FGB and FGG derived from plasma exosomes as potential biomarkers to distinguish benign from malignant pulmonary nodules

Diagnostic and prognostic value of circulating exosomal glypican-1 in pancreatic cancer: a meta-analysis

BACKGROUND

Pancreatic cancer (PC) is usually detected in the advanced stages. Liquid biopsy has become a revolutionary strategy for cancer diagnosis and prognosis prediction. This study aims to investigate the diagnostic and prognostic value of circulating exosomal glypican-1 (GPC-1) in PC.

METHODS

We systematically searched relevant studies. For diagnostic accuracy, pooled sensitivity and specificity and the area under the summary receiver operating characteristic curve (AUC) were calculated. Regarding prognostic value, hazard ratios (HRs) and 95% CIs for overall survival (OS) were summarized by using a random-effects model.

RESULTS

We found 8 studies that examined the diagnostic value of circulating exosomal GPC-1 in PC, and 3 studies that investigated its prognostic value. Pooled sensitivity and specificity were 0.88 (95% CI, 0.65-0.97) and 0.86 (95% CI, 0.72-0.94). The AUC was 0.93 (95% CI, 0.90-0.95). Prognostic analysis showed that higher levels of circulating exosomal GPC-1 were associated with poorer OS in PC patients, and the combined HR for OS was 4.59 (random-effects model, 95% CI = 1.17-18.03, P = .022). The results of both studies were robust and neither had publication bias.

CONCLUSION

Circulating exosomal GPC-1 may be used as a diagnostic and prognostic biomarker for PC. However, this result needs to be validated by further research using a larger sample size.

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.

Circ_16601 facilitates Hippo pathway signaling via the miR-5580-5p/FGB axis to promote my-CAF recruitment in the TME and LUAD progression

BACKGROUND

Lung cancer represents a significant public health issue in China, given its high incidence and mortality rates. Circular RNAs (circRNAs) have been recently proposed to participate in the development and progression of tumors. Nevertheless, their particular roles in the pathogenesis of lung adenocarcinoma (LUAD), the tumor microenvironment (TME), and the underlying molecular mechanisms are still not well understood.

METHODS

High-throughput sequencing was used to analyze the circRNAs expression profiles in 7 pairs of human LUAD tissues. shRNA was used to knockdown the YAP1 and FGB genes. RNA sequencing and RT-qPCR were performed to classify the regulatory effects of circ_16601 in LUAD cells. The progression effect of circ_16601 on lung cancer was investigated in vitro and in vivo.

RESULTS

The circ_16601 is significantly elevated in LUAD tissues compared to adjacent normal lung tissues, and its high expression is positively associated with poor prognosis in LUAD patients. Additionally, circ_16601 overexpression promotes LUAD cell proliferation in vitro and increases xenograft tissue growth in mice in vivo; circ_16601 also could recruit fibroblasts to cancer associate fibroblasts. Mechanistically, circ_16601 can directly bind to miR-5580-5p, preventing its ability to degrade FGB mRNA and enhancing its stability. Subsequently, circ_16601 promotes the activation of the Hippo pathway in a YAP1-dependent manner, leading to LUAD progression.

CONCLUSIONS

Our findings shed valuable insights into the regulatory role of circ_16601 in LUAD progression and highlight its potential as a diagnostic and therapeutic target in LUAD. Overall, this study provides theoretical support to improve the prognosis and quality of life of patients suffering from this devastating disease.

Development and validation of a risk model with variables related to non-small cell lung cancer in patients with pulmonary nodules: a retrospective study

BACKGROUND

Lung cancer is a major global threat to public health for which a novel predictive nomogram is urgently needed. Non-small cell lung cancer (NSCLC) which accounts for the main port of lung cancer cases is attracting more and more people's attention.

PATIENTS AND METHODS

Here, we designed a novel predictive nomogram using a design dataset consisting of 515 pulmonary nodules, with external validation being performed using a separate dataset consisting of 140 nodules and a separate dataset consisting of 237 nodules. The selection of significant variables for inclusion in this model was achieved using a least absolute shrinkage and selection operator (LASSO) logistic regression model, after which a corresponding nomogram was developed. C-index values, calibration plots, and decision curve analyses were used to gauge the discrimination, calibration, and clinical utility, respectively, of this predictive model. Validation was then performed with the internal bootstrapping validation and external cohorts.

