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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.

Blood-based liquid biopsies are an upcoming approach for earlier cancer detection, diagnostics, prognostics, therapy-response prediction, and therapy monitoring, including in patients with tumors of the central nervous system. Among these, liquid biopsies are plasma-derived markers such as cell-free DNA, RNA and proteins, extracellular vesicles, circulating glioma cells, immune cells, and blood platelets. Blood platelets are involved in the local and systemic response to the presence of cancer, thereby sequestering and splicing RNAs, which may be clinically useful as blood-based biomarkers. In this review, we discuss the available literature regarding the role of blood platelets in gliomas and provide suggestions for future research efforts.

Rationale: Pulmonary hypertension encompasses progressive disorders leading to right ventricular dysfunction and early death. Late detection is an important cause of poor clinical outcomes. However, biomarkers that accurately predict the presence of pulmonary hypertension are currently lacking. Objectives: In this study, we provide evidence that blood platelets contain a distinctive ribonucleic acid (RNA) profile that may be exploited for the detection of pulmonary hypertension. Methods: Blood platelet RNA was isolated prospectively from 177 prevalent patients with different subtypes of pulmonary hypertension as well as 195 control subjects clinically not suspected of pulmonary hypertension. Sequencing libraries were created using SMARTer (Switching Mechanism at 5' end of RNA Template) copy desoxyribonucleic acid amplification and sequenced on the Illumina High Throughput Sequencing platform. RNA-sequencing reads were mapped to the human reference genome, and intron-spanning spliced RNA reads were selected. Differential spliced RNA panels were calculated by analysis of variance statistics. A particle swarm optimization-enhanced classification algorithm was built employing a development (n = 213 samples) and independent validation series (n = 159 samples). Results: We detected a total of 4,014 different RNAs in blood platelets from patients with pulmonary hypertension (n = 177) and asymptomatic control subjects (n = 195). Gene ontology analysis revealed enhanced RNA concentrations for genes related to RNA processing, translation, and mitochondrial function. A particle swarm optimization-selected RNA panel of 408 distinctive differentially spliced RNAs mediated detection of pulmonary hypertension with 93% sensitivity, 62% specificity, 77% accuracy, 0.89 (95% confidence interval, 0.83-0.93) area under the curve, and a negative predictive value of 91% in the independent validation series. The prediction score was independent of age, sex, smoking, pulmonary hypertension subtype, and the use of pulmonary hypertension-specific medication or anticoagulants. Conclusions: A platelet RNA panel may accurately discriminate patients with pulmonary hypertension from asymptomatic control subjects. In the light of current diagnostic delays, this study is the starting point for further development and evaluation of a platelet RNA-based blood test to ultimately improve early diagnosis and clinical outcomes in patients with pulmonary hypertension.

Blood-based diagnostics tests, using individual or panels of biomarkers, may revolutionize disease diagnostics and enable minimally invasive therapy monitoring. However, selection of the most relevant biomarkers from liquid biosources remains an immense challenge. We recently presented the thromboSeq pipeline, which enables RNA sequencing and cancer classification via self-learning and swarm intelligence-enhanced bioinformatics algorithms using blood platelet RNA. Here, we provide the wet-lab protocol for the generation of platelet RNA-sequencing libraries and the dry-lab protocol for the development of swarm intelligence-enhanced machine-learning-based classification algorithms. The wet-lab protocol includes platelet RNA isolation, mRNA amplification, and preparation for next-generation sequencing. The dry-lab protocol describes the automated FASTQ file pre-processing to quantified gene counts, quality controls, data normalization and correction, and swarm intelligence-enhanced support vector machine (SVM) algorithm development. This protocol enables platelet RNA profiling from 500 pg of platelet RNA and allows automated and optimized biomarker panel selection. The wet-lab protocol can be performed in 5 d before sequencing, and the algorithm development can be completed in 2 d, depending on computational resources. The protocol requires basic molecular biology skills and a basic understanding of Linux and R. In all, with this protocol, we aim to enable the scientific community to test platelet RNA for diagnostic algorithm development.

