MicroRNAs are small noncoding RNAs that regulate gene expression within cells through the translational repression or degradation of targeted mRNA. miRNAs undergo a multiphase synthesis that includes conformational changes mediated by Drosha, Dicer, and Argonaute to integrate mature miRNA into the RNA-induced silencing complex to target messenger (m)RNA. miRNAs have been characterized through their transcription and biogenesis; however, the mechanism regarding miRNA turnover is less comprehensible because of the stability of each miRNA. Target-directed miRNA degradation (TDMD) is dependent on the stability of miRNAs, which modulates the decay rate of miRNAs. This mechanism is initiated through target RNAs' engagement with miRNAs via the 3' end complements, which induces Argonaute rearrangement. These rearrangements of Argonaute can be induced through tailing and trimming, with one of the central initiators being the ZSWIM8 E3 ubiquitin ligase. Tailing and trimming are often associated with TDMD, and the mechanistic role is context-dependent. This mechanism provides a regulation process in which mRNA is actively repressed and silenced by the miRNA. The significance of TDMD lies in its role in post-transcriptional regulation of miRNA expression, its implications for therapeutic treatments, and its association with various diseases.

Abstract Digital PCR (dPCR) is a powerful technology for absolute quantification of nucleic acids, valued for its accuracy, sensitivity, and repeatability. Yet, the commercialization of different instruments with proprietary software has introduced challenges to data analysis, interoperability, and comparability. Therefore, we present the Digital PCR Data Essentials Standard (DDES) – a lightweight, human- and machine-readable, and cross-platform data standard developed in collaboration with the dPCR community. The standard consists of three file types designed to enable both manual inspection and automated analysis: (i) a main file summarizing experiment and reaction-level (meta-)data; (ii) an assay file describing targets and detection chemistry, and (iii) intensity files capturing partition-level raw fluorescence data per reaction. DDES supports a wide range of current dPCR applications, including singleplex and multiplex assays, endpoint and real-time readouts, and will be curated to implement future dPCR developments. By harmonizing the data structure, DDES lays out the foundation for FAIR dPCR data practices and supports improved software compatibility, collaborative and reproducible research, and future dPCR data repositories.

Inter-sample tumor heterogeneity poses significant challenges to metastatic cancer treatment. Although multiomics analyses provide nuanced molecular insights into tumor heterogeneity, current molecular pathway analysis tools focus on group-based comparisons, which may overlook differential single-sample perturbations. Here, we present normalized single-sample single-omic pathway analysis (SOPA), and its extension, normalized single-sample integrated multiomics pathway analysis (SIMPA), as a bioinformatics pipeline for performing supervised differential pathway analysis. The pipeline utilizes custom algorithms to analyze differential pathway activity in single samples, comparing the molecular profile in each sample to a range of controls. In single -omics analysis, SOPA shows advantages compared to standard tools such as single sample gene set enrichment analysis and gene set variation analysis in identifying single sample deviations from predefined controls. For integrated multiomics, we show that in predefined-control contexts, SIMPA provides an effective alternative over unsupervised tools such as multiomics gene set analysis (MOGSA) and PAthway Deviation scores using Multiple Factor Analysis (padma), addressing tumor heterogeneity. Particularly, SIMPA unveiled particular tumor subgroups with dysregulated immune and metabolic pathway activity marked by variable immune infiltration and survival differences, which were missed by MOGSA and padma. Overall, SOPA and SIMPA are valuable in the supervised analysis of single samples and allow for the investigation of complex multiomics data to gain personalized hypothesis-generating insights. The flexibility of this pipeline allows implementation in preclinical and clinical research, offering significant advantages over prior pathway analysis tools in studying systems biology. The Python package for SOPA and SIMPA is freely accessible at https://github.com/hasanalsharoh/SIMPApy/.

Estimating tumor-specific transcript proportions from mixed bulk samples has potential to inform novel biology. However, estimation accuracy using existing methods in sparse-count data such as microRNA-seq and spatial transcriptomics has yet to be established. We generated a mixed small RNA benchmark dataset to demonstrate analytical challenges. To resolve them, we developed DeMixNB, a semi-reference-based deconvolution model assuming a sum of negative binomial distributions. Applications to miRNA-seq from 856 patients with breast cancer and 3,755 spatial spots from lung cancer generated either clinical or mechanistic insights into tumor cell plasticity. This supports the important utility of DeMixNB to investigate cancer RNomes.