RESULTS

A predictive nomogram was successfully constructed incorporating hypertension status, plasma fibrinogen levels, blood urea nitrogen (BUN), density, ground-glass opacity (GGO), and pulmonary nodule size as significant variables associated with nodule status. This model exhibited good discriminative ability, with a C-index value of 0.765 (95% CI: 0.722-0.808), and was well-calibrated. In validation analyses, this model yielded C-index values of 0.892 (95% CI: 0.844-0.940) for external cohort and 0.853 (95% CI: 0.807-0.899) for external cohort 2. In the internal bootstrapping validation, C-index value could still reach 0.753. Decision curve analyses supported the clinical value of this predictive nomogram when used at a NSCLC possibility threshold of 18%.

CONCLUSION

The nomogram constructed in this study, which incorporates hypertension status, plasma fibrinogen levels, BUN, density, GGO status, and pulmonary nodule size, was able to reliably predict NSCLC risk in this Chinese cohort of patients presenting with pulmonary nodules.

Characterization of platelet-related genes and constructing signature combined with immune-related genes for predicting outcomes and immunotherapy response in lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is a highly malignant subtype of non-small cell lung cancer with poor prognosis. Platelets are known to play a critical role in cancer development and progression, and recent studies suggest that they can also regulate immune response in tumors. However, the relationship between platelet-related genes (PRGs) and LUSC prognosis and tumor microenvironments remains unclear. In this study, we used multiple bioinformatics algorithms to identify 25 dysregulated PRGs that were significantly associated with LUSC prognosis. We found that PRGs were involved in multiple biological processes, particularly in the tumor microenvironment, and that platelet-related scores (PRS) were a risk factor. Additionally, we established a 6-gene prognostic signature combining PRGs and immune-related genes that accurately predicted outcomes and immunotherapy efficacy in LUSC patients. Our study provides a comprehensive analysis of the biological functions and potential therapeutic targets of PRGs in LUSC, which may inform the development of new treatments for this disease.

The Roles of Exosomal Proteins: Classification, Function, and Applications

Exosome, a subpopulation of extracellular vesicles, plays diverse roles in various biological processes. As one of the most abundant components of exosomes, exosomal proteins have been revealed to participate in the development of many diseases, such as carcinoma, sarcoma, melanoma, neurological disorders, immune responses, cardiovascular diseases, and infection. Thus, understanding the functions and mechanisms of exosomal proteins potentially assists clinical diagnosis and targeted delivery of therapies. However, current knowledge about the function and application of exosomal proteins is still limited. In this review, we summarize the classification of exosomal proteins, and the roles of exosomal proteins in exosome biogenesis and disease development, as well as in the clinical applications.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

miR-877-5p Inhibits Epithelial Mesenchymal Transformation of Breast Cancer Cells by Targeting FGB

PURPOSE

This present study is aimed at exploring the FGB expression in breast cancer (BC) and the role of FGB in BC.

METHODS

A total of 150 pairs of BC tissues and adjacent tissues from BC surgery patients were collected. RT-qPCR was utilized to evaluate the mRNA expression of FGB and miR-877-5p. Immunohistochemistry was applied to evaluate the protein expression of FGB. Chi-square test was performed to evaluate the relationship between FGB expression level and clinical characteristics. Cell proliferation was examined using CCK-8 assay. Cell invasion was evaluated by transwell assay. Flow cytometry assay was applied to measure cell apoptosis. The protein expression was evaluated by western blot. BALB/C nude mice were used to establish the xenograft tumor model.

RESULTS

FGB was more highly expressed in BC tumor, and the expression of FGB was relevant to TNM stage and lymph node metastasis and showed a positive correlation. FGB was proved to be directly regulated via miR-877-5p and enhanced proliferation and invasion of BC cells. FGB downregulation markedly inhibited the tumor growth, including tumor weight and volume. In addition, the Ki-67 expression was observably declined in the sh-FGB group. The protein expression of E-cadherin was markedly raised in the sh-FGB group while the protein expression of N-cadherin and vimentin was markedly declined in the sh-FGB group.

