IFITM1, CD10, SMA, and h-caldesmon as a helpful combination in differential diagnosis between endometrial stromal sarcoma and cellular leiomyoma

IFITM1, CD10, SMA, and h-caldesmon as a helpful combination in differential diagnosis between endometrial stromal sarcoma and cellular leiomyoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research IFITM1, CD10, SMA, and h-caldesmon as a helpful combination in differential diagnosis between endometrial stromal sarcoma and cellular leiomyoma Weilin Zhao, Cui Mei, Xin Hua Ji, Xin Xiong, Xi Hua Shen, Lin Tao, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.23242/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The differential diagnosis of endometrial stromal sarcoma (ESS) and uterine cellular leiomyoma (CL) remains a challenge in clinical practice. Cluster of differentiation 10 (CD10) and smooth muscle actin (SMA) are commonly used in the differential diagnosis of ESS and CL. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, suggesting the need for novel immunomarkers panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1) is a novel immunomarker for endometrial stromal cells, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than SMA. So this study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for diagnosing between ESS and CL. Tissue microarrays were used to detect IFITM1, CD10, SMA, and h-caldesmon immunohistochemical staining in 30 ESS and 33 CL cases. The expressions of IFITM1 and CD10 were high in ESS (86.7% and 63.3%, respectively) but low in CL (18.2% and 21.2%), whereas those of h-caldesmon and SMA were high in both CL (87.9% and 100%) and low in ESS (6.9% and 40%). In diagnosing ESS, IFITM1 had better sensitivity and specificity (86.7% and 81.8%, respectively) than CD10 (63.3% and 78.8%). The specificity of h-caldesmon in diagnosing CL was significantly higher (93.1%) than that of SMA (60%). When all four antibodies were combined for the differential diagnosis, the area-under-the-curve predictive value was 0.995. The most sensitive and specific combinations for diagnosing ESS were IFITM1(+) or CD10(+) and h-caldesmon(-) ( sensitivity 86.7%, specificity 93.9%), IFITM1(+) and h-caldesmon(-) ((sensitivity 80%, specificity 100%). The most sensitive and specific combinations for diagnosing CL were h-caldesmon(+) and SMA(+)(sensitivity 87.9%, specificity 100%), h-caldesmon(+) or SMA(+) and IFITM1(-)(sensitivity 81.8% , specificity 93.1%).Therefore, IFITM1, CD10, SMA, and h-caldesmon are a good combination of biomarkers for the differential diagnosis of ESS and CL.The differential diagnosis of endometrial stromal sarcoma (ESS) and uterine cellular leiomyoma (CL) remains a challenge in clinical practice. Cluster of differentiation 10 (CD10) and smooth muscle actin (SMA) are commonly used in the differential diagnosis of ESS and CL. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, suggesting the need for novel immunomarkers panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1) is a novel immunomarker for endometrial stromal cells, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than SMA. So this study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for diagnosing between ESS and CL. Tissue microarrays were used to detect IFITM1, CD10, SMA, and h-caldesmon immunohistochemical staining in 30 ESS and 33 CL cases. The expressions of IFITM1 and CD10 were high in ESS (86.7% and 63.3%, respectively) but low in CL (18.2% and 21.2%), whereas those of h-caldesmon and SMA were high in both CL (87.9% and 100%) and low in ESS (6.9% and 40%). In diagnosing ESS, IFITM1 had better sensitivity and specificity (86.7% and 81.8%, respectively) than CD10 (63.3% and 78.8%). The specificity of h-caldesmon in diagnosing CL was significantly higher (93.1%) than that of SMA (60%). When all four antibodies were combined for the differential diagnosis, the area-under-the-curve predictive value was 0.995. The most sensitive and specific combinations for diagnosing ESS were IFITM1(+) or CD10(+) and h-caldesmon(-) ( sensitivity 86.7%, specificity 93.9%), IFITM1(+) and h-caldesmon(-) ((sensitivity 80%, specificity 100%). The most sensitive and specific combinations for diagnosing CL were h-caldesmon(+) and SMA(+)(sensitivity 87.9%, specificity 100%), h-caldesmon(+) or SMA(+) and IFITM1(-)(sensitivity 81.8% , specificity 93.1%).Therefore, IFITM1, CD10, SMA, and h-caldesmon are a good combination of biomarkers for the differential diagnosis of ESS and CL.The differential diagnosis of endometrial stromal sarcoma (ESS) and uterine cellular leiomyoma (CL) remains a challenge in clinical practice. Cluster of differentiation 10 (CD10) and smooth muscle actin (SMA) are commonly used in the differential diagnosis of ESS and CL. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, suggesting the need for novel immunomarkers panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1) is a novel immunomarker for endometrial stromal cells, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than SMA. So this study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for diagnosing between ESS and CL. Tissue microarrays were used to detect IFITM1, CD10, SMA, and h-caldesmon immunohistochemical staining in 30 ESS and 33 CL cases. The expressions of IFITM1 and CD10 were high in ESS (86.7% and 63.3%, respectively) but low in CL (18.2% and 21.2%), whereas those of h-caldesmon and SMA were high in both CL (87.9% and 100%) and low in ESS (6.9% and 40%). In diagnosing ESS, IFITM1 had better sensitivity and specificity (86.7% and 81.8%, respectively) than CD10 (63.3% and 78.8%). The specificity of h-caldesmon in diagnosing CL was significantly higher (93.1%) than that of SMA (60%). When all four antibodies were combined for the differential diagnosis, the area-under-the-curve predictive value was 0.995. The most sensitive and specific combinations for diagnosing ESS were IFITM1(+) or CD10(+) and h-caldesmon(-) ( sensitivity 86.7%, specificity 93.9%), IFITM1(+) and h-caldesmon(-) ((sensitivity 80%, specificity 100%). The most sensitive and specific combinations for diagnosing CL were h-caldesmon(+) and SMA(+)(sensitivity 87.9%, specificity 100%), h-caldesmon(+) or SMA(+) and IFITM1(-)(sensitivity 81.8% , specificity 93.1%).Therefore, IFITM1, CD10, SMA, and h-caldesmon are a good combination of biomarkers for the differential diagnosis of ESS and CL. Translational Medicine IFITM1 CD10 SMA h-caldesmon Immunohistochemical Differential Diagnosis ESS CL Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Endometrial stromal sarcoma (ESS) is a rare malignant mesenchymal tumor of the uterine. In 2014, the World Health Organization classified ESS as low-grade ESS, high-grade ESS, and undifferentiated endometrial sarcoma[ 1 ]. However, there is a overlap in morphology and immunohistochemistry between ESS and leiomyoma, especially for the low grade ESS from cellular leiomyoma (CL). Currently, cluster of differentiation 10 (CD10) has been considered as the best immunomarker for endometrial stromal cells[ 2 – 6 ], but it not expressed in all mesenchymal tumors[ 7 – 9 ]. Rather, CD10 is sometimes expressed in leiomyoma[ 10 , 11 ]. Smooth muscle actin (SMA) is a common biomarker for smooth muscle, however, SMA is sometimes expressed in ESS [ 12 – 15 ], suggesting the need for novel immunomarkers and immunohistochemical panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1), also called CD225, is a novel immunomarker for endometrial stromal cells and tumors[ 16 , 17 ] and outperforms CD10 in distinguishing LG ESS from CL[ 18 , 19 ]. Meanwhile, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than smooth muscle actin (SMA). However, there has been no study on the combined use of IFITM1, CD10, SMA, and h-caldesmon in distinguishing between ESS and CL. This study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for the differential diagnosis of ESS and CL. Materials And Methods The study were approved by the Review Boards of First Affiliated Hospital, Shihezi University School of Medicine and Xinjiang Uygur Autonomous Region People’s Hospital. Clinical data This study enrolled 30 patients with ESS (5 with endometrial stromal nodules,16 with LG ESS, 5 with high-grade ESS, and 4 with undifferentiated endometrial sarcoma) and 33 patients with CL. Data were collected from 2012 to 2017 from the Department of Pathology of the First Affiliated Hospital of Shihezi University School of Medicine and the Department of Pathology of Xinjiang Uygur Autonomous Region People’s Hospital. The average age of 30 ESS patients was 49.8 (27–73) years, and the main clinical symptoms were irregular vaginal bleeding, abdominal pain, postmenopausal vaginal bleeding, and uterine fibroids. The 33 CL patients had an average age of 40.2 (26–60) years and mainly showed clinical manifestations of dysmenorrhea, prolonged menstrual period, and increased menstrual volume. All pertinent clinical information was obtained from the hospital electronic medical records. All patients had complete medical history and clinicopathologic data, and all cases were confirmed by surgery and pathology. Tissue