SERS analysis of cancer cell-secreted purines reveals a unique paracrine crosstalk in MTAP-deficient tumors.

The tumor microenvironment (TME) is a dynamic pseudoorgan that shapes the development and progression of cancers. It is a complex ecosystem shaped by interactions between tumor and stromal cells. Although the traditional focus has been on the paracrine communication mediated by protein messengers, recent attention has turned to the metabolic secretome in tumors. Metabolic enzymes, together with exchanged substrates and products, have emerged as potential biomarkers and therapeutic targets. However, traditional techniques for profiling secreted metabolites in complex cellular contexts are limited. Surface-enhanced Raman scattering (SERS) has emerged as a promising alternative due to its nontargeted nature and simplicity of operation. Although SERS has demonstrated its potential for detecting metabolites in biological settings, its application in deciphering metabolic interactions within multicellular systems like the TME remains underexplored. In this study, we introduce a SERS-based strategy to investigate the secreted purine metabolites of tumor cells lacking methylthioadenosine phosphorylase (MTAP), a common genetic event associated with poor prognosis in various cancers. Our SERS analysis reveals that MTAP-deficient cancer cells selectively produce methylthioadenosine (MTA), which is taken up and metabolized by fibroblasts. Fibroblasts exposed to MTA exhibit: i) molecular reprogramming compatible with cancer aggressiveness, ii) a significant production of purine derivatives that could be readily recycled by cancer cells, and iii) the capacity to secrete purine derivatives that induce macrophage polarization. Our study supports the potential of SERS for cancer metabolism research and reveals an unprecedented paracrine crosstalk that explains TME reprogramming in MTAP-deleted cancers.

Machine Learning-Assisted High-Throughput SERS Classification of Cell Secretomes.

During the response to different stress conditions, damaged cells react in multiple ways, including the release of a diverse cocktail of metabolites. Moreover, secretomes from dying cells can contribute to the effectiveness of anticancer therapies and can be exploited as predictive biomarkers. The nature of the stress and the resulting intracellular responses are key determinants of the secretome composition, but monitoring such processes remains technically arduous. Hence, there is growing interest in developing tools for noninvasive secretome screening. In this regard, it has been previously shown that the relative concentrations of relevant metabolites can be traced by surface-enhanced Raman scattering (SERS), thereby allowing label-free biofluid interrogation. However, conventional SERS approaches are insufficient to tackle the requirements imposed by high-throughput modalities, namely fast data acquisition and automatized analysis. Therefore, machine learning methods were implemented to identify cell secretome variations while extracting standard features for cell death classification. To this end, ad hoc microfluidic chips were devised, to readily conduct SERS measurements through a prototype relying on capillary pumps made of filter paper, which eventually would function as the SERS substrates. The developed strategy may pave the way toward a faster implementation of SERS into cell secretome classification, which can be extended even to laboratories lacking highly specialized facilities.

The bone marrow niche regulates redox and energy balance in MLL::AF9 leukemia stem cells.

Eradicating leukemia requires a deep understanding of the interaction between leukemic cells and their protective microenvironment. The CXCL12/CXCR4 axis has been postulated as a critical pathway dictating leukemia stem cell (LSC) chemoresistance in AML due to its role in controlling cellular egress from the marrow. Nevertheless, the cellular source of CXCL12 in the acute myeloid leukemia (AML) microenvironment and the mechanism by which CXCL12 exerts its protective role in vivo remain unresolved. Here, we show that CXCL12 produced by Prx1+ mesenchymal cells but not by mature osteolineage cells provide the necessary cues for the maintenance of LSCs in the marrow of an MLL::AF9-induced AML model. Prx1+ cells promote survival of LSCs by modulating energy metabolism and the REDOX balance in LSCs. Deletion of Cxcl12 leads to the accumulation of reactive oxygen species and DNA damage in LSCs, impairing their ability to perpetuate leukemia in transplantation experiments, a defect that can be attenuated by antioxidant therapy. Importantly, our data suggest that this phenomenon appears to be conserved in human patients. Hence, we have identified Prx1+ mesenchymal cells as an integral part of the complex niche-AML metabolic intertwining, pointing towards CXCL12/CXCR4 as a target to eradicate parenchymal LSCs in AML.

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine.

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification of patients based on their predicted disease risk, prognosis, and response to a specific treatment. Up to now, genomics, transcriptomics, and immunohistochemistry have been the main clinically amenable tools at hand for identifying key diagnostic, prognostic, and predictive biomarkers. However, other molecular strategies, including metabolomics, are still in their infancy and require the development of new biomarker detection technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has been recognized as a promising technology for clinical monitoring thanks to its high sensitivity and label-free operation, which should help accelerate the discovery of biomarkers and their corresponding screening in a simpler, faster, and less-expensive manner. Many studies have demonstrated the excellent performance of SERS in biomedical applications. However, such studies have also revealed several variables that should be considered for accurate SERS monitoring, in particular, when the signal is collected from biological sources (tissues, cells or biofluids). This Perspective is aimed at piecing together the puzzle of SERS in biomarker monitoring, with a view on future challenges and implications. We address the most relevant requirements of plasmonic substrates for biomedical applications, as well as the implementation of tools from artificial intelligence or biotechnology to guide the development of highly versatile sensors.

Analyses of Genetic Diversity in the Endangered "Berrenda" Spanish Cattle Breeds Using Pedigree Data.

