ExoBCD: a comprehensive database for exosomal biomarker discovery in breast cancer

Current status and future perspectives of platelet-derived extracellular vesicles in cancer diagnosis and treatment

Platelets are a significant component of the cell population in the tumour microenvironment (TME). Platelets influence other immune cells and perform cross-talk with tumour cells, playing an important role in tumour development. Extracellular vesicles (EVs) are small membrane vesicles released from the cells into the TME. They can transfer biological information, including proteins, nucleic acids, and metabolites, from secretory cells to target receptor cells. This process affects the progression of various human diseases, particularly cancer. In recent years, several studies have demonstrated that platelet-derived extracellular vesicles (PEVs) can help regulate the malignant biological behaviours of tumours, including malignant proliferation, resistance to cell death, invasion and metastasis, metabolic reprogramming, immunity, and angiogenesis. Consequently, PEVs have been identified as key regulators of tumour progression. Therefore, targeting PEVs is a potential strategy for tumour treatment. Furthermore, the extensive use of nanomaterials in medical research has indicated that engineered PEVs are ideal delivery systems for therapeutic drugs. Recent studies have demonstrated that PEV engineering technologies play a pivotal role in the treatment of tumours by combining photothermal therapy, immunotherapy, and chemotherapy. In addition, aberrant changes in PEVs are closely associated with the clinicopathological features of patients with tumours, which may serve as liquid biopsy markers for early diagnosis, monitoring disease progression, and the prognostic assessment of patients with tumours. A comprehensive investigation into the role and potential mechanisms of PEVs in tumourigenesis may provide novel diagnostic biomarkers and potential therapeutic strategies for treating human tumours.

Exosomal lncRNAs as regulators of breast cancer chemoresistance and metastasis and their potential use as biomarkers

Breast cancer is the most common cancer in women and the leading cause of female deaths by cancer in the world worldwide. Hence, understanding the molecular mechanisms associated with breast cancer development and progression, including drug resistance and breast cancer metastasis, is essential for achieving the best management of breast cancer patients. Cancer-related long noncoding RNAs have been shown to be involved in the regulation of each stage of breast cancer progression. Additionally, exosomes are extracellular microvesicles that are central to intercellular communication and play an important role in tumorigenesis. Exosomes can be released from primary tumor cells into the bloodstream and transmit cellular signals to distant body sites. In this work, we review the findings regarding the cellular mechanisms regulated by exosomal lncRNAs that are essentials to chemoresistance development and metastasis of breast cancer. Likewise, we evaluate the outcomes of the potential clinical use of exosomal lncRNAs as breast cancer biomarkers to achieve personalized management of the patients. This finding highlights the importance of transcriptomic analysis of exosomal lncRNAs to understand the breast cancer tumorigenesis as well as to improve the clinical tests available for this disease.

Exosome theranostics: Comparative analysis of P body and exosome proteins and their mutations for clinical applications

Exosomes are lipid-bilayered vesicles, originating from early endosomes that capture cellular proteins and genetic materials to form multi-vesicular bodies. These exosomes are secreted into extracellular fluids such as cerebrospinal fluid, blood, urine, and cell culture supernatants. They play a key role in intercellular communication by carrying active molecules like lipids, cytokines, growth factors, metabolites, proteins, and RNAs. Recently, the potential of exosomal delivery for therapeutic purposes has been explored due to their low immunogenicity, nano-scale size, and ability to cross cellular barriers. This review comprehensively examines the biogenesis of exosomes, their isolation techniques, and their diverse applications in theranostics. We delve into the mechanisms and methods for loading exosomes with mRNA, miRNA, proteins, and drugs, highlighting their transformative role in delivering therapeutic payloads. Additionally, the utility of exosomes in stem cell therapy is discussed, showcasing their potential in regenerative medicine. Insights into exosome cargo using pre- or post-loading techniques are critical for exosome theranostics. We review exosome databases such as ExoCarta, Expedia, and ExoBCD, which document exosome cargo. From these databases, we identified 25 proteins common to both exosomes and P-bodies, known for mutations in the COSMIC database. Exosome databases do not integrate with mutation analysis programs; hence, we performed mutation analysis using additional databases. Accounting for the mutation status of parental cells and exosomal cargo is crucial in exosome theranostics. This review provides a comprehensive report on exosome databases, proteins common to exosomes and P-bodies, and their mutation analysis, along with the latest studies on exosome-engineered theranostics.

