中华病理学杂志最新文献

Objective: To investigate the clinicopathological features, immunophenotype and molecule characteristics of EWSR1::CREM fusion malignant epithelioid neoplasm in soft tissue. Methods: The clinical and pathological data of 2 cases of EWSR1::CREM fusion malignant epithelioid neoplasm in soft tissue diagnosed at the Department of Pathology, Beijing Jishuitan Hospital, Beijing, China from May 2023 to May 2024 were analyzed. Immunohistochemical study, fluorescence in situ hybridization (FISH) and next generation sequencing (NGS) were performed. Relevant literature was reviewed. Results: There were one male and one female patients, aged 35 and 29 years, respectively. The tumors developed in the somatic soft tissue, including calf and chest wall, and were 6.0 and 6.2 cm in size, respectively. The imaging studies suggested space-occupying lesions in muscle tissue. Case 1 did not involve the bone, while Case 2 showed fracture of the 8th rib. Microscopically, a fibrous pseudocapsule surrounded by lymphocytes and plasma cells was identified. The tumors were composed of small to medium-sized round and short spindle-shaped cells, showing nodular or sheet-like pattern. The tumor cells showed round nuclear outline, coarse chromatin with prominent nucleoli. Immunohistochemically, tumor cells showed diffuse positivity of ALK (D5F3), MUM1 and Syn, focal or patchy positivity of CKpan, EMA, S-100, NSE, WT-1 and SMA, and a high Ki-67 index (20%-30%). FISH demonstrated break-apart signals of EWSR1 gene in the 2 cases. NGS revealed EWSR1::CREM gene fusion. Case 2 showed an ATRX gene mutation. The two patients were free of recurrence or metastasis at the 10-month and 1-month follow-up, respectively. Conclusions: EWSR1::CREM fusion malignant epithelioid neoplasm is rare and lacks distinctive morphological and immunohistochemical features. FISH and NGS can help make a definitive diagnosis.

Objective: To investigate the expression of keratin 1 (KRT1) and sialyl-Tn antigen (sTn) in cervical squamous cell carcinoma and its possible mechanism. Methods: Six cervical squamous cell carcinoma specimens were collected at the First Affiliated Hospital of Soochow University, Suzhou, China from 2022 to 2023. Spatial transcriptomics analysis was performed on the paraffin sections of 6 patients to analyze the transcriptomes of invasive squamous cell carcinoma and adjacent normal cervical squamous epithelium. The differential gene KRT1 was selected. Kaplan-Meier survival analysis was used to examine the prognostic value of KRT1 in cervical squamous cell carcinoma patients using the TCGA database. The possible downstream molecule sTn was identified according to literature research. Immunohistochemistry was carried out to investigate the expression of KRT1 and sTn proteins in the primary tumor and metastases of cervical squamous cell carcinoma (40 cases with pelvic lymph node metastasis and 30 cases without). Spearman correlation analysis was conducted to analyze the correlation of their expression. Results: The spatial transcriptomic results of the 6 specimens indicated that the level of KRT1 mRNA significantly decreased in cervical squamous cell carcinoma (compared with that in adjacent normal cervical squamous epithelium), while Kaplan-Meier survival analysis revealed that cervical squamous cell carcinoma patients with low KRT1 mRNA levels (versus high) had a worse prognosis. Immunohistochemistry proved that KRT1 expression was significantly lower in cervical squamous cell carcinoma than in adjacent normal squamous epithelium (P<0.05), but sTn showed the opposite change (increased in carcinoma, P<0.05). The expression changes of KRT1 and sTn were inversely correlated (r=-0.217, P<0.05). In addition, the expression levels of KRT1 and sTn in lymph node metastases were not significantly different from those in primary tumors. Conclusions: The decreased expression of KRT1 in primary cervical squamous cell carcinoma and lymph node metastasis may promote tumor cell proliferation and inhibit apoptosis by upregulating sTn, contributing to the poor prognosis of advanced cervical squamous cell carcinoma.

Medullary thyroid carcinoma (MTC) is the most common neuroendocrine carcinoma within the thyroid gland, characterized by strong invasiveness, high metastasis and recurrence rates. It is relatively rare among thyroid malignancies. The cytological and histological features of MTC are diverse and disperse, presenting as papillary, follicular, solid, trabecular, and spindle cell patterns. Immunohistochemical staining shows variable expression of calcitonin, carcinoembryonic antigen, and neuroendocrine markers. MTC can be classified into hereditary and sporadic types, with most cases caused by germline or somatic mutations in the RET gene located on chromosome 10. The 5th edition World Health Organization classification of endocrine and neuroendocrine tumors categorizes MTC into low-grade and high-grade based on tumor necrosis, mitotic figures, and Ki-67 proliferation index, highlighting that histological grading and RET gene mutations are independent prognostic predictors. This paper summarizes the recent advances in the pathological diagnosis of MTC, focusing on the key roles of the MTC grading system, molecular characteristics, and genetic screening and counseling in risk stratification for recurrence and targeted therapy.

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

With the development of precision medicine and molecular pathology, fluorescence in situ hybridization (FISH) technology has been widely promoted and applied in department of pathology. In FISH detection, the most commonly used probes are HER2 amplification probes and a variety of separation probes. When detecting pathological specimens using separation probes, some specimens may show atypical signals other than the typical red-green separation signals. The observation, understanding and interpretation of atypical signals may affect the results of FISH, which are related to molecular subtyping and drug treatment of the patient. Eight types of atypical signals of separation probes in FISH detection based on reading experience were summarized and analyzed. At the same time, this article provides evidence and analysis on whether the gene has been rearrangedthrough verification experiments, image analysis and experimental analysis in literature, aiming to enhance the understanding of readers to atypical signals of FISH separation probes.