Background: Morpho-physiological alternations of platelets provided a rationale to harness RNA sequencing of tumor-educated platelets (TEPs) for preoperative diagnosis of cancer. Timely, accurate, and non-invasive detection of ovarian cancer in women with adnexal masses presents a significant clinical challenge. Patients and Methods: 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. Results: 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. Analysis of public datasets suggested that TEPs had potential to detect multiple malignancies (Table 1). Conclusions: TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, early-stage ovarian cancer as well as other malignancies. However, these observations warrant prospective validations in a larger population before clinical utilities. Table 1. Performance for TEPs in public pan-cancer datasets. Disease n Healthy Control AUC, area under the curve (95% CI) Women NSCLC (non-small-cell lung cancer) 126 77 0.758 (0.691-0.825) Breast cancer 38 77 0.817 (0.726-0.909) Colorectal cancer 18 77 0.973 (0.945-1.000) Pancreatic cancer 16 77 0.993 (0.981-1.000) Glioblastoma 10 77 0.923 (0.831-1.000) Men NSCLC 119 82 0.746 (0.677-0.815) Colorectal cancer 25 82 0.933 (0.884-0.982) Pancreatic cancer 22 82 0.993 (0.984-1.000) Glioblastoma 19 82 0.981 (0.959-1.000) All NSCLC 245 159 0.774 (0.728-0.820) Colorectal cancer 40 159 0.978 (0.961-0.996) Breast cancer 38 159 0.821 (0.736-0.906) Pancreatic cancer 35 159 0.987 (0.974-0.999) Glioblastoma 35 159 0.931 (0.890-0.972) Hepatobiliary carcinomas 14 159 0.991 (0.978-1.000) Citation Format: Yue Gao, Chun-Jie Liu, Hua-Yi Li, Xiao-Ming Xiong, Sjors G.j.g. In ‘t Veld, Gui-Ling Li, Jia-Hao Liu, Guang-Yao Cai, Gui-Yan Xie, Shao-Qing Zeng, Yuan Wu, Jian-Hua Chi, Qiong Zhang, Xiao-Fei Jiao, Lin-Li Shi, Wan-Rong Lu, Wei-Guo Lv, Xing-Sheng Yang, Jurgen M.j. Piek, Cornelis D de Kroon, C.a.r. Lok, Anna Supernat, Sylwia Łapińska-Szumczyk, Anna Łojkowska, Anna J. Żaczek, Jacek Jassem, Bakhos A. Tannous, Nik Sol, Edward Post, Myron G. Best, Bei-Hua Kong, Xing Xie, Ding Ma, Thomas Wurdinger, An-Yuan Guo, Qing-Lei Gao. Platelet RNA signature enables early and accurate detection of ovarian cancer: An intercontinental, biomarker identification study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB168.

Summary Tumor-educated platelets (TEPs) are potential biomarkers for cancer diagnostics. We employ TEP-derived RNA panels, determined by swarm intelligence, to detect and monitor glioblastoma. We assessed specificity by comparing the spliced RNA profile of TEPs from glioblastoma patients with multiple sclerosis and brain metastasis patients (validation series, n = 157; accuracy, 80%; AUC, 0.81 [95% CI, 0.74–0.89; p < 0.001]). Second, analysis of patients with glioblastoma versus asymptomatic healthy controls in an independent validation series (n = 347) provided a detection accuracy of 95% and AUC of 0.97 (95% CI, 0.95–0.99; p < 0.001). Finally, we developed the digitalSWARM algorithm to improve monitoring of glioblastoma progression and demonstrate that the TEP tumor scores of individual glioblastoma patients represent tumor behavior and could be used to distinguish false positive progression from true progression (validation series, n = 20; accuracy, 85%; AUC, 0.86 [95% CI, 0.70–1.00; p < 0.012]). In conclusion, TEPs have potential as a minimally invasive biosource for blood-based diagnostics and monitoring of glioblastoma patients., Graphical Abstract, Highlights TEP RNA enables blood-based brain tumor diagnostics TEP RNA is dynamic throughout anti-tumor treatment TEP RNA may be employed for therapy monitoring, Sol et al. show that tumor-educated platelets (TEPs) can be employed for detection of glioblastoma. Glioblastoma TEP RNA profiles can be differentiated from patients with metastatic brain cancer or MS. Furthermore, the tumor signals in TEPs are dynamic, indicating that TEPs can be employed for blood-based therapy monitoring.