Extracellular Interactors of the IGF System: Impact on Cancer Hallmarks and Therapeutic Approaches

Dysregulation of the insulin-like growth factor (IGF) system determines the onset of various pathological conditions, including cancer. Accordingly, therapeutic strategies have been developed to block this system in tumor cells, but the results of clinical trials have been disappointing. After decades of research in the field, it is safe to say that one of the major reasons underlying the poor efficacy of anti-IGF-targeting agents is derived from an underestimation of the molecular complexity of this axis. Genetic, transcriptional, post-transcriptional and functional interactors interfere with the activity of canonical components of this axis, supporting the need for combinatorial approaches to effectively block this system. In addition, cancer cells interface with a multiplicity of factors from the extracellular compartment, which strongly affect cell destiny. In this review, we will cover novel extracellular mechanisms contributing to IGF system dysregulation and the implications of such dangerous liaisons for cancer hallmarks and responses to known and new anti-IGF drugs. A deeper understanding of both the intracellular and extracellular microenvironments might provide new impetus to better decipher the complexity of the IGF axis in cancer and provide new clues for designing novel therapeutic approaches.

Identification of exosome-related gene signature as a promising diagnostic and therapeutic tool for breast cancer

Background

Exosomes are promising tools for the development of new diagnostic and therapeutic approaches. Exosomes possess the ability to activate signaling pathways that contribute to the remodeling of the tumor microenvironment, angiogenesis, and the regulation of immune responses. We aimed to develop a prognostic score based on exosomes derived from breast cancer.

Materials and methods

Training was conducted on the TCGA-BRCA dataset, while validation was conducted on GSE20685, GSE5764, GSE7904, and GSE29431. A total of 121 genes related to exosomes were retrieved from the ExoBCD database. The Cox proportional hazards model is used to develop risk score model. The GSVA package was utilized to analyze single-sample gene sets and identify exosome signatures, while the WGCNA package was utilized to identify gene modules associated with clinical outcomes. The clusterProfiler and GSVA R packages facilitated gene set enrichment and variation analyses. Furthermore, CIBERSORT quantified immune infiltration, and a correlation between gene expression and drug sensitivity was assessed using the TIDE algorithm.

Results

An exosome-related prognostic score was established using the following selected genes: ABCC9, PIGR, CXCL13, DOK7, CD24, and IVL. Various immune cells that promote cancer immune evasion were associated with a high-risk prognostic score, which was an independent predictor of outcome. High-risk and low-risk groups exhibited significantly different infiltration abundances (p < 0.05). By conducting a sensitivity comparison, we found that patients with high-risk scores exhibited more favorable responses to immunotherapy than those with low-risk scores.

Conclusion

The exosome-related gene signature exhibits outstanding performance in predicting the prognosis and cancer status of patients with breast cancer and guiding immunotherapy.

VARIDT 3.0: the phenotypic and regulatory variability of drug transporter

The phenotypic and regulatory variability of drug transporter (DT) are vital for the understanding of drug responses, drug-drug interactions, multidrug resistances, and so on. The ADME property of a drug is collectively determined by multiple types of variability, such as: microbiota influence (MBI), transcriptional regulation (TSR), epigenetics regulation (EGR), exogenous modulation (EGM) and post-translational modification (PTM). However, no database has yet been available to comprehensively describe these valuable variabilities of DTs. In this study, a major update of VARIDT was therefore conducted, which gave 2072 MBIs, 10 610 TSRs, 46 748 EGRs, 12 209 EGMs and 10 255 PTMs. These variability data were closely related to the transportation of 585 approved and 301 clinical trial drugs for treating 572 diseases. Moreover, the majority of the DTs in this database were found with multiple variabilities, which allowed a collective consideration in determining the ADME properties of a drug. All in all, VARIDT 3.0 is expected to be a popular data repository that could become an essential complement to existing pharmaceutical databases, and is freely accessible without any login requirement at: https://idrblab.org/varidt/.

