Blood platelet RNA profiles do not enable for nivolumab response prediction at baseline in patients with non-small cell lung cancer

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.

In vitro cross-talk between metastasis-competent circulating tumor cells and platelets in colon cancer: a malicious association during the harsh journey in the blood

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.

Discrimination Between Pre- and Postcapillary Pulmonary Hypertension Using Platelet RNA

Background Appropriate treatment of pulmonary hypertension (PH) is critically dependent on accurate discrimination between pre- and postcapillary PH. However, clinical discrimination is challenging and frequently requires a right heart catheterization. Existing risk scores to detect postcapillary PH have suboptimal discriminatory strength. We have previously shown that platelet-derived RNA profiles may have diagnostic value for PH detection. Here, we hypothesize that platelet-derived RNAs can be employed to select unique biomarker panels for the discrimination between pre- and postcapillary PH. Methods and Results Blood platelet RNA from whole blood was isolated and sequenced from 50 patients with precapillary PH (with different PH subtypes) as well as 50 patients with postcapillary PH. RNA panels were calculated by ANOVA statistics, and classifications were performed using a support vector machine algorithm, supported by particle swarm optimization. We identified in total 4279 different RNAs in blood platelets from patients with pre- and postcapillary PH. A particle swarm optimization-selected RNA panel of 1618 distinctive RNAs with differential levels together with a trained support vector machine algorithm accurately discriminated patients with precapillary PH from patients with postcapillary PH with 100% sensitivity, 60% specificity, 80% accuracy, and 0.95 (95% CI, 0.86-1.00) area under the curve in the independent validation series (n=20). Conclusions This proof-of-concept study demonstrates that particle swarm optimization/support vector machine-enhanced classification of platelet RNA panels may be able to discriminate precapillary PH from postcapillary PH. This research provides a foundation for the development of a blood test with a high negative predictive value that would improve early diagnosis of precapillary PH and prevents unnecessary invasive testing in patients with postcapillary PH.

Tumor-educated platelet blood tests for Non-Small Cell Lung Cancer detection and management

Liquid biopsy approaches offer a promising technology for early and minimally invasive cancer detection. Tumor-educated platelets (TEPs) have emerged as a promising liquid biopsy biosource for the detection of various cancer types. In this study, we processed and analyzed the TEPs collected from 466 Non-small Cell Lung Carcinoma (NSCLC) patients and 410 asymptomatic individuals (controls) using the previously established thromboSeq protocol. We developed a novel particle-swarm optimization machine learning algorithm which enabled the selection of an 881 RNA biomarker panel (AUC 0.88). Herein we propose and validate in an independent cohort of samples (n = 558) two approaches for blood samples testing: one with high sensitivity (95% NSCLC detected) and another with high specificity (94% controls detected). Our data explain how TEP-derived spliced RNAs may serve as a biomarker for minimally-invasive clinical blood tests, complement existing imaging tests, and assist the detection and management of lung cancer patients.

Platelet-Based Liquid Biopsies through the Lens of Machine Learning

Liquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability to the model. In this work, we have used RNA sequencing data of tumor-educated platelets (TEPs) and performed a binary classification (cancer vs. no-cancer). First, we compiled a large-scale dataset with more than a thousand donors. Further, we used different convolutional neural networks (CNNs) and boosting methods to evaluate the classifier performance. We have obtained an impressive result of 0.96 area under the curve. We then identified different clusters of splice variants using expert knowledge from the Kyoto Encyclopedia of Genes and Genomes (KEGG). Employing boosting algorithms, we identified the features with the highest predictive power. Finally, we tested the robustness of the models using test data from novel hospitals. Notably, we did not observe any decrease in model performance. Our work proves the great potential of using TEP data for cancer patient classification and opens the avenue for profound cancer diagnostics.

Platelet RNA sequencing for cancer screening in patients with unprovoked venous thromboembolism: a prospective cohort study

BACKGROUND

Platelet RNA sequencing has been shown to accurately detect cancer in previous studies.

OBJECTIVES

To compare the diagnostic accuracy of platelet RNA sequencing with standard-of-care limited cancer screening in patients with unprovoked venous thromboembolism (VTE).

METHODS

Patients aged ≥40 years with unprovoked VTE were recruited at 13 centers and followed for 12 months for cancer. Participants underwent standard-of-care limited cancer screening, and platelet RNA sequencing analysis was performed centrally at study end for cases and selected controls. Sensitivity and specificity were calculated, using the predefined primary positivity threshold of 0.54 for platelet RNA sequencing aiming at 86% test sensitivity, and an additional predefined threshold of 0.89 aiming at 99% test specificity.