BackgroundIn multiple sclerosis (MS), clinical assessment, MRI and cerebrospinal fluid are important in the diagnostic process. However, no blood biomarker has been confirmed as a useful tool in the diagnostic work-up.ObjectivesBlood platelets contain a rich spliced mRNA repertoire that can alter during megakaryocyte development but also during platelet formation and platelet circulation. In this proof of concept study, we evaluate the diagnostic potential of spliced blood platelet RNA for the detection of MS.MethodsWe isolated and sequenced platelet RNA of blood samples obtained from 57 MS patients and 66 age- and gender-matched healthy controls (HCs). 60% was used to develop a particle swarm-optimized (PSO) support vector machine classification algorithm. The remaining 40% served as an independent validation series.ResultsIn total, 1249 RNAs with differential spliced junction expression levels were identified between platelets of MS patients as compared to HCs, including EPSTI1, IFI6, and RPS6KA3, in line with reported inflammatory signatures in the blood of MS patients. The RNAs were subsequently used as input for a MS classifier, capable of detecting MS with 80% accuracy in the independent validation series.ConclusionsSpliced platelet RNA may enable the blood-based diagnosis of MS, warranting large-scale validation.

Diffuse gliomas are the most common malignant primary tumors of the central nervous system. Like other neoplasms, these gliomas release molecular information into the circulation. Tumor-derived biomarkers include proteins, nucleic acids, and tumor-derived extracellular vesicles that accumulate in plasma, serum, blood platelets, urine and/or cerebrospinal fluid. Recently, also circulating tumor cells have been identified in the blood of glioma patients. Circulating molecules, vesicles, platelets, and cells may be useful as easily accessible diagnostic, prognostic and/or predictive biomarkers to guide patient management. Thereby, this approach may help to circumvent problems related to tumor heterogeneity and sampling error at the time of diagnosis. Also, liquid biopsies may allow for serial monitoring of treatment responses and of changes in the molecular characteristics of gliomas over time. In this review, we summarize the literature on blood-based biomarkers and their potential value for improving the management of patients with a diffuse glioma. Incorporation of the study of circulating molecular biomarkers in clinical trials is essential for further assessment of the potential of liquid biopsies in this context. Electronic supplementary material The online version of this article (doi:10.1007/s00401-015-1399-y) contains supplementary material, which is available to authorized users.

Platelets are equipped with RNA processing machineries, such as pre-mRNA splicing, pre-miRNA processing, and mRNA translation. Since platelets are devoid of a nucleus, most RNA transcripts in platelets are derived from megakaryocytes during thrombocytogenesis. However, platelets can also ingest RNA molecules during circulation and/or interaction with other cell types. Since platelets were first described by Bizzozero in 1881, their well-established role in hemostasis and thrombosis has been intensively studied. However, in the past decades, the list of biological processes in which platelets play an important role keeps expanding. In this review, we discuss how platelet RNA biomarker signatures can be altered in the presence of cancer.

Introduction Detection of early-stage breast cancer from blood is a highly desirable screening application of liquid biopsies. Tumor-educated platelets (TEP) contain distinct spliced RNA repertoires and can function as a blood-based biosource for the detection of cancer (Best et al. Cancer Cell 2015). Here, we investigated the potential of TEP RNA profiles as an early breast cancer diagnostics algorithm. Material and methods We sequenced platelets of women with stage I-III breast cancer (n=134) and asymptomatic non-cancer females (n=121). Samples were divided over a training, evaluation and validation set. We developed a TEP RNA-based classification algorithm, which was tailored towards two clinically relevant diagnostic applications. The first application is to rule out breast cancer in women with an abnormal mammography. The second application is to rule in breast cancer in asymptomatic women carrying an elevated baseline breast cancer risk. We examined if classifications depended on patient age, tumour stage, subtype, BRCA mutation status, and breast density. In addition, we tested if the algorithm was breast cancer specific by testing our algorithm in a pan-cancer cohort (n=192). Results and discussions In the evaluation cohort (n=48 of which n=24 early breast cancer cases) the TEP RNA-based breast cancer classification had an accuracy of 90% with an AUC of 0.96 (95% confidence interval (CI) 0.92–1.00; p Conclusion We show that platelet RNA signatures may enable blood-based screening for early breast cancer, and warrant validation in a confirmatory and screening setting.

