FAM3C in circulating tumor-derived extracellular vesicles promotes non-small cell lung cancer growth in secondary sites

Exosome-based anticancer vaccines: From Bench to Bedside

Exosomes, a subset of extracellular vesicles, are released by all active cells and play a crucial role in intercellular communications. Exosomes could facilitate the transfer of various biologically active molecules, such as DNA, non-coding RNAs, and proteins, from donor to recipient cells, thereby participating in diverse biological and pathological processes. Besides, exosomes possess unique characteristics, including non-toxicity, low-immunogenicity, and stability within biological systems, rendering them highly advantageous for cancer drug development. Meanwhile, accumulating evidence suggests that exosomes originating from tumor cells and immune cells possess distinct composition profiles that play a direct role in anticancer immunotherapy. Of note, exosomes can transport their contents to specific cells, thereby exerting an impact on the phenotype and immune-regulatory functions of targeted cells. Therapeutic cancer vaccines, an emerging therapeutics of immunotherapy, could enhance antitumor immune responses by delivering a large number of tumor antigens, thereby augmenting the immune response against tumor cells. Therefore, the therapeutic rationale of cancer vaccines and exosome-based immunotherapy are almost similar to some extent, but some challenges have hindered their application in the clinical setting. Here, in this review, we first summarized the biogenesis, structure, compositions, and biological functions of exosomes. Then we described the roles of exosomes in cancer biology, particularly in tumor immunity. We also comprehensively reviewed current exosome-based anticancer vaccine development and we divided them into three types. Finally, we give some insights into clinical translation and clinical trial progress of exosome-based anticancer vaccines for future direction.

Proteomics provides insights into the theranostic potential of extracellular vesicles

Extracellular vesicles (EVs) encompass a diverse range of membranous structures derived from cells, including exosomes and microvesicles. These vesicles are present in biological fluids and play vital roles in various physiological and pathological processes. They facilitate intercellular communication by enabling the exchange of proteins, lipids, and genetic material between cells. Understanding the cellular processes that govern EV biology is essential for unraveling their physiological and pathological functions and their potential clinical applications. Despite significant advancements in EV research in recent years, there is still much to learn about these vesicles. The advent of improved mass spectrometry (MS)-based techniques has allowed for a deeper characterization of EV protein composition, providing valuable insights into their roles in different physiological and pathological conditions. In this chapter, we provide an overview of proteomics studies conducted to identify the protein contents of EVs, which contribute to their therapeutic and pathological features. We also provided evidence on the potential of EV proteome contents as biomarkers for early disease diagnosis, progression, and treatment response, as well as factors that influence their composition. Additionally, we discuss the available databases containing information on EV proteome contents, and finally, we highlight the need for further research to pave the way toward their utilization in clinical settings.

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes.

METHODS

Here, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes.

RESULTS

Our study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients.

CONCLUSIONS

These findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.

Single-cell characterization of self-renewing primary trophoblast organoids as modeling of EVT differentiation and interactions with decidual natural killer cells

BACKGROUND

Extravillous trophoblast cell (EVT) differentiation and its communication with maternal decidua especially the leading immune cell type natural killer (NK) cell are critical events for placentation. However, appropriate in vitro modelling system and regulatory programs of these two events are still lacking. Recent trophoblast organoid (TO) has advanced the molecular and mechanistic research in placentation. Here, we firstly generated the self-renewing TO from human placental villous and differentiated it into EVTs (EVT-TO) for investigating the differentiation events. We then co-cultured EVT-TO with freshly isolated decidual NKs for further study of cell communication. TO modelling of EVT differentiation as well as EVT interaction with dNK might cast new aspect for placentation research.

RESULTS

Single-cell RNA sequencing (scRNA-seq) was applied for comprehensive characterization and molecular exploration of TOs modelling of EVT differentiation and interaction with dNKs. Multiple distinct trophoblast states and dNK subpopulations were identified, representing CTB, STB, EVT, dNK1/2/3 and dNKp. Lineage trajectory and Seurat mapping analysis identified the close resemblance of TO and EVT-TO with the human placenta characteristic. Transcription factors regulatory network analysis revealed the cell-type specific essential TFs for controlling EVT differentiation. CellphoneDB analysis predicted the ligand-receptor complexes in dNK-EVT-TO co-cultures, which relate to cytokines, immunomodulation and angiogenesis. EVT was known to affect the immune properties of dNK. Our study found out that on the other way around, dNKs could exert effects on EVT causing expression changes which are functionally important.

CONCLUSION

Our study documented a single-cell atlas for TO and its applications on EVT differentiation and communications with dNKs, and thus provide methodology and novel research cues for future study of human placentation.

An integrated bioinformatic analysis of bulk and single-cell sequencing clarifies immune microenvironment and metabolic profiles of lung adenocarcinoma to predict immunotherapy efficacy

Targeting the tumor microenvironment is increasingly recognized as an effective treatment of advanced lung adenocarcinoma (LUAD). However, few studies have addressed the efficacy of immunotherapy for LUAD. Here, a novel method for predicting immunotherapy efficacy has been proposed, which combines single-cell and bulk sequencing to characterize the immune microenvironment and metabolic profile of LUAD. TCGA bulk dataset was used to cluster two immune subtypes: C1 with “cold” tumor characteristics and C2 with “hot” tumor characteristics, with different prognosis. The Scissor algorithm, which is based on these two immune subtypes, identified GSE131907 single cell dataset into two groups of epithelial cells, labeled as Scissor_C1 and Scissor_C2. The enrichment revealed that Scissor_C1 was characterized by hypoxia, and a hypoxic microenvironment is a potential inducing factor for tumor invasion, metastasis, and immune therapy non-response. Furthermore, single cell analysis was performed to investigate the molecular mechanism of hypoxic microenvironment-induced invasion, metastasis, and immune therapy non-response in LUAD. Notably, Scissor_C1 cells significantly interacted with T cells and cancer-associated fibroblasts (CAF), and exhibited epithelial–mesenchymal transition and immunosuppressive features. CellChat analysis revealed that a hypoxic microenvironment in Scissor_C1elevated TGFβ signaling and induced ANGPTL4 and SEMA3C secretion. Interaction with endothelial cells with ANGPTL4, which increases vascular permeability and achieves distant metastasis across the vascular endothelium. Additionally, interaction of tumor-associated macrophages (TAM) and Scissor_C1 via the EREG/EFGR pathway induces tyrosine kinase inhibitor drug-resistance in patients with LAUD. Thereafter, a subgroup of CAF cells that exhibited same features as those of Scissor_C1 that exert immunosuppressive functions in the tumor microenvironment were identified. Moreover, the key genes (EPHB2 and COL1A1) in the Scissor_C1 gene network were explored and their expressions were verified using immunohistochemistry. Finally, the metabolism dysfunction in cells crosstalk was determined, which is characterized by glutamine secretion by TAM and uptake by Scissor_C1 via SLC38A2 transporter, which may induce glutamine addiction in LUAD cells. Overall, single-cell sequencing clarifies how the tumor microenvironment affects immunotherapy efficacy via molecular mechanisms and biological processes, whereas bulk sequencing explains immunotherapy efficacy based on clinical information.