Background: Platelet-derived Extracellular Vesicles, or “Platelet Dust” (PD), are reported as the most-abundant extracellular vesicles in plasma. However, the PD molecular content, especially the small RNA profile, is still poorly characterized. This study aims to characterize PD and other extracellular vesicles (EVs) in patients with non-small-cell lung cancer (NSCLC), focusing on their small RNA signatures and diagnostic potential. Methods: The EVs were isolated directly from the plasma of healthy donors and patients with NSCLC using the surface markers CD9, CD63, CD81 (overall EVs), and CD61 (PD). Small RNA sequencing was then performed to comprehensively profile the miRNAs. Results: Our analysis revealed distinct small RNA profiles in the EVs and the PD from the patients with NSCLC. The EVs (CD9-, CD63-, and CD81-positive) showed the enrichment of four miRNAs and the depletion of ten miRNAs, while the PD (CD61-positive) exhibited a more complex profile, with nineteen miRNAs enriched and nine miRNAs depleted in the patients with NSCLC compared to those of the healthy controls. Conclusions: This exploratory study enhances our understanding of miRNA composition within different plasma vesicle populations, shedding light on the biology of plasma vesicles and their contents. Furthermore, utilizing an extracellular vesicle isolation method with potential clinical applicability offers the prospect of improved cancer characterization and detection by selecting the most informative subpopulation of plasma vesicles.

Background: Liquid biopsy has gained significant attention as a non-invasive method for cancer detection and monitoring. IsomiRs and tRNA-derived fragments (tRFs) are small non-coding RNAs that arise from non-canonical microRNA (miRNAs) processing and the cleavage of tRNAs, respectively. These small non-coding RNAs have emerged as pro-mising cancer biomarkers, and their distinct expression patterns highlight the need for further exploration of their roles in cancer research. Methods: In this study, we investigated the differential expression profiles of miRNAs, isomiRs, and tRFs in plasma extracellular vesicles (EVs) from colorectal and prostate cancer patients compared to healthy controls. Subsequently, a combinatorial analysis using the CombiROC package was performed to identify a panel of biomarkers with optimal diagnostic accuracy. Results: Our results demonstrate that a combination of miRNAs, isomiRs, and tRFs can effectively di- stinguish cancer patients from healthy controls, achieving accuracy and an area under the curve (AUC) of approximately 80%. Conclusions: These findings highlight the potential of a combinatorial approach to small RNA analysis in liquid biopsies for improved cancer diagnosis and management.

Over 95% of head and neck cancers are squamous cell carcinoma (HNSCC). HNSCC is mostly diagnosed late, causing a poor prognosis despite the application of invasive treatment protocols. Tumor-educated platelets (TEPs) have been shown to hold promise as a molecular tool for early cancer diagnosis. We sequenced platelet mRNA isolated from blood of 101 patients with HNSCC and 101 propensity-score matched noncancer controls. Two independent machine learning classification strategies were employed using a training and validation approach to identify a cancer predictor: a particle swarm optimized support vector machine (PSO-SVM) and a least absolute shrinkage and selection operator (LASSO) logistic regression model. The best performing PSO-SVM predictor consisted of 245 platelet transcripts and reached a maximum area under the curve (AUC) of 0.87. For the LASSO-based prediction model, 1,198 mRNAs were selected, resulting in a median AUC of 0.84, independent of HPV status. Our data show that TEP RNA classification by different AI tools is promising in the diagnosis of HNSCC.

The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and therapy personalization. This study presents a multiclass approach based on deep learning to analyze and classify diseases based on blood platelet RNA. Its primary objective is to enhance cancer-type diagnosis in clinical settings by leveraging the power of deep learning combined with high-throughput sequencing of liquid biopsy. Ultimately, the study demonstrates the potential of this approach to accurately identify the patient’s type of cancer. Methods: The developed method classifies patients using heatmap images, generated based on gene expression arranged according to the Kyoto Encyclopedia of Genes and Genomes pathways. The images represent samples of patients with ovarian cancer, endometrial cancer, glioblastoma, non-small cell lung cancer, and sarcoma, as well as cancer patients with brain metastasis. Results: Our deep learning-based models reached 66.51% balanced accuracy when distinguishing between those 6 sites of cancer origin and 90.5% balanced accuracy on a location-specific dataset where cancer types from close locations were grouped. The developed models were further investigated with an explainable artificial intelligence-based approach (XAI) - SHAP. They returned a set of 60 genes with the highest impact on the models’ decision-making process. Conclusions: Our results show that deep-learning methods are a promising opportunity for cancer detection and could support clinicians’ decision-making process in finding the solution for the black-box problem. Clinical and Translational Impact Statement— Utilizing TEPs-based liquid biopsies and deep learning, our study offers a novel approach to early cancer detection, highlighting cancer origin. The integration of Explainable AI reinforces trust in predictive outcomes. Category: Early/Pre-Clinical Research.

