Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; Biomarkers, Tumor

Humans ; Sarcoma ; NFATC Transcription Factors ; RNA-Binding Protein EWS

Humans ; Lymphoma, B-Cell

Animals ; Mice ; Colon ; Histological Techniques

Humans ; Child ; Pulmonary Blastoma/pathology* ; Lung Neoplasms/pathology*

Humans ; Anaplastic Lymphoma Kinase ; Histiocytosis, Langerhans-Cell ; Receptor Protein-Tyrosine Kinases ; Lymphoma, Large-Cell, Anaplastic/pathology*

Objective: To investigate the clinicopathological features, molecular genetic features, differential diagnosis and prognosis of ELOC mutated renal cell carcinoma. Methods: From January 2015 to June 2022, 11 cases of renal cell carcinoma with clear-cell morphology, expression of CAⅨ and CK7 and no 3p deletion were collected. Two cases of ELOC mutant renal cell carcinoma were diagnosed using whole exome sequencing (WES). The clinical features, morphology, immunophenotype, FISH and WES results were analyzed. The relevant literature was reviewed. Results: The two patients were both male, aged 29 and 51 years, respectively. They were both found to have a renal mass by physical examination. The maximum diameters of the tumors were 3.5 cm and 2.0 cm, respectively. At the low magnification, the tumors were well-defined. The tumor cells showed a pushing border and were separated by thick fibrous bands, forming nodules. The tumor cells were arranged in a variety of patterns, including tubular, papillary, solid nest or alveolar. At high magnification, the tumor cells were large, with well-defined cell borders and clear cytoplasm or fine eosinophilic granules. CAⅨ was diffusely box-like positive in both cases. Case 1 was partially and moderately positive for CK7, strongly positive for CD10, diffusely and moderately positive for P504S, and weakly positive for 34βE12. In case 2, CK7 and CD10 were both partially, moderately positive and P504s were diffusely positive, but 34βE12 was negative. FISH results showed that both cases had no 3p deletion. ELOC c.235T>A (p.Y79N) mutation was identified using WES in case 1, while ELOC c.236_237inv (p.Y79C) mutation was identified in case 2. Conclusions: As a new clinical entity, ELOC mutated renal cell carcinoma may be underdiagnosed due to its overlap with clear cell renal cell carcinoma in morphology and immunophenotype. The diagnosis of renal cell carcinoma with ELOC mutation should be confirmed by morphology, immunohistochemistry, FISH and gene mutation detection. However, more additional cases are needed to explain its biological behavior and prognosis.
Humans ; Male ; Biomarkers, Tumor/genetics* ; Carcinoma, Renal Cell/pathology* ; Chromosome Aberrations ; Kidney Neoplasms/pathology* ; Molecular Biology ; Mutation ; Prognosis

Objective: To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfoliative cytology and its clinical values. Methods: A total of 3 033 urine exfoliated cytology samples were collected at the Henan People's Hospital, Capital Medical University, Beijing, China. Liquid-based thin-layer cytology was prepared. The slides were manually read under the microscope and digitally presented using a scanner. The intelligent identification and analysis were carried out using an artificial intelligence TPS assisted screening system. The Paris Report Classification System of Urinary Exfoliated Cytology 2022 was used as the evaluation standard. Atypical urothelial cells and even higher grade lesions were considered as positive when evaluating the recognition sensitivity, specificity, and diagnostic accuracy of artificial intelligence-assisted screening systems and human-machine collaborative cytologic screening methods in urine exfoliative cytology. Among the collected cases, there were also 1 100 pathological tissue controls. Results: The accuracy, sensitivity and specificity of the AI-assisted cytologic screening system were 77.18%, 90.79% and 69.49%; those of human-machine coordination method were 92.89%, 99.63% and 89.09%, respectively. Compared with the histopathological results, the accuracy, sensitivity and specificity of manual reading were 79.82%, 74.20% and 95.80%, respectively, while those of AI-assisted cytologic screening system were 93.45%, 93.73% and 92.66%, respectively. The accuracy, sensitivity and specificity of human-machine coordination method were 95.36%, 95.21% and 95.80%, respectively. Both cytological and histological controls showed that human-machine coordination review method had higher diagnostic accuracy and sensitivity, and lower false negative rates. Conclusions: The artificial intelligence TPS assisted cytologic screening system has achieved acceptable accuracy in urine exfoliation cytologic screening. The combination of manual screening and artificial intelligence TPS assisted screening system can effectively improve the sensitivity and accuracy of cytologic screening and reduce the risk of misdiagnosis.
Humans ; Artificial Intelligence ; Urothelium/pathology* ; Cytodiagnosis ; Epithelial Cells/pathology* ; Sensitivity and Specificity ; Urologic Neoplasms/urine*

Humans ; Fibrinogen ; Liver/pathology* ; Liver Diseases/pathology* ; Metabolic Diseases/pathology*

Humans ; Receptor, trkA/genetics* ; Neoplasms/genetics* ; Biomarkers, Tumor ; Gene Rearrangement ; Oncogene Proteins, Fusion/genetics*