Formation, contents, functions of exosomes and their potential in lung cancer diagnostics and therapeutics

Exosomal miR-1228-5p down-regulates DUSP22 to promotes cell proliferation and migration in small cell lung cancer

BACKGROUND

Exosomes play a crucial role in promoting tumor progression, dissemination, and resistance to treatment. These extracellular vesicles hold promise as valuable indicators for cancer detection. Our investigation focuses on exploring the significance and clinical relevance of exosomal miRNAs in small cell lung cancer (SCLC).

METHODS

Serum exosomes were isolated from both SCLC patients and healthy controls, and subjected to exosomal miRNA sequencing analysis. Mimics and inhibitors were employed to investigate the function of exosomal miR-1128-5p in cell migration and proliferation, both in vitro and in vivo. Western blot and luciferase assay were utilized to identify the interaction between miR-1228-5p and dual specificity phosphatase 22 (DUSP22).

RESULTS

Exosomal miRNA sequencing analysis revealed enrichment of specific miRNAs in SCLC compared to healthy controls. Circulating miR-1228-5p was upregulated in SCLC patients, associated with advanced stages, suggesting its potential oncogenic role. In vitro, miR-1228-5p expression was significantly higher in SCLC cells than in normal cells. SCLC cell-derived exosomes contained elevated levels of miR-1228-5p, facilitating its entry into co-cultured cells. Notably, migration and proliferation induced by SCLC exosomes were mainly mediated by miR-1228-5p. In vivo experiments confirmed these findings. Western blot analysis demonstrated miR-1228-5p's regulation of DUSP22 expression, and luciferase reporter assay validated DUSP22 as a direct target gene. Overexpressing DUSP22 counteracted miR-1228-5p's promotion of SCLC cell proliferation and migration.

CONCLUSIONS

Collectively, our results suggest that exosomes play a role in facilitating cancer growth and metastasis by delivering miR-1228-5p. Moreover, circulating exosomal miR-1228-5p may serve as a potential marker for SCLC diagnosis and prognosis.

Potential therapeutic and diagnostic approaches of exosomes in multiple sclerosis pathophysiology

Exosomes are bilayer lipid vesicles that are released by cells and contain proteins, nucleic acids, and lipids. They can be internalized by other cells, inducing inflammatory responses and instigating toxicities in the recipient cells. Exosomes can also serve as therapeutic vehicles by transporting protective cargo to maintain homeostasis. Multiple studies have shown that exosomes can initiate and participate in the regulation of neuroinflammation, improve neurogenesis, and are closely related to the pathogenesis of central nervous system (CNS) diseases, including multiple sclerosis (MS). Exosomes can be secreted by both neurons and glial cells in the CNS, and their contents change with disease occurrence. Due to their ability to penetrate the blood-brain barrier and their stability in peripheral fluids, exosomes are attractive biomarkers of CNS diseases. In recent years, exosomes have emerged as potential therapeutic agents for CNS diseases, including MS. However, the molecular pathways in the pathogenesis of MS are still unknown, and further research is needed to fully understand the role of exosomes in the occurrence or improvement of MS disease. Thereby, in this review, we intend to provide a more complete understanding of the pathways in which exosomes are involved and affect the occurrence or improvement of MS disease.

Enigmatic exosomal connection in lung cancer drug resistance

Lung cancer remains a significant global health concern with limited treatment options and poor prognosis, particularly in advanced stages. Small extracellular vesicles such as exosomes, secreted by cancer cells, play a pivotal role in mediating drug resistance in lung cancer. Exosomes have been found to facilitate intercellular communication by transferring various biomolecules between cancer cells and their microenvironment. Additionally, exosomes can transport signaling molecules promoting cancer cell survival and proliferation conferring resistance to chemotherapy. Moreover, exosomes can modulate the tumor microenvironment by inducing phenotypic changes hindering drug response. Understanding the role of exosomes in mediating drug resistance in lung cancer is crucial for developing novel therapeutic strategies and biomarkers to overcome treatment limitations. In this review, we summarize the current knowledge on conventional and emerging drug resistance mechanisms and the involvement of exosomes as well as exosome-mediated factors mediating drug resistance in lung cancer.

