Lipid droplets are a metabolic vulnerability in melanoma

Phospholipid isotope tracing suggests β-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma

Activating mutations in the CTNNB1 gene encoding β-catenin are among the most frequently observed oncogenic alterations in hepatocellular carcinoma (HCC). Profound alterations in lipid metabolism, including increases in fatty acid oxidation and transformation of the phospholipidome, occur in HCC with CTNNB1 mutations, but it is unclear what mechanisms give rise to these changes. We employed untargeted lipidomics and targeted isotope tracing to measure phospholipid synthesis activity in an inducible human liver cell line expressing mutant β-catenin, as well as in transgenic zebrafish with activated β-catenin-driven HCC. In both models, activated β-catenin expression was associated with large changes in the lipidome including conserved increases in acylcarnitines and ceramides and decreases in triglycerides. Lipid isotope tracing analysis in human cells revealed a reduction in phosphatidylcholine (PC) production rates as assayed by choline incorporation. We developed lipid isotope tracing analysis for zebrafish tumors and observed reductions in phosphatidylcholine synthesis by both the CDP-choline and PEMT pathways. The observed changes in the β-catenin-driven HCC phospholipidome suggest that zebrafish can recapitulate conserved features of HCC lipid metabolism and may serve as a model for identifying future HCC-specific lipid metabolic targets.

The path to leptomeningeal metastasis

The leptomeninges, the cerebrospinal-fluid-filled tissues surrounding the central nervous system, play host to various pathologies including infection, neuroinflammation and malignancy. Spread of systemic cancer into this space, termed leptomeningeal metastasis, occurs in 5-10% of patients with solid tumours and portends a bleak clinical prognosis. Previous, predominantly descriptive, clinical studies have provided few insights. Recent development of preclinical leptomeningeal metastasis models, alongside genomic, transcriptomic and proteomic sequencing efforts, has provided groundwork for mechanistic understanding and identification of long-needed therapeutic targets. Although previously understood as an anatomically isolated compartment, the leptomeninges are increasingly appreciated as a major conduit of communication between the systemic circulation and the central nervous system. Despite the unique nature of the leptomeningeal microenvironment, the general principles of metastasis hold true: cells metastasizing to the leptomeninges must gain access to the new environment, survive within the space and evade the immune system. The study of leptomeningeal metastasis has the potential to uncover novel site-specific metastatic principles and illuminate the physiology of the leptomeningeal space. In this Review, we provide a biology-focused overview of how metastatic cells reach the leptomeninges, thrive in this nutritionally sparse environment and evade the detection of the omnipresent immune system.

Prognosis and immunotherapy in melanoma based on selenoprotein k-related signature

Selenium and selenoproteins are closely related to melanoma progression. However, it is unclear how SELENOK affects lipid metabolism, endoplasmic reticulum stress (ERS), immune cell infiltration, survival, and prognosis in melanoma patients. Transcriptome data from melanoma patients was used to investigate SELENOK levels and their effect on prognosis, followed by an investigation of SELENOK's effects on immune cell infiltration. Furthermore, a risk model based on ERS, lipid metabolism, and immune-related genes was constructed, and its utility in melanoma prognosis was evaluated. Finally, the drug sensitivity of the risk model was analyzed to provide a reference for melanoma therapy. The results showed that melanoma with a high SELENOK level had a greater degree of immune cell infiltration and a better prognosis. Additionally, SELENOK was found to regulate ERS, lipid metabolism, and immune cell infiltration in melanoma. The risk model based on SELENOK signature genes successfully predicted the prognosis of melanoma, and the low-risk group exhibited a favorable immunological microenvironment. Furthermore, high-risk patients with melanoma were candidates for chemotherapy with RAS pathway inhibitors, whereas low-risk patients were more susceptible to routinely used chemotherapy medicines. In summary, SELENOK was shown to regulate ERS, lipid metabolism, and immune cell infiltration in melanoma, and SELENOK was positively associated with the prognosis of melanoma. The risk model based on SELENOK signature genes was valuable for melanoma prognosis and therapy.

Tumor Biomechanics Alters Metastatic Dissemination of Triple Negative Breast Cancer via Rewiring Fatty Acid Metabolism

In recent decades, the role of tumor biomechanics on cancer cell behavior at the primary site has been increasingly appreciated. However, the effect of primary tumor biomechanics on the latter stages of the metastatic cascade, such as metastatic seeding of secondary sites and outgrowth remains underappreciated. This work sought to address this in the context of triple negative breast cancer (TNBC), a cancer type known to aggressively disseminate at all stages of disease progression. Using mechanically tuneable model systems, mimicking the range of stiffness's typically found within breast tumors, it is found that, contrary to expectations, cancer cells exposed to softer microenvironments are more able to colonize secondary tissues. It is shown that heightened cell survival is driven by enhanced metabolism of fatty acids within TNBC cells exposed to softer microenvironments. It is demonstrated that uncoupling cellular mechanosensing through integrin β1 blocking antibody effectively causes stiff primed TNBC cells to behave like their soft counterparts, both in vitro and in vivo. This work is the first to show that softer tumor microenvironments may be contributing to changes in disease outcome by imprinting on TNBC cells a greater metabolic flexibility and conferring discrete cell survival advantages.