BioKA: a curated and integrated biomarker knowledgebase for animals

Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap in non-human animal disease understanding and breeding research. To address this limitation, we present BioKA (Biomarker Knowledgebase for Animals, https://ngdc.cncb.ac.cn/bioka), a curated and integrated knowledgebase encompassing multiple animal species, diseases/traits, and annotated resources. Currently, BioKA houses 16 296 biomarkers associated with 951 mapped diseases/traits across 31 species from 4747 references, including 11 925 gene/protein biomarkers, 1784 miRNA biomarkers, 1043 mutation biomarkers, 773 metabolic biomarkers, 357 circRNA biomarkers and 127 lncRNA biomarkers. Furthermore, BioKA integrates various annotations such as GOs, protein structures, protein-protein interaction networks, miRNA targets and so on, and constructs an interactive knowledge network of biomarkers including circRNA-miRNA-mRNA associations, lncRNA-miRNA associations and protein-protein associations, which is convenient for efficient data exploration. Moreover, BioKA provides detailed information on 308 breeds/strains of 13 species, and homologous annotations for 8784 biomarkers across 16 species, and offers three online application tools. The comprehensive knowledge provided by BioKA not only advances human disease research but also contributes to a deeper understanding of animal diseases and supports livestock breeding.

cfOmics: a cell-free multi-Omics database for diseases

Liquid biopsy has emerged as a promising non-invasive approach for detecting, monitoring diseases, and predicting their recurrence. However, the effective utilization of liquid biopsy data to identify reliable biomarkers for various cancers and other diseases requires further exploration. Here, we present cfOmics, a web-accessible database (https://cfomics.ncRNAlab.org/) that integrates comprehensive multi-omics liquid biopsy data, including cfDNA, cfRNA based on next-generation sequencing, and proteome, metabolome based on mass-spectrometry data. As the first multi-omics database in the field, cfOmics encompasses a total of 17 distinct data types and 13 specimen variations across 69 disease conditions, with a collection of 11345 samples. Moreover, cfOmics includes reported potential biomarkers for reference. To facilitate effective analysis and visualization of multi-omics data, cfOmics offers powerful functionalities to its users. These functionalities include browsing, profile visualization, the Integrative Genomic Viewer, and correlation analysis, all centered around genes, microbes, or end-motifs. The primary objective of cfOmics is to assist researchers in the field of liquid biopsy by providing comprehensive multi-omics data. This enables them to explore cell-free data and extract profound insights that can significantly impact disease diagnosis, treatment monitoring, and management.

TheMarker: a comprehensive database of therapeutic biomarkers

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

Effective exosomes in breast cancer: focusing on diagnosis and treatment of cancer progression

Breast cancer (BC) is the most prevalent aggressive malignant tumor in women worldwide and develops from breast tissue. Although cutting-edge treatment methods have been used and current mortality rates have decreased, BC control is still not satisfactory. Clarifying the underlying molecular mechanisms will help clinical options. Extracellular vesicles known as exosomes mediate cellular communication by delivering a variety of biomolecules, including proteins, oncogenes, oncomiRs, and even pharmacological substances. These transferable bioactive molecules can alter the transcriptome of target cells and affect signaling pathways that are related to tumors. Numerous studies have linked exosomes to BC biology, including therapeutic resistance and the local microenvironment. Exosomes' roles in tumor treatment resistance, invasion, and BC metastasis are the main topics of discussion in this review.

International Society for Extracellular Vesicles Workshop. QuantitatEVs: multiscale analyses, from bulk to single extracellular vesicle

The 'QuantitatEVs: multiscale analyses, from bulk to single vesicle' workshop aimed to discuss quantitative strategies and harmonized wet and computational approaches toward the comprehensive analysis of extracellular vesicles (EVs) from bulk to single vesicle analyses with a special focus on emerging technologies. The workshop covered the key issues in the quantitative analysis of different EV-associated molecular components and EV biophysical features, which are considered the core of EV-associated biomarker discovery and validation for their clinical translation. The in-person-only workshop was held in Trento, Italy, from January 31st to February 2nd, 2023, and continued in Milan on February 3rd with "Next Generation EVs", a satellite event dedicated to early career researchers (ECR). This report summarizes the main topics and outcomes of the workshop.