Unraveling the role of the circadian clock genes in cervical squamous cell carcinoma and endocervical adenocarcinoma: A prognostic indicator for prognostic, immunotherapy response, and chemotherapy sensitivity

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) account for a significant proportion of gynecological malignancies and represent a major global health concern. Globally, CESC is ranked as the fourth most common cancer among women. Conventional treatment of this disease has a less favorable prognosis for most patients. However, the discovery of early molecular biomarkers is therefore important for the diagnosis of CESC, as well as for slowing down their progression process. Methods: To identify differentially expressed genes strongly associated with prognosis, univariate Cox proportional hazard analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used. Using multiple Cox proportional hazard regression, a multifactorial model for prognostic risk assessment was then created. Results: The expression of biological clock-related genes, which varied considerably among distinct subtypes and were associated with significantly diverse prognoses, was used to categorize CESC patients. These findings demonstrate how the nomogram developed based on the 7-CRGs signature may assist physicians in creating more precise, accurate, and successful treatment plans that can aid CESC patients at 1, 3, and 5 years. Conclusions: By using machine learning techniques, we thoroughly investigated the impact of CRGs on the prognosis of CESC patients in this study. By creating a unique nomogram, we were able to accurately predict patient prognosis. At the same time, we showed new perspectives on the development of CESC and its treatment by analyzing the associations of the prognostic model with immunity, enrichment pathways, chemotherapy sensitivity, and so on. This research provides a new direction for clinical treatment.

Copper-binding protein modelling by single-cell transcriptome and Bulk transcriptome to predict overall survival in lung adenocarcinoma patients

Background: Copper and copper-binding proteins are key components of tumour progression as they play an important role in tumour invasion and migration, and abnormal accumulation of copper (Cu) may be intimately linked to with lung adenocarcinoma (LUAD). Methods: Data on lung adenocarcinoma were sourced from the Cancer Genome Atlas (TCGA) database and the National Centre for Biotechnology Information (GEO). 10x scRNA sequencing, which is from Bischoff P et al, was used for down-sequencing clustering and subgroup identification using TSNE. The genes for Copper-binding proteins (CBP) were acquired from the MSigDB database. LASSO-Cox analysis was subsequently used to construct a model for copper-binding proteins (CBPRS), which was then compared to lung adenocarcinoma models developed by others. External validation was carried out in the GSE31210 and GSE50081 cohorts. The effectiveness of immunotherapy was evaluated using the TIDE algorithm and the IMvigor210, GSE78220, and TCIA cohorts. Furthermore, differences in mutational profiles and the immune microenvironment between different risk groups were investigated. The CBPRS's key regulatory genes were screened using ROC diagnostic and KM survival curves. The differential expression of these genes was then verified by RT-qPCR. Results: The six CBP genes were identified as highly predictive of LUAD prognosis and significantly correlated with it. Multivariate analysis showed that patients in the low-risk group had a higher overall survival rate than those in the high-risk group, indicating that the model was an independent predictor of LUAD. The CBPRS demonstrated superior predictive ability compared to 11 previously published models. We constructed a column-line graph that includes CBPRS and clinical characteristics, which exhibits high predictive performance. Additionally, we observed significant differences in biological functions, mutational landscapes, and immune cell infiltration in the tumour microenvironment between the high-risk and low-risk groups. It is noteworthy that immunotherapy was also significant in both the high- and low-risk groups. These results suggest that the model has good predictive efficacy. Conclusions: The CBP model demonstrated good predictive performance, revealing characteristics of the tumour microenvironment. This provides a new method for assessing the efficacy of pre-immunisation and offers a potential strategy for future treatment of lung adenocarcinoma.