microarray building Paraffin blocks and corresponding hematoxylin and eosin (HE)-stained sections were collected, and the HE-stained sections were evaluated by two senior pathologists. Morphologically representative regions were carefully selected on each individual paraffin-embedded block, and a hollow needle (1.0 mm diameter) was used to puncture the selected area to a new small wax block. Considering the specificity of the tumor and the tendency of the paraffin tissue to flake off, two punctures were performed in different areas of each tumor wax block. Immunohistochemistry For immunohistochemical analysis, biopsy specimens were fixed in 10% neutral-buffered formalin and routinely processed. The paraffin-embedded blocks were sectioned (4 µm thickness), stained with HE, and observed by microscopy. The two-step immunohistochemical EnVision method was applied. The primary antibodies used are listed in Table 1 . The extent of staining was evaluated as 0%, 0–25%, 26–50%, 51–75%, and 76–100%, and the intensity of staining as absent (0), weak (1+), moderate (2+), and strong (3+). The second staining was conducted after 1 month, and the results were interpreted as described above. When a different staining evaluation was used, the higher intensity score was used as the final score. Table 1 Commercial Sources and Characteristics of IFITM1,CD10,h-caldesmon and SMA Antibodies. Name Dilution Company Antigen retrieval Location IFITM1 1:400 Sigma citrate Nucleus/plasma CD10 1:50 ZSGB-BIO EDTA Cytoplasm/membrane SMA 1:100 ZSGB-BIO citrate Cytoplasm h-caldesmon 1:100 ZSGB-BIO citrate Cytoplasm Statistical analysis Differences between the two groups were compared using the chi-squared test. The sensitivity, specificity, and positive predictive values (PPVs) were calculated from the screening and diagnostic tests. The staining score was obtained by multiplying the extent with the intensity, and the resulting score was used for the receiver operating characteristic curve. All statistical analyses were performed using SPSS version 17.0. A p-value of < 0.05 was considered as statistically significant. Results The immunohistochemical results are summarized in Table 2 and illustrated in Fig. 1 . The sensitivity, specificity, PPVs, and negative predictive values (NPVs) are summarized in Tables 3 – 6 and shown in Figs. 2 – 4 . Table 2 Intensity and Extent of Immunohistochemical Staining of IFITM1,CD10,h-caldesmon and SMA in endometrial stromal sarcoma and celluar leiomyoma. Antibodies ESS(30 cases) CL(33 cases) Positive Category Intensity Positive Category Intensity 0 1+ 2+ 3+ 0 1+ 2+ 3+ IFITM1 26(86.7%) 4 10 8 8 6(18.2%) 27 6 0 0 CD10 19(63.3%) 11 6 7 6 7(21.2%) 26 7 0 0 h-caldesmon 2(6.7%) 28 2 0 0 29(87.9%) 4 15 10 4 SMA 12(40%) 18 4 6 2 33(100%) 0 22 9 2 Abbreviations: ESS indicates Endometrial Stromal Sarcomas; CL indicates Celluar Leiomyoma. Table 3 Sensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of IFITM1 and CD10 for endometrial stromal sarcoma. Antibodies Sensitivity (%) Specificity (%) PPV(%) NPV(%) IFITM1 86.7 81.8 81.3 87.1 CD10 63.3 78.8 73.1 70.3 Abbreviations: PPV indicates Positive Predictive Value, NPV indicates Negative Predictive Value. IFITM1 and CD10 Both ESS (Fig. 1 -A) and CL cases (Fig. 1 -B) showed a dense spindle-cell braid-like arrangement. Among the 30 ESS cases, 26 (86.7%) demonstrated IFITM1 nuclear positivity (Fig. 1 -C). The staining intensity was strong (3+) in 8 cases, moderate (2+) in 8 cases, and weak (1+) in 10 cases. The average intensity score was 1.7. Of the 33 CL cases, only 6 (18.2%) demonstrated IFITM1 nuclear positivity (Fig. 1 -D), all of which scored weak (1+) in intensity. CD10 was expressed in 19 (63.3%) of the 30 ESS cases (Fig. 1 -E). The staining in these cases occurred in the cell cytoplasm and was strong (3+) in 6 cases, moderate (2+) in 7 cases, and weak (1+) in 6 cases. The average intensity score was 1.3. Only 7 (21.2%) of the 33 CL cases were CD10(+), and all positive cases had a weak (1+) intensity (Fig. 1 -F). SMA and h-caldesmon SMA was positive in 12 (40%) of the 30 ESS cases (Fig. 1 -G). The staining in these cases was expressed in the cytoplasm and was moderate to strong (2 + to 3+) in 8 cases and weak (1+) in 4 cases. All 33 (100%) CL cases expressed SMA (Fig. 1 -H), and among them, the staining was moderate to strong (2 + to 3+) in 11 cases and weak (1+) in the remaining cases. The average intensity score was 1.7. Meanwhile, h-caldesmon was expressed in the cell cytoplasm of only 2 (6.7%) of the 30 ESS cases (Fig. 1 -I), and the staining in these positive cases were weak (1+). However, 29 (87.9%) of the 33 CL cases exhibited h-caldesmon positivity (Fig. 1 -J). In these 33 CL cases, the staining was strong (3+) in 4 cases, moderate (2+) in 10 cases, and weak (1+) in 15 cases. The average intensity score was 1.4. Sensitivity, specificity, PPVs, and NPVs of IFITM1, CD10, h-caldesmon, and SMA In the diagnosis of ESS, IFITM1 showed a sensitivity of 86.7%, a specificity of 81.8%, a PPV of 81.3%, and an NPV of 87.1%. For CD10, the sensitivity, specificity, PPV, and NPV were 63.3%, 78.8%, 73.1%, and 70.3%, respectively. h-caldesmon positivity may support a diagnosis of CL, showing a sensitivity of 87.9%, a specificity of 93.3%, a PPV of 93.5%, and an NPV of 87.5%. SMA had the highest sensitivity (100%), but its specificity was 60%, significantly lower than that of h-caldesmon. SMA had a PPV and an NPV of 73.3% and 100%, respectively (Tables 3 and 4 ). Table 4 Sensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of h-caldesmon and SMA for celluar leiomyoma. Antibodies Sensitivity (%) Specificity (%) PPV(%) NPV(%) h-caldesmon 87.9 93.3 93.5 87.5 SMA 100.0 60.0 73.3 100.0 Abbreviations: PPV indicates Positive Predictive Value, NPV indicates Negative Predictive Value. IFITM1, CD10, h-caldesmon, and SMA as a useful combination for differential diagnosis Based on the expressions of the four antibodies and their receiver operating characteristic curve(the area-under-the-curve predictive value was 0.995 (Fig. 2 ), we speculate that their combinations could be helpful in the differential diagnosis of ESS and CL. When all four antibodies were combined for the ESS diagnosis (Table 5 , Fig. 3 ), The most sensitive combination was IFITM1(+) or CD10(+), IFITM1(+) or CD10(+) and h-caldesmon(-), IFITM1(+) and h-caldesmon(-), with a sensitivity of 93.3%, 86.7%,80%, respectively (Fig. 3 -A). The combination of antibodies greatly increased the specificity of ESS diagnosis (Fig. 3 -B), the specificity of combinations of IFITM1(+) and h-caldesmon(-), IFITM1(+) and SMA(-), IFITM1(+) and CD10(+) and h-caldesmon(-), IFITM1(+) and CD10(+) and h-caldesmon(-) and SMA(-), and IFITM1(+) or CD10(+) and h-caldesmon(-) and SMA(-) were 100%. Considering both sensitivity and specificity, the combination with the best diagnostic value for ESS was IFITM1(+) or CD10(+) and h-caldesmon(-), with a sensitivity and a specificity of 86.7% and 93.9%, respectively. Table 5 The Sensitivity and Specificity of combined IFITM1, CD10, h-caldesmon and SMA immunostaining in the Diagnosis of endometrial stromal sarcoma. Groups Sensitivity (%) Specificity (%) IFITM1(+) and h-caldesmon(-) for ESS 80.0 100.0 IFITM1(+) and SMA(-) for ESS 60.0 97.0 CD10(+) and h-caldesmon(-) for ESS 50.0 100.0 CD10(+) and SMA(-) for ESS 36.7 100.0 IFITM1(+) and CD10(+) for ESS 56.7 93.9 IFITM1(+) or CD10(+) for ESS 93.3 66.7 IFITM1(+) or CD10(+) and h-caldesmon(-) for ESS 86.7 93.9 IFITM1(+) and CD10(+) and h-caldesmon(-) for ESS 53.3 100.0 IFITM1(+) or CD10(+) and SMA(-) for ESS 56.7 100.0 IFITM1(+) and CD10(+) and SMA(-) for ESS 30.0 100.0 IFITM1(+) and CD10(+) and h-caldesmon(-) and SMA(-) for ESS 31.0 100.0 IFITM1(+) or CD10(+) and h-caldesmon(-) and SMA(-) for ESS 56.7 100.0 Abbreviations: ESS indicates Endometrial Stromal Sarcomas. In diagnosing CL (Table 6 , Fig. 4 ), the combinations h-caldesmon(+) or SMA(+), h-caldesmon(+) and SMA(+), and h-caldesmon(+) or SMA(+) and IFITM1(-) showed better sensitivity for differentiating CL from ESS, with sensitivity values of 100%, 87.9%, and 81.8%, respectively(Fig. 4 -A). On the other hand, h-caldesmon(+) and IFITM1(-), h-caldesmon(+) and SMA(+), h-caldesmon(+) and SMA(+) and IFITM1(-), and h-caldesmon(+) and SMA(+) and IFITM1(-) and CD10(-) showed better specificity for predicting CL from ESS, with all specificity were 100% (Fig. 4 -B). Taking into account both sensitivity and specificity, h-caldesmon(+) and SMA(+) was the best combination for distinguishing CL from ESS, with a sensitivity of 87.9% and a specificity of 100%. The second best combination for distinguishing CL from ESS was h-caldesmon(+) or SMA(+) and IFITM1(-), with a sensitivity of 81.8% and a specificity of 93.1%. Table 6 The Sensitivity and Specificity of combined IFITM1,CD10,h-caldesmon and SMA immunostaining in the Diagnosis of celluar leiomyoma. Groups Sensitivity (%) Specificity (%) h-caldesmon(+) andIFITM1(-) for CL 69.7 100.0 SMA(+) and IFITM1(-) for CL 81.8 93.1 h-caldesmon(+) and CD10(-) for CL 72.7 96.6 SMA(+) and CD10(-) for CL 78.8 82.8 h-caldesmon(+) and SMA(+) for CL 87.9 100.0 h-caldesmon(+) or SMA(+) for CL 100.0 57.1 h-caldesmon(+) and SMA(+) and IFITM1(-) for CL 69.7 100.0 h-caldesmon(+) or SMA(+) and IFITM1(-) for CL 81.8 93.1 h-caldesmon(+) and SMA(+) and CD10(-) for CL 72.7 96.6 h-caldesmon(+) or SMA(+) and CD1(-) for CL 78.8 82.8 h-caldesmon(+) and SMA(+) and IFITM1(-) and CD10(-) for CL 57.6 100.0 h-caldesmon(+) or SMA(+) and IFITM1(-) and CD10(-) for CL 66.7 93.1 Abbreviations: CL indicates celluar leiomyoma. Discussion The standard routine immunomarker panel used by most pathologists to distinguish ESS from CL consists of CD10, h-caldesmon, and SMA [ 10 , 20 – 22 ], and an immunoprofile of CD10(+), h-caldesmon(-), and SMA(-) supports the diagnosis of ESS [ 15 ]. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, especially when diagnosing endometrial stromal tumors using CD10 alone[ 3 , 10 ]. CD10 is not merely expressed in endometrial stromal tumors but is also positively expressed in 20–30% of smooth muscle tumors [ 13 , 15 ]. SMA is a common muscle marker for endometrial stromal tumors and therefore has a very low specificity. Although h-caldesmon has a higher specificity that of SMA, its sensitivity is worse[ 10 , 13 , 15 , 23 ]. Thus, the need for a novel biomarker or a new immunohistochemical combination is imperative. IFITM1 is a novel biomarker for endometrium stromal cells and is reported to be more valuable than CD10 [ 19 , 24 ]. According to Busca et al[ 19 ], IFITM1 and CD10 were expressed in 14 ESS cases, and although their sensitivities were 83% and 91%, respectively, IFITM1 showed a higher specificity than CD10, that is, 70% vs. 45%. These findings are consistent with our findings, which state that IFITM1 was more specific and sensitive than CD10 in endometrial stromal tumors (sensitivity 86.7% vs. 63.3%, specificity 81.8% vs. 78.8%). Rush et al.[ 13 ] compared the expressions of SMA and h-caldesmon between ESS and CL and found that SMA was more sensitive than h-caldesmon (90.9% vs. 72.7%); however, h-caldesmon was more specific than SMA (100% vs. 91.7%). In our study, h-caldesmon showed a lower sensitivity than SMA (87.9% vs. 100%), but its specificity was significantly higher (93.3% vs. 60%). Based on the expressions of the four antibodies and their receiver operating characteristic curve, we speculate that their combination could be useful in the clinical and differential diagnosis of ESS and CL. When such combination was used for diagnosis, the area-under-the-curve predictive value was 0.995. However, there are certain limitations in that the receiver operating characteristic curve cannot completely show the positive and negative expressions of the antibodies. We therefore compared the sensitivities and specificities of the four combined antibodies using a screening test and selected the best biomarker panel. For the diagnosis of ESS, the combination IFITM1(+) or CD10(+) had the highest sensitivity (93.3%), followed by IFITM1(+) or CD10(+) and h-caldesmon(-) (86.7%). In terms of specificity, the combinations IFITM1(+) and h-caldesmon(-), IFITM1(+) and SMA(-), and CD10(+) and SMA(-) were the best panels, having a specificity of up to 100%, while IFITM1(+) or CD10(+) was the worst panel, with a specificity of only 66.7%. Considering both sensitivity and specificity, the best panel for diagnosing ESS was IFITM1(+) or CD10(+) and h-caldesmon(-), with a sensitivity of 86.7% and a specificity of 93.9%. The other good predictive panel for distinguishing ESS from CL was IFITM1(+) and h-caldesmon(-), with a sensitivity of 80% and a specificity of 100%. In general, no one immunomarker is sensitive and specific enough to make an accurate diagnosis, and so we usually use an immunohistochemical panel for differential diagnosis. This study revealed that the combination of IFITM1, CD10, SMA, and h-caldesmon comprised the best immunohistochemical panel for differentiating between ESS and CL. Considering the costs, we also recommend the combinations IFITM1 and h-caldesmon for the same purpose. Conclusion Immunohistochemical combinations of the novel antibody IFITM1 with traditional antibodies CD10, SMA, and h-caldesmon can be very useful in distinguishing ESS from CL, especially when the clinical history and histological morphology cannot be differentiated totally. Declarations Acknowledgments This work were supported by the National Natural Science Foundation of China [grant numbers 81460383, 81660411], the International Cooperation Project of Xinjiang Production and Construction Corps of China [grant number 2019BC001], the Key Areas Innovation Team Project of Xinjiang Production and Construction Corps of China [grant number 2018CB002]. Ethics approval and consent to participate Ethical approval was obtained from the Institutional Ethics Review Board (IERB) of the First Affiliated Hospital of School of Medicine, Shihezi University.Research was conducted according to all ethical standards, and written informed consent was obtained from all patients. Consent for publication Consent to publish has been obtained from all authors. Availability of data and materials All data in our study are available upon request. Competing interests The authors have no conflicts of interest to declare. No funding or other benefits related to the subject of this article were received from any commercial entity. Fundings This work were supported by the National Natural Science Foundation of China [grant numbers 81460383, 81660411], the International Cooperation Project of Xinjiang Production and Construction Corps of China [grant number 2019BC001], the Key Areas Innovation Team Project of Xinjiang Production and Construction Corps of China [grant number 2018CB002]. Authors' contributions ZH , SZZ and WC conceived and designed this study; CM provided the clinical specimens; ZWL, JXH and XX performed the experiments; SXH ,JW and TL acquired the data; ZWL and CM analyzed the data and results; ZWL wrote the manuscript; ZH and PLJ improved and revised the manuscript. All authors read and approved the final manuscript. References Conklin, C.M. and T.A. Longacre, Endometrial stromal tumors: the new WHO classification. 2014. 21(6): p. 383. 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De Leval, L., et al., Use of Histone Deacetylase 8 (HDAC8), a New Marker of Smooth Muscle Differentiation, in the Classification of Mesenchymal Tumors of the Uterus. American Journal of Surgical Pathology. 30(3): p. 319-327. Hwang, H., et al., Immunohistochemical panel to differentiate endometrial stromal sarcoma, uterine leiomyosarcoma and leiomyoma: something old and something new. Journal of Clinical Pathology: p. jclinpath-2015-202915. Franquemont, D.W., H.F. Frierson, and S.E. Mills, An Immunohistochemical Study of Normal Endometrial Stroma and Endometrial Stromal Neoplasms. American Journal of Surgical Pathology. 15(9): p. 861-870. Busca, A., et al., IFITM1 Is Superior to CD10 as a Marker of Endometrial Stroma in the Evaluation of Myometrial Invasion by Endometrioid Adenocarcinoma. American Journal of Clinical Pathology. 145(4): p. 486-496. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-13811","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":341249,"identity":"13a473e0-d277-4425-b835-aa6b05f9bf78","order_by":1,"name":"Weilin Zhao","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weilin","middleName":"","lastName":"Zhao","suffix":""},{"id":341250,"identity":"074cfb61-ce60-44e9-8669-56d91b11a7bc","order_by":2,"name":"Cui Mei","email":"","orcid":"","institution":"Department of Pathology, Xinjiang Uygur Autonomous Region People’s Hospital, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cui","middleName":"","lastName":"Mei","suffix":""},{"id":341251,"identity":"73f809a0-c521-4723-953e-fb6b7e64d239","order_by":3,"name":"Xin Hua Ji","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xin","middleName":"Hua","lastName":"Ji","suffix":""},{"id":341252,"identity":"81fb2c9a-38fc-45d6-b52a-2ba19b5d8e84","order_by":4,"name":"Xin Xiong","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Xiong","suffix":""},{"id":341253,"identity":"5d362333-61ab-40e5-8b87-ec27813f356f","order_by":5,"name":"Xi Hua Shen","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xi","middleName":"Hua","lastName":"Shen","suffix":""},{"id":341254,"identity":"cead5dcc-2bb2-48ed-868c-052a2c007376","order_by":6,"name":"Lin Tao","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Tao","suffix":""},{"id":341255,"identity":"42d2de5a-c4dd-40a8-9982-f74e3665e18f","order_by":7,"name":"Wei Jia","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Jia","suffix":""},{"id":341256,"identity":"546de1c2-af98-4473-91f3-48d01bb25870","order_by":8,"name":"Li Juan Pang","email":"","orcid":"","institution":"Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Li","middleName":"Juan","lastName":"Pang","suffix":""},{"id":341257,"identity":"f0a0459b-351d-4222-bb5a-100024da9b18","order_by":9,"name":"Zhen Zhu Sun","email":"","orcid":"","institution":"Department of Pathology, Xinjiang Uygur Autonomous Region People’s