Pedigree analyses of two endangered cattle breeds were performed in order to study the structure and the genetic variability in their populations. Pedigree data were analyzed from 12,057 individuals belonging to the "Berrenda en Negro" cattle breed (BN) and 20,389 individuals belonging to the "Berrenda en Colorado" cattle breed (BC) that were born between 1983 and 2020. BN and BC reference populations (RP) were set up by 2300 and 3988 animals, respectively. The generation interval in BN and BC reference populations was equal to 6.50 and 6.92 years, respectively. The pedigree completeness level was 82.76% in BN and 79.57% in BC. The inbreeding rates were 4.5% in BN and 3.4% in BC, respectively. The relationship among animals when they were born in different herds was 1.8% in BN and 5% in BC; these values increased to 8.5% and 7.7%, respectively when comparing animals that were born in the same herd. The effective number of founding herds was 23.9 in BN and 60.9 in BC. Number of ancestors needed to explain 50% of genes pool in the whole population was 50 and 101, in BN and in BC, respectively. The effective population size based on co-ancestries was 92.28 in BN and 169.92 in BC. The genetic variability has been maintained in both populations over time and the results of this study suggest that measures to promote the conservation of the genetic variability in these two breeds would go through for the exchange of breeding animals among farms and for monitoring the genetic contributions before implementing any selective action.

Notch3 Deficiency Attenuates Pulmonary Fibrosis and Impedes Lung-Function Decline.

Fibroblast activation includes differentiation to myofibroblasts and is a key feature of organ fibrosis. The Notch pathway has been involved in myofibroblast differentiation in several tissues, including the lung. Here, we identify a subset of collagen-expressing cells in the lung that exhibit Notch3 activity at homeostasis. After injury, this activation increases, being found in αSMA-expressing myofibroblasts in the mouse and human fibrotic lung. Although previous studies suggest a contribution of Notch3 in stromal activation, in vivo evidence of the role of Notch3 in lung fibrosis remains unknown. In this study, we examine the effects of Notch3 deletion in pulmonary fibrosis and demonstrate that Notch3-deficient lungs are protected from lung injury with significantly reduced collagen deposition after bleomycin administration. The induction of profibrotic genes is reduced in bleomycin-treated Notch3-knockout lungs that consistently present fewer αSMA-positive myofibroblasts. As a result, the volume of healthy lung tissue is higher and lung function is improved in the absence of Notch3. Using in vitro cultures of lung primary fibroblasts, we confirmed that Notch3 participates in their survival and differentiation. Thus, Notch3 deficiency mitigates the development of lung fibrosis because of its role in mediating fibroblast activation. Our findings reveal a previously unidentified mechanism underlying lung fibrogenesis and provide a potential novel therapeutic approach to target pulmonary fibrosis.

Anticancer Agent Edelfosine Exhibits a High Affinity for Cholesterol and Disorganizes Liquid-Ordered Membrane Structures.

Edelfosine is an anticancer drug with an asymmetric structure because, being a derivative of glycerol, it possesses two hydrophobic substituents of very different lengths. We showed that edelfosine destabilizes liquid-ordered membranes formed by either 1-palmitoyl-2-oleoyl- sn-glycero-3-phosphocholine, sphingomyelin (SM), and cholesterol (1:1:1 molar ratio) or SM and cholesterol (2:1 molar ratio). This was observed by differential scanning calorimetry in which phase transition arises from either of these membrane systems after the addition of edelfosine. The alteration in the liquid-ordered domains was characterized by using a small-angle X-ray diffraction that revealed the formation of gel phases as a consequence of the addition of edelfosine at low temperatures and by a wide-angle X-ray diffraction that confirmed changes in the membranes, indicating the formation of these gel phases. The increase in phase transition derived by the edelfosine addition was further confirmed by Fourier-transform infrared spectroscopy. The effect of edelfosine was compared with that of structurally analogue lipids: platelet-activating factor and 1-palmitoyl-2-acetyl- sn-glycero-3-phosphocholine, which also have the capacity of destabilizing liquid-ordered domains, although they are less potent than edelfosine for this activity, and lysophosphatidylcholine, which lacks this capacity. It was concluded that edelfosine may be associated with cholesterol favorably competing with sphingomyelin, and that this sets sphingomyelin free to undergo a phase transition. Finally, the experimental observations can be described by molecular dynamics calculations in terms of intermolecular interaction energies in phospholipid-cholesterol membranes. Higher interaction energies between asymmetric phospholipids and cholesterol than between sphingomyelin and cholesterol were obtained. These results are interesting because they biophysically characterize one of the main molecular mechanisms to trigger apoptosis of the cancer cells.

Methods to control the pharmaceutical cost impact of chronic conditions in the elderly.

Multimorbidity is the main cause of polypharmacy in elderly people, with the consequent increment in cost and use of inappropriate medication. To control cost, specific strategies have been implemented in healthcare services to reduce potentially inappropriate prescription. Many interventions are applied online during the prescription process using computerized decision support systems, for example, therapeutic algorithms and alerts. Other interventions can be categorized as offline due to their application before or after the prescription process, the main strategies being financial incentives, medication reviews and organizational change. All these strategies are complementary and multifaceted. There is evidence that some of these interventions are effective, but further research should be directed in this field, including investigation of patient cost and outcomes.