Head and neck squamous cell carcinoma (HNSCC) is notoriously resistant to immunotherapy. The interplay between β-adrenergic signaling and p53 loss, both key regulators of immune responses, has remained largely unexplored in the setting of tumor-immune evasion. This study demonstrates that pharmacologic stimulation of β2-adrenergic receptors with isoprenaline significantly enhances cytotoxic T cell activity against p53-deficient HNSCC cells via a CXCL10-dependent paracrine mechanism. Comprehensive transcriptomic and co-culture assays reveal that p53-null cancer cells upregulate CXCL10, which promotes CD8+ T cell recruitment and activation. Neutralization of CXCL10 abolishes the β-adrenergic-induced cytotoxic T cell response, establishing this chemokine as a pivotal mediator. Using tyrosine hydroxylase knockout mouse models, we show that adrenergic innervation is essential for intra-tumoral CXCL10 expression and the infiltration of effector CXCR3+ T cells in vivo. Notably, the CXCL10-driven T cell response is associated with simultaneous upregulation of both activation and exhaustion markers, indicating a robust but transient effector state within the tumor microenvironment. Collectively, these findings uncover a neuro-immune axis that reverses immune escape in p53-deficient HNSCC and suggest novel therapeutic strategies targeting adrenergic signaling to convert immune "cold" tumors into "hot" ones more amenable to immunotherapy.

BACKGROUND:Gastric adenocarcinoma (GAC) remains a major global health burden with marked heterogeneity, complicating diagnosis and prognostic assessment. The Laurén classification, though widely used, suffers from interobserver variability, particularly in defining the mixed subtype. Artificial intelligence (AI)-driven image analysis may improve standardization and prognostic assessment in GAC. METHODS:We retrospectively analyzed 404 patients with resected GAC (2015-2022) from Fundeni Clinical Institute. Whole-slide images (WSIs) were annotated by pathologists with expertise and processed into patches for training a two-stage deep learning pipeline based on YOLO26m-cls. The first model (GAC-I) distinguished malignant from non-malignant tissue, while the second (GAC-ST) classified malignant patches as intestinal or diffuse. We developed the diffuse prognostic score (DPS), defined as the proportion of diffuse patches relative to total patches, and correlated it with overall survival (OS). RESULTS:GAC-I and GAC-ST achieved high diagnostic performances, with accuracies of 0.9437 ± 0.0317 (F1 score: 0.9456 ± 0.0243) and 0.8080 ± 0.0833 (F1 score: 0.7528 ± 0.1094). DPS ≥ 0.5 was significantly associated with lower median OS (16.1 months) compared to DPS < 0.5 (42.067 months), association confirmed by multivariate Cox-regression analysis (HR 3.88, p < 0.001) and matched case-control analysis. Groups were balanced across all variables except tumor differentiation, which was more frequently high-grade in DPS ≥ 0.5. After adjustment, DPS ≥ 0.5 remained an independent predictor of mortality (HR 2.684, p = 0.027). CONCLUSION:We developed and validated a robust AI-based framework for automated GAC classification and prognostic stratification using H&E WSIs. DPS is an independent, reproducible marker of OS, supporting its potential integration into clinical pathology workflows to guide personalized treatment.

