Ascites cytology is a cost-effective test for metastatic colorectal cancer (CRC) in the abdominal cavity. However, metastatic carcinoma of the peritoneum is difficult to diagnose based on biopsy findings, and ascitic aspiration cytology has a low sensitivity and specificity and a high inter-observer variability. The aim of the present study was to apply artificial intelligence (AI) to classify benign and malignant cells in ascites cytology patch images of metastatic CRC using a deep convolutional neural network. Datasets were collected from The OPEN AI Dataset Project, a nationwide cytology dataset for AI research. The numbers of patch images used for training, validation, and testing were 56,560, 7068, and 6534, respectively. We evaluated 1041 patch images of benign and metastatic CRC in the ascitic fluid to compare the performance of pathologists and an AI algorithm, and to examine whether the diagnostic accuracy of pathologists improved with the assistance of AI. This AI method showed an accuracy, a sensitivity, and a specificity of 93.74%, 87.76%, and 99.75%, respectively, for the differential diagnosis of malignant and benign ascites. The diagnostic accuracy and sensitivity of the pathologist with the assistance of the proposed AI method increased from 86.8% to 90.5% and from 73.3% to 79.3%, respectively. The proposed deep learning method may assist pathologists with different levels of experience in diagnosing metastatic CRC cells of ascites.

A 57-year-old man with left flank pain was referred to our institute. Computed tomography scans revealed two enhancing masses in the left kidney. The clinical diagnosis was renal cell carcinoma (RCC). He underwent a radical nephrectomy with an adrenalectomy. Two well-circumscribed solid masses in the hilum and the lower pole (4.5 × 3.5 cm and 7.0 × 4.1 cm) were present. Poorly cohesive uniform round to polygonal epithelioid cells making solid sheets accounted for most of the tumor area. The initial diagnosis was RCC, undifferentiated with rhabdoid features. As the tumor showed loss of INI1 expression and a mutation in the SMARCB1 gene on chromosome 22, the revised diagnosis was a malignant rhabdoid tumor (MRT) of the kidney. To date, only a few cases of renal MRT in adults have been reported. To the best of our knowledge, this is the first report of MRT in the native kidney of an adult demonstrating a SMARCB1 gene mutation, a hallmark of MRT.

Purpose The programmed death-ligand 1 (PD-L1) SP142 assay identifies patients with triple-negative breast cancer (TNBC) who are most likely to respond to the anti–PD-L1 agent atezolizumab. We aimed to compare PD-L1 (SP142) expression between primary and recurrent/metastatic TNBCs and elucidate the clinicopathological features associated with its expression.Materials and Methods Primary and recurrent/metastatic TNBCs tested with PD-L1 (SP142) were collected, and clinicopathological information of these cases was obtained through a review of slides and medical records.Results PD-L1 (SP142) positivity was observed in 50.9% (144/283) of primary tumors and 37.8% (31/82) of recurrent/metastatic TNBCs with a significant difference. Recurrent or metastatic sites were associated with PD-L1 positivity, with high PD-L1 positivity in the lung, breast, and soft tissues, and low positivity in the bone, skin, liver, and brain. When comparing PD-L1 expression between primary and matched recurrent/metastatic TNBCs using 55 paired samples, 20 cases (36.4%) showed discordance; 10 cases revealed positive conversion, and another 10 cases revealed negative conversion during metastatic progression. In primary TNBCs, PD-L1 expression was associated with a higher histologic grade, lower T category, pushing border, and higher tumor-infiltrating lymphocyte infiltration. In survival analyses, PD-L1 positivity, especially high positivity, was found to be associated with favorable prognosis of patients.Conclusion PD-L1 (SP142) expression was lower in recurrent/metastatic TNBCs, and substantial cases showed discordance in its expression between primary and recurrent/metastatic sites, suggesting that multiple sites may need to be tested for PD-L1 (SP142) when considering atezolizumab therapy. PD-L1 (SP142)–positive TNBCs seems to be associated with favorable clinical outcomes.

Ubiquitin-specific protease 13 (USP13) is a deubiquitinating enzyme that stabilizes phosphatase and tensin homolog deleted on chromosome 10 (PTEN), a well-established tumor suppressor involved in PI3K/AKT signaling. This study aimed to evaluate the relationship between USP13 immunohistochemical staining intensity and clinicopathological factors associated with prostate cancer progression. USP13 staining was scored as grade 0 (negative), 1 (weak), 2 (moderate), or 3 (strong) in 242 prostate cancer tissues and 22 adjacent non-neoplastic control tissues. Higher USP13 grades were exhibited by adjacent non-neoplastic tissues than prostate carcinoma. In comparison, lower USP13 grades were observed in 88.6% of the neoplastic regions (p < 0.001). No differences in PSA level, Gleason’s score, disease stage, involvement of either the seminal vesicle or lymph nodes, surgical margin positivity, biochemical or clinical recurrence rates, or overall survival statistics were found. Cox proportional hazards modeling showed no significant association between USP13 expression and biochemical recurrence-free survival or overall survival. Kaplan–Meier analysis demonstrated no statistically significant differences in survival outcomes according to USP13 expression, although a descriptive trend was observed. USP13 immunohistochemical staining distinguished malignant prostate tissue from adjacent non-neoplastic tissue in tissue microarrays. However, USP13 expression was not independently associated with pathological aggressiveness or survival outcomes in this cohort.

Kim HK, et al. J Korean Med Sci. 2026 Nov;41:e280. https://doi.org/10.3346/jkms.2026.41.e280

Purpose: For downregulating phosphate and tensin homolog deleted on chromosome 10, well-established tumor suppressor, requires the ubiquitin-proteasome system such as USP13. The aim of this study was to identify the relationships between the intensity of immunohistochemical staining for USP13 and factors associated with the progression of prostate carcinoma. Materials and methods: USP13 staining was scored for each histological cohort as either high, medium, low or negative in 242 prostate cancer tissues and 22 controls. Results: Higher UPS13 grades were exhibited by non-malignant tissues than prostate carcinoma. In comparison, lower USP13 grades were observed in 88.6% of the neoplastic regions (p < 0.001). No differences in PSA level, Gleason’s score, disease stage, involvement of either the seminal vesical or lymph nodes, surgical margin positivity, biochemical or clinical recurrence rates or overall survival statistics were found. No relationship was identified between USP13 immunohistochemical staining intensity and either biochemical recurrence free or overall survival following Cox proportional hazard modeling. The grade of USP immunohistochemical staining was associated, according to the Kaplan-Meier technique, with biochemical or clinical tumor recurrence, and overall survival. Conclusion: In tissue microarrays (TMAs) from patients with prostate carcinoma, USP13 immunohistochemical staining can be used to differentiate neoplastic tissue from non-malignant neighboring tissue regions.