Hospital, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"Zhu","lastName":"Sun","suffix":""},{"id":341258,"identity":"257ed9a7-7794-4c08-9bdc-7566d78a5283","order_by":10,"name":"Chun Wang","email":"","orcid":"","institution":"Department of Pathology, Xinjiang Uygur Autonomous Region People’s Hospital, Xinjiang 832002, China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Wang","suffix":""},{"id":341259,"identity":"cbecca21-81c2-444c-b019-159196ec7763","order_by":11,"name":"Hong Zou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYHACNiRGhYScPAlamIGMMxbGhg0kaWFsq0hkOEBAvXx7j9mDjztqGczZzx978HGeRAJjA/PDRzfwaGHsOWNuOPPMcQbLnmR2w5nbJPLYGdiMjXPwaGGWyDGT5m07xmBwIJlNmnebRDFjAw+bND4tbHAt5x8DtcyRSGw4QEALD0RLDYPBDZAtDURokeA5ViY5s+0Ag+WMx2aSM45JGBs2E/CLfHvzNomPbXUM5vyJzyQ+1NTJybM3P3yMTwsUHK7fAGczE1YOAnUMBsQpHAWjYBSMgpEIAK+2Qoe+aTv+AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-3051-8006","institution":"Department of Pathology, Shihezi University School of Medicine, Xinjiang 832002, China","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Zou","suffix":""}],"badges":[],"createdAt":"2020-02-08 16:10:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.23242/v1","doiUrl":"https://doi.org/10.21203/rs.2.23242/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":480964,"identity":"eb0e466a-a535-4d6e-a335-cb70280b329a","added_by":"auto","created_at":"2020-02-11 22:38:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9139775,"visible":true,"origin":"","legend":"Immunohistochemical results. (A) Endometrial stromal sarcomas (hematoxylin and eosin stains, magnification 200). (B) Cellular leiomyomas (hematoxylin and eosin stains, magnification ×200). (C) Endometrial stromal sarcomas showing strong positive results for IFITM1. (D) Cellular leiomyomas showing a negative or weak expression of IFITM1. (E) Endometrial stromal sarcomas exhibiting a positive expression of CD10. (F) Cellular leiomyomas exhibiting a weekly CD10 positivity. (G) Endometrial stromal sarcomas demonstrating SMA reactivity. (H) Cellular leiomyomas showing strong positive results for SMA. (I) Endometrial stromal sarcomas showing a negative or weak expression of h-caldesmon. (J) Cellular leiomyomas demonstrating strong positive results for h-caldesmon.","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/6d4cb624-9cac-4c4d-923d-1a878a2b5df7/v1/Fig. 1.jpg"},{"id":480965,"identity":"5da86fab-83e6-42c2-87f2-2580a0c7b7e1","added_by":"auto","created_at":"2020-02-11 22:38:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1489902,"visible":true,"origin":"","legend":"Receiver operating characteristic curve for prediction of Endometrial stromal sarcoma and cellular leiomyoma.","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/6d4cb624-9cac-4c4d-923d-1a878a2b5df7/v1/Fig. 2.jpg"},{"id":480966,"identity":"116b059f-4a38-4430-b7e5-f148681236eb","added_by":"auto","created_at":"2020-02-11 22:38:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2396187,"visible":true,"origin":"","legend":"The Sensitivity and Specificity of combined IFITM1,CD10,h-caldesmon and SMA immunostaining in the Diagnosis of endometrial stromal sarcoma. (A) The Sensitivity of different combinations for endometrial stromal sarcoma. (B) The Specificity of different combinations for endometrial stromal sarcoma.\nAbbreviations: I indicates IFITM1, C indicates CD10, H indicates h-caldesmon, S indicates SMA.","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/6d4cb624-9cac-4c4d-923d-1a878a2b5df7/v1/Fig. 3.jpg"},{"id":480967,"identity":"c64cec7b-8d46-46c5-b0b9-5a3457bf65eb","added_by":"auto","created_at":"2020-02-11 22:38:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2090250,"visible":true,"origin":"","legend":"The Sensitivity and Specificity of combined IFITM1,CD10,h-caldesmon and SMA immunostaining in the Diagnosis of cellular leiomyoma. (A) The Sensitivity of different combinations for cellular leiomyoma. (B) The Specificity of different combinations for cellular leiomyoma.\nAbbreviations: I indicates IFITM1, C indicates CD10, H indicates h-caldesmon, S indicates SMA.","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/6d4cb624-9cac-4c4d-923d-1a878a2b5df7/v1/Fig. 4.jpg"},{"id":13488598,"identity":"32ce5501-0c56-43b5-90e8-3835a9e0144a","added_by":"auto","created_at":"2021-09-16 22:15:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1007102,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-13811/v1/5b3e0c1c-67b1-4ef2-ae2e-91856be562f8.pdf"}],"financialInterests":"","formattedTitle":"IFITM1, CD10, SMA, and h-caldesmon as a helpful combination in differential diagnosis between endometrial stromal sarcoma and cellular leiomyoma","fulltext":[{"header":"Background","content":" \u003cp\u003eEndometrial stromal sarcoma (ESS) is a rare malignant mesenchymal tumor of the uterine. In 2014, the World Health Organization classified ESS as low-grade ESS, high-grade ESS, and undifferentiated endometrial sarcoma[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, there is a overlap in morphology and immunohistochemistry between ESS and leiomyoma, especially for the low grade ESS from cellular leiomyoma (CL). Currently, cluster of differentiation 10 (CD10) has been considered as the best immunomarker for endometrial stromal cells[\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], but it not expressed in all mesenchymal tumors[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Rather, CD10 is sometimes expressed in leiomyoma[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Smooth muscle actin (SMA) is a common biomarker for smooth muscle, however, SMA is sometimes expressed in ESS [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], suggesting the need for novel immunomarkers and immunohistochemical panels for differentiating between ESS and CL.\u003c/p\u003e \u003cp\u003eInterferon-induced transmembrane protein 1 (IFITM1), also called CD225, is a novel immunomarker for endometrial stromal cells and tumors[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and outperforms CD10 in distinguishing LG ESS from CL[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Meanwhile, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than smooth muscle actin (SMA). However, there has been no study on the combined use of IFITM1, CD10, SMA, and h-caldesmon in distinguishing between ESS and CL. This study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for the differential diagnosis of ESS and CL.\u003c/p\u003e "},{"header":"Materials And Methods","content":" \u003cp\u003eThe study were approved by the Review Boards of First Affiliated Hospital, Shihezi University School of Medicine and Xinjiang Uygur Autonomous Region People\u0026rsquo;s Hospital.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClinical data\u003c/h2\u003e \u003cp\u003eThis study enrolled 30 patients with ESS (5 with endometrial stromal nodules,16 with LG ESS, 5 with high-grade ESS, and 4 with undifferentiated endometrial sarcoma) and 33 patients with CL. Data were collected from 2012 to 2017 from the Department of Pathology of the First Affiliated Hospital of Shihezi University School of Medicine and the Department of Pathology of Xinjiang Uygur Autonomous Region People\u0026rsquo;s Hospital. The average age of 30 ESS patients was 49.8 (27\u0026ndash;73) years, and the main clinical symptoms were irregular vaginal bleeding, abdominal pain, postmenopausal vaginal bleeding, and uterine fibroids. The 33 CL patients had an average age of 40.2 (26\u0026ndash;60) years and mainly showed clinical manifestations of dysmenorrhea, prolonged menstrual period, and increased menstrual volume. All pertinent clinical information was obtained from the hospital electronic medical records. All patients had complete medical history and clinicopathologic data, and all cases were confirmed by surgery and pathology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTissue microarray building\u003c/h2\u003e \u003cp\u003eParaffin blocks and corresponding hematoxylin and eosin (HE)-stained sections were collected, and the HE-stained sections were evaluated by two senior pathologists. Morphologically representative regions were carefully selected on each individual paraffin-embedded block, and a hollow needle (1.0\u0026nbsp;mm diameter) was used to puncture the selected area to a new small wax block. Considering the specificity of the tumor and the tendency of the paraffin tissue to flake off, two punctures were performed in different areas of each tumor wax block.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eFor immunohistochemical analysis, biopsy specimens were fixed in 10% neutral-buffered formalin and routinely processed. The paraffin-embedded blocks were sectioned (4\u0026nbsp;\u0026micro;m thickness), stained with HE, and observed by microscopy. The two-step immunohistochemical EnVision method was applied. The primary antibodies used are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The extent of staining was evaluated as 0%, 0\u0026ndash;25%, 26\u0026ndash;50%, 51\u0026ndash;75%, and 76\u0026ndash;100%, and the intensity of staining as absent (0), weak (1+), moderate (2+), and strong (3+). The second staining was conducted after 1 month, and the results were interpreted as described above. When a different staining evaluation was used, the higher intensity score was used as the final score.