Seipin deficiency-induced lipid dysregulation leads to hypomyelination-associated cognitive deficits via compromising oligodendrocyte precursor cell differentiation

Seipin is one key mediator of lipid metabolism that is highly expressed in adipose tissues as well as in the brain. Lack of Seipin gene, Bscl2, leads to not only severe lipid metabolic disorders but also cognitive impairments and motor disabilities. Myelin, composed mainly of lipids, facilitates nerve transmission and is important for motor coordination and learning. Whether Seipin deficiency-leaded defects in learning and motor coordination is underlined by lipid dysregulation and its consequent myelin abnormalities remains to be elucidated. In the present study, we verified the expression of Seipin in oligodendrocytes (OLs) and their precursors, oligodendrocyte precursor cells (OPCs), and demonstrated that Seipin deficiency compromised OPC differentiation, which led to decreased OL numbers, myelin protein, myelinated fiber proportion and thickness of myelin. Deficiency of Seipin resulted in impaired spatial cognition and motor coordination in mice. Mechanistically, Seipin deficiency suppressed sphingolipid metabolism-related genes in OPCs and caused morphological abnormalities in lipid droplets (LDs), which markedly impeded OPC differentiation. Importantly, rosiglitazone, one agonist of PPAR-gamma, substantially restored phenotypes resulting from Seipin deficiency, such as aberrant LDs, reduced sphingolipids, obstructed OPC differentiation, and neurobehavioral defects. Collectively, the present study elucidated how Seipin deficiency-induced lipid dysregulation leads to neurobehavioral deficits via impairing myelination, which may pave the way for developing novel intervention strategy for treating metabolism-involved neurological disorders.

The fatty acid-related gene signature stratifies poor prognosis patients and characterizes TIME in cutaneous melanoma

BACKGROUND

The aim of this study is to build a prognostic model for cutaneous melanoma (CM) using fatty acid-related genes and evaluate its capacity for predicting prognosis, identifying the tumor immune microenvironment (TIME) composition, and assessing drug sensitivity.

METHODS

Through the analysis of transcriptional data from TCGA-SKCM and GTEx datasets, we screened for differentially expressed fatty acids-related genes (DEFAGs). Additionally, we employed clinical data from TCGA-SKCM and GSE65904 to identify genes associated with prognosis. Subsequently, utilizing all the identified prognosis-related fatty acid genes, we performed unsupervised clustering analysis using the ConsensusClusterPlus R package. We further validated the significant differences between subtypes through survival analysis and pathway analysis. To predict prognosis, we developed a LASSO-Cox prognostic signature. This signature's predictive ability was rigorously examined through multivariant Cox regression, survival analysis, and ROC curve analysis. Following this, we constructed a nomogram based on the aforementioned signature and evaluated its accuracy and clinical utility using calibration curves, cumulative hazard rates, and decision curve analysis. Using this signature, we stratified all cases into high- and low-risk groups and compared the differences in immune characteristics and drug treatment responsiveness between these two subgroups. Additionally, in this study, we provided preliminary confirmation of the pivotal role of CD1D in the TIME of CM. We analyzed its expression across various immune cell types and its correlation with intercellular communication using single-cell data from the GSE139249 dataset.

RESULTS

In this study, a total of 84 DEFAGs were identified, among which 18 were associated with prognosis. Utilizing these 18 prognosis-related genes, all cases were categorized into three subtypes. Significant differences were observed between subtypes in terms of survival outcomes, the expression of the 18 DEFAGs, immune cell proportions, and enriched pathways. A LASSO-Cox regression analysis was performed on these 18 genes, leading to the development of a signature comprising 6 DEFAGs. Risk scores were calculated for all cases, dividing them into high-risk and low-risk groups. High-risk patients exhibited significantly poorer prognosis than low-risk patients, both in the training group (p < 0.001) and the test group (p = 0.002). Multivariate Cox regression analysis indicated that this signature could independently predict outcomes [HR = 2.03 (1.69-2.45), p < 0.001]. The area under the ROC curve for the training and test groups was 0.715 and 0.661, respectively. Combining risk scores with clinical factors including metastatic status and patient age, a nomogram was constructed, which demonstrated significant predictive power for 3  and 5 years patient outcomes. Furthermore, the high and low-risk subgroups displayed differences in the composition of various immune cells, including M1 macrophages, M0 macrophages, and CD8+ T cells. The low-risk subgroup exhibited higher StromalScore, ImmuneScore, and ESTIMATEScore (p < 0.001) and demonstrated better responsiveness to immune therapy for patients with PD1-positive and CTLA4-negative or positive expressions (p < 0.001). The signature gene CD1D was found to be mainly expressed in monocytes/macrophages and dendritic cells within the TIME. Through intercellular communication analysis, it was observed that cases with high CD1D expression exhibited significantly enhanced signal transductions from other immune cells to monocytes/macrophages, particularly the (HLA-A/B/C/E/F)-CD8A signaling from natural killer (NK) cells to monocytes/macrophages (p < 0.01).

