Background: MYCN amplification directly correlates with the clinical course of neuroblastoma and poor patient survival, and serves as the most critical negative prognostic marker. Although fluorescence in situ hybridization (FISH) remains the gold standard for clinical diagnosis of MYCN status in neuroblastoma, its limitations warrant the identification of rapid, reliable, less technically challenging, and inexpensive alternate approaches.
Methods: In the present study, we examined the concordance of droplet digital PCR (ddPCR, in combination with immunohistochemistry, IHC) with FISH for MYCN detection in a panel of formalin-fixed paraffin-embedded (FFPE) human neuroblastoma samples.
Results: In 112 neuroblastoma cases, ddPCR analysis demonstrated a 96-100% concordance with FISH. Consistently, IHC grading revealed 92-100% concordance with FISH. Comparing ddPCR with IHC, we observed a concordance of 95-98%.
Conclusions: The results demonstrate that MYCN amplification status in NB cases can be assessed with ddPCR, and suggest that ddPCR could be a technically less challenging method of detecting MYCN status in FFPE specimens. More importantly, these findings illustrate the concordance between FISH and ddPCR in the detection of MYCN status. Together, the results suggest that rapid, less technically demanding, and inexpensive ddPCR in conjunction with IHC could serve as an alternate approach to detect MYCN status in NB cases, with near-identical sensitivity to that of FISH.
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http://dx.doi.org/10.1186/s12885-019-5306-0 | DOI Listing |
PLoS One
November 2024
Department of Pathology, Anhui Provincial Children's Hospital, Hefei, Anhui, China.
Background: Neuroblastoma (NB) is the most common extracranial solid tumor in children, and the AURKA gene encodes a protein kinase involved in cell cycle regulation that plays an oncogenic role in a variety of human cancers. The aim of this study was to validate the biological function and prognostic significance of AURKA in NB using basic experiments and bioinformatics.
Methods: Data obtained from Target and GEO databases were analyzed using various bioinformatic techniques.
Front Oncol
November 2024
Study Office of Pediatric and Thoracic Surgery, Hebei Medical University, Shijiazhuang, Hebei, China.
Background: Cancer cells induce neutrophil extracellular traps (NETs) to promote tumor progression and metastasis. However, only a few studies have focused on the role of NETs in Neuroblastoma (NB).
Methods: First, based on the expression of NET-related genes, consensus clustering analysis was conducted to cluster NB samples into different subtypes.
Front Immunol
November 2024
State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.
NPJ Precis Oncol
November 2024
Department of Pediatrics, University of Chicago, Chicago, IL, USA.
A deep learning model using attention-based multiple instance learning (aMIL) and self-supervised learning (SSL) was developed to perform pathologic classification of neuroblastic tumors and assess MYCN-amplification status using H&E-stained whole slide images from the largest reported cohort to date. The model showed promising performance in identifying diagnostic category, grade, mitosis-karyorrhexis index (MKI), and MYCN-amplification with validation on an external test dataset, suggesting potential for AI-assisted neuroblastoma classification.
View Article and Find Full Text PDFAdv Pharm Bull
October 2024
Cancer Chemoprevention Research Center, Faculty of Pharmacy, Universitas Gadjah Mada, Sleman, Yogyakarta, Indonesia.
Purpose: The HLF and HuH-6 cell lines represent hepatocellular carcinoma (HCC) with different characteristics in chromosome content that may give different drug responses. Here, PGV-1 was intended to challenge the growth-suppressing effect on HLF and HuH-6 and trace the molecular target mechanism of action compared to sorafenib.
Methods: We applied MTT cytotoxic assay, colony forming assay, flow cytometry analysis, immunofluorescence assay and western blot assay.
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