Monitoring Metabolic Changes in Response to Chemotherapies in Cancer with Raman Spectroscopy and Metabolomics

Resistance to clinical therapies remains a major barrier in cancer management. There is a critical need for rapid and highly sensitive diagnostic tools that enable early prediction of treatment response to allow accurate clinical decisions. Here, Raman spectroscopy was employed to monitor changes in key metabolites as early predictors of response in KRAS-mutant colorectal cancer (CRC) cells, HCT116, treated with chemotherapies. We show at the single cell level that HCT116 is resistant to cetuximab (CTX), the first-line treatment in CRC, but this resistance can be overcome with pre-sensitization of cells with oxaliplatin (OX). In combination treatment of CTX + OX, sequential delivery of OX followed by CTX rather than simultaneous administration of drugs was observed to be critical for effective therapy. Our results demonstrated that metabolic changes are well aligned to cellular mechanical changes where Young’s modulus decreased after effective treatment, indicating that both changes in mechanical properties and metabolism in cells are likely responsible for cancer proliferation. Raman findings were verified with mass spectrometry (MS) metabolomics, and both platforms showed changes in lipids, nucleic acids, and amino acids as predictors of resistance/response. Finally, key metabolic pathways enriched were identified when cells are resistant to CTX but downregulated with effective treatment. This study highlights that drug-induced metabolic changes both at the single cell level (Raman) and ensemble level (MS) have the potential to identify mechanisms of response to clinical cancer therapies

Poly(PEGA)‑<i>b</i>‑poly(l‑lysine)‑<i>b</i>‑poly(l‑histidine) Hybrid Vesicles for Tumoral pH-Triggered Intracellular Delivery of Doxorubicin Hydrochloride

A series of poly­(ethylene glycol) methyl ether acrylate-<i>block</i>-poly­(l-lysine)-<i>block</i>-poly­(l-histidine) [p­(PEGA)₃₀-<i>b</i>-p­(Lys)₂₅-<i>b</i>-p­(His)_<i>n</i>] (<i>n</i> = 25, 50, 75, 100) triblock copolypeptides were designed and synthesized for tumoral pH-responsive intracellular release of anticancer drug doxorubicin hydrochloride (Dox). The tumoral acidic pH-responsive hybrid vesicles fabricated were stable at physiological pH 7.4 and could gradually destabilize in acidic pH as a result of pH-induced swelling of the p­(His) block. The blank vesicles were nontoxic over a wide concentration range (0.01–100 μg/mL) in normal cell lines. The tumor acidic pH responsiveness of these vesicles was exploited for intracellular delivery of Dox. Vesicles efficiently encapsulated Dox, and pH-induced destabilization resulted in the controlled and sustained release of Dox in CT26 murine cancer cells, and dose-dependent cytotoxicity. The tumor-specific controlled release Dox from vesicles demonstrates this system represents a promising theranostic agent for tumor-targeted delivery

First Trimester Prediction of Preterm Birth in Patient Plasma with Machine-Learning-Guided Raman Spectroscopy and Metabolomics

Preterm birth (PTB) is the leading cause of infant deaths globally. Current clinical measures often fail to identify women who may deliver preterm. Therefore, accurate screening tools are imperative for early prediction of PTB. Here, we show that Raman spectroscopy is a promising tool for studying biological interfaces, and we examine differences in the maternal metabolome of the first trimester plasma of PTB patients and those that delivered at term (healthy). We identified fifteen statistically significant metabolites that are predictive of the onset of PTB. Mass spectrometry metabolomics validates the Raman findings identifying key metabolic pathways that are enriched in PTB. We also show that patient clinical information alone and protein quantification of standard inflammatory cytokines both fail to identify PTB patients. We show for the first time that synergistic integration of Raman and clinical data guided with machine learning results in an unprecedented 85.1% accuracy of risk stratification of PTB in the first trimester that is currently not possible clinically. Correlations between metabolites and clinical features highlight the body mass index and maternal age as contributors of metabolic rewiring. Our findings show that Raman spectral screening may complement current prenatal care for early prediction of PTB, and our approach can be translated to other patient-specific biological interfaces

