Excess adiposity is a risk factor for several cancer types. This is likely due to complex mechanisms including alterations in the lipid milieu that plays a pivotal role in multiple aspects of carcinogenesis. Here we consider the direct role of lipids in regulating well-known hallmarks of cancer. Furthermore, we suggest that obesity-associated remodelling of membranes and organelles drives cancer cell proliferation and invasion. Identification of cancer-related lipid-mediated mechanisms amongst the broad metabolic disturbances due to excess adiposity is central to the identification of novel and more efficacious prevention and intervention strategies.

Background: Caveolae proteins play diverse roles in cancer development and progression. In prostate cancer, non‐caveolar caveolin‐1 (CAV1) promotes metastasis, while CAVIN1 attenuates CAV1‐induced metastasis. Here, we unveil a novel mechanism linking CAV1 to selective loading of exosomes with metastasis‐promoting microRNAs.Results: We identify hnRNPK as a CAV1‐regulated microRNA binding protein. In the absence of CAVIN1, non‐caveolar CAV1 drives localisation of hnRPNK to multi‐vesicular bodies (MVBs), recruiting AsUGnA motif‐containing miRNAs and causing their release within exosomes. This process is dependent on the lipid environment of membranes as shown by cholesterol depletion using methyl‐β‐cyclodextrin or by treatment with n‐3 polyunsaturated fatty acids. Consistent with a role in bone metastasis, knockdown of hnRNPK in prostate cancer PC3 cells abolished the ability of PC3 extracellular vesicles (EV) to induce osteoclastogenesis, and biofluid EV hnRNPK is elevated in metastatic prostate and colorectal cancer.Conclusions: Taken together, these results support a novel pan‐cancer mechanism for CAV1‐driven exosomal release of hnRNPK and associated miRNA in metastasis, which is modulated by the membrane lipid environment.

During chronic liver injury hepatic stellate cells (HSCs), the principal source of extracellular matrix in the fibrotic liver, transdifferentiate into pro-fibrotic myofibroblast-like cells - a process potentially regulated by microRNAs (miRNAs). Recently, we found serum miRNA-25-3p (miR-25) levels were upregulated in children with Cystic Fibrosis (CF) without liver disease, compared to children with CF-associated liver disease and healthy individuals. Here we examine the role of miR-25 in HSC biology. MiR-25 was detected in the human HSC cell line LX-2 and in primary murine HSCs, and increased with culture-induced activation. Transient overexpression of miR-25 inhibited TGF-β and its type 1 receptor (TGFBR1) mRNA expression, TGF-β-induced Smad2 phosphorylation and subsequent collagen1α1 induction in LX-2 cells. Pull-down experiments with biotinylated miR-25 revealed Notch signaling (co-)activators ADAM-17 and FKBP14 as miR-25 targets in HSCs. NanoString analysis confirmed miR-25 regulation of Notch- and Wnt-signaling pathways. Expression of Notch signaling pathway components and endogenous Notch1 signaling was downregulated in miR-25 overexpressing LX-2 cells, as were components of Wnt signaling such as Wnt5a. We propose that miR-25 acts as a negative feedback anti-fibrotic control during HSC activation by reducing the reactivity of HSCs to TGF-β-induced collagen expression and modulating the cross-talk between Notch, Wnt and TGF-β signaling.

Fourier transform infrared (FTIR) spectroscopy provides a (bio)chemical snapshot of the sample, and was recently used in proof-of-concept cohort studies for COVID-19 saliva screening. However, the biological basis of the proposed technology has not been established. To investigate underlying pathophysiology, we conducted controlled infection experiments on Vero E6 cells in vitro and K18-hACE2 mice in vivo. Potentially infectious culture supernatant or mouse oral lavage samples were treated with ethanol or 75% (v/v) Trizol for attenuated total reflectance (ATR)-FTIR spectroscopy and proteomics, or RT-PCR, respectively. Controlled infection with UV-inactivated SARS-CoV-2 elicited strong biochemical changes in culture supernatant/oral lavage despite a lack of viral replication, determined by RT-PCR or a cell culture infectious dose 50% assay. Nevertheless, SARS-CoV-2 infection induced additional FTIR signals over UV-inactivated SARS-CoV-2 infection in both cell and mouse models, which correspond to aggregated proteins and RNA. Proteomics of mouse oral lavage revealed increased secretion of kallikreins and immune modulatory proteins. Next, we collected saliva from a cohort of human participants (n = 104) and developed a predictive model for COVID-19 using partial least squares discriminant analysis. While high sensitivity of 93.48% was achieved through leave-one-out cross-validation, COVID-19 patients testing negative on follow-up on the day of saliva sampling using RT-PCR was poorly predicted in this model. Importantly, COVID-19 vaccination did not lead to the misclassification of COVID-19 negatives. Finally, meta-analysis revealed that SARS-CoV-2 induced increases in the amide II band in all arms of this study and in recently published cohort studies, indicative of altered β-sheet structures in secreted proteins. In conclusion, this study reveals a consistent secretory pathophysiological response to SARS-CoV-2, as well as a simple, robust method for COVID-19 saliva screening using ATR-FTIR.

Despite the increasing popularity of liquid chromatography–mass spectrometry (LC-MS)-based lipidomics, there is a lack of accepted and validated methods for lipid extract quality and quantity assessment prior to LC-MS. Fourier-Transform Infrared Spectroscopy (FTIR) has been reported for quantification of pure lipids. However, the impact of complex lipid sample complexity and purity on total lipid quantification accuracy has not been investigated. Here, we report comprehensive assessment of the sample matrix on the accuracy of lipid quantification using Attenuated Total Reflectance (ATR)-FTIR and establish a simple workflow for lipidomics sample quantification. We show that both pure and complex lipids show characteristic FTIR vibrations of CH- and C=O-stretching vibrations, with a quantitative range of 40–3000 ng and a limit of detection of 12 ng, but sample extraction method and local baseline subtraction during FTIR spectral processing significantly impact lipid quantification via CH stretching. To facilitate sample quality screening, we developed the Lipid Quality (LiQ) score from a spectral library of common contaminants, using a ratio of peak heights between CH stretching vibrations maxima and the collective vibrations from amide/amine, CH-stretching minima and sugar moieties. Taking all tested parameters together, we propose a rapid FTIR workflow for routine lipidomics sample quality and quantity assessment and tested this workflow by comparing to the total LC-MS intensity of targeted lipidomics of 107 human plasma lipid extracts. Exclusion of poor-quality samples based on LiQ score improved the correlation between FTIR and LC-MS quantification. The uncertainty of absolute quantification by FTIR was estimated using a 795 ng SPLASH LipidoMix standard to be <10%. With low sample requirement, we anticipate this simple and rapid method will enhance lipidomics workflow by enabling accurate total lipid quantification and normalization of lipid quantity for MS analysis.