An Exosome-Related Long Non-coding RNA (lncRNA)-Based Signature for Prognosis and Therapeutic Interventions in Lung Adenocarcinoma

Background The poor prognosis of lung adenocarcinoma (LUAD) has been confirmed by a large number of studies, so it is necessary to construct a prognosis model. In addition, exosome is closely related to tumors, but there are few studies on exosome-related long non-coding RNA (lncRNA) (ExolncRNA). Methods In this study, we designed a prognostic model, exosome-related lncRNA-based signature (ExoLncSig), using ExolncRNA expression profiles of LUAD patients from The Cancer Genome Atlas (TCGA). ExolncRNAs were identified through univariate and multivariate and Lasso analyses. Subsequently, based on the ExoLncSig, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, immune function and immunotherapy analysis, drug screening, and so on were performed. Results AC026355.2, AC108136.1, AL590428.1, and LINC01312 were examined to establish the ExoLncSig. Gene enrichment analysis identified potential prognostic markers and therapeutic targets, including human leukocyte antigen (HLA), parainflammation, chemokine receptor (CCR), antigen-presenting cell (APC) co-inhibition, cancer-associated fibroblast (CAF), and myeloid-derived suppressor cell (MDSC). Moreover, we ascertained that the high-risk subgroup exhibits heightened susceptibility to pharmaceutical agents. Conclusion Our findings indicate that ExoLncSig holds promise as a valuable prognostic marker in LUAD. Furthermore, the immunogenic properties of ExolncRNAs may pave the way for the development of a therapeutic vaccine against LUAD.

Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients

Background

Glioblastoma (GBM) is a malignant primary brain tumor. This study focused on exploring the exosome-related features of glioblastoma to better understand its cellular composition and molecular characteristics.

Methods

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptome RNA sequencing (stRNA-seq) were used to analyze the heterogeneity of glioblastomas. After data integration, cell clustering, and annotation, five algorithms were used to calculate scores for exosome-related genes(ERGs). Cell trajectory analysis and intercellular communication analysis were performed to explore exosome-related communication patterns. Spatial transcriptome sequencing data were analyzed to validate the findings. To further utilize exosome-related features to aid in clinical decision-making, a prognostic model was constructed using GBM's bulk RNA-seq.

Results

Different cell subpopulations were observed in GBM, with Monocytes/macrophages and malignant cells in tumor samples showing higher exosome-related scores. After identifying differentially expressed ERGs in malignant cells, pseudotime analysis revealed the cellular status of malignant cells during development. Intercellular communication analysis highlighted signaling pathways and ligand-receptor interactions. Spatial transcriptome sequencing confirmed the high expression of exosome-related gene features in the tumor core region. A prognostic model based on six ERGs was shown to be predictive of overall survival and immunotherapy outcome in GBM patients. Finally, based on the results of scRNA-seq and prognostic modeling as well as a series of cell function experiments, BARD1 was identified as a novel target for the treatment of GBM.

Conclusion

This study provides a comprehensive understanding of the exosome-related features of GBM in both scRNA-seq and stRNA-seq, with malignant cells with higher exosome-related scores exhibiting stronger communication with Monocytes/macrophages. In terms of spatial data, highly scored malignant cells were also concentrated in the tumor core region. In bulk RNA-seq, patients with a high exosome-related index exhibited an immunosuppressive microenvironment, which was accompanied by a worse prognosis as well as immunotherapy outcomes. Prognostic models constructed using ERGs are expected to be independent prognostic indicators for GBM patients, with potential implications for personalized treatment strategies for GBM. Knockdown of BARD1 in GBM cell lines reduces the invasive and value-added capacity of tumor cells, and thus BARD1-positively expressing malignant cells are a risk factor for GBM patients.

Tumor-Derived Exosomes and Their Role in Breast Cancer Metastasis

Breast cancer has been the most common cancer in women worldwide, and metastasis is the leading cause of death from breast cancer. Even though the study of breast cancer metastasis has been extensively carried out, the molecular mechanism is still not fully understood, and diagnosis and prognosis need to be improved. Breast cancer metastasis is a complicated process involving multiple physiological changes, and lung, brain, bone and liver are the main metastatic targets. Exosomes are membrane-bound extracellular vesicles that contain secreted cellular constitutes. The biogenesis and functions of exosomes in cancer have been intensively studied, and mounting studies have indicated that exosomes play a crucial role in cancer metastasis. In this review, we summarize recent findings on the role of breast cancer-derived exosomes in metastasis organotropism and discuss the potential promising clinical applications of targeting exosomes as novel strategies for breast cancer diagnosis and therapy.

