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Unlabelled: Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2).
Significance: We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses.
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http://dx.doi.org/10.1158/2159-8290.CD-15-0235 | DOI Listing |
JDS Commun
September 2025
Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Canada, J2S 2M2.
The objective of this ambidirectional observational cohort study was to explore how nonesterified fatty acids (NEFA) 22 to 35 d before calving were related to NEFA 1 to 14 d before calving and to determine a threshold that could be used to identify cows at risk of poor postpartum health. We enrolled 855 dairy cows from 46 herds, 362 prospectively and 493 retrospectively. The NEFA concentrations were measured during the far-off period (foNEFA; 3 to 5 wk before calving) and in the close-up period (cuNEFA; up to 2 wk before calving), and postpartum infectious and metabolic disorders, reproduction success, and culling were recorded.
View Article and Find Full Text PDFArch Esp Urol
August 2025
Department of Urology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, 214000 Wuxi, Jiangsu, China.
Background: A plethora of studies have demonstrated that the level of uric acid (UA) and gout are the risk factors for erectile dysfunction (ED). However, the causal effect of UA level and gout on ED is still unclear. This Mendelian randomization (MR) study aims to examine the bidirectional causality between ED and UA levels as well as gout.
View Article and Find Full Text PDFMed Sci Monit
September 2025
Department of Radiology, Faculty of Medicine, Erzincan Binali Yildirim University, Erzincan, Turkey.
BACKGROUND This study used CT imaging analyzed with deep learning techniques to assess the diagnostic accuracy of lung metastasis detection in patients with breast cancer. The aim of the research was to create and verify a system for detecting malignant and metastatic lung lesions that uses YOLOv10 and transfer learning. MATERIAL AND METHODS From January 2023 to 2024, CT scans of 16 patients with breast cancer who had confirmed lung metastases were gathered retrospectively from Erzincan Mengücek Gazi Training and Research Hospital.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Department of Hepatobiliary and Vascular Surgery, First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Background: Primary liver cancer, particularly hepatocellular carcinoma (HCC), poses significant clinical challenges due to late-stage diagnosis, tumor heterogeneity, and rapidly evolving therapeutic strategies. While systematic reviews and meta-analyses are essential for updating clinical guidelines, their labor-intensive nature limits timely evidence synthesis.
Objective: This study proposes an automated literature screening workflow powered by large language models (LLMs) to accelerate evidence synthesis for HCC treatment guidelines.
J Ultrasound Med
September 2025
Department of Clinical Analysis, Federal University of Santa Catarina (UFSC), Florianópolis, Brazil.
Objectives: To evaluate the performance of artificial intelligence (AI)-based models in predicting elevated neonatal insulin levels through fetal hepatic echotexture analysis.
Methods: This diagnostic accuracy study analyzed ultrasound images of fetal livers from pregnancies between 37 and 42 weeks, including cases with and without gestational diabetes mellitus (GDM). Images were stored in Digital Imaging and Communications in Medicine (DICOM) format, annotated by experts, and converted to segmented masks after quality checks.