Circulating exosomal mRNA signatures for the early diagnosis of clear cell renal cell carcinoma

Emerging roles of exosomes in the diagnosis and treatment of kidney diseases

The complex etiology and spectrum of kidney diseases necessitate vigilant attention; the focus on early diagnosis and intervention in kidney diseases remains a critical issue in medical research. Recently, with the expanding studies on extracellular vesicles, exosomes have garnered increasing interest as a promising tool for the diagnosis and treatment of kidney diseases. Exosomes are nano-sized extracellular vesicles that transport a diverse array of bioactive substances, which can influence various pathological processes associated with kidney diseases and exhibit detrimental or beneficial effects. Within the kidney, exosomes derived from the glomeruli and renal tubules possess the ability to enter systemic circulation or urine. The biomarkers they carry can reflect alterations in the pathological state of the kidneys, thereby offering novel avenues for early diagnosis. Furthermore, research studies have confirmed that exosomes originating from multiple cell types exhibit therapeutic potential in treating kidney disease; notably, those derived from mesenchymal stem cells (MSCs) have shown significant treatment efficacy. This comprehensive review summarizes the contributions of exosomes from different cell types within the kidneys while exploring their physiological and pathological roles therein. Additionally, we emphasize recent advancements in exosome applications for the diagnosis and treatment of various forms of kidney diseases over the past decades. We not only introduce the urinary and blood biomarkers linked to kidney diseases found within exosomes but also explore their therapeutic effects. Finally, we discuss existing challenges and future directions concerning the clinical applications of exosomes for diagnostic and therapeutic purposes.

Exosomes: innovative biomarkers leading the charge in non-invasive cancer diagnostics

Exosomes, nanoscale extracellular vesicles secreted by diverse cell types, have emerged as promising biomarkers for non-invasive tumor diagnostics, offering significant advantages over traditional methods. These vesicles, typically ranging from 30 to 150 nanometers in size, carry a diverse cargo of proteins, lipids, RNA, and microRNAs, which reflect the molecular alterations occurring within their parent cells. Notably, exosomes can be isolated from easily accessible biofluids such as blood, urine, and saliva, making them ideal candidates for liquid biopsy applications. This review explores the transformative potential of exosome-based biomarkers in the early detection and monitoring of cancers across diverse organ systems, including respiratory, digestive, hematological, neurological, endocrine malignancies and so on. Special emphasis is placed on their application in clinical trials, where exosome-based diagnostics have demonstrated promising results in detecting tumors at early stages and monitoring treatment responses, offering a less invasive and more accessible alternative to traditional biopsies. While recent advancements in exosome isolation and characterization technologies have significantly improved the sensitivity and specificity of these diagnostics, challenges such as biological heterogeneity, lack of standardization, and regulatory hurdles remain. Nevertheless, exosome-based diagnostics hold the promise of providing real-time, dynamic insights into tumor progression, enhancing personalized medicine. The integration of exosomes into clinical practice could revolutionize cancer diagnostics and therapy, improving patient outcomes. Further research and large-scale clinical validation are essential to fully realize the clinical potential of exosome-based biomarker applications in routine clinical settings.

Exosomes in Precision Oncology and Beyond: From Bench to Bedside in Diagnostics and Therapeutics

Exosomes have emerged as pivotal players in precision oncology, offering innovative solutions to longstanding challenges such as metastasis, therapeutic resistance, and immune evasion. These nanoscale extracellular vesicles facilitate intercellular communication by transferring bioactive molecules that mirror the biological state of their parent cells, positioning them as transformative tools for cancer diagnostics and therapeutics. Recent advancements in exosome engineering, artificial intelligence (AI)-driven analytics, and isolation technologies are breaking barriers in scalability, reproducibility, and clinical application. Bioengineered exosomes are being leveraged for CRISPR-Cas9 delivery, while AI models are enhancing biomarker discovery and liquid biopsy accuracy. Despite these advancements, key obstacles such as heterogeneity in exosome populations and the lack of standardized isolation protocols persist. This review synthesizes pioneering research on exosome biology, molecular engineering, and clinical translation, emphasizing their dual roles as both mediators of tumor progression and tools for intervention. It also explores emerging areas, including microbiome-exosome interactions and the integration of machine learning in exosome-based precision medicine. By bridging innovation with translational strategies, this work charts a forward-looking path for integrating exosomes into next-generation cancer care, setting it apart as a comprehensive guide to overcoming clinical and technological hurdles in this rapidly evolving field.

