We aimed to assess HKII expression and its prognostic significance in diffuse large B-cell lymphoma (DLBCL) patients. The HKII protein level was determined by immunohistochemistry in 159 newly diagnosed DLBCL patients, and its relationship with overall response rate, progression-free survival (PFS), and overall survival (OS) was analyzed. HKII was expressed in 95 DLBCL patients (59.7%). HKII-positive patients had poorer outcomes than negative patients for 5-y PFS (68% vs. 84%, p = 0.029) and 5-y OS (78% vs. 94%, p = 0.05). When only patients without no bulky disease, B symptoms, or extranodal involvement who had low IPI scores were considered, those with positive HKII had worse 5y-PFS and 5y-OS (p < 0.05). Multivariate analysis indicated that HKII status was an independent prognostic factor of OS. In subgroup analysis, HKII expression was associated with inferior OS in the CHOP group (p = 0.017). In CHOP group patients without bulky disease or extranodal involvement who had low LDH and low IPI scores (p < 0.05), positive HKII was associated with worse PFS and OS. No differences in PFS and OS, or any independent prognostic factors, were found in the RCHOP group. In DLBCL, HKII is valuable as a prognostic biomarker and may be useful as a tool for assessing disease risk.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s12185-022-03358-0 | DOI Listing |
Eur J Radiol Open
June 2025
Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany.
Objective: [F]FDG imaging is an integral part of patient management in CAR-T-cell therapy for recurrent or therapy-refractory DLBCL. The calculation methods of predictive power of specific imaging parameters still remains elusive. With this retrospective study, we sought to evaluate the predictive power of the baseline metabolic parameters and tumor burden calculated with automated segmentation via different thresholding methods for early therapy failure and mortality risk in DLBCL patients.
View Article and Find Full Text PDFHere, we have discussed the molecular mechanisms of p53-responsive microRNAs dysregulation in response to genotoxic stress in diffuse large B-cell lymphoma (DLBCL) patients. The role of micro ribonucleic acids (microRNAs) in p53-signaling cellular stress has been studied. MicroRNAs are the small non-coding RNAs, which regulate genes expression at post-transcriptional level.
View Article and Find Full Text PDFExpert Opin Biol Ther
January 2025
OU Stephenson Cancer Center, Oklahoma City.
Introduction: Antibody-drug conjugates (ADCs) are a rapidly evolving class of anti-cancer drugs with a significant impact on management of hematological malignancies including diffuse large B-cell lymphoma (DLBCL). ADCs combine a cytotoxic drug (a.k.
View Article and Find Full Text PDFCancers (Basel)
December 2024
Hematology Division, A.O.U. Città della Salute e della Scienza di Torino, C.so Bramante 88, 10126 Turin, Italy.
Backgroud: The introduction of highly active immunotherapies has changed the outcome of B-cell non-Hodgkin lymphomas (B-NHLs) in the last two decades. Since then, important progress has been shown using newer and more active immunotherapies, including chimeric antigen receptor T-cell therapy (CAR-T), conjugated monoclonal antibodies, and bispecific antobodies, which currently plays a significant role in the treatment of diffuse large B-cell (DLBCL), follicular (FL), and mantle cell (MCL) lymphoma.
Purpose: In this review, we provide an updated overview of recently completed and ongoing BsAb trials in patients with relapsed/refractory(R/R) B-NHL and Hodgkin's lymphoma, including single-agent results, emerging combinations, safety data, and novel constructs.
Cancers (Basel)
December 2024
Institute of Health System Science, Feinstein Institutes for Medical Research, Manhasset, NY 11030, USA.
: Positron emission tomography (PET) is a valuable tool for the assessment of lymphoma, while artificial intelligence (AI) holds promise as a reliable resource for the analysis of medical images. In this context, we systematically reviewed the applications of deep learning (DL) for the interpretation of lymphoma PET images. : We searched PubMed until 11 September 2024 for studies developing DL models for the evaluation of PET images of patients with lymphoma.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!