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Objective: To investigate the value of predicting the degree of differentiation of pulmonary invasive adenocarcinoma (IAC) based on CT image radiomics model and the expression difference of immunohistochemical factors between different degrees of differentiation of lesions. Methods: The clinicopathological data of patients with pulmonary IAC confirmed by surgical pathology in the Affiliated Huai'an First People's Hospital to Nanjing Medical University from December 2017 to September 2018 were collected. High-throughput feature acquisition was performed for all outlined regions of interest, and prediction models were constructed after dimensionality reduction by the minimum absolute shrinkage operator. Receiver operating characteristic curve was used to assess the predictive efficacy of clinical characteristic model, radiomics model and individualized prediction model combined with both to identify the degree of pulmonary IAC differentiation, and immunohistochemical expressions of Ki-67, NapsinA and TTF-1 were compared between groups with different degrees of IAC differentiation using rank sum test. Results: A total of 396 high-throughput features were extracted from all IAC lesions, and 10 features with high generalization ability and correlation with the degree of IAC differentiation were screened. The mean radiomics score of poorly differentiated IAC in the training group (1.206) was higher than that of patients with high and medium differentiation (0.969, P=0.001), and the mean radiomics score of poorly differentiated IAC in the test group (1.545) was higher than that of patients with high and medium differentiation (-0.815, P<0.001). The differences in gender (P<0.001), pleural stretch sign (P=0.005), and burr sign (P=0.033) were statistically significant between patients in the well and poorly differentiated IAC groups. Multifactorial logistic regression analysis showed that gender and pleural stretch sign were related to the degree of IAC differentiation (P<0.05). The clinical feature model consisted of age, gender, pleural stretch sign, burr sign, tumor vessel sign, and vacuolar sign, and the individualized prediction model consisted of gender, pleural stretch sign, and radiomic score, and was represented by a nomogram. The Akaike information standard values of the radiomics model, clinical feature model and individualized prediction model were 54.756, 82.214 and 53.282, respectively. The individualized prediction model was most effective in identifying the degree of differentiation of pulmonary IAC, and the area under the curves (AUC) of the individualized prediction model in the training group and the test group were 0.92 (95% CI: 0.86-0.99) and 0.88 (95% CI: 0.74-1.00, respectively). The AUCs of the radiomics group model for predicting the degree of differentiation of pulmonary IAC in the training group and the test group were 0.91 (95% CI: 0.83-0.98) and 0.87 (95% CI: 0.72-1.00), respectively. The AUCs of the clinical characteristics model for predicting the degree of differentiation of pulmonary IACs in the training and test groups were 0.75 (95% CI: 0.63-0.86) and 0.76 (95% CI: 0.59-0.94), respectively. The expression level of Ki-67 in poorly differentiated IAC was higher than that in well-differentiated IAC (P<0.001). The expression levels of NapsinA, TTF-1 in poorly differentiated IAC were higher than those in well-differentiated IAC (P<0.05). Conclusions: Individualized prediction model consisted of gender, pleural stretch sign and radiomics score can discriminate the differentiation degree of IAC with the best performance in comparison with clinical feature model and radiomics model. Ki-67, NapsinA and TTF-1 express differently in different degrees of differentiation of IAC.