CONCLUSIONS

The prognostic signature constructed in this study, based on six fatty acid-related genes, exhibits strong capabilities in predicting patient outcomes, identifying the TIME, and assessing drug sensitivity. This signature can aid in patient risk stratification and provide guidance for clinical treatment strategies. Additionally, our research highlights the crucial role of CD1D in the CM's TIME, laying a theoretical foundation for future related studies.

Phenotype-specific melanoma uptake of fatty acid from human adipocytes activates AXL and CAV1-dependent β-catenin nuclear accumulation

Phenotypic diversity of cancer cells within tumors generated through bi-directional interactions with the tumor microenvironment has emerged as a major driver of disease progression and therapy resistance. Nutrient availability plays a critical role in determining phenotype, but whether specific nutrients elicit different responses on distinct phenotypes is poorly understood. Here we show, using melanoma as a model, that only MITF Low undifferentiated cells, but not MITF High cells, are competent to drive lipolysis in human adipocytes. In contrast to MITF High melanomas, adipocyte-derived free fatty acids are taken up by undifferentiated MITF Low cells via a fatty acid transporter (FATP)-independent mechanism. Importantly, oleic acid (OA), a monounsaturated long chain fatty acid abundant in adipose tissue and lymph, reprograms MITF Low undifferentiated melanoma cells to a highly invasive state by ligand-independent activation of AXL, a receptor tyrosine kinase associated with therapy resistance in a wide range of cancers. AXL activation by OA then drives SRC-dependent formation and nuclear translocation of a β-catenin-CAV1 complex. The results highlight how a specific nutritional input drives phenotype-specific activation of a pro-metastasis program with implications for FATP-targeted therapies.

Extracellular lipidosomes containing lipid droplets and mitochondria are released during melanoma cell division

BACKGROUND

The incidence of melanoma is increasing worldwide. Since metastatic melanoma is highly aggressive, it is important to decipher all the biological aspects of melanoma cells. In this context, we have previously shown that metastatic FEMX-I melanoma cells release small (< 150 nm) extracellular vesicles (EVs) known as exosomes and ectosomes containing the stem (and cancer stem) cell antigenic marker CD133. EVs play an important role in intercellular communication, which could have a micro-environmental impact on surrounding tissues.

RESULTS

We report here a new type of large CD133+ EVs released by FEMX-I cells. Their sizes range from 2 to 6 µm and they contain lipid droplets and mitochondria. Real-time video microscopy revealed that these EVs originate from the lipid droplet-enriched cell extremities that did not completely retract during the cell division process. Once released, they can be taken up by other cells. Silencing CD133 significantly affected the cellular distribution of lipid droplets, with a re-localization around the nuclear compartment. As a result, the formation of large EVs containing lipid droplets was severely compromised.

CONCLUSION

Given the biochemical effect of lipid droplets and mitochondria and/or their complexes on cell metabolism, the release and uptake of these new large CD133+ EVs from dividing aggressive melanoma cells can influence both donor and recipient cells, and therefore impact melanoma growth and dissemination.

Phospholipid isotope tracing reveals β-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma

Background and Aims

Activating mutations in the CTNNB1 gene encoding β-catenin are among the most frequently observed oncogenic alterations in hepatocellular carcinoma (HCC). HCC with CTNNB1 mutations show profound alterations in lipid metabolism including increases in fatty acid oxidation and transformation of the phospholipidome, but it is unclear how these changes arise and whether they contribute to the oncogenic program in HCC.

Methods

We employed untargeted lipidomics and targeted isotope tracing to quantify phospholipid production fluxes in an inducible human liver cell line expressing mutant β-catenin, as well as in transgenic zebrafish with activated β-catenin-driven HCC.

Results

In both models, activated β-catenin expression was associated with large changes in the lipidome including conserved increases in acylcarnitines and ceramides and decreases in triglycerides. Lipid flux analysis in human cells revealed a large reduction in phosphatidylcholine (PC) production rates as assayed by choline tracer incorporation. We developed isotope tracing lipid flux analysis for zebrafish and observed similar reductions in phosphatidylcholine synthesis flux accomplished by sex-specific mechanisms.

Conclusions

The integration of isotope tracing with lipid abundances highlights specific lipid class transformations downstream of β-catenin signaling in HCC and suggests future HCC-specific lipid metabolic targets.