Raman Microspectroscopy Identifies Biochemical Activation Fingerprints in THP-1- and PBMC-Derived Macrophages

Human tissue-resident peritoneal macrophages reveal resistance towards oxidative cell stress induced by non-invasive physical plasma

In the context of multimodal treatments for abdominal cancer, including procedures such as cytoreductive surgery and intraperitoneal chemotherapy, recurrence rates remain high, and long-term survival benefits are uncertain due to post-operative complications. Notably, treatment-limiting side effects often arise from an uncontrolled activation of the immune system, particularly peritoneally localized macrophages, leading to massive cytokine secretion and phenotype changes. Exploring alternatives, an increasing number of studies investigated the potential of plasma-activated liquids (PAL) for adjuvant peritoneal cancer treatment, aiming to mitigate side effects, preserve healthy tissue, and reduce cytotoxicity towards non-cancer cells. To assess the non-toxicity of PAL, we isolated primary human macrophages from the peritoneum and subjected them to PAL exposure. Employing an extensive methodological spectrum, including flow cytometry, Raman microspectroscopy, and DigiWest protein analysis, we observed a pronounced resistance of macrophages towards PAL. This resistance was characterized by an upregulation of proliferation and anti-oxidative pathways, countering PAL-derived oxidative stress-induced cell death. The observed cellular effects of PAL treatment on human tissue-resident peritoneal macrophages unveil a potential avenue for PAL-derived immunomodulatory effects within the human peritoneal cavity. Our findings contribute to understanding the intricate interplay between PAL and macrophages, shedding light on the promising prospects for PAL in the adjuvant treatment of peritoneal cancer.

Immunomodulatory Peptides as Vaccine Adjuvants and Antimicrobial Agents

The underdevelopment of adjuvant discovery and diversity, compared to core vaccine technology, is evident. On the other hand, antibiotic resistance is on the list of the top ten threats to global health. Immunomodulatory peptides that target a pathogen and modulate the immune system simultaneously are promising for the development of preventive and therapeutic molecules. Since investigating innate immunity in insects has led to prominent achievements in human immunology, such as toll-like receptor (TLR) discovery, we used the capacity of the immunomodulatory peptides of arthropods with concomitant antimicrobial or antitumor activity. An SVM-based machine learning classifier identified short immunomodulatory sequences encrypted in 643 antimicrobial peptides from 55 foe-to-friend arthropods. The critical features involved in efficacy and safety were calculated. Finally, 76 safe immunomodulators were identified. Then, molecular docking and simulation studies defined the target of the most optimal peptide ligands among all human cell-surface TLRs. SPalf2-453 from a crab is a cell-penetrating immunoadjuvant with antiviral properties. The peptide interacts with the TLR1/2 heterodimer. SBsib-711 from a blackfly is a TLR4/MD2 ligand used as a cancer vaccine immunoadjuvant. In addition, SBsib-711 binds CD47 and PD-L1 on tumor cells, which is applicable in cancer immunotherapy as a checkpoint inhibitor. MRh4-679 from a shrimp is a broad-spectrum or universal immunoadjuvant with a putative Th1/Th2-balanced response. We also implemented a pathway enrichment analysis to define fingerprints or immunological signatures for further in vitro and in vivo immunogenicity and reactogenicity measurements. Conclusively, combinatorial machine learning, molecular docking, and simulation studies, as well as systems biology, open a new opportunity for the discovery and development of multifunctional prophylactic and therapeutic lead peptides.

Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning

Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluation.

Raman Spectroscopy Profiling of Splenic T-Cells in Sepsis and Endotoxemia in Mice

Sepsis is a life-threatening condition that results from an overwhelming and disproportionate host response to an infection. Currently, the quality and extent of the immune response are evaluated based on clinical symptoms and the concentration of inflammatory biomarkers released or expressed by the immune cells. However, the host response toward sepsis is heterogeneous, and the roles of the individual immune cell types have not been fully conceptualized. During sepsis, the spleen plays a vital role in pathogen clearance, such as bacteria by an antibody response, macrophage bactericidal capacity, and bacterial endotoxin detoxification. This study uses Raman spectroscopy to understand the splenic T-lymphocyte compartment profile changes during bona fide bacterial sepsis versus hyperinflammatory endotoxemia. The Raman spectral analysis showed marked changes in splenocytes of mice subjected to septic peritonitis principally in the DNA region, with minor changes in the amino acids and lipoprotein areas, indicating significant transcriptomic activity during sepsis. Furthermore, splenocytes from mice exposed to endotoxic shock by injection of a high dose of lipopolysaccharide showed significant changes in the protein and lipid profiles, albeit with interindividual variations in inflammation severity. In summary, this study provided experimental evidence for the applicability and informative value of Raman spectroscopy for profiling the immune response in a complex, systemic infection scenario. Importantly, changes within the acute phase of inflammation onset (24 h) were reliably detected, lending support to the concept of early treatment and severity control by extracorporeal Raman profiling of immunocyte signatures.

Review: Current trends, challenges, and success stories in adjuvant research

Vaccine adjuvant research is being fueled and driven by progress in the field of innate immunity that has significantly advanced in the past two decades with the discovery of countless innate immune receptors and innate immune pathways. Receptors for pathogen-associated molecules (PAMPs) or host-derived, danger-associated molecules (DAMPs), as well as molecules in the signaling pathways used by such receptors, are a rich source of potential targets for agonists that enable the tuning of innate immune responses in an unprecedented manner. Targeted modulation of immune responses is achieved not only through the choice of immunostimulator - or select combinations of adjuvants - but also through formulation and systematic modifications of the chemical structure of immunostimulatory molecules. The use of medium and high-throughput screening methods for finding immunostimulators has further accelerated the identification of promising novel adjuvants. However, despite the progress that has been made in finding new adjuvants through systematic screening campaigns, the process is far from perfect. A major bottleneck that significantly slows the process of turning confirmed or putative innate immune receptor agonists into vaccine adjuvants continues to be the lack of defined in vitro correlates of in vivo adjuvanticity. This brief review discusses recent developments, exciting trends, and notable successes in the adjuvant research field, albeit acknowledging challenges and areas for improvement.