Identification of blood-derived exosomal tumor RNA signatures as noninvasive diagnostic biomarkers for multi-cancer: a multi-phase, multi-center study

BACKGROUND

Cancer remains a leading global cause of mortality, making early detection crucial for improving survival outcomes. The study aims to develop a machine learning-enabled blood-derived exosomal RNA profiling platform for multi-cancer detection and localization.

METHODS

In this multi-phase, multi-center study, we analyzed RNA from exosomes derived from peripheral blood plasma in 818 participants across eight cancer types during the discovery phase. Machine learning techniques were applied to identify potential pan-cancer biomarkers. During the screening and model validation phases, the sample size was progressively expanded to 1,385 participants in two steps, while the candidate biomarkers were refined into a set of 12 exosomal tumor RNA signatures (ETR.sig). In the subsequent model construction phase, diagnostic models were developed using the expanded cohort and ETR.sig. Statistical analyses included the calculation of receiver operating characteristic (ROC) curves and AUC values to assess the models' ability to distinguish cancer cases from controls and determine tumor origins. To further validate and explore the biological relevance of the identified biomarkers, we integrated tissue RNA-seq, single-cell data, and clinical information.

RESULTS

Machine learning analysis initially identified 33 candidate biomarkers, which were narrowed down to 20 ETR.sig in the screening phase and 12 ETR.sig in the validation phase. In the model construction phase, a diagnostic model based on ETR.sig, built using the Random Forest (RF) algorithm, showed excellent performance with an AUC of 0.915 for distinguishing pan-cancer from controls. The multi-class classification model also demonstrated strong classification power, with macro-average and micro-average AUCs of 0.983 and 0.985, respectively, for differentiating between eight cancer types. Additionally, tumor origin classification using the RF-based diagnostic models achieved high AUC values: BRCA 0.976, COAD 0.98, KIRC 0.947, LIHC 0.967, LUAD 0.853, OV 0.972, PAAD 0.977, and PRAD 0.898. Integration of tissue RNA-seq, single-cell data, and clinical information revealed key associations between ETR.sig-related genes and tumor development.

CONCLUSIONS

The study demonstrates the robust potential of exosomal RNA as a minimally invasive biomarker resource for cancer detection. The developed ETR.sig platform offers a promising tool for precision oncology and broad-spectrum cancer screening, integrating advanced computational models with nanoscale vesicle biology for accurate and rapid diagnosis.

Toward the use of nanopore RNA sequencing technologies in the clinic: challenges and opportunities

RNA molecules have garnered increased attention as potential clinical biomarkers in recent years. While short-read sequencing and quantitative polymerase chain reaction have been the primary methods for quantifying RNA abundance, they typically fail to capture critical post-transcriptional regulatory elements, such as RNA modifications, which are often dysregulated in disease contexts. A promising cutting-edge technique sequencing method that addresses this gap is direct RNA sequencing, offered by Oxford Nanopore Technologies, which can simultaneously capture both RNA abundance and modification information. The rapid advancements in this platform, along with growing evidence of dysregulated RNA species in biofluids, presents a compelling clinical opportunity. In this review, we discuss the challenges and the emerging opportunities for the adoption of nanopore RNA sequencing technologies in the clinic, highlighting their potential to revolutionize personalized medicine and disease monitoring.

Liquid biopsy for renal cell carcinoma

Liquid biopsies offer a less invasive alternative to tissue biopsies for diagnosis, prognosis, and determining therapeutic potential in renal cell carcinoma (RCC). Unfortunately, clinical studies using liquid biopsy biomarkers in RCC are limited. Accordingly, we examine RCC biomarkers, derived from urine, plasma, serum and feces of potential impact and clinical outcome in these patients. A PRISMA checklist was used to identify valuable liquid biopsy biomarkers for diagnosis (plasma cfDNA, serum- or urine-derived circulating RNAs, exosomes and proteins), prognosis (plasma cfDNA, plasma- or serum-derived RNAs, and proteins), and therapeutic response (plasma- and serum-derived proteins). Although other analytes have been identified, their application for routine clinical use remains unclear. In general, panels appear more effective than single biomarkers. Important considerations included proof of reproducibility. Unfortunately, many of the examined studies were insufficiently large and lacked multi-center rigor. Cost-effectiveness was also not available. Accordingly, it is clear that more standardized protocols need to be developed before liquid biopsies can be successfully integrated into clinical practice in RCC.