BACKGROUND:Anti-PD-(L)1 immunotherapy has emerged as a promising treatment approach for non-small cell lung cancer (NSCLC), though the response rates remain low. Pre-treatment response prediction may improve patient allocation for immunotherapy. Blood platelets act as active immune-like cells, thereby constraining T-cell activity, propagating cancer metastasis, and adjusting their spliced mRNA content.OBJECTIVE:We investigated whether platelet RNA profiles before start of nivolumab anti-PD1 immunotherapy may predict treatment responses.METHODS:We performed RNA-sequencing of platelet RNA samples isolated from stage III-IV NSCLC patients before treatment with nivolumab. Treatment response was scored by the RECIST-criteria. Data were analyzed using a predefined thromboSeq analysis including a particle-swarm-enhanced support vector machine (PSO/SVM) classification algorithm.RESULTS:We collected and processed a 286-samples cohort, separated into a training/evaluation and validation series and subjected those to training of the PSO/SVM-classification algorithm. We observed only low classification accuracy in the 107-samples validation series (area under the curve (AUC) training series: 0.73 (95% -CI: 0.63-0.84, n = 88 samples), AUC evaluation series: 0.64 (95% -CI: 0.51-0.76, n = 91 samples), AUC validation series: 0.58 (95% -CI: 0.45-0.70, n = 107 samples)), employing a five-RNAs biomarker panel.CONCLUSIONS:We concluded that platelet RNA may have minimally discriminative capacity for anti-PD1 nivolumab response prediction, with which the current methodology is insufficient for diagnostic application.

BackgroundGlioblastomas manipulate the immune system both locally and systemically, yet, glioblastoma-associated changes in peripheral blood immune composition are poorly studied. Age and dexamethasone administration in glioblastoma patients have been hypothesized to limit the effectiveness of immunotherapy, but their effects remain unclear. We compared peripheral blood immune composition in patients with different types of brain tumor to determine the influence of age, dexamethasone treatment, and tumor volume.MethodsHigh-dimensional mass cytometry was used to characterise peripheral blood mononuclear cells of 169 patients with glioblastoma, lower grade astrocytoma, metastases and meningioma. We used blood from medically-refractory epilepsy patients and healthy controls as control groups. Immune phenotyping was performed using FlowSOM and t-SNE analysis in R followed by supervised annotation of the resulting clusters. We conducted multiple linear regression analysis between intracranial pathology and cell type abundance, corrected for clinical variables. We tested correlations between cell type abundance and survival with Cox-regression analyses.ResultsGlioblastoma patients had significantly fewer naive CD4+ T cells, but higher percentages of mature NK cells than controls. Decreases of naive CD8+ T cells and alternative monocytes and an increase of memory B cells in glioblastoma patients were influenced by age and dexamethasone treatment, and only memory B cells by tumor volume. Progression free survival was associated with percentages of CD4+ regulatory T cells and double negative T cells.ConclusionHigh-dimensional mass cytometry of peripheral blood in patients with different types of intracranial tumor provides insight into the relation between intracranial pathology and peripheral immune status. Wide immunosuppression associated with age and pre-operative dexamethasone treatment provide further evidence for their deleterious effects on treatment with immunotherapy.