Exosome as a crucial communicator between tumor microenvironment and gastric cancer (Review)

Gastric cancer is one of the most common malignancies and has relatively high morbidity and mortality rates. Exosomes are nanoscale extracellular vesicles that originate from a diverse array of cells and may be found throughout various bodily fluids. These vesicles are endogenous nanocarriers in their natural state with the unique ability to transport lipids, proteins, DNA and RNA. Exosomes contain DNA, RNA, proteins, lipids and other bioactive components that have crucial roles in the transmission of information and regulation of cell activities in gastric cancer. This paper begins with an exploration of the composition, formation and release mechanisms of exosomes. Subsequently, the role of exosomes in the tumor microenvironment is reviewed in terms of the immune cell population, nonimmune cell population and other factors. Finally, the current status and challenges of exosome‑based research on the progression, diagnosis and therapeutic methods of gastric cancer are summarized. This holistic review offers insight that may guide future research directions for exosomes and potentially pave the way for novel therapeutic interventions in the management of gastric cancer.

Identification of T-cell exhaustion-related genes and prediction of their immunotherapeutic role in lung adenocarcinoma

Background: Lung adenocarcinoma ranks as the second most widespread form of cancer globally, accompanied by a significant mortality rate. Several studies have shown that T cell exhaustion is associated with immunotherapy of tumours. Consequently, it is essential to comprehend the possible impact of T cell exhaustion on the tumor microenvironment. The purpose of this research was to create a TEX-based model that would use single-cell RNA-seq (scRNA-seq) and bulk-RNA sequencing to explore new possibilities for assessing the prognosis and immunotherapeutic response of LUAD patients. Methods: RNA-seq data from LUAD patients was downloaded from the Cancer Genome Atlas (TCGA) database and the National Center for Biotechnology Information (GEO). 10X scRNA sequencing data, as reported by Bischoff P et al., was utilized for down-sampling clustering and subgroup identification using TSNE. TEX-associated genes were identified through gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). We utilized LASSO-Cox analysis to establish predicted TEX features. External validation was conducted in GSE31210 and GSE30219 cohorts. Immunotherapeutic response was assessed in IMvigor210, GSE78220, GSE35640 and GSE100797 cohorts. Furthermore, we investigated differences in mutational profiles and immune microenvironment between various risk groups. We then screened TEXRS key regulatory genes using ROC diagnostic curves and KM survival curves. Finally, we verified the differential expression of key regulatory genes through RT-qPCR. Results: Nine TEX genes were identified as highly predictive of LUAD prognosis and strongly correlated with disease outcome. Univariate and multivariate analysis revealed that patients in the low-risk group had significantly better overall survival rates compared with those in the high-risk group, highlighting the model's ability to independently predict LUAD prognosis. Our analysis revealed significant variation in the biological function, mutational landscape, and immune cell infiltration within the tumor microenvironment of both high-risk and low-risk groups. Additionally, immunotherapy was found to have a significant impact on both groups, indicating strong predictive efficacy of the model. Conclusions: The TEX model showed good predictive performance and provided a new perspective for evaluating the efficacy of preimmunization, which provides a new strategy for the future treatment of lung adenocarcinoma.

Clinical relevance of exosome-derived microRNAs in Ovarian Cancer: Looking for new tumor biological fingerprints

Specific tumor-derived extracellular vesicles, called exosomes, are considered as potential key players in cross-talk between immune system and tumor microenvironment in several solid tumors. Different studies highlighted the clinical relevance of exosomes in ovarian cancer (OC) for their role in early diagnosis, prognosis, chemoresistance, targeted therapy. The exosomes are nanosize vesicles carrying lipids, proteins, and nucleic acids. In particular, exosomes shuttle a wide spectrum of microRNAs (miRNAs) able to induce phenotypic reprogramming of target cells, contributing to tumor progression. In this review, we will discuss the promising role of miRNAs shuttled by exosomes, called exosomal miRNAs (exo-miRNAs), as potential biomarkers for early detection, tumour progression and metastasis, prognosis, and response to therapy in OC women, in order to search for new potential biological fingerprints able to better characterize the evolution of this malignancy and provide a clinically relevant non-invasive approach useful for adopting, in future, personalized therapeutic strategies.