Extracellular vesicles: From large-scale production and engineering to clinical applications

Extracellular vesicles (EVs) have emerged as a promising strategy for treating a wide spectrum of pathologies, as they can deliver their cargo to recipient cells and regulate the signaling pathway of these cells to modulate their fate. Despite the great potential of EVs in clinical applications, their low yield and the challenges of cargo loading remain significant obstacles, hindering their transition from experimental research to clinical practice. Therefore, promoting EV release and enhancing EV cargo-loading are promising fields with substantial research potential and broad application prospects. In this review, we summarize the clinical applications of EVs, the methods and technologies for their large-scale production, engineering, and modification, as well as the challenges that must be addressed during their development. We also discuss the future perspectives of this exciting field of research to facilitate its transformation from bench to clinical reality.

New perspectives of exosomes in urologic malignancies - Mainly focus on biomarkers and tumor microenvironment

Bladder cancer (BCa) and renal cell carcinoma (RCC) are prevalent urologic malignancies (UM) characterized by high morbidity and frequent recurrence. Current diagnostic approaches, often invasive, often indicate an advanced disease stage. And the complex tumor microenvironment often promotes tumor progression and induces resistance to chemotherapy. Current diagnostic and therapeutic modalities often fail to achieve satisfactory outcomes for patients. Exosomes transport diverse cargoes, including cytokines, proteins, lipids, non-coding RNAs, and microRNAs, crucial for intercellular communication. Exosomes have shown potential as biomarkers for UM, participating in tumor progression, especially within the tumor microenvironment (TME), including tumor cell apoptosis, proliferation, migration, invasion, depletion of immune cell function, epithelial-mesenchymal transition (EMT), angiogenesis, and more.In this review, we summarize research advances related to exosomes in UM, focusing on the role of exosomes as biomarkers in bladder and renal cancer, highlighting their significance within the TME.

Emerging advanced approaches for liquid biopsy: in situ nucleic acid assays of extracellular vesicles

Extracellular vesicles (EVs) have emerged as valuable biomarkers in liquid biopsies owing to their stability, accessibility, and ability to encapsulate nucleic acids. The majority of existing methodologies for detecting EV nucleic acid biomarkers require the lysis of EVs to extract DNA or RNA. This process is labor-intensive and may lead to the loss and degradation of nucleic acids. However, the emerging field of in situ EV assays offers innovative tools for liquid biopsy, facilitating direct profiling of nucleic acids within intact EVs and reducing sample handling procedures. This review focuses on the promising and innovative field of in situ EV nucleic acid analysis. It examines the translational potential of in situ EV nucleic acid analysis in liquid biopsies from detection strategies, diagnostic applications, and diagnostic aids for single EV analysis and machine learning techniques. We highlight the innovative approach of in situ EV nucleic acid assays and provide novel insights into advancing liquid biopsy technology. This approach shows a promising avenue for improving EV-based cancer diagnosis and guiding personalized treatment with minimal invasiveness.

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics

Objective

This study aimed to delineate the clear cell renal cell carcinoma (ccRCC) intrinsic subtypes through unsupervised clustering of radiomics and transcriptomics data and to evaluate their associations with clinicopathological features, prognosis, and molecular characteristics.

Methods

Using a retrospective dual-center approach, we gathered transcriptomic and clinical data from ccRCC patients registered in The Cancer Genome Atlas and contrast-enhanced computed tomography images from The Cancer Imaging Archive and local databases. Following the segmentation of images, radiomics feature extraction, and feature preprocessing, we performed unsupervised clustering based on the "CancerSubtypes" package to identify distinct radiotranscriptomic subtypes, which were then correlated with clinical-pathological, prognostic, immune, and molecular characteristics.

Results

Clustering identified three subtypes, C1, C2, and C3, each of which displayed unique clinicopathological, prognostic, immune, and molecular distinctions. Notably, subtypes C1 and C3 were associated with poorer survival outcomes than subtype C2. Pathway analysis highlighted immune pathway activation in C1 and metabolic pathway prominence in C2. Gene mutation analysis identified VHL and PBRM1 as the most commonly mutated genes, with more mutated genes observed in the C3 subtype. Despite similar tumor mutation burdens, microsatellite instability, and RNA interference across subtypes, C1 and C3 demonstrated greater tumor immune dysfunction and rejection. In the validation cohort, the various subtypes showed comparable results in terms of clinicopathological features and prognosis to those observed in the training cohort, thus confirming the efficacy of our algorithm.