CONCLUSION

In conclusion, miR-877-5p inhibits epithelial mesenchymal transformation, cell proliferation, and invasion of BC cells via downregulating FGB.

Integrated Pipeline of Rapid Isolation and Analysis of Human Plasma Exosomes for Cancer Discrimination Based on Deep Learning of MALDI-TOF MS Fingerprints

Plasma exosomes have shown great potential for liquid biopsy in clinical cancer diagnosis. Herein, we present an integrated strategy for isolating and analyzing exosomes from human plasma rapidly and then discriminating different cancers excellently based on deep learning fingerprints of plasma exosomes. Sequential size-exclusion chromatography (SSEC) was developed efficiently for separating exosomes from human plasma. SSEC isolated plasma exosomes, taking as less as 2 h for a single sample with high purity such that the discard rates of high-density lipoproteins and low/very low-density lipoproteins were 93 and 85%, respectively. Benefitting from the rapid and high-purity isolation, the contents encapsulated in exosomes, covered by plasma proteins, were well profiled by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS). We further analyzed 220 clinical samples, including 79 breast cancer patients, 57 pancreatic cancer patients, and 84 healthy controls. After MS data pre-processing and feature selection, the extracted MS feature peaks were utilized as inputs for constructing a multi-classifier artificial neural network (denoted as Exo-ANN) model. The optimized model avoided overfitting and performed well in both training cohorts and test cohorts. For the samples in the independent test cohort, it realized a diagnosed accuracy of 80.0% with an area under the curve of 0.91 for the whole group. These results suggest that our integrated pipeline may become a generic tool for liquid biopsy based on the analysis of plasma exosomes in clinics.

Proteomic profiling reveals a distinctive molecular signature for critically ill COVID-19 patients compared with asthma and COPD: A distinctive molecular signature for critically ill COVID-19 patients

Objective

The mortality rate for critically ill COVID-19 cases was more than 80%. Nonetheless, research about the effect of common respiratory diseases on critically ill COVID-19 expression and outcomes is scarce.

Design

We performed proteomic analyses on airway mucus obtained by bronchoscopy from patients with severe COVID-19, or induced sputum from patients with chronic obstructive pulmonary disease (COPD), asthma, and healthy controls.

Results

Of the total identified and quantified proteins, 445 differentially expressed proteins (DEPs) were found in different comparison groups. In comparison with COPD, asthma, and controls, 11 proteins were uniquely present in COVID-19 patients. Apart from DEPs associated with COPD versus controls and asthma versus controls, there was a total of 59 DEPs specific to COVID-19 patients. Finally, the findings revealed that there were 8 overlapping proteins in COVID-19 patients, including C9, FGB, FGG, PRTN3, HBB, HBA1, IGLV3-19, and COTL1. Functional analyses revealed that most of them were associated with complement and coagulation cascades, platelet activation, or iron metabolism, and anemia-related pathways.

Conclusions

This study provides fundamental data for identifying COVID-19–specific proteomic changes in comparison with COPD and asthma, which may suggest molecular targets for specialized therapy.

Combination of CT and telomerase+ circulating tumor cells improves diagnosis of small pulmonary nodules

BACKGROUND

Early diagnosis and treatment are key to the long-term survival of lung cancer patients. Although CT has significantly contributed to the early diagnosis of lung cancer, there are still consequences of excessive or delayed treatment. By improving the sensitivity and specificity of circulating tumor cell (CTC) detection, a solution was proposed for differentiating benign from malignant pulmonary nodules.

METHODS

In this study, we used telomerase reverse transcriptase–based (TERT-based) CTC detection (TBCD) to distinguish benign from malignant pulmonary nodules < 2 cm and compared this method with the pathological diagnosis as the gold standard. FlowSight and FISH were used to confirm the CTCs detected by TBCD.