EV-ADD, a database for EV-associated DNA in human liquid biopsy samples

Extracellular vesicles (EVs) play a key role in cellular communication both in physiological conditions and in pathologies such as cancer. Emerging evidence has shown that EVs are active carriers of molecular cargo (e.g. protein and nucleic acids) and a powerful source of biomarkers and targets. While recent studies on EV‐associated DNA (EV‐DNA) in human biofluids have generated a large amount of data, there is currently no database that catalogues information on EV‐DNA. To fill this gap, we have manually curated a database of EV‐DNA data derived from human biofluids (liquid biopsy) and in‐vitro studies, called the Extracellular Vesicle‐Associated DNA Database (EV‐ADD). This database contains validated experimental details and data extracted from peer‐reviewed published literature. It can be easily queried to search for EV isolation methods and characterization, EV‐DNA isolation techniques, quality validation, DNA fragment size, volume of starting material, gene names and disease context. Currently, our database contains samples representing 23 diseases, with 13 different types of EV isolation techniques applied on eight different human biofluids (e.g. blood, saliva). In addition, EV‐ADD encompasses EV‐DNA data both representing the whole genome and specifically including oncogenes, such as KRAS, EGFR, BRAF, MYC, and mitochondrial DNA (mtDNA). An EV‐ADD data metric system was also integrated to assign a compliancy score to the MISEV guidelines based on experimental parameters reported in each study. While currently available databases document the presence of proteins, lipids, RNA and metabolites in EVs (e.g. Vesiclepedia, ExoCarta, ExoBCD, EVpedia, and EV‐TRACK), to the best of our knowledge, EV‐ADD is the first of its kind to compile all available EV‐DNA datasets derived from human biofluid samples. We believe that this database provides an important reference resource on EV‐DNA‐based liquid biopsy research, serving as a learning tool and to showcase the latest developments in the EV‐DNA field. EV‐ADD will be updated yearly as newly published EV‐DNA data becomes available and it is freely available at www.evdnadatabase.com.

Identification of stage-associated exosome miRNAs in colorectal cancer by improved robust and corroborative approach embedded miRNA-target network

Background

Colorectal cancer (CRC) is a common gastrointestinal tumor with high morbidity and mortality. At the molecular level, patients at different stages present considerable heterogeneity. Although the miRNA in exosome is an effective biomarker to reveal tumor progression, studies based on stage-associated exosome miRNA regulatory network analysis still lacking. This study aims to identify CRC stage-associated exosome miRNAs and reveal their potential function in tumor progression.

Methods

In this study, serum and cellular exosome miRNA expression microarrays associated with CRC were downloaded from GEO database. Stage-common (SC) and stage-specific (SS) differentially expressed miRNAs were extracted and their targets were identified based on 11 databases. Furthermore, miRNA SC and SS regulatory function networks were built based on the CRC phenotypic relevance of miRNA targets, and the corresponding transcription factors were identified. Concurrently, the potential stage-associated miRNAs were identified by receiver-operating characteristic (ROC) curve analysis, survival analysis, drug response analysis, ceRNA analysis, pathway analysis and a comprehensive investigation of 159 publications.

Results

Ten candidate stage-associated miRNAs were identified, with three SC (miR-146a-5p, miR-22-3p, miR-23b-3p) and seven SS (I: miR-301a-3p, miR-548i; IIIA: miR-23a-3p; IV: miR-194-3p, miR-33a-3p, miR-485-3p, miR-194-5p) miRNAs. Additionally, their targets were enriched in several vital cancer-associated pathways such as TGF-beta, p53, and hippo signaling pathways. Moreover, five key hotspot target genes (CCNA2, MAPK1, PTPRD, MET, and CDKN1A) were demonstrated to associated with better overall survival in CRC patients. Finally, miR-23b-3p, miR-301a-3p and miR-194-3p were validated being the most stably expressed stage-associated miRNAs in CRC serum exosomes, cell exosomes and tissues.

Conclusions

These CRC stage-associated exosome miRNAs aid to further mechanism research of tumor progression and provide support for better clinical management in patients with different stages.