RESULTS

A total of 476 participants were enrolled, of whom 25 (5.3%) were diagnosed with cancer during 12-month follow-up. For each cancer patient, 3 cancer-free patients were randomly selected for the analysis. The sensitivity of limited screening was 72% (95% CI, 52-86) at a specificity of 91% (95% CI, 82-95). The area under the receiver operator characteristic for platelet RNA sequencing was 0.54 (95% CI, 0.41-0.66). At the primary positivity threshold, all patients had a positive test, for a sensitivity estimated at 100% (95% CI, 87-99) and a specificity of 8% (95% CI, 3.7-16.4). At the secondary threshold, sensitivity was 68% (95% CI, 48-83; p value compared with limited screening 0.71) at a specificity of 36% (95% CI, 26-47).

CONCLUSION

Platelet RNA sequencing had poor diagnostic accuracy for detecting occult cancer in patients with unprovoked VTE with the current algorithm.

Radio-sensitizing effect of MEK inhibition in glioblastoma in vitro and in vivo

INTRODUCTION

Glioblastoma (GBM) is an incurable cancer type. New therapeutic options are investigated, including targeting the mitogen-activated protein kinase (MAPK) pathway using MEK inhibitors as radio-sensitizers. In this study, we investigated whether MEK inhibition via PD0325901 leads to radio-sensitization in experimental in vitro and in vivo models of GBM.

MATERIALS AND METHODS

In vitro, GBM8 multicellular spheroids were irradiated with 3 fractions of 2 Gy, during 5 consecutive days of incubation with either PD0325901 or MEK-162. In vivo, we combined PD0325901 with radiotherapy in the GBM8 orthotopic mouse model, tumor growth was measured weekly by bioluminescence imaging and overall survival and toxicity were assessed.

RESULTS

Regrowth and viability of spheroids monitored until day 18, showed that both MEK inhibitors had an in vitro radio-sensitizing effect. In vivo, PD0325901 concentrations were relatively constant throughout multiple brain areas and temporal PD0325901-related adverse events such as dermatitis were observed in 4 out of 14 mice (29%). Mice that were treated with radiation alone or combined with PD0325901 had significantly better survival compared to vehicle (both P < 0.005), however, no significant interaction between PD0325901 MEK inhibition and irradiation was observed.

CONCLUSION

The difference between the radiotherapy-enhancing effect of PD0325901 in vitro and in vivo urges further pharmacodynamic/pharmacokinetic investigation of PD0325901 and possibly other candidate MEK inhibitors.

Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures

Background

In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments are commonly performed as an endpoint where cells are lysed, longitudinal drug-interaction monitoring is currently only possible through combined endpoint assays.

Methods

We provide a method for massive parallel monitoring of drug interactions for 16 drug combinations in 3 glioblastoma models over a time frame of 18 days. In our assay, viabilities of single neurospheres are to be estimated based on image information taken at different time points. Neurosphere images taken on the final day (day 18) were matched to the respective viability measured by CellTiter-Glo 3D on the same day. This allowed to use of machine learning to decode image information to viability values on day 18 as well as for the earlier time points (on days 8, 11, and 15).

Results

Our study shows that neurosphere images allow us to predict cell viability from extrapolated viabilities. This enables to assess of the drug interactions in a time window of 18 days. Our results show a clear and persistent synergistic interaction for several drug combinations over time.

Conclusions

Our method facilitates longitudinal drug-interaction assessment, providing new insights into the temporal-dynamic effects of drug combinations in 3D neurospheres which can help to identify more effective therapies against glioblastoma.

Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies

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.

Blood platelets as an RNA biomarker platform for neuro-oncological diseases

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.

Platelet RNA enables accurate detection of ovarian cancer: an intercontinental, biomarker identification study

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.

Detection and localization of early- and late-stage cancers using platelet RNA

Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I-IV cancer patients and in half of 352 stage I-III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening.

Abstract LB168: Platelet RNA signature enables early and accurate detection of ovarian cancer: An intercontinental, biomarker identification study

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.