Supplementary data, tables and legends

Abstract Background: Cervical adenocarcinoma exhibits poor responsiveness to radiotherapy and inferior survival compared with squamous cell carcinoma. The molecular mechanisms underlying its intrinsic radiation resistance remain largely unknown. Methods: Integrative analysis of TCGA and our RNA-seq cohort identified CYP4A22-AS1 as one of the most upregulated lncRNAs in cervical adenocarcinoma. qRT-PCR confirmed higher CYP4A22-AS1 expression in tumors with short disease-free survival (DFS). RNA pulldown, mass spectrometry, and RIP assays defined YBX1 as a direct CYP4A22-AS1-binding partner. Immunofluorescence and ChIP-qPCR assays examined YBX1 nuclear localization and promoter occupancy of PGK1, respectively. Functional effects of CYP4A22-AS1, YBX1, and PGK1 silencing were assessed by CCK-8, colony, EdU, and TUNEL assays in HeLa and C33A cells, and validated in xenograft models. Results: CYP4A22-AS1 was markedly overexpressed in cervical adenocarcinoma relative to normal cervix. Clinically, high CYP4A22-AS1 and PGK1 levels correlated with shorter DFS. Mechanistically, CYP4A22-AS1 binds YBX1 and enhances its nuclear translocation, thereby promoting YBX1 recruitment to the PGK1 promoter and activating glycolytic metabolism. Knockdown of CYP4A22-AS1 or PGK1 suppressed proliferation and markedly increased radiosensitivity both in vitro and in vivo. Conclusions: This study identifies CYP4A22-AS1 as a novel oncogenic lncRNA that drives radiation resistance through YBX1-mediated PGK1 transactivation. Clinically, CYP4A22-AS1 overexpression predicts poor outcome, while its inhibition restores radiation sensitivity. Targeting the CYP4A22-AS1-YBX1-PGK1 signaling axis offers a promising therapeutic strategy to overcome radioresistance in cervical adenocarcinoma. Citation Format: Mingyi Zhou, Chunlai Li, Cristina Ivan, Simone Anfossi, Linda Fabris, Melanie Winkle, Recep Bayraktar, Meng Chen, Lan Pang, Masayoshi Shimizu, Francois Claret, George Calin, . CYP4A22-AS1-YBX1 axis drives radiation resistance in cervical adenocarcinoma via PGK1 transactivation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1366.

Non-coding RNAs (ncRNAs) regulate gene expression through transcriptional, post-transcriptional, and epigenetic mechanisms, shaping hallmarks of cancer, including metastasis, therapy resistance, and relapse. Carcinogenesis arises when aberrant ncRNA networks initiate malignant transformation and sustain oncogenic changes through epigenetic modifications, shifts in cell identity, failures in genome protection, metabolic changes, and alterations in the tumour microenvironment. Environmental exposures, combined with chronic inflammation, reorganise these networks early on, leading to the formation of premalignant fields and persistent epigenetic changes. The four major ncRNA classes, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and PIWI-interacting RNAs (piRNAs) function as either oncogenes or tumour suppressors depending on the specific cancer type. Their stability, cell-type-specific expression, and presence in biofluids make them suitable candidates for biomarker discovery and liquid biopsy applications. Therapeutic strategies now include antisense oligonucleotides, small interfering RNAs, synthetic miRNA mimics, RNA aptamers, and aptamer-siRNA conjugates, which can either inhibit oncogenic ncRNAs or restore tumour-suppressive regulatory networks. CRISPR-based ncRNA modulation, including Cas9-mediated locus editing, CRISPR interference/activation, and Cas13-mediated transcript targeting, remains largely investigational because delivery, off-target activity, and an incomplete understanding of ncRNA context dependence continue to limit translation. High-throughput sequencing, single-cell transcriptomics, and computational modelling have accelerated the identification of cancer-related ncRNAs and elucidated their biological functions. This review examines how different types of ncRNAs contribute to cancer initiation, progression, and treatment resistance, and assesses their potential as diagnostic markers, prognostic factors, and therapeutic targets.

In this issue of Molecular Cell, Zhu et al.1 uncover a lncRNA-derived micropeptide that disrupts mitochondrial RNA processing, revealing a new layer of metabolic vulnerability in hepatocellular carcinoma (HCC).

Triple-negative breast cancer (TNBC) is a highly metastatic subtype of breast cancer. The epithelial-to-mesenchymal transition is a nonbinary process in the metastatic cascade that generates tumor cells with both epithelial and mesenchymal traits known as hybrid EM cells. Recent studies have elucidated the enhanced metastatic potential of cancers featuring the hybrid EM phenotype, highlighting the need to uncover molecular drivers and targetable vulnerabilities of the hybrid EM state. Here, we discovered that hybrid EM breast tumors are enriched in CD38, an immunosuppressive molecule associated with worse clinical outcomes in liquid malignancies. Altering CD38 expression in tumor cell impacted migratory, invasive, and metastatic capabilities of hybrid EM cells. Abrogation of CD38 expression stimulated an antitumor immune response, thereby preventing the generation of an immunosuppressive microenvironment in hybrid EM tumors. CD38 levels positively correlated with PD-L1 expression in samples from patients with TNBC. Moreover, targeting CD38 potentiated the activity of anti-PD-L1, eliciting strong antitumor immunity, with reduced tumor growth in hybrid EM models. Overall, this research exposes upregulation of CD38 as a specific survival strategy utilized by hybrid EM breast tumors to suppress immune cell activity and sustain metastasis, with strong implications in other carcinomas that have hybrid EM properties. Significance: Hybrid cells co-featuring epithelial and mesenchymal traits in triple-negative breast cancer express elevated levels of CD38 to induce immunosuppression and metastasis, indicating CD38 inhibition as potential strategy for treating breast cancer.