Additional file 1 of Inflammation-sensing catalase-mimicking nanozymes alleviate acute kidney injury via reversing local oxidative stress

Additional file 1: Figure S1. (A) Powder sample of prepared dMn3O4 (B) Schematic representation and (C) EDS analysis of dMn3O4. Figure S2. XPS analysis individual peaks in dMn3O4. Figure S3. NMR analysis (A) PTC and (B) PC. Figure S4. Low magnification FE-TEM images of (A) PTC (B) PC-M, PC-M + H2O2, PTC-M and PTC-M + H2O2. Figure S5. EDS elemental mapping of PTC-M. Figure S6. (A) Lyophilized sample of PTC-M (B) TGA analysis. Figure S7. (A) Hydrodynamic diameter and (B) zeta potential of PTC-M and PC-M before and after exposure to H2O2. Figure S8. (A) Hydrodynamic size distribution and (B) zeta potential of empty nanomicelles (PTC and PC) before and after treatment with H2O2. Figure S9. Stability of PTC-M in 10% FBS. Figure S10. Catalase like activity of PTC-M at different concentrations. Figure S11. (A) Disproportionation of H2O2 by PTC-M resulting in bubble formation (B) Dissolved oxygen production by dMn3O4 and PTC-M. Data is shown as mean ± SEM (n = 3 replicates). Statistics were performed by a one-way ANOVA (*P < 0.05, **P < 0.01, *** P < 0.001, and **** P < 0.0001). Figure S12. In vitro cell viability of the empty nanomicelles (PTC, PC) as well as dMn3O4 loaded nanomicelles (PTC-M, PC-M). Figure S13. Cellular uptake and intracellular IR780 release. High magnification images (Scalebar=75µm). Figure S14. (A) Ex-vivo images of organs at different time points post injection form I/R model mice administered with PC-IR780 and IR780 (B) NIRF signal intensity quantification from isolated kidneys of PTC-IR780, PC-IR780 and IR780 administered mice in I/R model at different time points. Figure S15. Ex-vivo images of major organs at different time points post injection form normal C57 mice administered with PTC-IR780. Figure S16. ICP-MS analysis of major organs, feces and urine collected from AKI mice administered with PTC-M at 72 h and 168h. Figure S17. H & E staining of all major organs (liver, lung, spleen, heart, and intestine) collected from the control and PTC-M treated AKI mice (at 72 h), scale bar = 200 μm. Table S1. List of primary and secondary antibodies for immunoblotting. Table S2. List of primer sequences for real-time qPCR. Table S3. List of primary and secondary antibodies for immunohistochemistry

Inhibiting the cGAS-STING Pathway in Ulcerative Colitis with Programmable Micelles

Ulcerative colitis is a chronic condition in which a dysregulated immune response contributes to the acute intestinal inflammation of the colon. Current clinical therapies often exhibit limited efficacy and undesirable side effects. Here, programmable nanomicelles were designed for colitis treatment and loaded with RU.521, an inhibitor of the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway. STING-inhibiting micelles (SIMs) comprise hyaluronic acid-stearic acid conjugates and include a reactive oxygen species (ROS)-responsive thioketal linker. SIMs were designed to selectively accumulate at the site of inflammation and trigger drug release in the presence of ROS. Our in vitro studies in macrophages and in vivo studies in a murine model of colitis demonstrated that SIMs leverage HA-CD44 binding to target sites of inflammation. Oral delivery of SIMs to mice in both preventive and delayed therapeutic models ameliorated colitis’s severity by reducing STING expression, suppressing the secretion of proinflammatory cytokines, enabling bodyweight recovery, protecting mice from colon shortening, and restoring colonic epithelium. In vivo end points combined with metabolomics identified key metabolites with a therapeutic role in reducing intestinal and mucosal inflammation. Our findings highlight the significance of programmable delivery platforms that downregulate inflammatory pathways at the intestinal mucosa for managing inflammatory bowel diseases