Results 131 to 140 of about 490,234 (264)
Characterization of Mitochondrial Double-Stranded RNA Levels in Non-Small Cell Lung Carcinoma. [PDF]
Krieger MR +12 more
europepmc +1 more source
Hijacked and educated by HNSCC cells, HLA‐DR+ Schwann cells lost their normal neural‐related functions but acquired immunoregulatory phenotypes to promote CD4+ T cells transform into Tregs. HLA‐DR+ Schwann cells induced a macrophage subpopulation, Il1β.
Xiaoyan Meng +7 more
wiley +1 more source
PARP inhibitors induce a senescence phenotype in non-small cell lung carcinoma cell lines. [PDF]
Huart C +7 more
europepmc +1 more source
Single‐cell RNA editing analysis identifies ADAR1 as a regulator of dysfunctional T cell states in colorectal cancer. Elevated ADAR1 activity promotes T cell exhaustion and impairs antitumor immunity partly through TGF‐β‐SMAD signaling, contributing to anti‐PD‐1 resistance and highlighting T cell ADAR1 as a potential therapeutic target and biomarker ...
Da Kang +10 more
wiley +1 more source
Testicular Metastasis From Small Cell Lung Carcinoma: A Case Report. [PDF]
Alami R +4 more
europepmc +1 more source
Inhibition of KDELR2 in a small fraction of tumor cells generates sustainable immunogenic cell death conditions within the tumor microenvironment. These conditions promote the regression of tumors in a T cell independent manner. During regression, macrophages prime T cells that subsequently provide systemic protection against recurrence. The potency of
Shakti P Pattanayak +6 more
wiley +1 more source
Fibrotic liver stiffness activates hepatic stellate cells through Piezo1‐dependent calcium influx and ER stress, promoting EV‐associated GMFG release. Delivered GMFG engages TNS4 in pancreatic cancer cells, triggering FAK/AKT signaling, adhesion, and fatty acid synthesis.
Biwen Zhu +11 more
wiley +1 more source
Identifying regulatory driver motifs in non-small cell lung carcinoma via a systematic approach. [PDF]
Kumar R +8 more
europepmc +1 more source
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
wiley +1 more source
Update on the Treatment of Non-Small Cell Lung Carcinoma (NSCLC). [PDF]
Kariri YA.
europepmc +1 more source