Small extracellular vesicles (sEVs) are heterogenous lipid membrane particles typically less than 200 nm in size and secreted by most cell types either constitutively or upon activation signals. sEVs isolated from biofluids contain RNAs, including small non-coding RNAs (ncRNAs), that can be either encapsulated within the EV lumen or bound to the EV surface. EV-associated microRNAs (miRNAs) are, despite a relatively low abundance, extensively investigated for their selective incorporation and their role in cell-cell communication. In contrast, the sorting of highly-structured ncRNA species is understudied, mainly due to technical limitations of traditional small RNA sequencing protocols. Here, we adapted ALL-tRNAseq to profile the relative abundance of highly structured and potentially methylated small ncRNA species, including transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), and Y RNAs in bulk EV preparations. We determined that full-length tRNAs, typically 75 to 90 nucleotides in length, were the dominant small ncRNA species (>60% of all reads in the 18-120 nucleotides size-range) in all cell culture-derived EVs, as well as in human plasma-derived EV samples, vastly outnumbering 21 nucleotides-long miRNAs. Nearly all EV-associated tRNAs were protected from external RNAse treatment, indicating a location within the EV lumen. Strikingly, the vast majority of luminal-sorted, full-length, nucleobase modification-containing EV-tRNA sequences, harbored a dysfunctional 3' CCA tail, 1 to 3 nucleotides truncated, rendering them incompetent for amino acid loading. In contrast, in non-EV associated extracellular particle fractions (NVEPs), tRNAs appeared almost exclusively fragmented or 'nicked' into tRNA-derived small RNAs (tsRNAs) with lengths between 18 to 35 nucleotides. We propose that in mammalian cells, tRNAs that lack a functional 3' CCA tail are selectively sorted into EVs and shuttled out of the producing cell, offering a new perspective into the physiological role of secreted EVs and luminal cargo-selection.

PDF file, 67KB, (A) List of down-regulated genes in medulloblastoma versus normal cerebellar precursor cells in at least five out of seven mouse medulloblastoma datasets that are also down-regulated in human medulloblastoma versus normal cerebellum. (B) List of genes with GeneOntology "tumor suppressor" own-regulated in at least three out of seven mouse medulloblastoma datasets that are also down-regulated in human medulloblastoma versus normal cerebellum.

Supplementary Methods Supplementary Figure S1. Characterization of KIF5B- and STARD3NL-MET rearrangements. A) IGV screenshots of next-generation sequencing reads from breakpoint regions of KIF5B- and STARD3NL-MET positive patient tissue. Due to homology in both regions the breakpoint region is marked with a red bar. The spanning read indicates the genomic sequence of the rearrangement. B) Dideoxy sequencing of exonic breakpoint regions of patient cDNA extracted from FFPE cuts for KIF5B- and STARD3NL-MET. C) PET/CT scans of KIF5B-MET patient. Numbers below indicate reduction of SUVmax under crizotinib therapy. D) Immunoblots of NIH-3T3 cells transduced with KIF5B-MET (upper panel) and STARD3NL-MET (lower panel) treated with 1 µM crizotinib or tepotinib over time. HSP90 serves as loading control. A representative blot from n=3 independent experiments is shown. E) Dose-response curves (72 h) of Ba/F3 cells stably transduced with KIF5B-MET or STARD3NL-MET supplemented with IL-3 (10% conditioned Wehi-3b media) and treated with crizotinib, tepotinib and erlotinib (as control compound). (n=3) Supplementary Figure S1. Characterization of KIF5B- and STARD3NL-MET rearrangements. A) IGV screenshots of next-generation sequencing reads from breakpoint regions of KIF5B- and STARD3NL-MET positive patient tissue. Due to homology in both regions the breakpoint region is marked with a red bar. The spanning read indicates the genomic sequence of the rearrangement. B) Dideoxy sequencing of exonic breakpoint regions of patient cDNA extracted from FFPE cuts for KIF5B- and STARD3NL-MET. C) PET/CT scans of KIF5B-MET patient. Numbers below indicate reduction of SUVmax under crizotinib therapy. D) Immunoblots of NIH-3T3 cells transduced with KIF5B-MET (upper panel) and STARD3NL-MET (lower panel) treated with 1 µM crizotinib or tepotinib over time. HSP90 serves as loading control. A representative blot from n=3 independent experiments is shown. E) Dose-response curves (72 h) of Ba/F3 cells stably transduced with KIF5B-MET or STARD3NL-MET supplemented with IL-3 (10% conditioned Wehi-3b media) and treated with crizotinib, tepotinib and erlotinib (as control compound). (n=3)

PDF file, 58KB, Kaplan-Meier analysis shows that medulloblastoma patients that have lower expression of DAB2IP have a lower overall survival probability in both metastatic and non-metastatic patients.