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eCommercial Sources and Characteristics of IFITM1,CD10,h-caldesmon and SMA Antibodies.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eName\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eDilution\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eCompany\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003eAntigen retrieval\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003eLocation\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1:400\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eSigma\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003ecitrate\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003eNucleus/plasma\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCD10\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1:50\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eZSGB-BIO\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003eEDTA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003eCytoplasm/membrane\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1:100\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eZSGB-BIO\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003ecitrate\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003eCytoplasm\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1:100\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eZSGB-BIO\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003ecitrate\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cdiv class=\"SimplePara\"\u003eCytoplasm\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDifferences between the two groups were compared using the chi-squared test. The sensitivity, specificity, and positive predictive values (PPVs) were calculated from the screening and diagnostic tests. The staining score was obtained by multiplying the extent with the intensity, and the resulting score was used for the receiver operating characteristic curve. All statistical analyses were performed using SPSS version 17.0. A p-value of \u0026lt;\u0026thinsp;0.05 was considered as statistically significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003eThe immunohistochemical results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e2\u003c/span\u003e and illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The sensitivity, specificity, PPVs, and negative predictive values (NPVs) are summarized in Tables\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e6\u003c/span\u003e and shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eIntensity and Extent of Immunohistochemical Staining of IFITM1,CD10,h-caldesmon and SMA in endometrial stromal sarcoma and celluar leiomyoma.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cdiv class=\"SimplePara\"\u003eAntibodies\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eESS(30 cases)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c14\" namest=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003eCL(33 cases)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003ePositive\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eCategory Intensity\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003ePositive\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cdiv class=\"SimplePara\"\u003eCategory Intensity\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1+\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e2+\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e3+\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cdiv class=\"SimplePara\"\u003e1+\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cdiv class=\"SimplePara\"\u003e2+\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cdiv class=\"SimplePara\"\u003e3+\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e26(86.7%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e4\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e10\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e6(18.2%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cdiv class=\"SimplePara\"\u003e27\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cdiv class=\"SimplePara\"\u003e6\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCD10\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e19(63.3%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e11\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e6\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e6\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e7(21.2%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cdiv class=\"SimplePara\"\u003e26\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cdiv class=\"SimplePara\"\u003e7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e2(6.7%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e28\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e29(87.9%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cdiv class=\"SimplePara\"\u003e4\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cdiv class=\"SimplePara\"\u003e15\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cdiv class=\"SimplePara\"\u003e10\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cdiv class=\"SimplePara\"\u003e4\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e12(40%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e18\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e4\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cdiv class=\"SimplePara\"\u003e6\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e33(100%)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cdiv class=\"SimplePara\"\u003e22\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cdiv class=\"SimplePara\"\u003e9\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cdiv class=\"SimplePara\"\u003e2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003eAbbreviations: ESS indicates Endometrial Stromal Sarcomas; CL indicates Celluar Leiomyoma.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eSensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of IFITM1 and CD10 for endometrial stromal sarcoma.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAntibodies\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eSensitivity (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpecificity (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003ePPV(%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003eNPV(%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e86.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e87.1\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCD10\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e63.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e78.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e73.1\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e70.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eAbbreviations: PPV indicates Positive Predictive Value, NPV indicates Negative Predictive Value.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIFITM1 and CD10\u003c/h2\u003e \u003cp\u003eBoth ESS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-A) and CL cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-B) showed a dense spindle-cell braid-like arrangement. Among the 30 ESS cases, 26 (86.7%) demonstrated IFITM1 nuclear positivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-C). The staining intensity was strong (3+) in 8 cases, moderate (2+) in 8 cases, and weak (1+) in 10 cases. The average intensity score was 1.7. Of the 33 CL cases, only 6 (18.2%) demonstrated IFITM1 nuclear positivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-D), all of which scored weak (1+) in intensity. CD10 was expressed in 19 (63.3%) of the 30 ESS cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-E). The staining in these cases occurred in the cell cytoplasm and was strong (3+) in 6 cases, moderate (2+) in 7 cases, and weak (1+) in 6 cases. The average intensity score was 1.3. Only 7 (21.2%) of the 33 CL cases were CD10(+), and all positive cases had a weak (1+) intensity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-F).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSMA and h-caldesmon\u003c/h2\u003e \u003cp\u003eSMA was positive in 12 (40%) of the 30 ESS cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-G). The staining in these cases was expressed in the cytoplasm and was moderate to strong (2\u0026thinsp;+\u0026thinsp;to 3+) in 8 cases and weak (1+) in 4 cases. All 33 (100%) CL cases expressed SMA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-H), and among them, the staining was moderate to strong (2\u0026thinsp;+\u0026thinsp;to 3+) in 11 cases and weak (1+) in the remaining cases. The average intensity score was 1.7. Meanwhile, h-caldesmon was expressed in the cell cytoplasm of only 2 (6.7%) of the 30 ESS cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-I), and the staining in these positive cases were weak (1+). However, 29 (87.9%) of the 33 CL cases exhibited h-caldesmon positivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-J). In these 33 CL cases, the staining was strong (3+) in 4 cases, moderate (2+) in 10 cases, and weak (1+) in 15 cases. The average intensity score was 1.4.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity, specificity, PPVs, and NPVs of IFITM1, CD10, h-caldesmon, and SMA\u003c/h2\u003e \u003cp\u003eIn the diagnosis of ESS, IFITM1 showed a sensitivity of 86.7%, a specificity of 81.8%, a PPV of 81.3%, and an NPV of 87.1%. For CD10, the sensitivity, specificity, PPV, and NPV were 63.3%, 78.8%, 73.1%, and 70.3%, respectively. h-caldesmon positivity may support a diagnosis of CL, showing a sensitivity of 87.9%, a specificity of 93.3%, a PPV of 93.5%, and an NPV of 87.5%. SMA had the highest sensitivity (100%), but its specificity was 60%, significantly lower than that of h-caldesmon. SMA had a PPV and an NPV of 73.3% and 100%, respectively (Tables\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eSensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of h-caldesmon and SMA for celluar leiomyoma.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAntibodies\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eSensitivity (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpecificity (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003ePPV(%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003eNPV(%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e87.9\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.5\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e87.5\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e60.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cdiv class=\"SimplePara\"\u003e73.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eAbbreviations: PPV indicates Positive Predictive Value, NPV indicates Negative Predictive Value.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIFITM1, CD10, h-caldesmon, and SMA as a useful combination for differential diagnosis\u003c/h2\u003e \u003cp\u003eBased on the expressions of the four antibodies and their receiver operating characteristic curve(the area-under-the-curve predictive value was 0.995 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), we speculate that their combinations could be helpful in the differential diagnosis of ESS and CL.\u003c/p\u003e \u003cp\u003eWhen all four antibodies were combined for the ESS diagnosis (Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), The most sensitive combination was IFITM1(+) or CD10(+), IFITM1(+) or CD10(+) and h-caldesmon(-), IFITM1(+) and h-caldesmon(-), with a sensitivity of 93.3%, 86.7%,80%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-A). The combination of antibodies greatly increased the specificity of ESS diagnosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-B), the specificity of combinations of IFITM1(+) and h-caldesmon(-), IFITM1(+) and SMA(-), IFITM1(+) and CD10(+) and h-caldesmon(-), IFITM1(+) and CD10(+) and h-caldesmon(-) and SMA(-), and IFITM1(+) or CD10(+) and h-caldesmon(-) and SMA(-) were 100%. Considering both sensitivity and specificity, the combination with the best diagnostic value for ESS was IFITM1(+) or CD10(+) and h-caldesmon(-), with a sensitivity and a specificity of 86.7% and 93.9%, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eThe Sensitivity and Specificity of combined IFITM1, CD10, h-caldesmon and SMA immunostaining in the Diagnosis of endometrial stromal sarcoma.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eGroups\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSensitivity (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpecificity (%)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) and h-caldesmon(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e80.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) and SMA(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e60.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e97.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCD10(+) and h-caldesmon(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e50.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCD10(+) and SMA(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e36.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) and CD10(+) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e56.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.9\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) or CD10(+) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e66.7\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) or CD10(+) and h-caldesmon(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e86.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.9\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) and CD10(+) and h-caldesmon(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e53.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) or CD10(+) and SMA(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e56.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) and CD10(+) and SMA(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e30.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) and CD10(+) and h-caldesmon(-) and SMA(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e31.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIFITM1(+) or CD10(+) and h-caldesmon(-) and SMA(-) for ESS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e56.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: ESS indicates Endometrial Stromal Sarcomas.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn diagnosing CL (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), the combinations h-caldesmon(+) or SMA(+), h-caldesmon(+) and SMA(+), and h-caldesmon(+) or SMA(+) and IFITM1(-) showed better sensitivity for differentiating CL from ESS, with sensitivity values of 100%, 87.9%, and 81.8%, respectively(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-A). On the other hand, h-caldesmon(+) and IFITM1(-), h-caldesmon(+) and SMA(+), h-caldesmon(+) and SMA(+) and IFITM1(-), and h-caldesmon(+) and SMA(+) and IFITM1(-) and CD10(-) showed better specificity for predicting CL from ESS, with all specificity were 100% (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-B). Taking into account both sensitivity and specificity, h-caldesmon(+) and SMA(+) was the best combination for distinguishing CL from ESS, with a sensitivity of 87.9% and a specificity of 100%. The second best combination for distinguishing CL from ESS was h-caldesmon(+) or SMA(+) and IFITM1(-), with a sensitivity of 81.8% and a specificity of 93.1%.\u003c/p\u003e \u003c/div\u003e \n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eThe Sensitivity and Specificity of combined IFITM1,CD10,h-caldesmon and SMA immunostaining in the Diagnosis of celluar leiomyoma.\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eGroups\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSensitivity (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpecificity (%)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) andIFITM1(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e69.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMA(+) and IFITM1(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.1\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) and CD10(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e72.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e96.6\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMA(+) and CD10(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e78.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e82.8\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) and SMA(+) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e87.9\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) or SMA(+) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.1\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) and SMA(+) and IFITM1(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e69.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) or SMA(+) and IFITM1(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.1\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) and SMA(+) and CD10(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e72.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e96.6\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) or SMA(+) and CD1(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e78.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e82.8\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) and SMA(+) and IFITM1(-) and CD10(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.6\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e100.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eh-caldesmon(+) or SMA(+) and IFITM1(-) and CD10(-) for CL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e66.7\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e93.1\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: CL indicates celluar leiomyoma.