Transcriptomic landscape of blood platelets in healthy donors

Blood platelet RNA-sequencing is increasingly used among the scientific community. Aberrant platelet transcriptome is common in cancer or cardiovascular disease, but reference data on platelet RNA content in healthy individuals are scarce and merit complex investigation. We sought to explore the dynamics of platelet transcriptome. Datasets from 204 healthy donors were used for the analysis of splice variants, particularly with regard to age, sex, blood storage time, unit of collection or library size. Genes B2M, PPBP, TMSB4X, ACTB, FTL, CLU, PF4, F13A1, GNAS, SPARC, PTMA, TAGLN2, OAZ1 and OST4 demonstrated the highest expression in the analysed cohort, remaining substantial transcription consistency. CSF3R gene was found upregulated in males (fold change 2.10, FDR q < 0.05). Cohort dichotomisation according to the median age, showed upregulated KSR1 in the older donors (fold change 2.11, FDR q < 0.05). Unsupervised hierarchical clustering revealed two clusters which were irrespective of age, sex, storage time, collecting unit or library size. However, when donors are analysed globally (as vectors), sex, storage time, library size, the unit of blood collection as well as age impose a certain degree of between- and/or within-group variability. Healthy donor platelet transcriptome retains general consistency, with very few splice variants deviating from the landscape. Although multidimensional analysis reveals statistically significant variability between and within the analysed groups, biologically, these changes are minor and irrelevant while considering disease classification. Our work provides a reference for studies working both on healthy platelets and pathological conditions affecting platelet transcriptome.

Blood-Based Biomarkers for Glioma in the Context of Gliomagenesis: A Systematic Review

BACKGROUND

Gliomas are the most common and aggressive tumors of the central nervous system. A robust and widely used blood-based biomarker for glioma has not yet been identified. In recent years, a plethora of new research on blood-based biomarkers for glial tumors has been published. In this review, we question which molecules, including proteins, nucleic acids, circulating cells, and metabolomics, are most promising blood-based biomarkers for glioma diagnosis, prognosis, monitoring and other purposes, and align them to the seminal processes of cancer.

METHODS

The Pubmed and Embase databases were systematically searched. Biomarkers were categorized in the identified biomolecules and biosources. Biomarker characteristics were assessed using the area under the curve (AUC), accuracy, sensitivity and/or specificity values and the degree of statistical significance among the assessed clinical groups was reported.

RESULTS

7,919 references were identified: 3,596 in PubMed and 4,323 in Embase. Following screening of titles, abstracts and availability of full-text, 262 articles were included in the final systematic review. Panels of multiple biomarkers together consistently reached AUCs >0.8 and accuracies >80% for various purposes but especially for diagnostics. The accuracy of single biomarkers, consisting of only one measurement, was far more variable, but single microRNAs and proteins are generally more promising as compared to other biomarker types.

CONCLUSION

Panels of microRNAs and proteins are most promising biomarkers, while single biomarkers such as GFAP, IL-10 and individual miRNAs also hold promise. It is possible that panels are more accurate once these are involved in different, complementary cancer-related molecular pathways, because not all pathways may be dysregulated in cancer patients. As biomarkers seem to be increasingly dysregulated in patients with short survival, higher tumor grades and more pathological tumor types, it can be hypothesized that more pathways are dysregulated as the degree of malignancy of the glial tumor increases. Despite, none of the biomarkers found in the literature search seem to be currently ready for clinical implementation, and most of the studies report only preliminary application of the identified biomarkers. Hence, large-scale validation of currently identified and potential novel biomarkers to show clinical utility is warranted.

Tumor-educated platelets for breast cancer detection: Biological and technical insights

3031

Background: Mammographic screening has enabled early detection of breast cancer, both in a general population and in women with increased risk of breast cancer. However, mammography yields many false positive results, leading to unnecessary invasive diagnostic procedures, and has limited sensitivity, particularly in women with high breast density. Blood-based markers may improve breast cancer screening, but no marker has proven sufficiently sensitive and specific for this purpose thus far. The mRNA repertoire in blood platelets (tumor educated platelets, TEPs) differs between patients with cancer and healthy controls. In this study, we aimed to train a classification algorithm on TEP mRNA profiles to distinguish patients with breast cancer from healthy controls. Methods: Platelet mRNA was sequenced from 266 women with stage I-IV breast cancer and 214 female asymptomatic controls from six different hospitals. First, a particle-swarm optimized support vector machine (PSO-SVM) classifier was trained (Best et al., Nature Protocols, 2019). To this end, 71% of the dataset was randomly allocated to train the algorithm, while the remaining 29% was used for internal validation. Second, an alternative classifier was trained on the same samples as in the PSO-SVM using elastic net (EN) regression. Reproducibility of classifier performance was evaluated in a single-center, independent, blinded set, consisting of cases (n = 37) and age-matched controls (n = 36). Post-hoc analyses were performed to assess the influence of hospital of origin and other factors on TEP gene expression and classifier performance. Results: Performance of both classifiers in the internal validation set was adequate with an area under the curve (AUC) of 0.86 for the PSO-SVM and 0.87 for the EN classifier. A strong correlation was observed between case control status and hospital of origin (Fisher’s exact test, p < 0.001). Performance in the single-center, independent set was poor with an AUC of 0.57 and 0.60 for the PSO-SVM and EN, respectively. Post-hoc analyses indicated that 25% of the variance in gene expression was associated with hospital of origin, 6% with case control status, whereas 69% remained unexplained. Gene expression related to platelet activity was significantly different between the two hospitals that contributed most samples, and between cases and controls. Conclusions: We were unable to successfully validate two TEP RNA based classifiers for breast cancer detection in a single-center, independent, blinded set, regardless of the algorithm employed. Gene expression was severely influenced by hospital of origin and other factors unrelated to case-control status, suggesting that the wet lab protocol is highly sensitive to within-protocol variations in execution. Therefore, we suggest that thorough revision of the protocol is necessary before TEP RNA based classifiers can be reconsidered for breast cancer detection in the future.