Conclusion

Unsupervised clustering based on radiotranscriptomics can identify the intrinsic subtypes of ccRCC, and radiotranscriptomic subtypes can characterize the prognosis and molecular features of tumors, enabling noninvasive tumor risk stratification.

Exosome-related lncRNA score: A value-based individual treatment strategy for predicting the response to immunotherapy in clear cell renal cell carcinoma

BACKGROUND

Exosomes play a crucial role in intercellular communication in clear cell renal cell carcinoma (ccRCC), while the long non-coding RNAs (lncRNAs) are implicated in tumorigenesis and progression.

AIMS

The purpose of this study is to construction a exosomes-related lncRNA score and a ceRNA network to predict the response to immunotherapy and potential targeted drug in ccRCC.

METHODS

Data of ccRCC patients were obtained from the TCGA database. Pearson correlation analysis was used to identify eExosomes-related lncRNAs (ERLRs) from Top10 exosomes-related genes that have been screened. The entire cohort was randomly divided into a training cohort and a validation cohort in equal scale. LASSO regression and multivariate cox regression was used to construct the ERLRs-based score. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and drug susceptibility between the high- and low-risk groups were also investigated. Finally, the relevant ceRNA network was constructed by machine learning to analyze their potential targets in immunotherapy and drug use of ccRCC patients.

RESULTS

A score consisting of 4ERLRs was identified, and patients with higher ERLRs-based score tended to have a worse prognosis than those with lower ERLRs-based score. ROC curves and multivariate Cox regression analysis demonstrated that the score could be considered as a risk factor for prognosis in both training and validation cohorts. Moreover, patients with high scores are predisposed to experience poor overall survival, a larger prevalence of advanced stage (III-IV), a greater tumor mutational burden, a higher infiltration of immunosuppressive cells, and a greater likelihood of responding favorably to immunotherapy. The importance of EMX2OS was determined by mechanical learning, and the ceRNA network was constructed, and EMX2OS may be a potential therapeutic target, possibly exerting its function through the EMX2OS/hsa-miR-31-5p/TLN2 axis.

CONCLUSIONS

Based on machine learning, a novel ERLRs-based score was constructed for predicting the survival of ccRCC patients. The ERLRs-based score is a promising potential independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. Meanwhile, we screened out key lncRNAEMX2OS and identified the EMX2OS/hsa-miR-31-5p/TLN2 axis, which may provide new clues for the targeted therapy of ccRCC.

Construction of exosome-related genes risk model in kidney cell carcinoma predicts prognosis and immune therapy response

Renal cell carcinoma (RCC) is one of the most prevalent types of urological cancer. Exosomes are vesicles derived from cells and have been found to promote the development of RCC, but the potential biomarker and molecular mechanism of exosomes on RCC remain ambiguous. Here, we first screened differentially expressed exosome-related genes (ERGs) by analyzing The Cancer Genome Atlas (TCGA) database and exoRBase 2.0 database. We then determined prognosis-related ERGs (PRERGs) by univariate Cox regression analysis. Gene Dependency Score (gDS), target development level, and pathway correlation analysis were utilized to examine the importance of PRERGs. Machine learning and lasso-cox regression were utilized to screen and construct a 5-gene risk model. The risk model showed high predictive accuracy for the prognosis of patients and proved to be an independent prognostic factor in three RCC datasets, including TCGA-KIRC, E-MTAB-1980, and TCGA-KIRP datasets. Patients with high-risk scores showed worse outcomes in different clinical subgroups, revealing that the risk score is robust. In addition, we found that immune-related pathways are highly enriched in the high-risk group. Activities of immune cells were distinct in high-/low-risk groups. In independent immune therapeutic cohorts, high-risk patients show worse immune therapy responses. In summary, we identified several exosome-derived genes that might play essential roles in RCC and constructed a 5-gene risk signature to predict the prognosis of RCC and immune therapy response.