RESULTS

Our results suggest that CTCs based on TBCD can be used as independent biomarkers to distinguish benign from malignant nodules and are significantly superior to serum tumor markers. When the detection threshold was 1, the detection sensitivity and specificity of CTC diagnosis were 0.854 and 0.839, respectively. For pulmonary nodules ≤ 1 cm and 1–2 cm, the sensitivity and specificity of CTCs were both higher than 77%. Additionally, the diagnostic ability of CTC-assisted CT was compared by CT detection. The results show that CT combined with CTCs could significantly improve the differentiation ability of benign and malignant nodules in lung nodules < 2 cm and that the sensitivity and specificity could reach 0.899 and 0.839, respectively.

CONCLUSION

TBCD can effectively diagnose pulmonary nodules and be used as an effective auxiliary diagnostic scheme for CT diagnosis.

FUNDING

National Key Research and Development Project grant nos. 2019YFC1315700 and 2017YFC1308702, CAMS Initiative for Innovative Medicine grant no. 2017-I2M-1-005, and National Natural Science Foundation of China grant no. 81472013.

Isolation and characterization of extracellular vesicles for clinical applications in cancer - time for standardization?

Extracellular vesicles (EVs) are nanometer sized lipid enclosed particles released by all cell types into the extracellular space and biological fluids in vivo, and into cell culture media in vitro. An important physiological role of EVs is cell-cell communication. EVs interact with, and deliver, their contents to recipient cells in a functional capacity; this makes EVs desirable vehicles for the delivery of therapeutic cargoes. In addition, as EVs contain proteins, lipids, glycans, and nucleic acids that reflect their cell of origin, their potential utility in disease diagnosis and prognostication is of great interest. The number of published studies analyzing EVs and their contents in the pre-clinical and clinical setting is rapidly expanding. However, there is little standardization as to what techniques should be used to isolate, purify and characterize EVs. Here we provide a comprehensive literature review encompassing the use of EVs as diagnostic and prognostic biomarkers in cancer. We also detail their use as therapeutic delivery vehicles to treat cancer in pre-clinical and clinical settings and assess the EV isolation and characterization strategies currently being employed. Our report details diverse isolation strategies which are often dependent upon multiple factors such as biofluid type, sample volume, and desired purity of EVs. As isolation strategies vary greatly between studies, thorough EV characterization would be of great importance. However, to date, EV characterization in pre-clinical and clinical studies is not consistently or routinely adhered to. Standardization of EV characterization so that all studies image EVs, quantitate protein concentration, identify the presence of EV protein markers and contaminants, and measure EV particle size and concentration is suggested. Additionally, the use of RNase, DNase and protease EV membrane protection control experiments is recommended to ensure that the cargo being investigated is truly EV associated. Overall, diverse methodology for EV isolation is advantageous as it can support different sample types and volumes. Nevertheless, EV characterization is crucial and should be performed in a rigorous manor.

Exosomes from COVID-19 Patients Carry Tenascin-C and Fibrinogen-β in Triggering Inflammatory Signals in Cells of Distant Organ

SARS-CoV-2 infection can cause cytokine storm and may overshoot immunity in humans; however, it remains to be determined whether virus-induced soluble mediators from infected cells are carried by exosomes as vehicles to distant organs and cause tissue damage in COVID-19 patients. We took an unbiased proteomic approach for analyses of exosomes isolated from plasma of healthy volunteers and COVID-19 patients. Our results revealed that tenascin-C (TNC) and fibrinogen-β (FGB) are highly abundant in exosomes from COVID-19 patients’ plasma compared with that of healthy normal controls. Since TNC and FGB stimulate pro-inflammatory cytokines via the Nuclear factor-κB (NF-κB) pathway, we examined the status of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and C–C motif chemokine ligand 5 (CCL5) expression upon exposure of hepatocytes to exosomes from COVID-19 patients and observed significant increase compared with that from healthy subjects. Together, our results demonstrate that TNC and FGB are transported through plasma exosomes and potentially trigger pro-inflammatory cytokine signaling in cells of distant organ.