Small extracellular vesicles: from promoting pre-metastatic niche formation to therapeutic strategies in breast cancer

Breast cancer is the most common cancer in females, and to date, the mortality rate of breast cancer metastasis cannot be ignored. The metastasis of breast cancer is a complex, staged process, and the pattern of metastatic spread is not random. The pre-metastatic niche, as an organ-specific home for metastasis, is a favourable environment for tumour cell colonization. As detection techniques improve, the role of the pre-metastatic niche in breast cancer metastasis is being uncovered. sEVs (small extracellular vesicles) can deliver cargo, which is vital for the formation of pre-metastatic niches. sEVs participate in multiple aspects of creating a distant microenvironment to promote tumour invasion, including the secretion of inflammatory molecules, immunosuppression, angiogenesis and enhancement of vascular permeability, as well as regulation of the stromal environment. Here, we discuss the multifaceted mechanisms through which breast cancer-derived sEVs contribute to pre-metastatic niches. In addition, sEVs as biomarkers and antimetastatic therapies are also discussed, particularly their use in transporting exosomal microRNAs. The study of sEVs may provide insight into immunotherapy and targeted therapies for breast cancer, and we also provide an overview of their potential role in antitumour metastasis.

A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer

Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified.

Methods: We obtained 371 tumor specimens and 50 normal tissues from the TCGA database. These samples were randomly divided into the training queue and verification queue. The exosome-related lncRNA risk model was verified by correlation analysis, Lasso regression analysis, and Cox regression analysis. The differences in the immune microenvironment in the two risk groups were obtained by analyzing the infiltration of different immune cells.

Results: Five exosome-related lncRNAs associated (MKLN1-AS, TMCC1-AS1, AL031985.3, LINC01138, AC099850.3) with a poor prognosis were identified and used to construct the signature. Receiver operating curve (ROC) and survival curves were used to confirm the predictive ability of this signature. Based on multivariate regression analysis in the training cohort (HR: 3.033, 95% CI: 1.762–5.220) and validation cohort (HR: 1.998, 95% CI: 1.065–3.751), the risk score was found to be an independent risk factor for patient prognosis. Subsequently, a nomogram was constructed to predict the 1-, 3-, 5-years survival rates of liver cancer patients. Moreover, this signature was also related to overexpressed immune checkpoints (PD-1, B7-H3, VSIR, PD-L1, LAG3, TIGIT and CTLA4).

Conclusion: Our study showed that exosome-related lncRNAs and the corresponding nomogram could be used as a better index to predict the outcome and immune regulation of liver cancer patients. This signature might provide a new idea for the immunotherapy of liver cancer in the future.

GlioMarker: An integrated database for knowledge exploration of diagnostic biomarkers in gliomas

Gliomas are the most frequent malignant and aggressive tumors in the central nervous system. Early and effective diagnosis of glioma using diagnostic biomarkers can prolong patients' lives and aid in the development of new personalized treatments. Therefore, a thorough and comprehensive understanding of the diagnostic biomarkers in gliomas is of great significance. To this end, we developed the integrated and web-based database GlioMarker (http://gliomarker.prophetdb.org/), the first comprehensive database for knowledge exploration of glioma diagnostic biomarkers. In GlioMarker, accurate information on 406 glioma diagnostic biomarkers from 1559 publications was manually extracted, including biomarker descriptions, clinical information, associated literature, experimental records, associated diseases, statistical indicators, etc. Importantly, we integrated many external resources to provide clinicians and researchers with the capability to further explore knowledge on these diagnostic biomarkers based on three aspects. (1) Obtain more ontology annotations of the biomarker. (2) Identify the relationship between any two or more components of diseases, drugs, genes, and variants to explore the knowledge related to precision medicine. (3) Explore the clinical application value of a specific diagnostic biomarker through online analysis of genomic and expression data from glioma cohort studies. GlioMarker provides a powerful, practical, and user-friendly web-based tool that may serve as a specialized platform for clinicians and researchers by providing rapid and comprehensive knowledge of glioma diagnostic biomarkers to subsequently facilitates high-quality research and applications.

Role of an Exosomes-Related lncRNAs Signature in Tumor Immune Microenvironment of Gastric Cancer

Background: Exosomes plays a crucial role in intercellular communication of gastric cancer (GC), while long non-coding RNAs (lncRNAs) contributes to the tumorigenesis and progression of GC. This study aims to explore the prognostic exosomes-related lncRNAs of GC patients.

Methods: Data of 375 GC patients were obtained from the TCGA database. The entire cohort was randomly divided into a training cohort and a validation cohort in a 2:1 ratio. Exosomes-related lncRNAs were identified by the Pearson correlation analysis with reported exosomes-related genes. LASSO Cox regression was used to construct the signature.