GHITM regulates malignant phenotype and sensitivity to PD-1 blockade of renal cancer cells via Notch signalling

Growth hormone inducible transmembrane protein (GHITM), one member of Bax inhibitory protein-like family, has been rarely studied, and the clinical importance and biological functions of GHITM in kidney renal clear cell carcinoma (KIRC) still remain unknown. In the present study, we found that GHITM was downregulated in KIRC. Aberrant GHITM downregulation related to clinicopathological feature and unfavourable prognosis of KIRC patients. GHITM overexpression inhibited KIRC cell proliferation, migration and invasion in vitro and in vivo. Mechanistically, GHITM overexpression could induce the downregulation of Notch1, which acts as an oncogene in KIRC. Overexpression of Notch1 effectively rescued the inhibitory effect induced by GHITM upregulation. More importantly, GHITM could regulate PD-L1 protein abundance and ectopic overexpression of GHITM enhanced the antitumour efficiency of PD-1 blockade in KIRC, which provided new insights into antitumour therapy. Furthermore, we also showed that YY1 could decrease GHITM level via binding to its promoter. Taken together, our study revealed that GHITM was a promising therapeutic target for KIRC, which could modulate malignant phenotype and sensitivity to PD-1 blockade of renal cancer cells via Notch signalling pathway.

Exosomes in renal cell carcinoma: challenges and opportunities

Renal cell carcinoma (RCC) is the most common type of kidney cancer that accounts for approximately 2-3% of adult malignancies. Among the primary treatment methods for this type of cancer are surgery and targeted treatment. Still, due to less than optimal effectiveness, there are problems such as advanced distant metastasis, delayed diagnosis, and drug resistance that continue to plague patients. In recent years, therapeutic advances have increased life expectancy and effective treatment in renal cell carcinoma patients. One of these methods is the use of stem cells. Although the therapeutic effects of stem cells, especially mesenchymal stem cells, are still impressive, today, extracellular vesicles (EVs) as carrying molecules and various mediators in intercellular communications, having a central role in tumorigenesis, metastasis, immune evasion, and drug response, and on the other hand, due to its low immunogenicity and strong regulatory properties of the immune system, has received much attention from researchers and doctors. Despite the increasing interest in exosomes as the most versatile type of EVs, the heterogeneity of their efficacy presents challenges and, on the other hand, exciting opportunities for diagnostic and clinical interventions.In the upcoming article, we will review the various aspects of exosomes' effects in the prevention, treatment, and progress of renal cell carcinoma and also ways to optimize them to strengthen their positive sides.

Diagnostic liquid biopsy biomarkers in renal cell cancer

The clinical presentation of renal cell cancer (RCC) is shifting towards incidental and early detection, creating new challenges in RCC diagnosis. Overtreatment might be reduced with the development of new diagnostic biomarkers to distinguish benign from malignant small renal masses (SRMs). Differently from tissue biopsies, liquid biopsies are obtained from a patient's blood or urine and, therefore, are minimally invasive and suitable for longitudinal monitoring. The most promising types of liquid biopsy biomarkers for RCC diagnosis are circulating tumour cells, extracellular vesicles (EVs) and cell-free DNA. Circulating tumour cell assays have the highest specificity, with low processing time and costs. However, the biological characteristics and low sensitivity limit the use of these markers in SRM diagnostics. Cell-free DNA might complement the diagnosis of high-volume RCC, but the potential for clinical application in SRMs is limited. EVs have the highest biological abundance and the highest sensitivity in identifying low-volume disease; moreover, the molecular characteristics of these markers make EVs suitable for multiple analytical applications. Thus, currently, EV assays have the greatest potential for diagnostic application in RCC (including identification of SRMs). All these liquid biomarkers have potential in clinical practice, pending validation studies. Biomarker implementation will be needed to also improve characterization of RCC subtypes. Last, diagnostic biomarkers might be extended to prognostic or predictive applications.

