Blastic plasmacytoid dendritic cell (pDC) neoplasm (BPDCN) is a relatively rare hematological malignancy with significantly complex clinicopathological features that are still unclear. This study aimed to analyze the clinicopathological data of BPDCN and evaluate immunohistochemical detection of minimal bone marrow (BM) involvement. In this study, we examined skin and BM lesions from 6 patients with BPDCN. Neoplastic cells tested positive for CD303 (polyclonal, 100%; monoclonal, 40%) in the skin lesions and for CD303 (polyclonal, 100%; monoclonal, 67%) in the BM clots. Although immunostaining of CD4, CD56, CD123, CD303, and TCLl detected minimal BM involvement in 3 patients, morphological identification was challenging in the BM clots stained with hematoxylin-eosin. In conclusion, our results demonstrate the significance of observing BM smears to detect neoplastic cells and that immunohistochemical examination, including CD303 antibodies, is useful to detect minimal BM involvement. This study is the first to report the expression of thymic stromal lymphopoietin (TSLP) and its receptor in BPDCN cells. Therefore, the TSLP/TSLP receptor axis may be associated with the proliferation of BPDCN, and consequently, the survival of patients.
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http://dx.doi.org/10.3960/jslrt.17030 | DOI Listing |
Cancer Rep (Hoboken)
January 2025
Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Background: Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.
Aim: In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).
Methods And Results: Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes.
Front Immunol
January 2025
Leeds Institute of Medical Research, School of Medicine, University of Leeds, St. James University Hospital, Leeds, United Kingdom.
Background: There has been limited success of cancer immunotherapies in the treatment of ovarian cancer (OvCa) to date, largely due to the immunosuppressive tumour microenvironment (TME). Tumour-associated macrophages (TAMs) are a major component of both the primary tumour and malignant ascites, promoting tumour growth, angiogenesis, metastasis, chemotherapy resistance and immunosuppression. Differential microRNA (miRNA) profiles have been implicated in the plasticity of TAMs.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Gastroenterology, the First Affiliated Hospital of Ningbo University, Ningbo, 315020, China.
Background: Gastric cancer (GC) is known for its high heterogeneity, presenting challenges in current clinical treatment strategies. Accurate subtyping and in-depth analysis of the molecular heterogeneity of GC at the molecular level are still not fully understood.
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Mol Med
January 2025
General Surgery Department, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, China.
Several members of the NIMA-related kinase (NEK) family have been implicated in tumor progression; however, the role and underlying mechanisms of NEK8 in gastric cancer (GC) remain unclear. This study revealed a significant upregulation of NEK8 in GC, identifying it as an independent prognostic marker in patients with GC. Consistent with these findings, NEK8 silencing substantially impeded GC aggressiveness both in vitro and in vivo, while its overexpression produced the opposite effect.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedics, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, Hubei Province, China.
Osteosarcoma (OS) is a prevalent invasive bone cancer, with numerous homeobox family genes implicated in tumor progression. This study aimed to develop a prognostic model using HOX family genes to assess osteosarcoma patient outcomes. Data from osteosarcoma patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts were collected.
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