Omics Analysis of Educated Platelets in Cancer and Benign Disease of the Pancreas

Pancreatic ductal adenocarcinoma (PDAC) is traditionally associated with thrombocytosis/hypercoagulation and novel insights on platelet-PDAC "dangerous liaisons" are warranted. Here we performed an integrative omics study investigating the biological processes of mRNAs and expressed miRNAs, as well as proteins in PDAC blood platelets, using benign disease as a reference for inflammatory noise. Gene ontology mining revealed enrichment of RNA splicing, mRNA processing and translation initiation in miRNAs and proteins but depletion in RNA transcripts. Remarkably, correlation analyses revealed a negative regulation on SPARC transcription by isomiRs involved in cancer signaling, suggesting a specific "education" in PDAC platelets. Platelets of benign patients were enriched for non-templated additions of G nucleotides (#ntaG) miRNAs, while PDAC presented length variation on 3' (lv3p) as the most frequent modification on miRNAs. Additionally, we provided an actionable repertoire of PDAC and benign platelet-ome to be exploited for future studies. In conclusion, our data show that platelets change their biological repertoire in patients with PDAC, through dysregulation of miRNAs and splicing factors, supporting the presence of de novo protein machinery that can "educate" the platelet. These novel findings could be further exploited for innovative liquid biopsies platforms as well as possible therapeutic targets.

Tumor-Educated Platelet RNA for the Detection and (Pseudo)progression Monitoring of Glioblastoma

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.

TEP RNA enables blood-based brain tumor diagnostics

TEP RNA is dynamic throughout anti-tumor treatment

TEP RNA may be employed for therapy monitoring

Abstract B08: Tumor-educated platelets for early prostate cancer diagnosis, and therapy stratification in patients with metastasized castration resistant prostate cancer

One in every ten men diagnosed with prostate cancer will have metastases at some point, causing the high mortality of prostate cancer. Only earlier diagnosis has the chance to save those lives. However, correct therapy stratification may prolong the life of the patients without severely reducing the quality of life, thereby possibly turning a deadly disease into a chronic disease. For this to happen, we need predictive biomarkers that can be employed to longitudinally follow the disease in order to identify vulnerabilities and to monitor acquired resistance for personalized medicine. Using the platelet-enriched fraction of a blood sample, we here show that we can use the ability of platelets to sequester material during circulation to provide information derived from the tumor. This information could be used for early detection of prostate cancer. By using the platelet test in combination with PSA measurements, we may be able to rule out a majority of the false negatives associated with the PSA test. Furthermore, the platelet platform can be used in synergy with other biomarker sources such as circulating tumor DNA or protein biomarkers, providing the possibility to predict and monitor outcome of abiraterone therapy, and providing alternatives to the nonfunctional therapy by guiding therapy switching, in metastatic castration-resistant patients.

Citation Format: Lee-Ann Tjon-Kon-Fat, Linda Köhn, Myron Best, Marie Lundholm, Thomas Wurdinger, Anders Widmark, Camilla Thellenberg-Karlsson, Pernilla Wikström, Jonas Nilsson. Tumor-educated platelets for early prostate cancer diagnosis, and therapy stratification in patients with metastasized castration resistant prostate cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr B08.