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at advanced disease stages and invasive procedures are needed to confirm diagnosis. Innovative liquid biopsy-based approaches are warranted to diagnose early stages and prevent unnecessary treatment for advanced disease or misdiagnosed benign diseases. CA19.9 is the only clinically implemented biomarker, but its sensitivity is inadequate and it lacks specificity. Spliced messenger RNA (mRNA) of tumor-educated platelets (TEPs) emerged recently as new potent pan-cancer biomarker (Best et al, Cancer Cell 2015&2017). The aim of this study was to evaluate PDAC-specific TEP profiles as diagnostic and staging biomarker. Samples were collected at four international academic centers. Firstly, TEPs were isolated from blood of 135 PDAC patients including early disease (stage I-IIb), advanced disease (stage III) and metastatic patients (stage IV). In addition, 250 age-matched healthy controls (HC) and 72 patients with a benign disease in the pancreaticobiliary tract were included to create a heterogeneous control group that reflects the real patient population at the outpatient clinic. After total RNA was isolated, SMARTer amplification was performed and whole transcriptome mRNA was sequenced on the Illumina platform. Intron-spanning platelet mRNA reads were selected for further differential expression analysis. PDAC patients had a significant different mRNA TEP profile compared to HC (p-value Citation Format: Tessa Ya Sung Le Large, Laura L. Meijer, Sjors G. In ‘t Veld, Nik Sol, Myron G. Best, Giulia Mantini, Ewoud van der Lelij, Francois Rustenburg, Heleen Verschueren, Niccola Funel, Ingrid Garajova, Maarten F. Bijlsma, Marc G. Besselink, Elisa Giovannetti, Tom Wurdinger, Geert Kazemier. Spliced messenger RNA of tumor-educated platelets yields a new diagnostic prospective for pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2596.

INTRODUCTION: Blood-based liquid biopsies are a potential approach for leveraging clinical cancer diagnostics and patients' treatment. However, so far, diagnostic, prognostic, predictive, and monitoring biomarkers for patients with diffuse glioma are only limitedly available, and require further validation. Tumor-educated blood platelets (TEPs) sequester several biomolecules, including EGFRvIII mRNA, during tumor growth, thereby altering their RNA profile. Therefore, we reasoned that TEPs may serve as an potential biosource for blood-based biomarkers. METHODS: Blood platelets of patients with glioblastoma and healthy individuals were isolated and subjected to total RNA isolation. Platelet mRNA was amplified using full-length SMARTer mRNA amplification, and processed for sequencing on the Illumina platform. Raw sequencing data was aligned and summarized to the human reference genome using STAR and HTseq, and subjected to differential expression analyses, hierarchical clustering and support vector machine (SVM) classification. RESULTS: We characterized the platelet RNA of 39 glioblastoma patients, and 52 healthy individuals by high-throughput RNA-sequencing. Glioblastoma patient-derived TEPs contained 457 RNAs (FDR < 0.001) that were differentially expressed as compared to healthy individuals. Gene ontology showed that these RNAs are implicated in several biological processes such as RNA translation, immune response, and DNA repair. Using SVM classification we readily separated both groups from each other (accuracy: 94%, AUC: 0.982). CONCLUSIONS AND FUTURE EXPERIMENTS: Our results suggest that TEPs harbour potential as a diagnostic biosource. To further evaluate the biomarker potential, follow-up studies using additional samples, including samples of lower grade glioma and brain metastases patients are under way. Furthermore, we have initiated the collection of clinical follow-up platelet samples to identify the potential of TEPs as disease monitoring biomarkers in glioma patients. Eventually, we believe TEPs have the potential to guide clinical decision making in every day practice.

