone were all antibodies evaluated by univariate analysis to determine their abilities to distinguish MEM from all AdCA ( table 2, column 2 ), but the relative utility of each antibody was quantified by ROC bend analysis ( postpone 2, column 3 ), the relevant sensitivities and specificities were calculated for each MEM- and AdCA-associated antibody ( table 3 ), and LR was applied to determine the optimum combination of antibodies for distinguishing MEM from AdCA.

The quality of a marker is determined by the extent to which sensitivity and specificity both remain gamey at the threshold set to define marker positivity. As shown in Figure 2, the AUC is a commodious measurement for comparing the overall quality of markers. Calretinin is clearly the best marker for positively identifying MEM, in that it has the highest sensitivity, with relatively high specificity ; HBME-1 achieves over 80 % sensitivity in identifying MEM, but with a specificity of about 50 %. While BerEP4, BG8, CD15, polyclonal CEA, and MOC-31 all are capable of identifying AdCA with high sensitivity, coincident gamey specificity clearly makes BG8 and MOC-31 the optimum markers for positively identifying AdCA.

importantly, the LR model identified three antibodies ( BG8, calretinin, and MOC-31 ) capable of distinguishing MEM from AdCA with 100 % specificity and 96 % sensitivity when this model was applied to the validation data set. Since LR analysis was so effective at identifying optimum markers for distinguishing MEM from AdCA, this is probable to represent a general method acting for optimizing antibody panels to distinguish between other histologically exchangeable entities.

Despite the power of LR as an analytic proficiency, it is critical to remember that the quality of any immunohistochemical panel to distinguish MEM from AdCA will be influenced by the choice of antigens evaluated, the choice of antibody clones, the type of tissue, and the sex of the patient. While the influence of the type of tissue ( eg, surgical biopsy fabric vs cell block of cytological material vs autopsy material ) on the quality of immunohistochemical data is obvious, the importance of antigen and antibody choice is exemplified by a recent report 63 in which an anticalretinin antibody with relatively inadequate specificity was employed, and antibodies to sensitive and specific mesothelial-restricted proteins ( eg, mesothelin, cytokeratin 5, WT-1 ) were not employed. affected role gender directly impacts the specificity of both mesothelin and WT-1 to distinguish MEM from AdCA, since both antigens are expressed by ovarian serous carcinoma. therefore, we advocate the use of ‘ gender-neutral ’ empanel, which includes calretinin alternatively of WT-1 and mesothelin. The combination of calretinin, BG8, and MOC-31 would seem to be applicable across most clinicopathologic scenarios. There are several caveats regarding these findings. First, although tumor cells in fluids typically maintain their immunophenotypes, we did not confirm our classification algorithm in malignant pleural fluid effusions. second, we did not confirm our classification algorithm among peritoneal mesotheliomas, although such mesotheliomas appear to have slenderly unlike characteristics than pleural mesothelioma. 73 third base, we did not study metastatic carcinoma to the pleura, but focused on primary tumors of the respective organs ( lung, ovary, breast, digest ). While immunophenotypic fidelity of metastatic tumors compared to their origins has been documented, 74 it is possible that a particular antigen expressed at high flush by a primary tumor could be lost or importantly reduced in the metastatic sic. Fourth, we did not specifically address the differential gear diagnosis of MEM vs early types of AdCA, including prostate, pancreatic, and nephritic cell carcinoma, although the latter write out was recently addressed. 75 Fifth, we did not evaluate monoclonal antibodies to D2-40 and podoplanin, which besides appear to be highly sensitive for identifying MEM. 76, 77, 78 note that D2-40, like WT-1 and mesothelin, besides recognized ovarian serous carcinoma in one of these two studies, 76 and therefore does not appear to be highly specific for MEM. The two papers describing podoplanin in MEM and AdCA 77, 78 indicate that it is highly specific for MEM. We are uncertain whether adding either D2-40 or podoplanin to the combination of BG8, calretinin, and MOC-31 will improve the ability to discriminate MEM from AdCA. In conclusion, our study goes beyond most previous publications in this sphere, in the adopt ways : ( a ) we evaluated a particularly large number of markers, for which the immunohistochemical techniques were previously screened and optimized ; ( boron ) we evaluated a very large set of MEM and AdCA from numerous geographic locations ; and ( hundred ) we used a diverseness of full-bodied statistical methods 38, 39, 40, 41, 42 to design a cost-efficient empanel of only three monoclonal antibodies, without compromising sensitivity or specificity .

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