Results 181 to 190 of about 10,505,009 (388)

Cytomegalovirus infection is common in prostate cancer and antiviral therapies inhibit progression in disease models

open access: yesMolecular Oncology, EarlyView.
Human cytomegalovirus infection is common in normal prostate epithelium, prostate tumor tissue, and prostate cancer cell lines. CMV promotes cell survival, proliferation, and androgen receptor signaling. Anti‐CMV pharmaceutical compounds in clinical use inhibited cell expansion in prostate cancer models in vitro and in vivo, motivating investigation ...
Johanna Classon   +13 more
wiley   +1 more source

Integrative miRNOMe profiling reveals the miR‐195‐5p–CHEK1 axis and its impact on luminal breast cancer outcomes

open access: yesMolecular Oncology, EarlyView.
In luminal (ER+) breast carcinoma (BC), miRNA profiling identified miR‐195‐5p as a key regulator of proliferation that targets CHEK1, CDC25A, and CCNE1. High CHEK1 expression correlates with worse relapse‐free survival after chemotherapy, especially in patients with luminal A subtype.
Veronika Boušková   +14 more
wiley   +1 more source

Targeting carbonic anhydrase IX/XII prevents the anti‐ferroptotic effect of stromal lactic acid in prostate carcinoma

open access: yesMolecular Oncology, EarlyView.
In prostate carcinoma, lactic acid, secreted by highly glycolytic cancer‐associated fibroblasts, is imported into tumor cells through the MCT1 transporter and prevents RSL3 and erastin‐induced ferroptosis (A). Targeting of carbonic anhydrase IX/XII, the main extracellular pH regulators, in tumor and stromal cells reduces microenvironmental acidosis and
Elisa Pardella   +18 more
wiley   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

open access: yesMolecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima   +6 more
wiley   +1 more source

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