Gastric carcinoma is a highly heterogeneous disease with diverse subtypes, each with distinct histopathological and clinical characteristics, complicating prognosis and treatment. High mortality is driven by molecular and microenvironmental changes, often leading to peritoneal carcinomatosis. MicroRNAs (miRs), particularly miR-10b, play key roles in gastric cancer by promoting drug resistance, migration, and invasiveness. Targeting miR-10b with Small Molecule Inhibitors of miRNAs (SMIRs) offers a novel approach to disrupting RNA-small molecule interactions, presenting promising strategies for halting cancer progression and improving outcomes. We investigated the expression of miRNAs in patients with peritoneal carcinomatosis using miRNA sequencing, followed by RT-qPCR for validation, identifying miR-10b as a candidate therapeutic target. SMIR-10b, a small-molecule inhibitor of miR-10b, was employed to suppress miR-10b expression, leading to increased expression levels of PTEN and HOXD10 post-treatment. The antiproliferative effects of SMIR-10b were assessed in GA0518 cells, with miR-10b and precursor miR-10b expression, as well as target protein levels, evaluated using RT-qPCR, western blotting, and immunofluorescence. To examine the in vivo effects of SMIR-10b, GA0518 cells were xenografted into nude mice. We analyzed miRNA sequencing data and identified miR-10b as a specific target associated with peritoneal carcinomatosis, distinguishing it from normal and tumor tissues. In this context, a gradual increase in the concentration of SMIR-10b resulted in significant downregulation of miR-10b expression, which corresponded to an increase in PTEN and HOXD10 protein levels. Furthermore, SMIR-10b was found to target nuclear precursor miR-10b, suppressing its maturation into mature miR-10b. This led to an accumulation of precursor miR-10b in the nucleus and a concomitant reduction in mature miR-10b levels in the cytoplasm. Our in vivo studies demonstrated that SMIR-10b improved survival rates by reducing the tumorigenicity of GA0518 peritoneal carcinomatosis xenograft tumors. Collectively, these findings suggest that miR-10b is a promising therapeutic target in peritoneal carcinomatosis, contributing to tumorigenesis at least partially by regulating the expression of PTEN and HOXD10. Through specificity analysis, we identified miR-10b, among other miRNAs, as a potential biomarker for peritoneal carcinomatosis. These findings support the therapeutic potential of targeting miR-10b to suppress gastric cancer progression and inhibit the dissemination of cancer cells within the peritoneal cavity, a primary driver of peritoneal carcinomatosis. This approach offers valuable insights into novel therapeutic strategies aimed at combating this aggressive malignancy and improving patient outcomes. Maria-Ancuta Jurj, Michael A. Attathikhun, Meng Chen, Corina Minciuna, Venkata Narayana Vidadala, Gabriele Varani, Jaffer A. Ajani, George A. Calin. microRNA-targeted small molecule inhibitors in metastatic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1186.

