Cellular transformation promotes the incorporation of docosahexaenoic acid into the endolysosome-specific lipid bis(monoacylglycerol)phosphate in breast cancer

Berg, Anastasia L.; Showalter, Megan R.; Kosaisawe, Nont; Hu, Michelle; Stephens, Nathanial C.; Sa, Michael; Heil, Hailey; Castro, N.; Chen, Jenny J.; VanderVorst, Kacey; Wheeler, Madelyn R.; Rabow, Zachary; Čajka, Tomáš; Albeck, John G.; Fiehn, Oliver; Carraway, Kermit L.

doi:10.1016/j.canlet.2023.216090

Cited by 2 publications

(1 citation statement)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BMP is a structural isomers of phosphatidylglycerol that is highly enriched in endolysosomes and are responsible for activating sphingolipid catabolic enzymes[ 51 ]. A recent study described the changes in BMP diversity in breast cancer[ 52 ]. The investigators found that the total BMP levels were significantly reduced in breast cancer cells, suggesting that BMP was specifically inhibited during malignant transformation.…”

Section: Discussionmentioning

confidence: 99%

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

Li,

Su,

Tan

et al. 2024

World J Clin Cases

View full text Add to dashboard Cite

BACKGROUND Non-small cell lung cancer (NSCLC) is the primary form of lung cancer, and the combination of chemotherapy with immunotherapy offers promising treatment options for patients suffering from this disease. However, the emergence of drug resistance significantly limits the effectiveness of these therapeutic strategies. Consequently, it is imperative to devise methods for accurately detecting and evaluating the efficacy of these treatments. AIM To identify the metabolic signatures associated with neutrophil extracellular traps (NETs) and chemoimmunotherapy efficacy in NSCLC patients. METHODS In total, 159 NSCLC patients undergoing first-line chemoimmunotherapy were enrolled. We first investigated the characteristics influencing clinical efficacy. Circulating levels of NETs and cytokines were measured by commercial kits. Liquid chromatography tandem mass spectrometry quantified plasma metabolites, and differential metabolites were identified. Least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest algorithms were employed. By using plasma metabolic profiles and machine learning algorithms, predictive metabolic signatures were established. RESULTS First, the levels of circulating interleukin-8, neutrophil-to-lymphocyte ratio, and NETs were closely related to poor efficacy of first-line chemoimmunotherapy. Patients were classed into a low NET group or a high NET group. A total of 54 differential plasma metabolites were identified. These metabolites were primarily involved in arachidonic acid and purine metabolism. Three key metabolites were identified as crucial variables, including 8,9-epoxyeicosatrienoic acid, L-malate, and bis(monoacylglycerol)phosphate (18:1/16:0). Using metabolomic sequencing data and machine learning methods, key metabolic signatures were screened to predict NET level as well as chemoimmunotherapy efficacy. CONCLUSION The identified metabolic signatures may effectively distinguish NET levels and predict clinical benefit from chemoimmunotherapy in NSCLC patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

Li,

Su,

Tan

et al. 2024

World J Clin Cases

View full text Add to dashboard Cite

show abstract

The Bis(monoacylglycero)-phosphate Hypothesis: From Lysosomal Function to Therapeutic Avenues

Medoh,

Abu-Remaileh

2024

Annual Review of Biochemistry

View full text Add to dashboard Cite

Lysosomes catabolize and recycle lipids and other biological molecules to maintain cellular homeostasis in diverse nutrient environments. Lysosomal lipid catabolism relies on the stimulatory activity of bis(monoacylglycero)phosphate (BMP), an enigmatic lipid whose levels are altered across myriad lysosome-associated diseases. Here, we review the discovery of BMP over half a century ago and its structural properties that facilitate the activation of lipid hydrolases and recruitment of their coactivators. We further discuss the current, yet incomplete, understanding of BMP catabolism and anabolism. To conclude, we discuss its role in lysosome-associated diseases and the potential for modulating its levels by pharmacologically activating and inhibiting the BMP synthase to therapeutically target lysosomal storage disorders, drug-induced phospholipidosis, Alzheimer's disease, Parkinson's disease, frontotemporal dementia, cancer, and viral infection.

show abstract

Cellular transformation promotes the incorporation of docosahexaenoic acid into the endolysosome-specific lipid bis(monoacylglycerol)phosphate in breast cancer

Cited by 2 publications

References 63 publications

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

The Bis(monoacylglycero)-phosphate Hypothesis: From Lysosomal Function to Therapeutic Avenues

Contact Info

Product

Resources

About