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eThe standard routine immunomarker panel used by most pathologists to distinguish ESS from CL consists of CD10, h-caldesmon, and SMA [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and an immunoprofile of CD10(+), h-caldesmon(-), and SMA(-) supports the diagnosis of ESS [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, especially when diagnosing endometrial stromal tumors using CD10 alone[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. CD10 is not merely expressed in endometrial stromal tumors but is also positively expressed in 20\u0026ndash;30% of smooth muscle tumors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. SMA is a common muscle marker for endometrial stromal tumors and therefore has a very low specificity. Although h-caldesmon has a higher specificity that of SMA, its sensitivity is worse[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Thus, the need for a novel biomarker or a new immunohistochemical combination is imperative.\u003c/p\u003e \u003cp\u003eIFITM1 is a novel biomarker for endometrium stromal cells and is reported to be more valuable than CD10 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. According to Busca et al[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], IFITM1 and CD10 were expressed in 14 ESS cases, and although their sensitivities were 83% and 91%, respectively, IFITM1 showed a higher specificity than CD10, that is, 70% vs. 45%. These findings are consistent with our findings, which state that IFITM1 was more specific and sensitive than CD10 in endometrial stromal tumors (sensitivity 86.7% vs. 63.3%, specificity 81.8% vs. 78.8%). Rush et al.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] compared the expressions of SMA and h-caldesmon between ESS and CL and found that SMA was more sensitive than h-caldesmon (90.9% vs. 72.7%); however, h-caldesmon was more specific than SMA (100% vs. 91.7%). In our study, h-caldesmon showed a lower sensitivity than SMA (87.9% vs. 100%), but its specificity was significantly higher (93.3% vs. 60%).\u003c/p\u003e \u003cp\u003eBased on the expressions of the four antibodies and their receiver operating characteristic curve, we speculate that their combination could be useful in the clinical and differential diagnosis of ESS and CL. When such combination was used for diagnosis, the area-under-the-curve predictive value was 0.995. However, there are certain limitations in that the receiver operating characteristic curve cannot completely show the positive and negative expressions of the antibodies. We therefore compared the sensitivities and specificities of the four combined antibodies using a screening test and selected the best biomarker panel. For the diagnosis of ESS, the combination IFITM1(+) or CD10(+) had the highest sensitivity (93.3%), followed by IFITM1(+) or CD10(+) and h-caldesmon(-) (86.7%). In terms of specificity, the combinations IFITM1(+) and h-caldesmon(-), IFITM1(+) and SMA(-), and CD10(+) and SMA(-) were the best panels, having a specificity of up to 100%, while IFITM1(+) or CD10(+) was the worst panel, with a specificity of only 66.7%. Considering both sensitivity and specificity, the best panel for diagnosing ESS was IFITM1(+) or CD10(+) and h-caldesmon(-), with a sensitivity of 86.7% and a specificity of 93.9%. The other good predictive panel for distinguishing ESS from CL was IFITM1(+) and h-caldesmon(-), with a sensitivity of 80% and a specificity of 100%.\u003c/p\u003e \u003cp\u003eIn general, no one immunomarker is sensitive and specific enough to make an accurate diagnosis, and so we usually use an immunohistochemical panel for differential diagnosis. This study revealed that the combination of IFITM1, CD10, SMA, and h-caldesmon comprised the best immunohistochemical panel for differentiating between ESS and CL. Considering the costs, we also recommend the combinations IFITM1 and h-caldesmon for the same purpose.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eImmunohistochemical combinations of the novel antibody IFITM1 with traditional antibodies CD10, SMA, and h-caldesmon can be very useful in distinguishing ESS from CL, especially when the clinical history and histological morphology cannot be differentiated totally.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work were supported by the National Natural Science Foundation of China [grant numbers 81460383, 81660411], the International Cooperation Project of Xinjiang Production and Construction Corps of China [grant number 2019BC001], the Key Areas Innovation Team Project of Xinjiang Production and Construction Corps of China [grant number 2018CB002].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Institutional Ethics Review Board (IERB) of the First Affiliated Hospital of School of Medicine, Shihezi University.Research was conducted according to all ethical standards, and written informed consent was obtained from all patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent to publish has been obtained from all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data in our study are available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare. No funding or other benefits related to the subject of this article were received from any commercial entity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work were supported by the National Natural Science Foundation of China [grant numbers 81460383, 81660411], the International Cooperation Project of Xinjiang Production and Construction Corps of China [grant number 2019BC001], the Key Areas Innovation Team Project of Xinjiang Production and Construction Corps of China [grant number 2018CB002].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZH , SZZ and WC conceived and designed this study; CM provided the clinical specimens; ZWL, JXH and XX performed the experiments; SXH ,JW and TL acquired the data; ZWL and CM analyzed the data and results; ZWL wrote the manuscript; ZH and PLJ improved and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eConklin, C.M. and T.A. Longacre, Endometrial stromal tumors: the new WHO classification. 2014. 21(6): p. 383.\u003c/li\u003e\n\u003cli\u003eToki, T., et al., CD10 is a Marker for Normal and Neoplastic Endometrial Stromal Cells. International Journal of Gynecological Pathology Official Journal of the International Society of Gynecological Pathologists. 21(1): p. 41-47.\u003c/li\u003e\n\u003cli\u003eChu, P.G., et al., Utility of CD10 in Distinguishing between Endometrial Stromal Sarcoma and Uterine Smooth Muscle Tumors: An Immunohistochemical Comparison of 34 Cases. Mod Pathol. 14(5): p. 465-471.\u003c/li\u003e\n\u003cli\u003eMCCLUGGAGE, W., CD10 is a sensitive and diagnostically useful immunohistochemical marker of normal endometrial stroma and endometrial stromal neoplasms. Histopathology, 2001. 39.\u003c/li\u003e\n\u003cli\u003eVera, A.A. and M.B. Guadarrama, Endometrial stromal sarcoma: clinicopathological and immunophenotype study of 18 cases. 2011. 15(5): p. 312-317.\u003c/li\u003e\n\u003cli\u003eOliva and Esther, CD10 Expression in the Female Genital Tract. Advances in Anatomic Pathology. 11(6): p. 310-315.\u003c/li\u003e\n\u003cli\u003eGroisman, G.M. and A. Meir, CD10 is helpful in detecting occult or inconspicuous endometrial stromal cells in cases of presumptive endometriosis. Archives of Pathology \u0026amp; Laboratory Medicine, 2003. 127(8): p. 1003-1006.\u003c/li\u003e\n\u003cli\u003ePotlog-Nahari, C., et al., CD10 immunohistochemical staining enhances the histological detection of endometriosis. Fertility \u0026amp; Sterility. 82(1): p. 86-92.\u003c/li\u003e\n\u003cli\u003eSumathi, V., CD10 is useful in demonstrating endometrial stroma at actopic sites and in confirming a diagnosis of endometrosis. Journal of Clinical Pathology, 2002. 55.\u003c/li\u003e\n\u003cli\u003eAbeler, V.M. and M. Nenodovic, Diagnostic Immunohistochemistry in Uterine Sarcomas: A Study of 397 Cases. International Journal of Gynecological Pathology Official Journal of the International Society of Gynecological Pathologists, 2011. 30(3): p. 236-243.\u003c/li\u003e\n\u003cli\u003eComparative clinicopathologic and immunohistochemical analysis of uterine sarcomas diagnosed using the World Health Organization classification system. 40(11): p. 0-1585.\u003c/li\u003e\n\u003cli\u003eOliva, E., et al., An Immunohistochemical Analysis of Endometrial Stromal and Smooth Muscle Tumors of the gUterus. American Journal of Surgical Pathology. 26(4): p. 403-412.\u003c/li\u003e\n\u003cli\u003eRush, D.S., et al., h-caldesmon, a novel smooth muscle-specific antibody, distinguishes between cellular leiomyoma and endometrial stromal sarcoma. Am J Surg Pathol, 2001. 25(2): p. 253-8.\u003c/li\u003e\n\u003cli\u003eZhu, X.Q., et al., Immunohistochemical markers in differential diagnosis of endometrial stromal sarcoma and cellular leiomyoma. Gynecologic Oncology. 92(1): p. 71-79.\u003c/li\u003e\n\u003cli\u003eMittal, K., R. Soslow, and W.G. Mccluggage, Application of Immunohistochemistry to Gynecologic Pathology. Archives of Pathology \u0026amp; Laboratory Medicine, 2008. 