Comparative gene expression analysis in melanocytes driven by tumor cell-derived exosomes

Data-driven energy landscape reveals critical genes in cancer progression

The evolution of cancer is a complex process characterized by stable states and transitions among them. Studying the dynamic evolution of cancer and revealing the mechanisms of cancer progression based on experimental data is an important topic. In this study, we aim to employ a data-driven energy landscape approach to analyze the dynamic evolution of cancer. We take Kidney renal clear cell carcinoma (KIRC) as an example. From the energy landscape, we introduce two quantitative indicators (transition probability and barrier height) to study critical shifts in KIRC cancer evolution, including cancer onset and progression, and identify critical genes involved in these transitions. Our results successfully identify crucial genes that either promote or inhibit these transition processes in KIRC. We also conduct a comprehensive biological function analysis on these genes, validating the accuracy and reliability of our predictions. This work has implications for discovering new biomarkers, drug targets, and cancer treatment strategies in KIRC.

Tumor cells-derived extracellular vesicles carry circ_0064516 competitively inhibit microRNA-6805-3p and promote cervical cancer angiogenesis and tumor growth

BACKGROUND

The current study tried to elucidate the regulatory role of tumor cell-derived exosomes (Exos)-circ_0064516 in angiogenesis and growth of cervical cancer.

RESEARCH DESIGN AND METHODS

Related cirRNAs and downstream target genes were identified through bioinformatics analysis. Exos were isolated from cervical cancer cell line CaSki, followed by co-cultured with human umbilical vein endothelial cells (HUVECs). Then, the roles of circ_0064516, miR-6805-3p, and MAPK1 in migration and angiogenesis of HUVECs were assayed. Furthermore, xenografted tumors were transplanted into nude mice for in vivo validation.

RESULTS

In vitro assay validated highly expressed circ_0064516 in cervical cancer cells. Tumor cell-derived Exos carried circ_0064516 to HUVECs. circ_0064516 increased MAPK1 expression by binding to miR-6805-3p, thus enhancing migration and angiogenesis. Exos containing circ_0064516 also promoted tumorigenesis of cervical cancer cells in nude mice.

CONCLUSIONS

We confirmed the oncogenic role of tumor cell-derived Exos carrying circ_0064516 in cervical cancer progression through miR-6805-3p/MAPK1.

PSMA1 mediates tumor progression and poor prognosis of gastric carcinoma by deubiquitinating and stabilizing TAZ

The deubiquitinating enzyme family in tumor progression play important role in intracellular protein degradation. The proteasome subunit alpha type 1 (PSMA1) has been reported to act as an oncogene in several human cancers. The present study aimed to reveal the functional significance of PSMA1 in gastric cancer (GC) progression and the underlying mechanisms. The expression of PSMA1 in human GC samples and GC cell lines was examined by western blot analysis, real-time PCR, immunohistochemistry (IHC), and in vitro ubiquitination assays and established a xenograft mouse model. We found that PSMA1 was upregulated in GC and promoted proliferation, migration and invasion in GC cells. Herein, we report transcriptional co-activator with PDZ-binding motif (TAZ) was a downstream gene of PSMA1. Mechanistically, PSMA1 directly interacted with and stabilized TAZ via deubiquitination in GC. Furthermore, we found that TAZ was the essential mediator of PSMA1-modulated oncogenic activity in vitro and in vivo. Examination of clinical samples confirmed that elevated mediators of PSMA1, concomitant with increased TAZ abundance, correlate with human GC progression. These data suggested that PSMA1 promotes GC progression and proliferation by deubiquitinating TAZ. PSMA1 promotes GC progression and proliferation regarding PSMA1-mediated deubiquitinating enzyme activity and suggest potential therapeutic targets for GC management.

Role of exosomes in skin diseases

BACKGROUND

Exosomes, as a family member of extracellular vesicles, are cell-secreted nanoscale structures that play pivotal roles in regulating physiological and pathophysiological processes of the skin. Exosomes induce communication between cells and are responsible for transporting cellular components such as microRNAs, mRNAs, DNA, lipids, metabolites, and cell-surface proteins. Numerous preclinical and clinical trials searched the contribution of exosomes to skin functions and disorders. Thus, exosomes are gaining increasing attention within investigational dermatology. In advance, stem-cell-derived exosomes were integrated into the functional cosmetics industry nominated as cell-free regenerative medicine.

OBJECTIVE

This review aims to demonstrate the roles of exosomes in inflammatory skin disorders, stem cell, and tumor biology through a comprehensive evaluation of the diagnostic, prognostic, and therapeutic perspectives.

METHODS

A comprehensive literature search was performed using electronic online databases "PubMed" and "Google Scholar" using key words ''exosomes'', ''skin'', ''wound healing''.