Exosomal miR-487a derived from m2 macrophage promotes the progression of gastric cancer

Tumor-associated macrophages contribute to cell growth, development, and metastasis in various cancers. However, the underlying mechanisms of M2 macrophage that modulate the progression of gastric cancer (GC) remain largely unknown. In this study, we detected the ratio of macrophages in GC tissues and found that the proportion of M2 macrophages was increased in GC tissues. We then co-cultured GC cells with M1 and M2 macrophages, respectively, and then assessed cell proliferation and tumorigenicity of GC cells by MTT and colony formation assay. The results indicated that M2 macrophages promoted the proliferation of GC cells, but M1 not. Besides, GW4869, an exosomes inhibitor, reduced the effects induced by M2 macrophage. Then, we isolated and identified exosomes derived from M1 and M2 macrophage, and confirmed that the exosomes could be taken up by GC cells. We demonstrated that M2 macrophage-exosomes could induce the proliferation and tumorigenesis in vitro and in vivo. Moreover, miR-487a was enriched in M2 macrophage-exosomes and further determined that miR-487a exert the functions by targeting TIA1. In conclusion, exosomal miR-487a derived from M2 macrophage promotes the proliferation and tumorigenesis in gastric cancer, and the novel findings might be helpful to the development of novel diagnostic and therapeutic methods in GC.

The proteomic characteristics of airway mucus from critical ill COVID-19 patients

Background

The pandemic of the coronavirus disease 2019 (COVID-19) has brought a global public health crisis. However, the pathogenesis underlying COVID-19 are barely understood.

Methods

In this study, we performed proteomic analyses of airway mucus obtained by bronchoscopy from severe COVID-19 patients. In total, 2351 and 2073 proteins were identified and quantified in COVID-19 patients and healthy controls, respectively.

Results

Among them, 92 differentiated expressed proteins (DEPs) (46 up-regulated and 46 down-regulated) were found with a fold change >1.5 or <0.67 and a p-value <0.05, and 375 proteins were uniquely present in airway mucus from COVID-19 patients. Pathway and network enrichment analyses revealed that the 92 DEPs were mostly associated with metabolic, complement and coagulation cascades, lysosome, and cholesterol metabolism pathways, and the 375 COVID-19 only proteins were mainly enriched in amino acid degradation (Valine, Leucine and Isoleucine degradation), amino acid metabolism (beta-Alanine, Tryptophan, Cysteine and Methionine metabolism), oxidative phosphorylation, phagosome, and cholesterol metabolism pathways.

Conclusions

This study aims to provide fundamental data for elucidating proteomic changes of COVID-19, which may implicate further investigation of molecular targets directing at specific therapy.

Top 100 most-cited articles on exosomes in the field of cancer: a bibliometric analysis and evidence mapping

Several studies have demonstrated that exosomes have a very broad prospect in the field of cancer therapy. This study aims to identify the general characteristics, cooperation of authors, countries and explore the hot topics of the top 100 cited articles on tumor-related exosomes. We searched the Web of Science Core Collection on June 28, 2019, to collect related publications. Microsoft Excel 2016 and VOSviewer 1.6.9 were applied to analyze the publication year, citations, authors, countries, institutions, journals, and keywords. The top 100 articles were published between 1998 and 2017 with citations ranging from 181 to 2275. Cancer Research (n = 9) had the highest number of publications. Nature Cell Biology, Nature, and Nature Medicine are considered to be the core journals of tumor-related exosomes because they are among top 10 from different analytical perspectives. The USA (n = 49) and Harvard University (n = 9) were the most productive country and institution, respectively. There were active collaborations between countries. Kalluri R (n = 6) contributed the largest number of articles, and Taylor DD was the most co-cited author. Théry C and Al-Nedawi K are probably the two important experts as they are both the top 10 authors and top 10 co-cited authors. Three clusters were obtained after clustering analysis of the keywords. The main hot topics were the proteomic analysis and mechanism of vesicle activation and the role of exosomes in the diagnosis and progression of tumors. Further research should expand and develop new topics such as the role of exosomes in the treatment of cancers.