Abstract IA22: Tumor-educated platelets for the detection of cancer

Blood-based “liquid biopsies” provide a means for minimally invasive molecular diagnostics, overcoming limitations of tissue acquisition. Early detection of cancer, clinical cancer diagnostics, and companion diagnostics are regarded as important applications of liquid biopsies. It has been reported that tumor-educated platelets (TEPs) may enable blood-based cancer diagnostics. Platelets have emerged as central players in the systemic and local responses to tumor growth. Confrontation of platelets with tumor cells via transfer of tumor-associated biomolecules (“education”) is an emerging concept and can result in the sequestration of biomolecules. Moreover, external stimuli induce specific splicing of pre-mRNAs in circulating platelets. Platelets are considered to undergo queue-specific splice events in response to signals released by cancer cells and the tumor microenvironment, such as stromal and immune cells. The combination of specific splice events in response to external signals and the capacity of platelets to directly ingest (spliced) circulating mRNA can provide TEPs with a highly dynamic mRNA repertoire, with potential applicability to cancer diagnostics. We determined the diagnostic potential of TEPs by mRNA sequencing of platelet samples. Blood platelet samples of &gt;1,000 patients with cancer covering multiple tumor types and healthy donors were analyzed. Healthy donors and early- and late-stage cancer patients were distinguished by a self-learning support vector machine (SVM) algorithm, using a set of spliced platelet transcripts with moderate to high expression. These results suggest that blood platelets may advance blood-based “liquid biopsies,” including for the detection of stage I-II tumors.

Citation Format: Thomas Wurdinger. Tumor-educated platelets for the detection of cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr IA22.

Platelet RNA as Pan-Tumor Biomarker for Cancer Detection

Blood-based liquid biopsies are considered a screening approach for early cancer detection. Sequencing technologies enable in-depth analyses of nucleic acids, including mutant cell-free (cf) DNA in the plasma. However, in the blood of patients with early-stage cancer the detection level of mutant cfDNA is relatively low, and complicated by the natural presence of noncancer cfDNA mutants attributed to aging-related processes. Consequently, analysis of methylated cfDNA patterns and alternative approaches such as tumor-educated platelets are gaining traction for the detection of early-stage tumors. Here, we dissect the use of platelet RNA as a potential biomarker for the development of early-stage, pan-cancer blood tests.

Combined Expression of Plasma Thrombospondin-2 and CA19-9 for Diagnosis of Pancreatic Cancer and Distal Cholangiocarcinoma: A Proteome Approach

Background

Minimally invasive diagnostic biomarkers for patients with pancreatic ductal adenocarcinoma (PDAC) and distal cholangiocarcinoma (dCCA) are warranted to facilitate accurate diagnosis. This study identified diagnostic plasma proteins based on proteomics of tumor secretome.

Materials and Methods

Secretome of tumor and normal tissue was collected after resection of PDAC and dCCA. Differentially expressed proteins were measured by mass spectrometry. Selected candidate biomarkers and carbohydrate antigen 19‐9 (CA19‐9) were validated by enzyme‐linked immunosorbent assay in plasma from patients with PDAC (n = 82), dCCA (n = 29), benign disease (BD; n = 30), and healthy donors (HDs; n = 50). Areas under the curve (AUCs) of receiver operator characteristic curves were calculated to determine the discriminative power.

Results

In tumor secretome, 696 discriminatory proteins were identified, including 21 candidate biomarkers. Thrombospondin‐2 (THBS2) emerged as promising biomarker. Abundance of THBS2 in plasma from patients with cancer was significantly higher compared to HDs (p < .001, AUC = 0.844). Combined expression of THBS2 and CA19‐9 yielded the optimal discriminatory capacity (AUC = 0.952), similarly for early‐ and late‐stage disease (AUC = 0.971 and AUC = 0.911). Remarkably, this combination demonstrated a power similar to CA19‐9 to discriminate cancer from BD (AUC = 0.764), and THBS2 provided an additive value in patients with high expression levels of bilirubin.

Conclusion

Our proteome approach identified a promising set of candidate biomarkers. The combined plasma expression of THBS2/CA19‐9 is able to accurately distinguish patients with PDAC or dCCA from HD and BD.

Implications for Practice

The combined plasma expression of thrombospondin‐2 and carbohydrate antigen 19‐9 is able to accurately diagnose patients with pancreatic cancer and distal cholangiocarcinoma. This will facilitate minimally invasive diagnosis for these patients by distinguishing them from healthy individuals and benign diseases.