Blood-Derived Exosomal hTERT mRNA in Patients with Lung Cancer: Characterization and Correlation with Response to Therapy

Background: Telomerase (human telomerase reverse transcriptase (hTERT) is considered a hallmark of cancer, being active in cancer cells but repressed in human somatic cells. As such, it has the potential to serve as a valid cancer biomarker. Exosomal hTERT mRNA can be detected in the serum of patients with solid malignancies but not in healthy individuals. We sought to evaluate the feasibility of measuring serum exosomal hTERT transcripts levels in patients with lung cancer. Methods: A prospective analysis of exosomal hTERT mRNA levels was determined in serum-derived exosomes from 76 patients with stage III-IV lung cancer (11 SCLC and 65 NSCLC). An hTERT level above RQ = 1.2 was considered "detectable" according to a previous receiver operating characteristic curve (ROC) curve. Sequential measurements were obtained in 33 patients. Demographic and clinical data were collected retrospectively from patients' charts. Data on response to systemic therapy (chemotherapy, immunotherapy, and tyrosine kinase inhibitors) were collected by the treating physicians. Results: hTERT was detected in 53% (40/76) of patients with lung cancer (89% of SCLC and 46% of NSLCC). The mean hTERT levels were 3.7 in all 76 patients, 5.87 in SCLC patients, and 3.62 in NSCLC patients. In total, 25 of 43 patients with sequential measurements had detectable levels of hTERT. The sequential exosomal hTERT mRNA levels reflected the clinical course in 23 of them. Decreases in hTERT levels were detected in 17 and 5 patients with partial and complete response, respectively. Eleven patients with a progressive disease had an increase in the level of exosomal hTERT, and seven with stable disease presented increases in its exosomal levels. Another patient who progressed on the first line of treatment and had a partial response to the second line of treatment exhibited an increase in exosomal hTERT mRNA levels during the progression and a decrease during the response. Conclusions: Exosomal hTERT mRNA levels are elevated in over half of patients with lung cancer. The potential association between hTERT levels and response to therapy suggests its utility as a promising cancer biomarker for response to therapy. This issue should be further explored in future studies.

T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing

Background

Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients.

Methods

The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR.

Result

11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong.

Conclusion

TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.

Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma

Background

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults and is highly metastatic, resulting in a poor patient prognosis. Sphingolipid metabolism plays an important role in tumor development, diagnosis, and prognosis. This study aimed to establish a reliable signature based on sphingolipid metabolism genes (SMGs), thus providing a new perspective for assessing immunotherapy response and prognosis in patients with UVM.

Methods

In this study, SMGs were used to classify UVM from the TCGA-UVM and GEO cohorts. Genes significantly associated with prognosis in UVM patients were screened using univariate cox regression analysis. The most significantly characterized genes were obtained by machine learning, and 4-SMGs prognosis signature was constructed by stepwise multifactorial cox. External validation was performed in the GSE84976 cohort. The level of immune infiltration of 4-SMGs in high- and low-risk patients was analyzed by platforms such as CIBERSORT. The prediction of 4-SMGs on immunotherapy and immune checkpoint blockade (ICB) response in UVM patients was assessed by ImmuCellAI and TIP portals.

Results

4-SMGs were considered to be strongly associated with the prognosis of UVM and were good predictors of UVM prognosis. Multivariate analysis found that the model was an independent predictor of UVM, with patients in the low-risk group having higher overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores had good prognostic power. The high-risk group showed better results when receiving immunotherapy.

Conclusions

4-SMGs signature and nomogram showed excellent predictive performance and provided a new perspective for assessing pre-immune efficacy, which will facilitate future precision immuno-oncology studies.