Deciphering the Role of ERBB3 Isoforms in Renal Cell Carcinoma: A Comprehensive Genomic and Transcriptomic Analysis

ERBB3, a key member of the receptor tyrosine kinase family, is implicated in the progression and development of various human cancers, affecting cellular proliferation and survival. This study investigated the expression of ERBB3 isoforms in renal clear cell carcinoma (RCC), utilizing data from 538 patients from The Cancer Genome Atlas (TCGA) Firehose Legacy dataset. Employing the SUPPA2 tool, the activity of 10 ERBB3 isoforms was examined, revealing distinct expression patterns in RCC. Isoforms uc001sjg.3 and uc001sjh.3 were found to have reduced activity in tumor tissues, while uc010sqb.2 and uc001sjl.3 demonstrated increased activity. These variations in isoform expression correlate with patient survival and tumor aggressiveness, indicating their complex role in RCC. The study, further, utilizes CIBERSORTx to analyze the association between ERBB3 isoforms and immune cell profiles in the tumor microenvironment. Concurrently, Gene Set Enrichment Analysis (GSEA) was applied, establishing a strong link between elevated levels of ERBB3 isoforms and critical oncogenic pathways, including DNA repair and androgen response. RT-PCR analysis targeting the exon 21-23 and exon 23 regions of ERBB3 confirmed its heightened expression in tumor tissues, underscoring the significance of alternative splicing and exon utilization in cancer development. These findings elucidate the diverse impacts of ERBB3 isoforms on RCC, suggesting their potential as diagnostic markers and therapeutic targets. This study emphasizes the need for further exploration into the specific roles of these isoforms, which could inform more personalized and effective treatment modalities for renal clear cell carcinoma.

Extracellular vesicle small RNA cargo discriminates non-cancer donors from pediatric B-lymphoblastic leukemia patients

Pediatric B-acute lymphoblastic leukemia (B-ALL) is a disease of abnormally growing B lymphoblasts. Here we hypothesized that extracellular vesicles (EVs), which are nanosized particles released by all cells (including cancer cells), could be used to monitor B-ALL severity and progression by sampling plasma instead of bone marrow. EVs are especially attractive as they are present throughout the circulation regardless of the location of the originating cell. First, we used nanoparticle tracking analysis to compare EVs between non-cancer donor (NCD) and B-ALL blood plasma; we found that B-ALL plasma contains more EVs than NCD plasma. We then isolated EVs from NCD and pediatric B-ALL peripheral blood plasma using a synthetic peptide-based isolation technique (Vn96), which is clinically amenable and isolates a broad spectrum of EVs. RNA-seq analysis of small RNAs contained within the isolated EVs revealed a signature of differentially packaged and exclusively packaged RNAs that distinguish NCD from B-ALL. The plasma EVs contain a heterogenous mixture of miRNAs and fragments of long non-coding RNA (lncRNA) and messenger RNA (mRNA). Transcripts packaged in B-ALL EVs include those involved in negative cell cycle regulation, potentially suggesting that B-ALL cells may use EVs to discard gene sequences that control growth. In contrast, NCD EVs carry sequences representative of multiple organs, including brain, muscle, and epithelial cells. This signature could potentially be used to monitor B-ALL disease burden in pediatric B-ALL patients via blood draws instead of invasive bone marrow aspirates.

Advances in the research of exosomes in renal cell carcinoma: from mechanisms to applications

Renal cell carcinoma (RCC) is one of the most malignant urological tumors. Currently, there is a lack of molecular markers for early diagnosis of RCC. The 5-year survival rate for early-stage RCC is generally favorable; however, the prognosis takes a significant downturn when the tumor progresses to distant metastasis. Therefore, the identification of molecular markers for RCC is crucial in enhancing early diagnosis rates. Exosomes are a type of extracellular vesicle (EV) typically ranging in size from 30 nm to 150 nm, which contain RNA, DNA, proteins, lipids, etc. They can impact neighboring receptor cells through the autocrine or paracrine pathway, influence cellular communication, and regulate the local immune cells, consequently shaping the tumor immune microenvironment and closely associating with tumor development. The clinical application of exosomes as tumor markers and therapeutic targets has ignited significant interest within the research community. This review aims to provide a comprehensive summary of the advancements in exosome research within the context of RCC.