Subject(s)
Humans , Adenocarcinoma of Lung/pathology , Ki-67 Antigen , Lung Neoplasms/pathology , Retrospective Studies , Tomography, X-Ray Computed/methodsABSTRACT
Background: Alpha-methylacyl-coenzyme A racemase (AMACR, P504S) is a commonly used marker in immunohistochemical diagnosis of prostate cancer. Recent studies identified P504S markers of the clear cell histotype in the ovary and/or endometrium. Gastric-type adenocarcinoma (GAS) is difficult to diagnose histologically, particularly when there is crossover with clear cell carcinoma (CCC). However, the significance of P504S for differentially diagnosing GAS and CCC is unclear. Aim: To evaluate P504S as a potential diagnostic marker of GAS and CCC. Settings and Design: We analyzed P504S expression in 48 cervical carcinomas (32 GAS and 16 CCC), as well as the expression of other markers including hepatocyte nuclear factor-1 beta (HNF-1?) and NapsinA. Material and Methods: The expression differences of HNF-1?, NapsinA, and P504S in GAS and CCC were detected by immunohistochemistry. Immunohistochemical histoscores based on the intensity and extent of staining were calculated. Results: The positive rates of HNF-1? in GAS and CCC were 90.32% and 75%, respectively. (?2 = 2.251, P = 0.663). The positive rates of NapsinA in GAS and CCC were 19.36% and 81.25%, respectively. (?2 = 47.332, P < 0.01). The positive rates of P504S in GAS and CCC were 16.13% and 81.25%, respectively. (?2 = 41.420, P < 0.01). HNF-1? was frequently expressed in GAS and CCC, while NapsinA and P504S were frequently expressed in CCC, and reduced or lost in GAS. Conclusion: NapsinA and P504S can be used to differentiate between GAS and CCC.
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Objective To detect the expression and the differential significance of CK 5／6,DSG3,P40,TTF-1,CK7,NapsinA in small biopsy specimens of non -small cell lung cancer ( NSCLC),squamous cell carcinoma (SCC) and adenocarcinoma (AC).Methods Immunohistochemical SP method was used to detect the expressions of CK5／6,DSG3,P40,TTF-1,CK7 and NapsinA in 120 small biopsy specimens of NSCLC hospitalized in the Central People's Hospital of Tengzhou from January 2016 to December 2017,and the results were analyzed combined with the clinical characteristics of NSCLC.Results The positive expression rates of CK5／6,DSG3 and P40 in lung SCC were 100.0%(56／56),89.3%(50／56) and 96.4%(54／56), respectively,with specificity of 90.6%,100.0% and 100.0%,respectively.The positive expression rates of NapsinA ,TTF-1 and CK7 in lung AC were 81.3%(52／64), 90.6%(58／64) and 93.8%(60／64),respectively,with specificity of 100.0%,92.9% and 96.4%,respectively. The positive expression rates of CK5／6,DSG3,P40 in SCC had statistically significant differences compared with those in AC (all P＜0.05),and the expression of TTF -1,CK7 and NapsinA in AC had statistically significant differences compared with those in SCC ( all P＜0.05).Conclusion CK5／6,DSG3,P40,TTF-1,CK7 and NapsinA are of great significance in the differential diagnosis of SCC and AC in small biopsy specimens of NSCLC .
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Objective@#To detect the expression and the differential significance of CK5/6, DSG3, P40, TTF-1, CK7, NapsinA in small biopsy specimens of non-small cell lung cancer (NSCLC), squamous cell carcinoma (SCC) and adenocarcinoma (AC).@*Methods@#Immunohistochemical SP method was used to detect the expressions of CK5/6, DSG3, P40, TTF-1, CK7 and NapsinA in 120 small biopsy specimens of NSCLC hospitalized in the Central People's Hospital of Tengzhou from January 2016 to December 2017, and the results were analyzed combined with the clinical characteristics of NSCLC.@*Results@#The positive expression rates of CK5/6, DSG3 and P40 in lung SCC were 100.0%(56/56), 89.3%(50/56) and 96.4%(54/56), respectively, with specificity of 90.6%, 100.0% and 100.0%, respectively.The positive expression rates of NapsinA, TTF-1 and CK7 in lung AC were 81.3%(52/64), 90.6%(58/64) and 93.8%(60/64), respectively, with specificity of 100.0%, 92.9% and 96.4%, respectively.The positive expression rates of CK5/6, DSG3, P40 in SCC had statistically significant differences compared with those in AC (all P<0.05), and the expression of TTF-1, CK7 and NapsinA in AC had statistically significant differences compared with those in SCC (all P<0.05).@*Conclusion@#CK5/6, DSG3, P40, TTF-1, CK7 and NapsinA are of great significance in the differential diagnosis of SCC and AC in small biopsy specimens of NSCLC.