This article identifies diagnostic plasma proteins to distinguish patients with pancreatic ductal adenocarcinoma and distal cholangiocarcinoma from benign disease and health donors and evaluates these new markers for additive value with CA19‐9 at different disease stages.

p120-catenin-dependent collective brain infiltration by glioma cell networks

Diffuse brain infiltration by glioma cells causes detrimental disease progression, but its multicellular coordination is poorly understood. We show here that glioma cells infiltrate the brain collectively as multicellular networks. Contacts between moving glioma cells are adaptive epithelial-like or filamentous junctions stabilized by N-cadherin, β-catenin and p120-catenin, which undergo kinetic turnover, transmit intercellular calcium transients and mediate directional persistence. Downregulation of p120-catenin compromises cell-cell interaction and communication, disrupts collective networks, and both the cadherin and RhoA binding domains of p120-catenin are required for network formation and migration. Deregulating p120-catenin further prevents diffuse glioma cell infiltration of the mouse brain with marginalized microlesions as the outcome. Transcriptomics analysis has identified p120-catenin as an upstream regulator of neurogenesis and cell cycle pathways and a predictor of poor clinical outcome in glioma patients. Collective glioma networks infiltrating the brain thus depend on adherens junctions dynamics, the targeting of which may offer an unanticipated strategy to halt glioma progression.

Patient-Derived Glioma Models: From Patients to Dish to Animals

Glioblastoma (GBM) is the most common and malignant primary brain tumor in adults associated with a poor survival. Current standard of care consists of surgical resection followed by radiation and chemotherapy. GBMs are highly heterogeneous, having a complex interaction among different cells within the tumor as well as the tumor microenvironment. One of the main challenges in the neuro-oncology field in general, and GBM in particular, is to find an optimum culture condition that maintains the molecular genotype and phenotype as well as heterogeneity of the original tumor in vitro and in vivo. Established cell lines were shown to be a poor model of the disease, failing to recapitulate the phenotype and harboring non-parental genotypic mutations. Given the growing understanding of GBM biology, the discovery of glioma cancer stem-like cells (GSCs), and their role in tumor formation and therapeutic resistance, scientists are turning more towards patient-derived cells and xenografts as a more representative model. In this review, we will discuss the current state of patient-derived GSCs and their xenografts; and provide an overview of different established models to study GBM biology and to identify novel therapeutics in the pre-clinical phase.

RNA sequencing and swarm intelligence-enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA

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.

Recycling drug screen repurposes hydroxyurea as a sensitizer of glioblastomas to temozolomide targeting de novo DNA synthesis, irrespective of molecular subtype

Background

Glioblastoma (GBM) is the most common and most aggressive primary malignant brain tumor. Standard-of-care treatment involves maximal surgical resection of the tumor followed by radiation and chemotherapy (temozolomide [TMZ]). The 5-year survival rate of patients with GBM is <10%, a colossal failure that has been partially attributed to intrinsic and/or acquired resistance to TMZ through O6-methylguanine DNA methyltransferase (MGMT) promoter methylation status in the tumor.

Methods

A drug screening aimed at evaluating the potential recycling and repurposing of known drugs was conducted in TMZ-resistant GBM cell lines and primary cultures of newly diagnosed GBM with different MGMT promoter methylation status, phenotypic/genotypic background and subtype, and validated with sphere formation, cell migration assays, and quantitative invasive orthotopic in vivo models.

Results

We identified hydroxyurea (HU) to synergize with TMZ in GBM cells in culture and in vivo, irrespective of MGMT promoter methylation status, subtype, and/or stemness. HU acts specifically on the S-phase of the cell cycle by inhibiting the M2 unit of enzyme ribonucleotide reductase. Knockdown of this enzyme using RNA interference and other known chemical inhibitors exerted a similar effect to HU in combination with TMZ both in culture and in vivo.

Conclusions

We demonstrate preclinical efficacy of repurposing hydroxyurea in combination with TMZ for adjuvant GBM therapy. This combination benefit is of direct clinical interest given the extensive use of TMZ and the associated problems with TMZ-related resistance and treatment failure.

An Experimenter's Guide to Glioblastoma Invasion Pathways

Glioblastoma is a highly aggressive brain tumor that is characterized by its unparalleled invasiveness. Invasive glioblastoma cells not only escape surgery and focal therapies but also are more resistant to current radio- and chemo-therapeutic approaches. Thus, any curative therapy for this deadly disease likely should include treatment strategies that interfere with glioblastoma invasiveness. Understanding glioblastoma invasion mechanisms is therefore critical. We discuss the strengths and weaknesses of various glioblastoma invasion models and conclude that robust experimental evidence has been obtained for a pro-invasive role of Ephrin receptors, Rho GTPases, and casein kinase 2 (CK2). Extensive interplay occurs between these proteins, suggesting the existence of a glioblastoma invasion signaling network that comprises several targets for therapy.

