Aim: We aimed to evaluate the applicability of a customized NanoString panel for molecular subtyping of recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC). Additionally, histological analyses were conducted, correlated with the molecular subtypes and tested for their prognostic value.
Material And Methods: We conducted molecular subtyping of R/M-HNSCC according to the molecular subtypes defined by Keck et al. For molecular analyses a 231 gene customized NanoString panel (the most accurately subtype defining genes, based on previous analyses) was applied to tumor samples from R/M-HNSCC patients that were treated in the CeFCiD trial (AIO/IAG-KHT trial 1108). A total of 130 samples from 95 patients were available for sequencing, of which 80 samples from 67 patients passed quality controls and were included in histological analyses. H&E stained slides were evaluated regarding distinct morphological patterns (e.g. tumor budding, nuclear size, stroma content).
Results: Determination of molecular subtypes led to classification of tumor samples as basal (n = 46, 45 %), inflamed/mesenchymal (n = 31, 30 %) and classical (n = 26, 25 %). Expression levels of Amphiregulin (AREG) were significantly higher for the basal and classical subtypes compared to the mesenchymal subtype. While molecular subtypes did not have an impact on survival, high levels of tumor budding were associated with poor outcomes. No correlation was found between molecular subtypes and histological characteristics.
Conclusions: Utilizing the 231-gene NanoString panel we were able to determine the molecular subtype of R/M-HNSCC samples by the use of FFPE material. The value to stratify for different treatment options remains to be explored in the future. The prognostic value of tumor budding was underscored in this clinically well annotated cohort.
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http://dx.doi.org/10.1016/j.oraloncology.2023.106678 | DOI Listing |
J Cancer
January 2025
Department of Urology, Renmin Hospital of Wuhan University, 430060 Wuhan, Hubei, China.
Pro-apoptotic coiled-coil domain containing 8 (CCDC8) has been linked to tumor progression and metastasis, yet its prognostic significance and underlying molecular mechanisms in bladder cancer remain to be elucidated. This study utilized raw data from public databases along with a single-center retrospective case series. We performed bioinformatics analysis and immunohistochemistry to investigate the biological landscape of CCDC8 in various tumors, with a particular focus on bladder cancer.
View Article and Find Full Text PDFHistol Histopathol
October 2024
Department of Pathology, College of Medicine, QU Health, Qatar University, Doha, Qatar.
Introduction: Appendiceal mucinous neoplasms (AMNs) represent a rare and diagnostically challenging group of tumors. This systematic review aims to summarize the reported molecular and immunohistochemical markers (IHC) associated with AMNs and compare them with ovarian mucinous neoplasms (OMNs) and colorectal adenocarcinoma (CRC).
Methods: A comprehensive search was performed in PubMed/MEDLINE/PMC, Scopus, Embase, and Web of Science databases to identify studies looking at IHC and molecular markers in AMNs.
J Mol Neurosci
January 2025
Department of Neurology, Hebei General Hospital, Shijiazhuang, China.
Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological processes, which can lead to disability and death. This study aimed to determine necroptosis-associated genes in acute ischemic stroke (AIS) and to investigate their potential as diagnostic and therapeutic targets for AIS. Expression profiling data were acquired from the Gene Expression Omnibus database, and necroptosis-associated genes were retrieved from GeneCards.
View Article and Find Full Text PDFPathol Res Pract
December 2024
Division of Clinical Genome Research, Institute of Medical Science, The University of Tokyo, Tokyo, Japan. Electronic address:
Clin Imaging
December 2024
Department of Radiology, Neuroradiology Section, UT Southwestern Medical Center, Dallas, TX 75390, USA. Electronic address:
We aimed to systematically review and meta-analyze the predictive value of magnetic resonance imaging (MRI)-derived radiomics/end-to-end deep learning (DL) models in predicting glioma alpha thalassemia/mental retardation syndrome X-linked (ATRX) status. We conducted a comprehensive search across four major databases-Web of Science, PubMed, Scopus, and Embase. All the studies that assessed the performance of radiomics and/or end-to-end DL models for predicting glioma ATRX status were included.
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