Summary Tumor-educated blood platelets (TEPs) are implicated as central players in the systemic and local responses to tumor growth, thereby altering their RNA profile. We determined the diagnostic potential of TEPs by mRNA sequencing of 283 platelet samples. We distinguished 228 patients with localized and metastasized tumors from 55 healthy individuals with 96% accuracy. Across six different tumor types, the location of the primary tumor was correctly identified with 71% accuracy. Also, MET or HER2-positive, and mutant KRAS, EGFR, or PIK3CA tumors were accurately distinguished using surrogate TEP mRNA profiles. Our results indicate that blood platelets provide a valuable platform for pan-cancer, multiclass cancer, and companion diagnostics, possibly enabling clinical advances in blood-based “liquid biopsies”., Graphical Abstract, Highlights • Tumors “educate” platelets (TEPs) by altering the platelet RNA profile • TEPs provide a RNA biosource for pan-cancer, multiclass, and companion diagnostics • TEP-based liquid biopsies may guide clinical diagnostics and therapy selection • A total of 100–500 pg of total platelet RNA is sufficient for TEP-based diagnostics, Best et al. show that mRNA sequencing of tumor-educated blood platelets distinguishes cancer patients from healthy individuals with 96% accuracy, differentiates between six primary tumor types of patients with 71% accuracy, and identifies several genetic alterations found in tumors.

Summary Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92–0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83–0.95; p, Graphical Abstract, Highlights • Tumor-educated platelet (TEP) RNA profiles allow for blood-based cancer diagnostics • Inflammatory conditions only minimally confound TEP-based cancer detection • Swarm intelligence algorithms enable efficient selection of biomarker gene panels • TEP gene panels enable support vector machine-based classification of lung cancer, Best et al. use particle-swarm optimization algorithms and RNA-seq of tumor-educated platelets from patients to generate RNA sets capable of identifying patients with non-small-cell lung cancer, including those having early stage, from individuals without cancer, including those having inflammatory conditions.

I: Studies have shown the activity of anti-PD(L)-1 therapies in patients with advanced non-small-cell lung cancer (NSCLC), however response rates are rather low (~20%). Therefore, there is an urgent need to identify biomarkers that predict patient outcome to immunotherapy (IT). Previously we have shown that RNA signatures of tumor-educated platelets (TEPs) may have predictive value for tumor type-specific diagnostics. Platelets are intimately involved in immune responses. We hypothesized that TEP RNA profiles have predictive value for IT response. M: We collected baseline platelet pellets, isolated from whole blood by differential centrifugation, from 389 stage IV NSCLC patients treated with Nivolumab (table 1). Tumor response was evaluated at 3 and 6 months and reported according to RECIST 1.1. Platelet pellets were subjected to total RNA isolation, SMARTer cDNA amplification, and libraries were sequenced on the HiSeq platform. Raw data (~20 M reads per sample) was mapped to the human genome, intron-spanning spliced RNA reads were selected for analysis. Gene panels were calculated by ANOVA statistics. R: Until now 64 samples were sequenced, 30 of patients with clinical benefit (PR or SD at six months; CB) and 34 of patients with no clinical benefit (PD; no CB). 40 randomly selected samples (20 CB, 20 no CB) were used for training of the support vector machine (SVM)-based therapy response classification algorithm. 24 samples were used for independent evaluation of the classifier. Hierarchical clustering of genes with p Table 1.Patient CharacteristicsTotal CohortNumber of patients389Start of treatmentAugust 2015-november 2016Date lock1th of November, 2016Gender (Male)56%Age (med, range)64.5 years (29-83)Treatment lines1st line1%2nd line72%>2nd line27%DiagnosisNon-Squamous68%Squamous26%Other6%ResponseClinical benefit27%Progressive54%Unknown19%PD-L1 expressionResults expected in april Citation Format: Mirte Muller, Myron Best, Nik Sol, Anna-Larissa N. Niemeijer, Adrienne Vancura, Robert D. Schouten, Jeroen J.N. Hiltermann, Sjors G.J.G. In 't Veld, Daan van den Broek, Vincent van der Noort, Adrianus J. de Langen, Ed M.D. Schuuring, Thomas Wurdinger, Michel M. van den Heuvel. RNA-sequencing of tumor-educated platelets enables nivolumab immunotherapy response prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-248. doi:10.1158/1538-7445.AM2017-LB-248

In his letter “A word of caution on new and revolutionary diagnostic tests,” Dr. Diamandis argues that discoveries and progress in the field of biomarker discovery for the early detection of cancer are hampered by multiple factors, including pre- and post-analytical and bioinformatics artifacts. He further indicates that careful patient selection is crucial.