Deconvolution methods have traditionally focused on estimating cell-type proportions in bulk tissues with mRNA profiles. They often overlook the cell transcriptional proportion (i.e., transcriptional activity), which reflects the cell functional states and could be important for understanding disease progression (e.g., tumor). Current methods face additional challenges when analyzing other RNA species, such as miRNAs, due to their low abundance and inherent sparsity. Similar limitations also affect spatial transcriptomics (ST) technologies, which enable in situ gene expression profiling but suffer from high data sparsity and limited resolution, with each spot mimicking a mini-bulk sample. Besides, methods for estimating transcriptional activity in ST data remain underdeveloped. To fill this gap, we extended our semi-reference-based DeMixT framework by incorporating a negative binomial (NB) distribution to account for sparse profiling data, namely DeMixNB. DeMixNB models the observed mixed expression Yig for gene g in sample i as the sum of tumor (Tig) and non-tumor (Nig) components, with each component following an NB distribution parameterized by gene-specific means, dispersion parameters, and sample-specific tumor transcriptomic proportions. The NB framework naturally accommodates the sparsity and overdispersion. DeMixNB runs in two tiers: it first leverages non-tumor reference to estimate the non-tumor component parameters, then uses an Iterated Conditional Modes (ICM) to jointly estimate tumor-specific parameters and tumor proportions in mixed samples. We comprehensively validated DeMixNB from three aspects. First, we simulated data under various settings, including sample sizes, degrees of similarity between tumor and non-tumor components, and the number of distributions mixed in tumors. Across all scenarios, DeMixNB consistently achieved higher accuracy compared to existing methods. Then, to create a controlled experimental benchmark for miRNA analysis, we generated artificial mixtures using HS-5 fibroblasts combined with either wild-type or Dicer1 knockout HCT116 colorectal cancer cells at varying proportions. This design represents real tumor samples with known ground truth. DeMixNB maintained robust performance on sparse miRNA expression. To assess its broader utility, we applied DeMixNB to ST data from multiple cancer types. The estimated transcript proportions showed strong concordance with pathological annotations and revealed cell differentiation patterns not captured by conventional cell-type deconvolution methods. The DeMixT 2.0 framework, featuring DeMixNB, provides a robust solution for deconvolving sparse transcriptomic data. By accurately estimating tumor-specific transcriptional proportions, it enables deeper insight tumor heterogeneity at molecular and spatial levels. Hao Yan, Matthew Montierth, Liyang Xie, Peng Yang, Shuai Guo, Ruonan Li, Xiaoxi Pan, Caner Ercan, Yinyin Yuan, Kinga Németh, George A. Calin, Wenyi Wang. DeMixT 2.0: A deconvolution framework for sparse sequencing data using embedded negative binomial distribution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2480.

Neuroblastoma (NB), a devastating pediatric cancer originating from neural crest cells crucial for nervous system development, poses a significant therapeutic challenge. Despite chemotherapy being the primary treatment, approximately 70% of high-risk NB cases develop resistance. Autophagy is vital for neuronal development, balance, and differentiation of neural stem cells into mature neurons. However, the intricate mechanisms governing autophagy and the pivotal genes orchestrating its regulation in NB remain largely elusive. In this study, we first identified Sin3A Associated Protein 30 (SAP30) as a novel regulator of autophagy in NB. Silencing SAP30 inhibits autophagy and disrupts starvation-induced physiological autophagy in NB cells. Conversely, ectopic expression of SAP30 induces autophagy in NB cells under normal or starvation conditions. Mechanistically, SAP30 transcriptionally regulates STX17, a crucial protein involved in autophagosome-lysosome fusion during autophagy. Reduction of SAP30 decreases STX17 expression, hindering its translocation to the autophagic membrane and inhibiting autophagosome-lysosome fusion. SAP30-mediated autophagy enhances cell growth and provides protection in NB cells treated with chemotherapy drugs. Notably, suppressing SAP30 in vivo increases LC3B accumulation, an autophagy marker, along with reduced proliferation markers, both in vivo and in PDX tumors. Therefore, SAP30 emerges as a potential target to enhance NB responsiveness to chemotherapy drugs.

BACKGROUND:Lymph node metastasis is a key driver of poor outcomes in cervical cancer. However, the molecular mechanisms of circular RNAs (circRNAs) driving cervical cancer lymph node metastasis remain unclear. METHODS:We identified circZFR, fatty acid synthase (FASN) and YTH N6-methyladenosine RNA binding protein F3 (YTHDF3) protein expression in the cervical cancer patients with long and short disease-free survival (DFS). Functional experiments were performed to investigate the function of circZFR, FASN and YTHDF3 on cell migration and invasion. MeRIP-qPCR, RNA pulldown, RNA Immunoprecipitation (RIP), and Co-Immunoprecipitation (Co-IP) assays were executed to investigate the mechanism of circZFR regulating FASN protein expression. RESULTS:Our study reveals that elevated FASN protein is closely linked to metastasis and reduced survival, and identified a regulatory mechanism involving circular RNAs. We identified circZFR as a crucial regulator, significantly enhancing FASN protein expression. CircZFR overexpression was significantly correlated with accelerated lymph node metastasis and shortened DFS. Mechanistically, circZFR binds to the m6A reader protein YTHDF3, facilitating m6A recognition on FASN mRNA and recruiting the translation initiator eIF4A3, thereby boosting FASN translation. CONCLUSIONS:These findings establish circZFR as a pivotal driver of cervical cancer progression and highlight its inhibition as a promising therapeutic strategy.

