Dataset Information

Unveiling LOX-1 receptor interplay with nanotopography: mechanotransduction and atherosclerosis onset.

ABSTRACT: Lectin-like ox-LDL receptors (LOX-1) play a crucial role in the ox-LDL-induced pathological transformation of vessel-wall components, a crucial early step in atherogenesis. LOX-1 dynamics is quantitatively investigated in human endothelial cells (HUVECs) exposed to environmental nanotopographies. We demonstrate distinct nanotopography-induced cell phenotypes, characterized by different morphology, LOX-1 diffusivity and oligomerization state: HUVECs on flat surfaces exhibit the behavior found in pro-atherogenic conditions, while growth on nanogratings can interfere with LOX-1 dynamics and lead to a behavior characteristic of normal, non-pathological conditions.

SUBMITTER: Di Rienzo C

PROVIDER: S-EPMC3555090 | biostudies-other | 2013

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Unveiling LOX-1 receptor interplay with nanotopography: mechanotransduction and atherosclerosis onset.

Di Rienzo Carmine C Jacchetti Emanuela E Cardarelli Francesco F Bizzarri Ranieri R Beltram Fabio F Cecchini Marco M

Scientific reports 20130125

Lectin-like ox-LDL receptors (LOX-1) play a crucial role in the ox-LDL-induced pathological transformation of vessel-wall components, a crucial early step in atherogenesis. LOX-1 dynamics is quantitatively investigated in human endothelial cells (HUVECs) exposed to environmental nanotopographies. We demonstrate distinct nanotopography-induced cell phenotypes, characterized by different morphology, LOX-1 diffusivity and oligomerization state: HUVECs on flat surfaces exhibit the behavior found in ...[more]

PMID: 23355954

Similar Datasets

Project description:Background While recent studies have separately explored mutational signatures and the tumor microenvironment (TME), there is limited research on the associations of both factors in a pan-cancer context. Materials and methods We performed a pan-cancer analysis of over 8,000 tumor samples from The Cancer Genome Atlas (TCGA) project. Machine learning methods were employed to systematically explore the relationship between mutational signatures and TME and develop a risk score based on TME-associated mutational signatures to predict patient survival outcomes. We also constructed an interaction model to explore how mutational signatures and TME interact and influence cancer prognosis. Results Our analysis revealed a varied association between mutational signatures and TME, with the Clock-like signature showing the most widespread influence. Risk scores based on mutational signatures mainly induced by Clock-like and AID/APOBEC activity exhibited strong pan-cancer survival stratification ability. We also propose a novel approach to predict transcriptome decomposed infiltration levels using genome-derived mutational signatures as an alternative approach for exploring TME cell types when transcriptome data are unavailable. Our comprehensive analysis revealed that certain mutational signatures and their interaction with immune cells significantly impact clinical outcomes in particular cancer types. For instance, T cell infiltration levels only served as a prognostic biomarker in melanoma patients with high ultraviolet radiation exposure, breast cancer patients with high homologous recombination deficiency signature, and lung adenocarcinoma patients with high tobacco-associated mutational signature. Conclusion Our study comprehensively explains the complex interplay between mutational signatures and immune infiltration in cancer. The results highlight the importance of considering both mutational signatures and immune phenotypes in cancer research and their significant implications for developing personalized cancer treatments and more effective immunotherapy.

Dataset Information

Unveiling LOX-1 receptor interplay with nanotopography: mechanotransduction and atherosclerosis onset.

Publications

Unveiling LOX-1 receptor interplay with nanotopography: mechanotransduction and atherosclerosis onset.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets