: Prostate adenocarcinoma (PRAD) is one of the most common cancers in male. Increasing evidences pointed out that Neutrophil Extracellular Traps (NETs) play an important role in tumor angiogenesis, tumor metastasis and drug resistance. However, limited systematic studies regarding the role of NETs in PRAD have been performed. Identification of biomarkers based on NETs might facilitate risk stratification which help optimizing the clinical strategies. : NETs-related genes with differential expressions were identified between PRAD and adjacent normal tissues in TCGA-PRAD dataset. Consensus cluster analysis was performed to determine the PRAD subtypes based on the different-expressed NETs-related genes. The difference of pathway enrichment, infiltrating immune cell and genomic mutation were also evaluated between subtypes. LASSO cox regression analysis was conducted to construct a NETs-related prognostic signature. : We identified 19 NETs related genes with differential expressions between PRAD and adjacent normal tissue in TCGA-PRAD dataset. Two significant subtypes were identified based on these 19 genes by consensus cluster analysis, namely subtype 1 and subtype 2. Significant differences in prognosis, immune infiltration and tumor mutation burden were observed in subtypes. LASSO Cox regression analysis identified a NETs-associated prognostic signature including 13 genes, and this signature had a good performance in predicting the progression-free survival of PRAD patients. Further integrated analysis indicated that MMP9 mostly expressed in Mono/Macrophage cells might play a role in regulating NETs formation via neutrophil activation in PRAD. : To sum up, the current study identified two NETs-related molecular subtypes and based on which constructed a prognostic signature for PRAD.
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http://dx.doi.org/10.7150/jca.93275 | DOI Listing |
Pediatr Res
January 2025
Department of Pediatrics, Medical College of Wisconsin, Children's Wisconsin, Milwaukee, WI, USA.
Background: The immune heterogeneity of biliary atresia (BA) presents a challenge for development of prognostic biomarkers. This study aimed to identify early immune signatures associated with biliary drainage after Kasai Portoenterostomy (KPE).
Methods: Serum samples, liver slides, and clinical data were obtained from patients enrolled in the NIDDK-supported Childhood Liver Disease Research Network.
Discov Oncol
January 2025
Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Background: Diseases are often caused by multiple factors, angiogenesis-related genes (ARGs) have been shown to be associated with cancer, however, their role in colon cancer had not been fully explored. This study investigated potential biomarkers based on ARGs to improve prognosis and treatment effect in colon cancer.
Methods: ARGs associated with colon cancer prognosis were identified using Cox regression analysis and LASSO analysis.
Eur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
BJUI Compass
January 2025
OncoAssure Ltd, NovaUCD Dublin Ireland.
Objectives: This study aimed to clinically validate the six-gene prognostic molecular clinical risk score (MCRS) for the prediction of aggressive prostate cancer in diagnostic biopsy tissue.
Methods: MCRS was evaluated in prostate biopsy tissue from a Swedish cohort of men with prostate cancer (UPCA, = 100). The primary outcome of adverse pathology and secondary outcomes of high primary Gleason (≥G4) and high pathological T-stage (≥T3) were assessed by likelihood ratio statistics and area under the receiver operating characteristic curves from logistic regression models; time to biochemical recurrence was assessed by likelihood ratio statistics and C-indexes from Cox proportional hazard regression models.
Front Genet
January 2025
Department of General Surgery, The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, China.
Background: Neoadjuvant, endocrine, and targeted therapies have significantly improved the prognosis of breast cancer (BC). However, due to the high heterogeneity of cancer, some patients cannot benefit from existing treatments. Increasing evidence suggests that amino acids and their metabolites can alter the tumor malignant behavior through reshaping tumor microenvironment and regulation of immune cell function.
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