Tumor-Educated Platelets as a Noninvasive Biomarker Source for Cancer Detection and Progression Monitoring

Liquid biopsies represent a potential revolution in cancer diagnostics as a noninvasive method for detecting and monitoring diseases, complementary to or even replacing current tissue biopsy approaches. Several blood-based biosources and biomolecules, such as cell-free DNA and RNA, proteins, circulating tumor cells, and extracellular vesicles, have been explored for molecular test development. We recently discovered the potential of tumor-educated blood platelets (TEP) as a noninvasive biomarker trove for RNA biomarker panels. TEPs are involved in the progression and spread of several solid tumors, and spliced TEP RNA surrogate signatures can provide specific information on the presence, location, and molecular characteristics of cancers. So far, TEP samples from patients with different tumor types, including lung, brain, and breast cancers, have been tested, and it has been shown that TEPs from patients with cancer are distinct from those with inflammatory and other noncancerous diseases. It remains to be investigated how platelets are "educated," which mechanisms cause intraplatelet RNA splicing, and whether the relative contribution of specific platelet subpopulations changes in patients with cancer. Ultimately, TEP RNA may complement currently used biosources and biomolecules employed for liquid biopsy diagnosis, potentially enhancing the detection of cancer in an early stage and facilitating noninvasive disease monitoring. Cancer Res; 78(13); 3407-12. ©2018 AACR.

Platelet RNA signatures for the detection of cancer

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.

Glycosylated extracellular vesicles released by glioblastoma cells are decorated by CCL18 allowing for cellular uptake via chemokine receptor CCR8

Cancer cells release extracellular vesicles (EVs) that contain functional biomolecules such as RNA and proteins. EVs are transferred to recipient cancer cells and can promote tumour progression and therapy resistance. Through RNAi screening, we identified a novel EV uptake mechanism involving a triple interaction between the chemokine receptor CCR8 on the cells, glycans exposed on EVs and the soluble ligand CCL18. This ligand acts as bridging molecule, connecting EVs to cancer cells. We show that glioblastoma EVs promote cell proliferation and resistance to the alkylating agent temozolomide (TMZ). Using in vitro and in vivo stem-like glioblastoma models, we demonstrate that EV-induced phenotypes are neutralised by a small molecule CCR8 inhibitor, R243. Interference with chemokine receptors may offer therapeutic opportunities against EV-mediated cross-talk in glioblastoma.

Platelets harbor prostate cancer biomarkers and the ability to predict therapeutic response to abiraterone in castration resistant patients

BACKGROUND

Novel therapies for castration resistant prostate cancer (CRPC) have been introduced in the clinic with possibilities for individualized treatment plans. Best practice of those expensive drugs requires predictive biomarker monitoring. This study used circulating biomarker analysis to follow cancer-derived transcripts implicated in therapy resistance.

METHOD

The isolated platelet population of blood samples and digital-PCR were used to identify selected biomarker transcripts in patients with CRPC prior chemo- or androgen synthesis inhibiting therapy.

RESULTS

Fifty patients received either docetaxel (n = 24) or abiraterone (n = 26) therapy, with therapy response rates of 54% and 48%, respectively. Transcripts for the PC-associated biomarkers kallikrein-related peptidase-2 and -3 (KLK2, KLK3), folate hydrolase 1 (FOLH1), and neuropeptide-Y (NPY) were uniquely present within the platelet fraction of cancer patients and not detected in healthy controls (n = 15). In the abiraterone treated cohort, the biomarkers provided information on therapy outcome, demonstrating an association between detectable biomarkers and short progression free survival (PFS) (FOLH1, P < 0.01; KLK3, P < 0.05; and NPY, P < 0.05). Patients with biomarker-negative platelets had the best outcome, while FOLH1 (P < 0.05) and NPY (P = 0.05) biomarkers provided independent predictive information in a multivariate analysis regarding PFS. KLK2 (P < 0.01), KLK3 (P < 0.001), and FOLH1 (P < 0.05) biomarkers were associated with short overall survival (OS). Combining three biomarkers in a panel (KLK3, FOLH1, and NPY) made it possible to separate long-term responders from short-term responders with 87% sensitivity and 82% specificity.

CONCLUSION

Analyzing tumor-derived biomarkers in platelets of CRPC patients enabled prediction of the outcome after abiraterone therapy with higher accuracy than baseline serum PSA or PSA response.

