The adverse effect of anticancer drug toremifene on vascular smooth muscle cells is an important aspect of its tumor growth inhibition

Wang, Huiyun; Liu, Juan; Wang, Mingxing; Yang, Chun; Wang, Guixue; Hu, Tingzhang

doi:10.1007/s00432-023-04744-9

Cited by 2 publications

(1 citation statement)

References 40 publications

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“…The fatty acid metabolism was thought to inhibit LYM pathways, such as CPT1A, a key enzyme in fatty acid b-oxidation, inhibits LYM under pathological conditions (25), which may provide new evidence for the mechanism of LYM in LUAD with low-LYM-index. In addition, cell adhesion molecules and neuroative ligand-receptor interactions were involved in tumor progression (26)(27)(28), as indicated by the fact that CEACAM1, a cell adhesion molecule, was associated with tumor angiogenesis and LYM (29). Therefore, these pathways may reveal the potential mechanism involved in the difference between the high-and low-LYM-index groups.…”

Section: Gsea Analysis Of Lym Indexmentioning

confidence: 99%

Tumor lymphangiogenesis index reveals the immune landscape and immunotherapy response in lung adenocarcinoma

Yang,

Wu,

Cai

et al. 2024

Front. Immunol.

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BackgroundLymphangiogenesis (LYM) has an important role in tumor progression and is strongly associated with tumor metastasis. However, the clinical application of LYM has not progressed as expected. The potential value of LYM needs to be further developed in lung adenocarcinoma (LUAD) patients.MethodsThe Sequencing data and clinical characteristics of LUAD patients were downloaded from The Cancer Genome Atlas and GEO databases. Multiple machine learning algorithms were used to screen feature genes and develop the LYM index. Immune cell infiltration, immune checkpoint expression, Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and drug sensitivity analysis were used to explore the correlation of LYM index with immune profile and anti-tumor therapy.ResultsWe screened four lymphangiogenic feature genes (PECAM1, TIMP1, CXCL5 and PDGFB) to construct LYM index based on multiple machine learning algorithms. We divided LUAD patients into the high LYM index group and the low LYM index group based on the median LYM index. LYM index is a risk factor for the prognosis of LUAD patients. In addition, there was a significant difference in immune profile between high LYM index and low LYM index groups. LUAD patients in the low LYM index group seemed to benefit more from immunotherapy based on the results of TIDE algorithm.ConclusionOverall, we confirmed that the LYM index is a prognostic risk factor and a valuable predictor of immunotherapy response in LUAD patients, which provides new evidence for the potential application of LYM.

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