Virchows Archiv最新文献

Uterine sarcomas with KAT6B/A::KANSL1 fusion represent a new entity characterized by bland morphology, commonly with hybrid features of low-grade endometrial stromal sarcoma (LG-ESS) and tumors with smooth muscle differentiation. In our study, we performed a detailed morphological, immunohistochemical, and molecular analysis of 9 cases of these tumors. Six of those had been originally diagnosed as LG-ESS, one as leiomyoma, one as leiomyosarcoma, and the remaining case as sarcoma with the KAT6B/A::KANSL1 fusion. Seven cases showed overlapping features between endometrial stromal and smooth muscle tumors, one case resembled cellular leiomyoma, and one case resembled high-grade endometrial stromal sarcoma. Immunohistochemically, the tumors showed a common expression of smooth muscle markers and endometrial stromal markers. Molecular findings showed the KAT6B/A::KANSL1 fusion in all cases (by NGS and FISH). In addition, mutations affecting genes such as TP53, PDGFRB, NF1, RB1, PTEN, ATM, RB1, FANCD2, and TSC1 were present in all 5 cases with aggressive behavior. One patient with no evidence of disease showed no additional mutations, while another harbored a mutation of a single gene (ERCC3). Of the 8 patients with available follow-up, two died of disease, 3 are currently alive with disease, and 3 have no evidence of disease. The correct recognition of tumors with the KAT6B/A::KANSL1 fusion is essential because despite the bland morphological features of most cases, these tumors have a propensity for aggressive behavior.

Due to the overlap of histological and molecular features of primary mediastinal large B-cell lymphoma (PMBL) with other lymphomas and its low incidence, the diagnosis and prognostic assessment of PMBL pose certain challenges. This study included 51 PMBL and 375 diffuse large B-cell lymphoma, not otherwise specified (DLBCL-NOS) from the GEO database and 65 PMBL and 117 DLBCL-NOS from a single center. At the transcriptional and protein levels, RHOF expression in PMBL was significantly higher than in DLBCL-NOS (P < 0.001). ROC curve analysis suggested that high RHOF expression had a high discriminative diagnostic ability for PMBL and DLBCL-NOS (transcriptional level, AUC = 0.913-0.940; protein level, AUC = 0.878). Comparing RHOF with commonly used PMBL diagnostic markers CD23, CD30, and PD-L1, it was found that high RHOF expression is a more useful diagnostic marker for PMBL (AUC (RHOF) = 0.878 > AUC (CD23) = 0.818 > AUC (CD30) = 0.756 > AUC (PD-L1) = 0.590). The diagnostic model based on CD23, CD30, and RHOF exhibits higher sensitivity for the diagnosis of PMBL than any of the individual markers mentioned above. Concerning prognosis, high RHOF transcriptional expression was significantly associated with poorer overall survival (OS) in PMBL (P = 0.00037), while high RHOF protein expression was significantly associated with poorer OS and progression-free survival (PFS) in PMBL (P = 0.034; P = 0.034). This study indicates that high RHOF expression in PMBL is closely associated with the diagnosis, prognosis, and clinical pathological features of the disease. High RHOF expression demonstrates a superior diagnostic ability in distinguishing PMBL from DLBCL-NOS compared to existing markers. Furthermore, research on RHOF expression in PMBL holds promise for providing new targets and insights for prognosis assessment and treatment of PMBL.

The digital transformation of pathology, through automation and computational tools, addresses current challenges in the field. This study evaluates Paige Pan Cancer, a novel artificial intelligence tool based on the Virchow foundation model, designed to flag invasive cancer in haematoxylin and eosin-stained slides from 16 primary tissue types. Using 62 cases from the Ipatimup Pathology Laboratory, we found the tool had a sensitivity of 93.3% and specificity of 87.5% in biopsies, and 94.7% sensitivity and 75.0% specificity in resections. Overall accuracy was 90.3%. Despite some misclassifications, Paige Pan Cancer demonstrates high sensitivity as a multi-organ screening tool in clinical practice.

Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results of these challenges, nonclassical features such as bile-duct injury stays understudied in AIH. We aim to develop a deep learning tool (artificial intelligence for autoimmune hepatitis [AI(H)]) that analyzes the liver biopsies and provides reproducible, quantifiable, and interpretable results directly from routine pathology slides. A total of 123 pre-treatment liver biopsies, whole-slide images with confirmed AIH diagnosis from the archives of the Institute of Pathology at University Hospital Basel, were used to train several convolutional neural network models in the Aiforia artificial intelligence (AI) platform. The performance of AI models was evaluated on independent test set slides against pathologist's manual annotations. The AI models were 99.4%, 88.0%, 83.9%, 81.7%, and 79.2% accurate (ratios of correct predictions) for tissue detection, liver microanatomy, necroinflammation features, bile duct damage detection, and portal inflammation detection, respectively, on hematoxylin and eosin-stained slides. Additionally, the immune cells model could detect and classify different immune cells (lymphocyte, plasma cell, macrophage, eosinophil, and neutrophil) with 72.4% accuracy. On Sirius red-stained slides, the test accuracies were 99.4%, 94.0%, and 87.6% for tissue detection, liver microanatomy, and fibrosis detection, respectively. Additionally, AI(H) showed bile duct injury in 81 AIH cases (68.6%). The AI models were found to be accurate and efficient in predicting various morphological components of AIH biopsies. The computational analysis of biopsy slides provides detailed spatial and density data of immune cells in AIH landscape, which is difficult by manual counting. AI(H) can aid in improving the reproducibility of AIH biopsy assessment and bring new descriptive and quantitative aspects to AIH histology.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide and is a cause of significant mortality and morbidity. The epidemiology of this cancer varies worldwide due to either genetic differences in populations or differences in carcinogen exposure. The application of massive parallel sequencing-based techniques in HNSCC should provide a helpful understanding of the genetic alterations that eventually lead to HNSCC development and progression, and ideally, could be used for personalized therapy. In this review, the reader will find an overview of the mutational profile of conventional HNSCC according to published results on massive parallel sequencing data that confirm the pivotal role of TP53 and the frequent involvement of CDKN2A and PIK3CA. The reader will also find a more detailed description of the genes, such as NOTCH1 and FBXW7, that were not identified in HNSCCs before the development of these techniques, the differences that can be site-specific, such as the different mutational signatures that indicate specific carcinogens for various subsites of the head and neck, and finally, the actionability of these findings that should allow more personalized therapy for patients.

Carcinosarcoma (CS) is an uncommon and clinically aggressive malignancy. The objective of the present study was to characterize the molecular features of CS at various anatomic locations, including serous effusions. Specimens (n = 32) consisted of 25 biopsies/surgical resection specimens and 7 serous effusions (6 peritoneal, 1 pleural) from 25 patients. Fresh-frozen cell pellets and surgical specimens underwent targeted next-generation sequencing covering 50 unique genes. A total of 31 mutations were found in 25 of the 32 tumors studied, of which 1 had 3 mutations, 4 had 2 different mutations, and 20 had a single mutation. The most common mutations were in TP53 (n = 25 in 24 tumors; 1 tumor with 2 different mutations), with less common mutations found in RB1 (n = 2), MET (n = 1), KRAS (n = 1), PTEN (n = 1), and KIT (n = 1). Patient-matched specimens harbored the same TP53 mutation. Tumors with no detected mutations were more common in serous effusion specimens (3/7; 43%) compared with surgical specimens (4/25; 16%). In conclusion, the molecular landscape of CS is dominated by TP53 mutations, reinforcing the observation that the majority of these tumors develop from high-grade serous carcinoma. Whether CS cells in serous effusions differ from their counterparts in solid lesions remains uncertain.