132(3): p. 402-423.\u003c/li\u003e\n\u003cli\u003eSun, H., et al., IFITM1 is a Novel, Highly Sensitive Marker for Endometriotic Stromal Cells in Ovarian and Extragenital Endometriosis. Reproductive Sciences.\u003c/li\u003e\n\u003cli\u003eParra-Herran, C.E., et al., Targeted development of specific biomarkers of endometrial stromal cell differentiation using bioinformatics: the IFITM1 model. Modern Pathology An Official Journal of the United States \u0026amp; Canadian Academy of Pathology Inc. 27(4): p. 569-579.\u003c/li\u003e\n\u003cli\u003ePark, H.J., et al., Characterisation of mouse interferon-induced transmembrane protein-1 gene expression in the mouse uterus during the oestrous cycle and pregnancy. Reprod Fertil Dev, 2011. 23.\u003c/li\u003e\n\u003cli\u003eBusca, A., et al., IFITM1 Outperforms CD10 in Differentiating Low-grade Endometrial Stromal Sarcomas From Smooth Muscle Neoplasms of the Uterus. International Journal of Gynecological Pathology Official Journal of the International Society of Gynecological Pathologists, 2017. 37(4): p. 1.\u003c/li\u003e\n\u003cli\u003eKurihara, S., et al., Coincident expression of \u0026beta;-catenin and cyclin D1 in endometrial stromal tumors and related high-grade sarcomas. Modern Pathology. 23(2): p. 225-234.\u003c/li\u003e\n\u003cli\u003eDe Leval, L., et al., Use of Histone Deacetylase 8 (HDAC8), a New Marker of Smooth Muscle Differentiation, in the Classification of Mesenchymal Tumors of the Uterus. American Journal of Surgical Pathology. 30(3): p. 319-327.\u003c/li\u003e\n\u003cli\u003eHwang, H., et al., Immunohistochemical panel to differentiate endometrial stromal sarcoma, uterine leiomyosarcoma and leiomyoma: something old and something new. Journal of Clinical Pathology: p. jclinpath-2015-202915.\u003c/li\u003e\n\u003cli\u003eFranquemont, D.W., H.F. Frierson, and S.E. Mills, An Immunohistochemical Study of Normal Endometrial Stroma and Endometrial Stromal Neoplasms. American Journal of Surgical Pathology. 15(9): p. 861-870.\u003c/li\u003e\n\u003cli\u003eBusca, A., et al., IFITM1 Is Superior to CD10 as a Marker of Endometrial Stroma in the Evaluation of Myometrial Invasion by Endometrioid Adenocarcinoma. American Journal of Clinical Pathology. 145(4): p. 486-496.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"IFITM1, CD10, SMA, h-caldesmon, Immunohistochemical, Differential Diagnosis, ESS,CL","lastPublishedDoi":"10.21203/rs.2.23242/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.23242/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The differential diagnosis of endometrial stromal sarcoma (ESS) and uterine cellular leiomyoma (CL) remains a challenge in clinical practice. Cluster of differentiation 10 (CD10) and smooth muscle actin (SMA) are commonly used in the differential diagnosis of ESS and CL. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, suggesting the need for novel immunomarkers panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1) is a novel immunomarker for endometrial stromal cells, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than SMA. So this study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for diagnosing between ESS and CL. Tissue microarrays were used to detect IFITM1, CD10, SMA, and h-caldesmon immunohistochemical staining in 30 ESS and 33 CL cases. The expressions of IFITM1 and CD10 were high in ESS (86.7% and 63.3%, respectively) but low in CL (18.2% and 21.2%), whereas those of h-caldesmon and SMA were high in both CL (87.9% and 100%) and low in ESS (6.9% and 40%). In diagnosing ESS, IFITM1 had better sensitivity and specificity (86.7% and 81.8%, respectively) than CD10 (63.3% and 78.8%). The specificity of h-caldesmon in diagnosing CL was significantly higher (93.1%) than that of SMA (60%). When all four antibodies were combined for the differential diagnosis, the area-under-the-curve predictive value was 0.995. The most sensitive and specific combinations for diagnosing ESS were IFITM1(+) or CD10(+) and h-caldesmon(-) ( sensitivity 86.7%, specificity 93.9%), IFITM1(+) and h-caldesmon(-) ((sensitivity 80%, specificity 100%). The most sensitive and specific combinations for diagnosing CL were h-caldesmon(+) and SMA(+)(sensitivity 87.9%, specificity 100%), h-caldesmon(+) or SMA(+) and IFITM1(-)(sensitivity 81.8% , specificity 93.1%).Therefore, IFITM1, CD10, SMA, and h-caldesmon are a good combination of biomarkers for the differential diagnosis of ESS and CL.The differential diagnosis of endometrial stromal sarcoma (ESS) and uterine cellular leiomyoma (CL) remains a challenge in clinical practice. Cluster of differentiation 10 (CD10) and smooth muscle actin (SMA) are commonly used in the differential diagnosis of ESS and CL. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, suggesting the need for novel immunomarkers panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1) is a novel immunomarker for endometrial stromal cells, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than SMA. So this study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for diagnosing between ESS and CL. Tissue microarrays were used to detect IFITM1, CD10, SMA, and h-caldesmon immunohistochemical staining in 30 ESS and 33 CL cases. The expressions of IFITM1 and CD10 were high in ESS (86.7% and 63.3%, respectively) but low in CL (18.2% and 21.2%), whereas those of h-caldesmon and SMA were high in both CL (87.9% and 100%) and low in ESS (6.9% and 40%). In diagnosing ESS, IFITM1 had better sensitivity and specificity (86.7% and 81.8%, respectively) than CD10 (63.3% and 78.8%). The specificity of h-caldesmon in diagnosing CL was significantly higher (93.1%) than that of SMA (60%). When all four antibodies were combined for the differential diagnosis, the area-under-the-curve predictive value was 0.995. The most sensitive and specific combinations for diagnosing ESS were IFITM1(+) or CD10(+) and h-caldesmon(-) ( sensitivity 86.7%, specificity 93.9%), IFITM1(+) and h-caldesmon(-) ((sensitivity 80%, specificity 100%). The most sensitive and specific combinations for diagnosing CL were h-caldesmon(+) and SMA(+)(sensitivity 87.9%, specificity 100%), h-caldesmon(+) or SMA(+) and IFITM1(-)(sensitivity 81.8% , specificity 93.1%).Therefore, IFITM1, CD10, SMA, and h-caldesmon are a good combination of biomarkers for the differential diagnosis of ESS and CL.The differential diagnosis of endometrial stromal sarcoma (ESS) and uterine cellular leiomyoma (CL) remains a challenge in clinical practice. Cluster of differentiation 10 (CD10) and smooth muscle actin (SMA) are commonly used in the differential diagnosis of ESS and CL. However, the current combination of immunohistochemical antibodies has been shown to be inaccurate, suggesting the need for novel immunomarkers panels for differentiating between ESS and CL. Interferon-induced transmembrane protein 1 (IFITM1) is a novel immunomarker for endometrial stromal cells, h-caldesmon is an immunomarker for smooth muscle cells and has a higher specificity than SMA. So this study aimed to investigate IFITM1, CD10, SMA, and h-caldesmon as a useful combination of biomarkers for diagnosing between ESS and CL. Tissue microarrays were used to detect IFITM1, CD10, SMA, and h-caldesmon immunohistochemical staining in 30 ESS and 33 CL cases. The expressions of IFITM1 and CD10 were high in ESS (86.7% and 63.3%, respectively) but low in CL (18.2% and 21.2%), whereas those of h-caldesmon and SMA were high in both CL (87.9% and 100%) and low in ESS (6.9% and 40%). In diagnosing ESS, IFITM1 had better sensitivity and specificity (86.7% and 81.8%, respectively) than CD10 (63.3% and 78.8%). The specificity of h-caldesmon in diagnosing CL was significantly higher (93.1%) than that of SMA (60%). When all four antibodies were combined for the differential diagnosis, the area-under-the-curve predictive value was 0.995. The most sensitive and specific combinations for diagnosing ESS were IFITM1(+) or CD10(+) and h-caldesmon(-) ( sensitivity 86.7%, specificity 93.9%), IFITM1(+) and h-caldesmon(-) ((sensitivity 80%, specificity 100%). The most sensitive and specific combinations for diagnosing CL were h-caldesmon(+) and SMA(+)(sensitivity 87.9%, specificity 100%), h-caldesmon(+) or SMA(+) and IFITM1(-)(sensitivity 81.8% , specificity 93.1%).Therefore, IFITM1, CD10, SMA, and h-caldesmon are a good combination of biomarkers for the differential diagnosis of ESS and CL.","manuscriptTitle":"IFITM1, CD10, SMA, and h-caldesmon as a helpful combination in differential diagnosis between endometrial stromal sarcoma and cellular leiomyoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-02-11 22:38:51","doi":"10.21203/rs.2.23242/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1adf319-2d1e-4cc7-9307-c09e216cddb2","owner":[],"postedDate":"February 11th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57804,"name":"Translational Medicine"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2020-02-11 22:38:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-13811","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-13811","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}