BACKGROUND: Glioblastomas exhibit a high level of chemotherapeutic resistance, including to the antimitotic agents vincristine and taxol. During the mitotic agent-induced arrest, glioblastoma cells are able to perform damage-control and self-repair to continue proliferation. Monopolar spindle 1 (MPS1/TTK) is a checkpoint kinase and a gatekeeper of the mitotic arrest.METHODS: We used glioblastoma cells to determine the expression of MPS1 and to determine the effects of MPS1 inhibition on mitotic errors and cell viability in combination with vincristine and taxol. The effect of MPS1 inhibition was assessed in different orthotopic glioblastoma mouse models (n = 3-7 mice/group). MPS1 expression levels were examined in relation to patient survival.RESULTS: Using publicly available gene expression data, we determined that MPS1 overexpression corresponds positively with tumor grade and negatively with patient survival (two-sided t test, P < .001). Patients with high MPS1 expression (n = 203) had a median and mean survival of 487 and 913 days (95% confidence intervals [CI] = 751 to 1075), respectively, and a 2-year survival rate of 35%, whereas patients with intermediate MPS1 expression (n = 140) had a median and mean survival of 858 and 1183 days (95% CI = 1177 to 1189), respectively, and a 2-year survival rate of 56%. We demonstrate that MPS1 inhibition by RNAi results in sensitization to antimitotic agents. We developed a selective small-molecule inhibitor of MPS1, MPS1-IN-3, which caused mitotic aberrancies in glioblastoma cells and, in combination with vincristine, induced mitotic checkpoint override, increased aneuploidy, and augmented cell death. MPS1-IN-3 sensitizes glioblastoma cells to vincristine in orthotopic mouse models (two-sided log-rank test, P < .01), resulting in prolonged survival without toxicity.CONCLUSIONS: Our results collectively demonstrate that MPS1, a putative therapeutic target in glioblastoma, can be selectively inhibited by MPS1-IN-3 sensitizing glioblastoma cells to antimitotic drugs.

Allowance of tumor-educated platelets for multiclass liquid biopsy-based diagnosis of cancer

Tumor-educated Platelets (TEPs) have emerged as rich biosources of cancer-related RNA profiles in liquid biopsies applicable for cancer detection. Although human blood platelets have been found to be enriched in circular RNA (circRNA), no studies have investigated the potential of circRNA as platelet-derived biomarkers for cancer. In this proof-of-concept study, we examine whether the circRNA signature of blood platelets can be used as a liquid biopsy biomarker for the detection of non-small cell lung cancer (NSCLC). We analyzed the total RNA, extracted from the platelet samples collected from NSCLC patients and asymptomatic individuals, using RNA sequencing (RNA-Seq). Identification and quantification of known and novel circRNAs were performed using the accurate CircRNA finder suite (ACFS), followed by the differential transcript expression analysis using a modified version of our thromboSeq software. Out of 4732 detected circRNAs, we identified 411 circRNAs that are significantly (p-value < 0.05) differentially expressed between asymptomatic individuals and NSCLC patients. Using the false discovery rate (FDR) of 0.05 as cutoff, we selected the nuclear receptor-interacting protein 1 (NRIP1) circRNA (circNRIP1) as a potential biomarker candidate for further validation by reverse transcription–quantitative PCR (RT-qPCR). This analysis was performed on an independent cohort of platelet samples. The RT-qPCR results confirmed the RNA-Seq data analysis, with significant downregulation of circNRIP1 in platelets derived from NSCLC patients. Our findings suggest that circRNAs found in blood platelets may hold diagnostic biomarkers potential for the detection of NSCLC using liquid biopsies., Marie SkłodowskaCurie Grant Agreement No. 765492., Cancer Center Amsterdam (CCA) Foundation (Grant #CCA2017-2-16).