PDF file, 46KB, Scatterplot of DAB2IP mRNA expression levels (arbitrary units) in patients based on medulloblastoma subgroup stratification shows that average DAB2IP expression does correlate with a specific subgroup of medulloblastoma.

Background IDH-wildtype glioblastoma (GBM) is a highly malignant primary brain tumor with a median survival of 15 months after standard of care, which highlights the need for improved therapy. Personalized combination therapy has shown to be successful in many other tumor types and could be beneficial for GBM patients. Methods We performed the largest drug combination screen to date in GBM, using a high-throughput effort where we selected 90 drug combinations for their activity onto 25 patient-derived GBM cultures. 43 drug combinations were selected for interaction analysis based on their monotherapy efficacy and were tested in a short-term (3 days) as well as long-term (18 days) assay. Synergy was assessed using dose-equivalence and multiplicative survival metrics. Results We observed a consistent synergistic interaction for 15 out of 43 drug combinations on patient-derived GBM cultures. From these combinations, 11 out of 15 drug combinations showed a longitudinal synergistic effect on GBM cultures. The highest synergies were observed in the drug combinations Lapatinib with Thapsigargin and Lapatinib with Obatoclax Mesylate, both targeting epidermal growth factor receptor and affecting the apoptosis pathway. To further elaborate on the apoptosis cascade, we investigated other, more clinically relevant, apoptosis inducers and observed a strong synergistic effect while combining Venetoclax (BCL targeting) and AZD5991 (MCL1 targeting). Conclusions Overall, we have identified via a high-throughput drug screening several new treatment strategies for GBM. Moreover, an exceptionally strong synergistic interaction was discovered between kinase targeting and apoptosis induction which is suitable for further clinical evaluation as multi-targeted combination therapy.

PDF file, 79KB, (A) Microarray datasets characteristics. (B) List of tumor suppressor genes, established by interrogating the Amigo and NCBI Gene Ontology (GO) databases.

Abstract MicroRNA (miRNA) expression profiling studies revealed a number of miRNAs dysregulated in the malignant brain tumor glioblastoma. Molecular functions of these miRNAs in gliomagenesis are mainly unknown. We show that inhibition of miR-10b, a miRNA not expressed in human brain and strongly upregulated in both low-grade and high-grade gliomas, reduces glioma cell growth by cell-cycle arrest and apoptosis. These cellular responses are mediated by augmented expression of the direct targets of miR-10b, including BCL2L11/Bim, TFAP2C/AP-2γ, CDKN1A/p21, and CDKN2A/p16, which normally protect cells from uncontrolled growth. Analysis of The Cancer Genome Atlas expression data set reveals a strong positive correlation between numerous genes sustaining cellular growth and miR-10b levels in human glioblastomas, while proapoptotic genes anticorrelate with the expression of miR-10b. Furthermore, survival of glioblastoma patients expressing high levels of miR-10 family members is significantly reduced in comparison to patients with low miR-10 levels, indicating that miR-10 may contribute to glioma growth in vivo. Finally, inhibition of miR-10b in a mouse model of human glioma results in significant reduction of tumor growth. Altogether, our experiments validate an important role of miR-10b in gliomagenesis, reveal a novel mechanism of miR-10b–mediated regulation, and suggest the possibility of its future use as a therapeutic target in gliomas. Cancer Res; 71(10); 3563–72. ©2011 AACR.

PDF file, 27KB, Colony formation of DAB2IP overexpressing Daoy cells following treatment with a low dose of TNFα compared to untreated cells.