Theranostic Lipid Nanoparticles for Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a common urological malignancy and represents a leading threat to healthcare. Recent years have seen a series of progresses in the early diagnosis and management of RCC. Theranostic lipid nanoparticles (LNPs) are increasingly becoming one of the focuses in this field, because of their suitability for tumor targeting and multimodal therapy. LNPs can be precisely fabricated with desirable chemical compositions and biomedical properties, which closely match the physiological characteristics and clinical needs of RCC. Herein, a comprehensive review of theranostic LNPs is presented, emphasizing the generic tool nature of LNPs in developing advanced micro-nano biomaterials. It begins with a brief overview of the compositions and formation mechanism of LNPs, followed with an introduction to kidney-targeting approaches, such as passive, active, and stimulus responsive targeting. With examples provided, a series of modification strategies for enhancing the tumor targeting and functionality of LNPs are discussed. Thereafter, research advances on applications of these LNPs for RCC including bioimaging, liquid biopsy, drug delivery, physical therapy, and gene therapy are summarized and discussed from an interdisciplinary perspective. The final part highlights the milestone achievements of translation medicine, current challenges as well as future development directions of LNPs for the diagnosis and treatment of RCC.

Extracellular vesicles in renal cell carcinoma: challenges and opportunities coexist

Renal cell carcinoma (RCC) represents an extremely challenging disease in terms of both diagnosis and treatment. It poses a significant threat to human health, with incidence rates increasing at a yearly rate of roughly 2%. Extracellular vesicles (EVs) are lipid-based bilayer structures of membranes that are essential for intercellular interaction and have been linked to the advancement of RCC. This review provides an overview of recent studies on the role of EVs in RCC progression, including involvement in the interaction of tumor cells with M2 macrophages, mediating the generation of immune tolerance, and assuming the role of communication messengers in the tumor microenvironment leading to disease progression. Finally, the " troika " of EVs in RCC therapy is presented, including engineered sEVs' or EVs tumor vaccines, mesenchymal stem cell EVs therapy, and reduction of tumor-derived EVs secretion. In this context, we highlight the limitations and challenges of EV-based research and the prospects for future developments in this field. Overall, this review provides a comprehensive summary of the role of EVs in RCC and their potential as a viable pathway for the future treatment of this complex disease.

Exosomal cargos-mediated metabolic reprogramming in tumor microenvironment

Metabolic reprogramming is one of the hallmarks of cancer. As nutrients are scarce in the tumor microenvironment (TME), tumor cells adopt multiple metabolic adaptations to meet their growth requirements. Metabolic reprogramming is not only present in tumor cells, but exosomal cargos mediates intercellular communication between tumor cells and non-tumor cells in the TME, inducing metabolic remodeling to create an outpost of microvascular enrichment and immune escape. Here, we highlight the composition and characteristics of TME, meanwhile summarize the components of exosomal cargos and their corresponding sorting mode. Functionally, these exosomal cargos-mediated metabolic reprogramming improves the "soil" for tumor growth and metastasis. Moreover, we discuss the abnormal tumor metabolism targeted by exosomal cargos and its potential antitumor therapy. In conclusion, this review updates the current role of exosomal cargos in TME metabolic reprogramming and enriches the future application scenarios of exosomes.

Role of exosomes in non-small cell lung cancer and EGFR-mutated lung cancer

As an important mediator of information transfer between cells, exosomes play a unique role in regulating tumor growth, supporting vascular proliferation, tumor invasion, and metastasis. Exosomes are widely present in various body fluids, and therefore they can be used as a potential tool for non-invasive liquid biopsy. The present study reviews the role of exosomes in liquid biopsy, tumor microenvironment formation, and epithelial-mesenchymal transition in non-small cell lung cancer (NSCLC). By targeting epidermal growth factor receptor (EGFR) therapy as a first-line treatment for patients with NSCLC, this study also briefly describes the occurrence of EGRF+ exosomes and the role of exosomes and their contents in non-invasive detection and potential therapeutic targets in EGFR-mutated lung cancer.

Histone methyltransferase SETD2: An epigenetic driver in clear cell renal cell carcinoma

SET domain-containing 2 (SETD2) is a lysine methyltransferase that catalyzes histone H3 lysine36 trimethylation (H3K36me3) and has been revealed to play important roles in the regulation of transcriptional elongation, RNA splicing, and DNA damage repair. SETD2 mutations have been documented in several cancers, including clear cell renal cell carcinoma (ccRCC). SETD2 deficiency is associated with cancer occurrence and progression by regulating autophagy flux, general metabolic activity, and replication fork speed. Therefore, SETD2 is considered a potential epigenetic therapeutic target and is the subject of ongoing research on cancer-related diagnosis and treatment. This review presents an overview of the molecular functions of SETD2 in H3K36me3 regulation and its relationship with ccRCC, providing a theoretical basis for subsequent antitumor therapy based on SETD2 or H3K36me3 targets.