Results: A prognostic signature consisting of 11 exosomes-related lncRNAs was identified, and patients with lower risk scores had a better prognosis than those with higher risk scores. ROC curves and multivariate Cox regression analysis showed that the signature was an independent risk factor for prognosis in both the training (HR: 3.254, 95% CI: 2.310–4.583) and validation cohorts (HR: 1.974, 95% CI: 1.108–3.517). Gene set enrichment analysis (GSEA) suggested associations between the signature and several immune-related pathways. The identified signature was shown to be associated with GC tumor microenvironment. The expression of two immune checkpoints was also increased in the high-risk group, including B7-H3 and VSIR, indicating the potential role of the identified signature in GC immunotherapies.

Conclusion: A novel exosomes-related lncRNA signature, which may be associated with tumor immune microenvironment and potentially serve as an indicator for immunotherapy, has been identified to precisely predict the prognosis of GC patients.

Hyperthermia promotes exosome secretion by regulating Rab7b while increasing drug sensitivity in adriamycin-resistant breast cancer

PURPOSE

To investigate the mechanism through which hyperthermia promotes exosome secretion and drug sensitivity in adriamycin-resistant breast cancer.

MATERIALS AND METHODS

We first evaluated the effect of hyperthermia on adriamycin-resistant breast cancer viability and used transmission electron microscopy, nanoparticle tracking analysis, and a bicinchoninic acid kit to validate the effect of hyperthermia on exosome secretion. The effective targeting molecules and pathways changed by hyperthermia were explored by RNA microarray and verified in vitro. The adriamycin-resistant MCF-7/ADR cells co-incubated with the exosomes produced by MCF-7/ADR cells after hyperthermia were assessed. The uptake of exosomes by MCF-7/ADR cells after hyperthermia treatment was evaluated by confocal microscopy. Finally, the mechanism through which hyperthermia promotes exosome secretion by hyperthermia was determined.

RESULTS

Hyperthermia significantly suppressed the growth of adriamycin-resistant breast cancer cells and increased drug sensitivity by upregulating FOS and CREB5, genes related to longer overall survival in breast cancer patients. Moreover, hyperthermia promoted exosome secretion through Rab7b, a small GTPase that controls endosome transport. The upregulated FOS and CREB5 antioncogenes can be transferred to MCF-7/ADR cells by hyperthermia-treated MCF-7/ADR cell-secreted exosomes.

CONCLUSIONS

Our results demonstrated a novel function of hyperthermia in promoting exosome secretion in adriamycin-resistant breast cancer cells and revealed the effects of hyperthermia on tumor cell biology. These hyperthermia-triggered exosomes can carry antitumor genes to the residual tumor and tumor microenvironment, which may be more beneficial to the effects of hyperthermia. These results represent an exploration of the relationship between therapeutic strategies and exosome biology.

EVAtlas: a comprehensive database for ncRNA expression in human extracellular vesicles

Extracellular vesicles (EVs) packing various molecules play vital roles in intercellular communication. Non-coding RNAs (ncRNAs) are important functional molecules and biomarkers in EVs. A comprehensive investigation of ncRNAs expression in EVs under different conditions is a fundamental step for functional discovery and application of EVs. Here, we curated 2030 small RNA-seq datasets for human EVs (1506 sEV and 524 lEV) in 24 conditions and over 40 diseases. We performed a unified reads dynamic assignment algorithm (RDAA) considering mismatch and multi-mapping reads to quantify the expression profiles of seven ncRNA types (miRNA, snoRNA, piRNA, snRNA, rRNA, tRNA and Y RNA). We constructed EVAtlas (http://bioinfo.life.hust.edu.cn/EVAtlas), a comprehensive database for ncRNA expression in EVs with four functional modules: (i) browse and compare the distribution of ncRNAs in EVs from 24 conditions and eight sources (plasma, serum, saliva, urine, sperm, breast milk, primary cell and cell line); (ii) prioritize candidate ncRNAs in condition related tissues based on their expression; (iii) explore the specifically expressed ncRNAs in EVs from 24 conditions; (iv) investigate ncRNA functions, related drugs, target genes and EVs isolation methods. EVAtlas contains the most comprehensive ncRNA expression in EVs and will be a key resource in this field.