Background: Cannabinoids have been suggested to alleviate frequently experienced symptoms of reduced mental well-being such as anxiety and depression. Mental well-being is an important subdomain of health-related quality of life (HRQoL). Reducing symptoms and maintaining HRQoL are particularly important in malignant primary brain tumor patients, as treatment options are often noncurative and prognosis remains poor. These patients frequently report unprescribed cannabinoid use, presumably for symptom relieve. As studies on brain tumor patients specifically are lacking, we performed a meta-analysis of the current evidence on cannabinoid efficacy on HRQoL and mental well-being in oncological and neurological patients. Methods: We performed a systematic PubMed, PsychINFO, Embase, and Web of Science search according to PRISMA guidelines on August 2 and 3, 2021. We included randomized controlled trials (RCTs) that assessed the effects of tetrahydrocannabinol (THC) or cannabidiol (CBD) on general HRQoL and mental well-being. Pooled effect sizes were calculated using Hedges g. Risk of bias of included studies was assessed using Cochrane's Risk of Bias tool. Results: We included 17 studies: 4 in oncology and 13 in central nervous system (CNS) disease. Meta-analysis showed no effect of cannabinoids on general HRQoL (g=-0.02 confidence interval [95% CI -0.11 to 0.06]; p=0.57) or mental well-being (g=-0.02 [95% CI -0.16 to 0.13]; p=0.81). Conclusions: RCTs in patients with cancer or CNS disease showed no effect of cannabinoids on HRQoL or mental well-being. However, studies were clinically heterogeneous and since many glioma patients currently frequently use cannabinoids, future studies are necessary to evaluate its value in this specific population.

Platelets are reprogrammed by cancer via a process called education, which favors cancer development. The transcriptional profile of tumor-educated platelets (TEPs) is skewed and therefore practicable for cancer detection. This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n = 3; Netherlands, n = 5; Poland, n = 1) between September 2016 and May 2019. The main outcomes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889-0.948), 0.923 (0.855-0.990), 0.918 (0.872-0.963), and 0.887 (0.813-0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889-0.955) in the combined validation cohort; 0.955 (0.912-0.997) in VC1; 0.939 (0.901-0.977) in VC2; 0.917 (0.824-1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, and early-stage ovarian cancer. However, these observations warrant prospective validations in a larger population before clinical utilities.

PDF file, 63KB, (A) Expression levels of DAB2IP mRNA compared to EZH2 mRNA levels in individual patients show a significant negative correlation. (B) Protein expression analysis of DAB2IP and EZH2 in various medulloblastoma cells and non-neoplastic brain.

Background: Platelets are active players in hemostasis, coagulation and also tumorigenesis. The cross-talk between platelets and circulating tumor cells (CTCs) may have various pro-cancer effects, including promoting tumor growth, epithelial-mesenchymal transition (EMT), metastatic cell survival, adhesion, arrest and also pre-metastatic niche and metastasis formation. Interaction with CTCs might alter the platelet transcriptome. However, as CTCs are rare events, the cross-talk between CTCs and platelets is poorly understood. Here, we used our established colon CTC lines to investigate the colon CTC-platelet cross-talk in vitro and its impact on the behavior/phenotype of both cell types. Methods: We exposed platelets isolated from healthy donors to thrombin (positive control) or to conditioned medium from three CTC lines from one patient with colon cancer and then we monitored the morphological and protein expression changes by microscopy and flow cytometry. We then analyzed the transcriptome by RNA-sequencing of platelets indirectly (presence of a Transwell insert) co-cultured with the three CTC lines. We also quantified by reverse transcription-quantitative PCR the expression of genes related to EMT and cancer development in CTCs after direct co-culture (no Transwell insert) with platelets. Results: We observed morphological and transcriptomic changes in platelets upon exposure to CTC conditioned medium and indirect co-culture (secretome). Moreover, the expression levels of genes involved in EMT (p < 0.05) were decreased in CTCs co-cultured with platelets, but not of genes encoding mesenchymal markers (FN1 and SNAI2). The expression levels of genes involved in cancer invasiveness (MYC, VEGFB, IL33, PTGS2, and PTGER2) were increased. Conclusion: For the first time, we studied the CTC-platelet cross-talk using our unique colon CTC lines. Incubation with CTC conditioned medium led to platelet aggregation and activation, supporting the hypothesis that their interaction may contribute to preserve CTC integrity during their journey in the bloodstream. Moreover, co-culture with platelets influenced the expression of several genes involved in invasiveness and EMT maintenance in CTCs.

Supplementary Table 1 from miRNA-7 Attenuation in Schwannoma Tumors Stimulates Growth by Upregulating Three Oncogenic Signaling Pathways