Purpose: Until now molecular biologic techniques have not been easily used in daily clinical practice to stratify patients for therapeutic purposes. Therefore, we have investigated the prognostic relevance of the immunohistochemical (IHC) germinal center B-cell (GCB) versus non-GCB diffuse large B-cell lymphoma (DLBCL) subtypes.
Patients And Methods: We have analyzed tumor samples from patients treated in 2 prospective multicenter phase III trials, ie HOVON 25 (patients≥65 years, n=153) and HOVON 26 (patients<65 years, n=144) using whole sections (WS) or tissue microarray (TMA). CD10, BCL6, and MUM1 were applied in a specific IHC algorithm. The effect on clinical outcome using WS or TMA and variations in cut-off levels of these markers was also investigated.
Results: The GCB subtype was not associated with a better OS in either trial. Small differences were observed in the HOVON 25 trial between techniques, with TMA showing a better outcome for GCB than did WS. Variation of cut-off levels in the specific algorithm did not improve the prediction of clinical outcome.
Conclusion: We did not observe a consistent predictive power of the GCB and non-GCB classification by IHC in this large series of DLBCL patients treated with CHOP. This underscores the need to determine the biologic variation and the standardization of the protein expression levels and to further study the relevance of prognostic IHC classifications, preferably in phase III clinical trials.
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http://dx.doi.org/10.3816/CLML.2011.n.003 | DOI Listing |
World J Urol
January 2025
Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-dong Road, Wuhan, Hubei, 430060, P.R. China.
Purpose: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph node metastasis (LNM) status of muscle invasive bladder cancer (MIBC), while validating the prognostic value of the predicted aiN score in MIBC patients.
Methods: A total of 323 patients from The Cancer Genome Atlas (TCGA) were used as the training and internal validation set, with image features extracted using a visual encoder called UNI. We investigated the ability to predict LNM status while assessing the prognostic value of aiN score.
Eur Radiol
January 2025
Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
Objectives: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagnostic performance of a recently updated deep learning model (CorEx-2.0) for quantifying coronary stenosis, compared separately with two expert CCTA readers as references.
View Article and Find Full Text PDFClin Infect Dis
January 2025
Infectious Disease Department, Assistance-Publique Hôpitaux de Paris (AP-HP), Hôpital Necker-Enfants Malades.
Background: While invasive fusariosis and lomentosporiosis are known to be associated with fungemia, overall data on mold-related fungemia are limited, hampering early management. This study aimed to describe the epidemiology of mold-positive blood cultures.
Methods: Epidemiological and clinical data on mold-positive blood cultures from 2012 to 2022 were obtained from the RESSIF database.
Cancer Med
January 2025
Faculty of Medical Sciences, Neuroscience Research Center, Lebanese University, Hadath, Lebanon.
Background: Glioblastoma (GBM) is the most common primary brain tumor in adults and has a median survival of less than 15 months. Advancements in the field of epigenetics have expanded our understanding of cancer biology and helped explain the molecular heterogeneity of these tumors. B-cell-specific Moloney murine leukemia virus insertion site-1 (Bmi-1) is a member of the highly conserved polycomb group (PcG) protein family that acts as a transcriptional repressor of multiple genes, including those that determine cell proliferation and differentiation.
View Article and Find Full Text PDFJ Gynecol Oncol
December 2025
Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China.
Objective: To explore the characteristics and survival outcomes of ovarian squamous cell carcinoma (SCC) and the treatment effectiveness of immune checkpoint inhibitors (ICIs).
Methods: Patients diagnosed with ovarian SCC at Peking Union Medical College Hospital between January 2000 and September 2023 were included. Overall survival (OS) and progression-free survival (PFS) were analyzed using the Kaplan-Meier method.
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