CONCLUSION

Exosomes are regarded as promising diagnostic and prognostic biomarkers for various skin diseases. Future prospects are repurposing exosomes to treat skin disorders, either as drug carriers or drugs themselves.

Identifying the critical states and dynamic network biomarkers of cancers based on network entropy

Background

There are sudden deterioration phenomena during the progression of many complex diseases, including most cancers; that is, the biological system may go through a critical transition from one stable state (the normal state) to another (the disease state). It is of great importance to predict this critical transition or the so-called pre-disease state so that patients can receive appropriate and timely medical care. In practice, however, this critical transition is usually difficult to identify due to the high nonlinearity and complexity of biological systems.

Methods

In this study, we employed a model-free computational method, local network entropy (LNE), to identify the critical transition/pre-disease states of complex diseases. From a network perspective, this method effectively explores the key associations among biomolecules and captures their dynamic abnormalities.

Results

Based on LNE, the pre-disease states of ten cancers were successfully detected. Two types of new prognostic biomarkers, optimistic LNE (O-LNE) and pessimistic LNE (P-LNE) biomarkers, were identified, enabling identification of the pre-disease state and evaluation of prognosis. In addition, LNE helps to find “dark genes” with nondifferential gene expression but differential LNE values.

Conclusions

The proposed method effectively identified the critical transition states of complex diseases at the single-sample level. Our study not only identified the critical transition states of ten cancers but also provides two types of new prognostic biomarkers, O-LNE and P-LNE biomarkers, for further practical application. The method in this study therefore has great potential in personalized disease diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03445-0.

Multi-Omics Data Integration in Extracellular Vesicle Biology-Utopia or Future Reality?

Extracellular vesicles (EVs) are membranous structures derived from the endosomal system or generated by plasma membrane shedding. Due to their composition of DNA, RNA, proteins, and lipids, EVs have garnered a lot of attention as an essential mechanism of cell-to-cell communication, with various implications in physiological and pathological processes. EVs are not only a highly heterogeneous population by means of size and biogenesis, but they are also a source of diverse, functionally rich biomolecules. Recent advances in high-throughput processing of biological samples have facilitated the development of databases comprised of characteristic genomic, transcriptomic, proteomic, metabolomic, and lipidomic profiles for EV cargo. Despite the in-depth approach used to map functional molecules in EV-mediated cellular cross-talk, few integrative methods have been applied to analyze the molecular interplay in these targeted delivery systems. New perspectives arise from the field of systems biology, where accounting for heterogeneity may lead to finding patterns in an apparently random pool of data. In this review, we map the biological and methodological causes of heterogeneity in EV multi-omics data and present current applications or possible statistical methods for integrating such data while keeping track of the current bottlenecks in the field.

Proteomic Profiling of Serum Exosomes From Patients With Metastatic Gastric Cancer

Background: Clinical management of metastatic gastric cancer (mGC) remains a major challenge due to a lack of specific biomarkers and effective therapeutic targets. Recently, accumulating evidence has suggested that exosomes play an essential role in cancer metastasis and can be an excellent reservoir of novel biomarkers and candidate therapeutic targets for cancer. Therefore, in this study, we aimed to reveal the proteomic profile of mGC-derived exosomes. Methods: Exosomes were isolated from pooled serum samples of 20 mGC patients and 40 healthy controls (HC) by ultracentrifugation. Next, quantitative proteomic analyses were applied to analyze the protein profiles of the exosomes, and bioinformatic analyses were conducted on the proteomic data. Finally, the expression of exosomal protein candidates was selectively validated in individual subjects by western blot analysis. Results: We isolated exosomes from serum samples. The size of the serum derived exosomes ranged from 30 to 150 nm in diameter. The exosomal markers CD9 and CD81 were observed in the serum exosomes. However, the exosomal negative marker calnexin, an endoplasmic reticulum protein, was not detected in exosomes. Overall, 443 exosomal proteins, including 110 differentially expressed proteins (DEPs) were identified by quantitative proteomics analyses. The bioinformatics analyses indicated that the upregulated proteins were enriched in the process of protein metabolic, whereas the downregulated proteins were largely involved in cell-cell adhesion organization. Surprisingly, 10 highly vital proteins (UBA52, PSMA1, PSMA5, PSMB6, PSMA7, PSMA4, PSMA3, PSMB1, PSMA6, and FGA) were filtered from DEPs, most of which are proteasome subunits. Moreover, the validation data confirmed that PSMA3 and PSMA6 were explicitly enriched in the serum derived exosomes from patients with mGC. Conclusion: The present study provided a comprehensive description of the serum exosome proteome of mGC patients, which could be an excellent resource for further studies of mGC.