We investigated frequencies of HER2-low breast cancer (BC) (immunohistochemistry [IHC] 1+ or 2+ without gene amplification) before and after IHC conditions were modified in order to understand the impact of IHC staining conditions on frequencies of HER2-low BC. Primary BC cases diagnosed at the Yeungnam University Hospital (YUH, n = 728) or Keimyung University Dongsan Hospital (KUDH, n = 290) in 2022 were reviewed, and data on HER2 status and IHC conditions were collected (cohort 1). Both institutions used the 4B5 antibody for HER2 IHC but had different staining protocols. After modifications of the IHC conditions at both institutions, primary BC cases (YUH, n = 324 and KUDH, n = 135) diagnosed from April to July 2023 (cohort 2) were reviewed to assess any changes in the frequency of HER2 status. In cohort 1, of the 728 cases diagnosed at YUH, 556 (76.4%) were HER2-zero, 76 (10.4%) were HER2-low, and 96 (13.2%) were HER2-positive, and of the 290 cases diagnosed at KUDH, 135 (46.6%) were HER2-zero, 82 (28.3%) were HER2-low, and 73 (25.2%) were HER2-positive. Modifications in HER2 IHC staining conditions dramatically increased the frequencies of HER2-low BC in cohort 2 (YUH 38.9% and KUDH 49.6%), but they did not result in significant changes in the HER2-positive rates (YUH 15.4% and KUDH 25.2%) compared to cohort 1. In conclusion, minor modifications in HER2 IHC staining conditions significantly affected the frequency of HER2-low BC but had little impact on the HER2-positivity rate. Each pathology laboratory should verify IHC conditions using control slides (including 1+) to enable the accurate identification of HER2-low BC.

The classification of TFEB-altered renal cell carcinoma (RCC) has been revised to include TFEB-rearranged RCC and TFEB-amplified RCC in the 2022 World Health Organization (WHO) Classification of Tumors of the Urinary System. Given the wide spectrum of TFEB-altered RCC in terms of morphology and clinical behavior, an accurate diagnosis is challenging yet crucial, particularly in aggressive cases. Moreover, the concurrence of TFEB gene rearrangement and amplification/gene copy number (GCN) gains was also observed, but there was limited knowledge of these cases. We presented three TFEB-rearranged RCC cases, one TFEB-amplified RCC case, and one case of concomitant TFEB-rearranged and -amplified RCC, comparing the similarities and differences among these three subgroups. Furthermore, we summarized the clinicopathological and molecular features of TFEB-rearranged RCC concomitant with TFEB amplification/GCN gains from the literature and the present study. TFEB-altered RCCs exhibit significant heterogeneity in morphology and clinical behavior while displaying similar immunohistochemical profiles, including positive staining for Melan-A, PAX8, and CD117, and negative staining for CK7. A typical biphasic "rosette-like" morphology has been observed in a proportion of TFEB-rearranged RCC concomitant with TFEB amplification/GCN gains, which has been noted in TFEB-rearranged RCC, but not in cases with only TFEB amplification. Notably, TFEB-rearranged RCCs concomitant with TFEB amplification/GCN gains tend to be aggressive, in contrast to the often indolent nature of TFEB-rearranged cases, irrespective of the extent of TFEB gene copy increase. Therefore, a TFEB FISH assay is essential for unclassified RCC cases that exhibit melanocytic marker expression, and fluorescent signals should be counted and interpreted acurrately.

Succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) is a rare subtype of renal neoplasm predominantly affecting younger individuals. It is characterized by germline mutations in SDHx genes, particularly type B. Histologically, SDH-deficient RCC features eosinophilic cytoplasmic cells forming solid nests or microcysts, sometimes entrapping normal tubules. We present three SDH-deficient RCC cases with overlapping morphological features with fumarate hydratase-deficient RCC and TFEB-rearranged RCC, an appearance that has not been previously described. All tumors lacked SDHB expression and harbored pathogenic SDHB mutations, with the germline nature confirmed in two cases. Metastasis developed in two patients. Our case set highlights the diagnostic challenges of molecularly defined renal tumors and expands the morphological spectrum of SDH-deficient RCC with unusual histological features. Clinically, these tumors appear to be aggressive.