The origin of mucinous cystic neoplasms (MCNs) remains a major challenge in hepato‐pancreato‐biliary pathology. These cystic tumors are defined by their mucinous epithelium and ovarian‐like stroma, with an estimated 10% risk of progression to invasive carcinoma. The origin of the ovarian‐like stroma remains a subject of debate. In this study, we conducted immunohistochemical profiling, targeted DNA sequencing, and genome‐wide DNA methylation analysis on a cohort of 15 pancreatic MCNs (MCN‐P) and six hepatic MCNs (MCN‐L). Using immunohistochemistry and targeted DNA sequencing, we unequivocally established the diagnosis of MCN. Unsupervised DNA methylation profile analysis of reference classes of pancreatic neoplasms (11 entities and normal pancreatic tissue from 224 unique samples) revealed that MCN‐P predominantly forms a distinct group. In the DNA methylation landscape of liver tumors, encompassing five tumor types and normal bile duct tissue from 136 unique samples, MCN‐L demonstrated a specific methylation profile when compared with all other entities. Furthermore, within the DNA methylation landscape of ovarian tumors – featuring five tumor types, normal Fallopian tube, and normal ovarian tissue from 90 unique samples – we found that both MCN‐P and MCN‐L grouped with mucinous ovarian carcinoma and mucinous borderline ovarian tumors (mBOTs). Notably, low‐grade MCNs exhibited greater DNA methylation similarities to mBOTs, while high‐grade or invasive MCNs were primarily associated with mucinous ovarian carcinomas. When analyzing all samples together (19 tumor types and four normal tissue types, n = 430), MCNs similarly grouped with mucinous ovarian tumors and normal ovarian tissue. Additionally, in a network analysis of differentially methylated probes, MCN‐P and MCN‐L share significant methylation traits, closely resembling mucinous ovarian tumors. In conclusion, our findings highlight that MCN‐P and MCN‐L are distinct entities in the landscape of pancreatic and hepatic tumors and show DNA methylation profile similarities with mucinous ovarian tumors, suggesting a potential common origin. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Glioblastoma (GBM) remains difficult to treat due to poor drug delivery across the blood-brain barrier and an immunosuppressive tumor microenvironment (TME). Tumor-suppressive microRNAs (miRNAs) offer a promising strategy to reprogram both tumor cells and the TME, but inefficient delivery systems limit their clinical application. We previously reported that tumor-suppressive miR-138 regresses tumor growth in preclinical GBM models. Here, we demonstrate that trypsin digestion of extracellular vesicles (EVs) enhances labeling efficiency with folate (FA), enhancing selective targeting of folate receptor (FR)-positive GBM cells and enabling simultaneous targeting of tumor-associated macrophages (TAMs). FA-labeled trypsinized EVs (tEVs) loaded with miR-138 inhibit tumor growth, depolarize TAMs, and enhance antitumor immunity. This study represents the first preclinical attempt to modulate tumor cells and innate immunity via miRNA-loaded tEVs, offering a novel and more effective therapeutic approach to GBM treatment.

The origins of immunosuppression, neutropenia, and anemia in patients with chronic lymphocytic leukemia (CLL) are not fully understood. Because in patients with CLL, circulating exosomes, which participate in cell-to-cell interactions, are CLL cell-derived, we examined whether those exosomes contribute to abnormal features of this disease. Our data revealed that CLL cell-derived exosomes engulfed by healthy donors’ monocytes, fibrocytes, and lymphocytes altered target-cell gene and protein expression and suppressed normal hematopoiesis. CLL cell-derived exosomes increased normal monocytes’ CD14 and CD16 expression such that it mimicked the accessory-cell profile and upregulated T cells’ checkpoint PD-1 and CD160 protein levels, potentially reducing T-cell-mediated anti-CLL activity. In normal B cells, CLL cell-derived exosomes induced apoptosis and CD5 expression, suggesting that CLL cell-derived exosomes eliminate B cells and not all CD19+/CD5+ cells in CLL patients are clonal. RNA sequencing and quantitative real-time PCR revealed that CLL cell-derived exosomes harbored RNAs of pro-apoptotic genes and genes that increase metabolism, induce proliferation, and induce constitutive PI3K-mTOR pathway activation. CLL cell-derived exosomes inhibited hematopoietic progenitor proliferation, hindering the supportive effect of monocyte-derived fibrocytes. Together, our findings suggest that CLL cell-derived exosomes disrupt the immune and hematopoietic systems and contribute to disease progression in patients with CLL.