Initially described as a highly specific immunohistochemical marker for carcinomas of mammary origin, trichorhinophalangeal syndrome type 1 (TRPS1) has subsequently been detected in a variety of other non-mammary tumors. In this study, we examined the immunohistochemical expression of TRPS1 in 114 peripheral nerve sheath tumors, including 43 malignant peripheral nerve sheath tumors (MPNSTs), 58 schwannomas, including 9 cellular neurofibromas, and 13 neurofibromas, including 1 atypical neurofibroma. Notably, TRPS1 was expressed in 49% of MPNSTs and was absent in all schwannomas and neurofibromas. All MPNSTs showed TRPS1 labeling in >50% of nuclei, with 95% of cases demonstrating diffuse labeling. Most cases (67%) showed weak TRPS1 immunoreactivity, while a smaller subset showed moderate (24%) or strong (9%) intensity staining. Analysis of publicly available gene expression datasets revealed higher levels of TRPS1 mRNA in MPNSTs with PRC2 inactivation. In keeping with this finding, TRPS1 expression was more commonly observed in MPNSTs with loss of H3K27me3, suggesting a potential relationship between TRPS1 and the PRC2 complex. This study further broadens the spectrum of TRPS1-expressing tumors to include MPNST.
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http://dx.doi.org/10.1016/j.humpath.2024.105632 | DOI Listing |
J Cutan Pathol
January 2025
Department of Pathology and Dermatology, NYU Langone Medical Center, New York, New York, USA.
Background: Digital papillary adenocarcinoma (DPAC) is a rare but aggressive cutaneous malignant sweat gland neoplasm that occurs on acral sites. Despite its clinical significance, the cellular and genetic characteristics of DPAC remain incompletely understood.
Methods: We conducted a comprehensive genomic and transcriptomic analysis of DPAC (n = 14) using targeted next-generation DNA and RNA sequencing, along with gene expression profiling employing the Nanostring Technologies nCounter IO 360 Panel.
J Transl Med
December 2024
Tongji Medical College, Maternal and Child Health Hospital of Hubei Province, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430070, China.
Background: As a prevalent and deadly malignant tumor, the treatment outcomes for late-stage patients with cervical squamous cell carcinoma (CSCC) are often suboptimal. Previous studies have shown that tumor progression is closely related with tumor metabolism and microenvironment reshaping, with disruptions in energy metabolism playing a critical role in this process. To delve deeper into the understanding of CSCC development, our research focused on analyzing the tumor microenvironment and metabolic characteristics across different regions of tumor tissue.
View Article and Find Full Text PDFAm J Clin Pathol
December 2024
Department of Pathology & Laboratory Medicine, University of Rochester Medical Center, Rochester, NY, US.
Objectives: Distinction of metastatic breast carcinoma (BC) to the pancreas from primary pancreatic adenocarcinoma (PAC) is essential but challenging. Breast carcinoma shares similar morphology and exhibits an overlapping immunohistochemistry (IHC) profile with PAC. We investigated the utility of recently reported trichorhinophalangeal syndrome type 1 (TRPS1) IHC in differentiating metastatic BC from PAC in fine-needle aspiration (FNA) specimens.
View Article and Find Full Text PDFHistopathology
December 2024
Department of Pathology, University of California San Francisco, San Francisco, California, USA.
Aims: Unusual morphologic patterns of breast carcinomas can raise diagnostic consideration for metastasis or special breast cancer subtypes with management implications. We describe rare invasive breast cancers that mimic serous carcinoma of the gynaecologic tract (serous-like breast carcinomas, SLBC) and characterize their clinicopathologic, immunophenotypic, and genetic features.
Methods And Results: All patients were female (n = 15, median age 49 years) without a history of gynaecologic malignancy.
Despite the identification of several dozen genetic loci associated with ischemic stroke (IS), the genetic bases of this disease remain largely unexplored. In this research we present the results of genome-wide association studies (GWAS) based on classical statistical testing and machine learning algorithms (logistic regression, gradient boosting on decision trees, and tabular deep learning model TabNet). To build a consensus on the results obtained by different techniques, the Pareto-Optimal solution was proposed and applied.
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