Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis

Acetyl-CoA carboxylase 1 controls a lipid droplet-peroxisome axis and is a vulnerability of endocrine-resistant ER+ breast cancer

Targeting aromatase deprives ER+ breast cancers of estrogens and is an effective therapeutic approach for these tumors. However, drug resistance is an unmet clinical need. Lipidomic analysis of long-term estrogen-deprived (LTED) ER+ breast cancer cells, a model of aromatase inhibitor resistance, revealed enhanced intracellular lipid storage. Functional metabolic analysis showed that lipid droplets together with peroxisomes, which we showed to be enriched and active in the LTED cells, controlled redox homeostasis and conferred metabolic adaptability to the resistant tumors. This reprogramming was controlled by acetyl-CoA-carboxylase-1 (ACC1), whose targeting selectively impaired LTED survival. However, the addition of branched- and very long-chain fatty acids reverted ACC1 inhibition, a process that was mediated by peroxisome function and redox homeostasis. The therapeutic relevance of these findings was validated in aromatase inhibitor-treated patient-derived samples. Last, targeting ACC1 reduced tumor growth of resistant patient-derived xenografts, thus identifying a targetable hub to combat the acquisition of estrogen independence in ER+ breast cancers.

High-Throughput Microbore LC-MS Lipidomics to Investigate APOE Phenotypes

Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.

Clonal cooperation through soluble metabolite exchange facilitates metastatic outgrowth by modulating Allee effect

Cancers feature substantial intratumoral heterogeneity of genetic and phenotypically distinct lineages. Although interactions between coexisting lineages are emerging as a potential contributor to tumor evolution, the extent and nature of these interactions remain largely unknown. We postulated that tumors develop ecological interactions that sustain diversity and facilitate metastasis. Using a combination of fluorescent barcoding, mathematical modeling, metabolic analysis, and in vivo models, we show that the Allee effect, i.e., growth dependency on population size, is a feature of tumor lineages and that cooperative ecological interactions between lineages alleviate the Allee barriers to growth in a model of triple-negative breast cancer. Soluble metabolite exchange formed the basis for these cooperative interactions and catalyzed the establishment of a polyclonal community that displayed enhanced metastatic dissemination and outgrowth in xenograft models. Our results highlight interclonal metabolite exchange as a key modulator of tumor ecology and a contributing factor to overcoming Allee effect-associated growth barriers to metastasis.