PURPOSE: In order to suggest optimal anticancer drugs for patient-tailored chemotherapy, we developed a colorectal cancer (CRC)-liver metastasis patient-derived tumor xenograft (PDTX) model. METHODS: Tissue obtained from a patient with CRC-liver metastasis (F0) was transplanted in a nonobese female mouse with diabetic/severe combined immune deficiency (F1) and the tumor tissue was retransplanted into nude mice (F2). When tumor volumes reached ~500 mm³, the F2 mice were randomly divided into 4 groups (n = 4/group) of doxorubicin, cisplatin, docetaxel, and nontreated control groups. The tumor tissues were investigated using H&E staining, terminal deoxynucleotidyl transferase dUTP nick end labeling assays, and immunohistochemistry. To determine where the mutant allele frequencies varied across the different passages, we isolated genomic DNA from the primary tumor, liver metastasis, and PDTX models (F1/F2). RESULTS: The physiological properties of the tumor were in accord with those of the patient's tumors. Anticancer drugs delayed tumor growth, inhibited proliferation, and caused apoptosis. Histological assessments revealed no observable heterogeneity among the intragenerational PDTX models. Target exon sequencing analysis without high-quality filter conditions revealed some genetic variations in the 83 cancer-related genes across the generations. However, when de novo mutations were defined as a total count of zero in F0 and ≥5 in F2, exactly prognostic impact of clone cancer profiling (EGFR, KRAS, BRAF, PIK3CA, NRAS, APC and TP53) were detected in the paired. CONCLUSION: A CRC liver metastasis PDTX model was established for the evaluation of chemotherapeutic efficacy. This model retained the physiological characters of the patient tumors and potentially provides a powerful means of assessing chemotherapeutic efficacy.
Animals ; Apoptosis ; Cisplatin ; Clone Cells ; Colorectal Neoplasms* ; DNA ; DNA Nucleotidylexotransferase ; Doxorubicin ; Drug Therapy* ; Exons ; Family Characteristics ; Female ; Gene Frequency ; Genetic Variation ; Heterografts* ; Humans ; Immunohistochemistry ; Liver* ; Mice ; Mice, Nude ; Neoplasm Metastasis* ; Population Characteristics ; Sequence Analysis ; Xenograft Model Antitumor Assays

BACKGROUND: Warthin-like variant of papillary thyroid carcinoma (WLV-PTC) is a relatively rare variant of papillary thyroid carcinoma with favorable prognosis. However, preoperative diagnosis using fine-needle aspiration (FNA) specimens is challenging especially with lymphocytic thyroiditis characterized by Hürthle cells and lymphocytic background. To determine a helpful cytological differential point, we compared WLV-PTC FNA findings with conventional papillary thyroid carcinoma with lymphocytic thyroiditis (PTC-LT) and conventional papillary thyroid carcinoma without lymphocytic thyroiditis (PTC) regarding infiltrating inflammatory cells and their distribution. Preoperative diagnosis or potential for WLV-PTC will be helpful for surgeons to decide the scope of operation. METHODS: Of the 8,179 patients treated for papillary thyroid carcinoma between January 2007 and December 2012, 16 patients (0.2%) were pathologically confirmed as WLV-PTC and four cases were available for cytologic review. For comparison, we randomly selected six PTC-LT cases and five PTC cases during the same period. The number of intratumoral and background lymphocytes, histiocytes, neutrophils, and the presence of giant cells were evaluated and compared using conventional smear and ThinPrep preparations. RESULTS: WLV-PTC showed extensive lymphocytic smear with incorporation of thyroid follicular tumor cell clusters and frequent histiocytes. WLV-PTC was associated with higher intratumoral and background lymphocytes and histiocytes compared with PTC-LT or PTC. The difference was more distinct in liquid-based cytology. CONCLUSIONS: The lymphocytic smear pattern and the number of inflammatory cells of WLV-PTC are different from those of PTC-LT or PTC and will be helpful for the differential diagnosis of WLV-PTC in preoperative FNA.
Biopsy, Fine-Needle ; Diagnosis ; Diagnosis, Differential ; Giant Cells ; Hashimoto Disease ; Histiocytes ; Humans ; Lymphocytes ; Neutrophils ; Prognosis ; Surgeons ; Thyroid Gland ; Thyroid Neoplasms ; Thyroiditis, Autoimmune

Objective: To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN). Methods: A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me). For the test, Examiner-1 and Examiner-2 (3-year and 1-year orthodontic residents) and the Cascaded-CNN models marked the landmarks. After point-to-point errors of landmark identification, the successful detection rate (SDR) and distance and direction of the midline landmark deviation from the midsagittal line (ANS-mid, UDM-mid, LDM-mid, and Me-mid) were measured, and statistical analysis was performed. Results: The cascaded-CNN algorithm showed a clinically acceptable level of point-to-point error (1.26 mm vs.1.57 mm in Examiner-1 and 1.75 mm in Examiner-2). The average SDR within the 2 mm range was 83.2%, with high accuracy at the LO (right, 96.9%; left, 97.1%), and UDM (96.9%). The absolute measurement errors were less than 1 mm for ANSmid, UDM-mid, and LDM-mid compared with the gold standard. Conclusions The cascaded-CNN model may be considered an effective tool for the auto-identification of midline landmarks and quantification of midline deviation in PA cephalograms of adult patients, regardless of variations in the image acquisition method.