Extracellular Vesicle-Derived Protein File from Peripheral Blood Predicts Immune-Related Adverse Events in Gastric Cancer Patients Receiving Immunotherapy

Simple Summary

Most gastric cancer (GC) patients have already benefited from immune checkpoint inhibitors, but some of them may terminate immunotherapy due to immune-related adverse events (irAEs). Extracellular vesicles have been shown to carry proteins, nucleic acids and other biomacromolecules to recipient cells, which is very important for exploring the potential of biomarkers of irAEs via EV-derived proteins. In 62 GC patients, EV-ICOS and EV-IDO1 were screened from 42 vital proteins as biomarkers of irAEs, and then confirmed in a validating cohort of 40 GC patients. In summary, EV-ICOS and EV-IDO1 can perfectly predict irAEs of ICI treated GC patients.

Abstract

Immune checkpoint inhibitors (ICIs) initiate a new stage for gastric cancer (GC) therapeutics, and plenty of patients have already benefited from ICIs. Liquid biopsy promotes the development of precision medicine of GC. However, due to the lack of precision biomarkers of immune-related adverse events (irAEs), the safety of ICIs-treated GC patients cannot be guaranteed. In our study, GC patients treated with ICIs were included for investigating the correlation between irAEs of ICIs and corresponding outcomes. We also explored the potential of biomarkers of irAEs via EV-derived proteins. Dynamic plasma was taken from 102 ICIs-treated GC patients generated retrospectively or prospectively, who were divided into discovery and validating cohorts. Plasma EV-derived protein profiles were described, and two EV-proteins, inducible T-cell co-stimulator (EV-ICOS) and indoleamine 2,3-dioxygenase 1(EV-IDO1), from 42 vital proteins were screened to predict the prognosis of ICIs with irAEs. Our work is the first to propose that EV-proteins can predict ICIs-corresponding irAEs, which can be conducive to the diagnosis and treatment of GC patients, and to facilitate the screening of beneficiaries.

Exosomal Proteins and Lipids as Potential Biomarkers for Lung Cancer Diagnosis, Prognosis, and Treatment

Simple Summary

Exosomes (or extracellular vesicles) are known to mediate intercellular communication and to transmit molecular signals between cells. Molecules carried by exosomes have their own molecular roles in affecting surrounding and distant environment, as well as recipient cells. Molecular components of exosomes can be used as cancer biomarkers for diagnosis and prognosis, being promising therapeutic targets for the interruption of cellular signals. Therefore, the understanding of the molecular compositions and their functional indications of exosomes has the potential to help doctors to diagnose and monitor diseases and to allow researchers to design and develop potential targeted therapies. This review aims to provide a comprehensive protein and lipid characterization of lung cancer exosomes and to explore their molecular functions and mechanisms regulating physiological and pathological processes. This organization offers informative insight for lung cancer diagnosis and treatment.

Abstract

Exosomes participate in cell–cell communication by transferring molecular components between cells. Previous studies have shown that exosomal molecules derived from cancer cells and liquid biopsies can serve as biomarkers for cancer diagnosis and prognosis. The exploration of the molecules transferred by lung cancer-derived exosomes can advance the understanding of exosome-mediated signaling pathways and mechanisms. However, the molecular characterization and functional indications of exosomal proteins and lipids have not been comprehensively organized. This review thoroughly collected data concerning exosomal proteins and lipids from various lung cancer samples, including cancer cell lines and cancer patients. As potential diagnostic and prognostic biomarkers, exosomal proteins and lipids are available for clinical use in lung cancer. Potential therapeutic targets are mentioned for the future development of lung cancer therapy. Molecular functions implying their possible roles in exosome-mediated signaling are also discussed. Finally, we emphasized the importance and value of lung cancer stem cell-derived exosomes in lung cancer therapy. In summary, this review presents a comprehensive description of the protein and lipid composition and function of lung cancer-derived exosomes for lung cancer diagnosis, prognosis, and treatment.