Clinical impact of a cytological screening system using cyclin D1 immunostaining and genomic analysis for the diagnosis of thyroid nodules

Abstract Background Fine-needle aspiration (FNA) is the most reliable method for diagnosing thyroid nodules; however, some features such as atypia of undetermined significance or follicular lesion of undetermined significance can confound efforts to identify malignancies. Similar to BRAF, cyclin D1 may be a strong marker of cell proliferation. Methods One hundred two patients with thyroidal nodule were enrolled in this prospective study. Expression of cyclin D1 in thyroid nodules was determined by immunohistochemistry using both surgical specimens and their cytological specimens. The identification of the optimal cut off points for the diagnosis of malignancy were evaluated using the receiver operating characteristic (ROC) curves and the assessment of the area under the ROC curve (AUC). The specificity, sensitivity, positive predictive value (PPV) of markers were evaluated from crosstabs based on cut off points and significance were calculated. We also analyzed genetic variants by target NGS for thyroid nodule samples. Results The positive predictive value (PPV) and median stain ratio (MSR) of cyclin D1 nuclear staining was determined in papillary thyroid carcinoma (PPV = 91.5%, MSR = 48.5%), follicular adenoma (PPV = 66.7%, MSR = 13.1%), and adenomatous goiter and inflammation controls (MSR = 3.4%). In FNA samples, a threshold of 46% of immunolabelled cells allows to discriminate malignant lesions from benign ones (P < 0.0001), with 81% sensitivity and 100% specificity. A 46% cutoff value for positive cyclin D1 immunostaining in thyroid cells demonstrated 81% sensitivity and 100% specificity. In surgical specimens, ROC curve analysis showed a 5.8% cyclin D1 immunostaining score predicted thyroid neoplasms at 94.4% sensitivity and 92.3% specificity (P = 0.003), while a 15.7% score predicted malignancy at 86.4% sensitivity and 80.5% specificity (P < 0.0001). Finally, three tested clinico-pathological variables (extra thyroidal extension, intraglandular metastasis, and lymph node metastasis) were significant predictors of cyclin D1 immunostaining (P < 0.001). Conclusion Our cytological cyclin D1 screening system provides a simple, accurate, and convenient diagnostic method in precision medicine enabling ready determination of personalized treatment strategies for patients by next generation sequencing using cytological sample

Strategic Approach to Heterogeneity Analysis of Cutaneous Adnexal Carcinomas Using Computational Pathology and Genomics

Cutaneous adnexal tumors are neoplasms that arise from skin appendages. Their morphologic diversity and phenotypic variability with rare progression to malignancy make them difficult to diagnose and classify, and there is currently no established treatment strategy. To overcome these difficulties, this study investigated the transcription factor SOX9 expression, morphology, and genetics of skin adnexal tumors for understanding their biology, especially their histogenesis. We showed that cutaneous adnexal tumors and their nontumor counterparts of skin and appendages exhibit expression patterns similar to that of SOX9. Its expression intensity and pattern, as well as histopathologic evaluation of tumors, were analyzed using digital images of 69 normal skin adnexal 9-type organs and 185 skin adnexal 29-type tumors as references. It was possible to distinguish basal cell carcinoma from squamous cell carcinoma, sebaceous carcinoma, and pilomatrixoma with significant differences, along with porocarcinoma from squamous cell carcinoma. Furthermore, unsupervised machine learning “computational pathology” was used to derive a multiregion whole-exome sequencing fusion method termed “genocomputed pathology.” The genocomputed pathology of three representable adnexal carcinomas (porocarcinoma, hidradenocarcinoma, and spiradenocarcinoma) was evaluated for total nine cases. We showed that there was more heterogeneity than expected within the tumors as well as the coexistence of components lacking driver fusion genes. The presence or absence of potential driver genes, such as PIK3CA, YAP1, and PTEN, in each region was identified, highlighting a therapeutic strategy for cutaneous adnexal carcinoma encompassing heterogeneous tumors