Structural Alterations of MET Trigger Response to MET Kinase Inhibition in Lung Adenocarcinoma Patients

.

miR-129-3p controls centrosome number in metastatic prostate cancer cells by repressing CP110

The centrosome plays a key role in cancer invasion and metastasis. However, it is unclear how abnormal centrosome numbers are regulated when prostate cancer (PCa) cells become metastatic. CP110 was previously described for its contribution of centrosome amplification (CA) and early development of aggressive cell behaviour. However its regulation in metastatic cells remains unclear. Here we identified miR-129-3p as a novel metastatic microRNA. CP110 was identified as its target protein. In PCa cells that have metastatic capacity, CP110 expression was repressed by miR-129-3p. High miR-129-3p expression levels increased cell invasion, while increasing CP110 levels decreased cell invasion. Overexpression of CP110 in metastatic PCa cells resulted in a decrease in the number of metastasis. In tissues of PCa patients, low CP110 and high miR-129-3p expression levels correlated with metastasis, but not with the expression of genes related to EMT. Furthermore, overexpression of CP110 in metastatic PCa cells resulted in excessive-CA (E-CA), and a change in F-actin distribution which is in agreement with their reduced metastatic capacity. Our data demonstrate that miR-129-3p functions as a CA gatekeeper in metastatic PCa cells by maintaining pro-metastatic centrosome amplification (CA) and preventing anti-metastatic E-CA.

Platelet RNA in Cancer Diagnostics

Platelets are involved in several steps of cancer metastasis. During this process, platelets are exposed to the tumor and its environment, thereby exchanging biomolecules with the tumor cells and resulting in tumor-mediated “education” of the platelets and a change in their RNA profile. Analysis of platelet RNA profiles or direct measurement of tumor-derived biomarkers within platelets can provide information on ongoing cancer-related processes in the individual (e.g., whether the patient has cancer, the tumor type, and possibly identify oncogenic alterations driving the disease for treatment selection). The close interaction with the disease process and the ability to respond to systemic alterations make platelets an interesting biosource for implementation in precision medicine.

Ape1 guides DNA repair pathway choice that is associated with drug tolerance in glioblastoma

Ape1 is the major apurinic/apyrimidinic (AP) endonuclease activity in mammalian cells, and a key factor in base-excision repair of DNA. High expression or aberrant subcellular distribution of Ape1 has been detected in many cancer types, correlated with drug response, tumor prognosis, or patient survival. Here we present evidence that Ape1 facilitates BRCA1-mediated homologous recombination repair (HR), while counteracting error-prone non-homologous end joining of DNA double-strand breaks. Furthermore, Ape1, coordinated with checkpoint kinase Chk2, regulates drug response of glioblastoma cells. Suppression of Ape1/Chk2 signaling in glioblastoma cells facilitates alternative means of damage site recruitment of HR proteins as part of a genomic defense system. Through targeting "HR-addicted" temozolomide-resistant glioblastoma cells via a chemical inhibitor of Rad51, we demonstrated that targeting HR is a promising strategy for glioblastoma therapy. Our study uncovers a critical role for Ape1 in DNA repair pathway choice, and provides a mechanistic understanding of DNA repair-supported chemoresistance in glioblastoma cells.

Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets

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 < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.

Platelet RNA as a circulating biomarker trove for cancer diagnostics

Platelets are multifunctional cell fragments, circulating in blood in high abundance. Platelets assist in thrombus formation, sensing of pathogens entering the blood stream, signaling to immune cells, releasing vascular remodeling factors, and, negatively, enhancing cancer metastasis. Platelets are 'educated' by their environment, including in patients with cancer. Cancer cells appear to initiate intraplatelet signaling, resulting in splicing of platelet pre-mRNAs, and enhance secretion of cytokines. Platelets can induce leukocyte and endothelial cell modeling factors, for example, through adenine nucleotides (ATP), thereby facilitating extravasation of cancer cells. Besides releasing factors, platelets can also sequester RNAs and proteins released by cancer cells. Thus, platelets actively respond to queues from local and systemic conditions, thereby altering their transcriptome and molecular content. Platelets contain a rich repertoire of RNA species, including mRNAs, small non-coding RNAs and circular RNAs; although studies regarding the functionality of the various platelet RNA species require more attention. Recent advances in high-throughput characterization of platelet mRNAs revealed 10 to > 1000 altered mRNAs in platelets in the presence of disease. Hence, platelet RNA appears to be dynamically affected by pathological conditions, thus possibly providing opportunities to use platelet RNA as diagnostic, prognostic, predictive, or monitoring biomarkers. In this review, we cover the literature regarding the platelet RNA families, processing of platelet RNAs, and the potential application of platelet RNA as disease biomarkers.

Abstract LB-248: RNA-sequencing of tumor-educated platelets enables nivolumab immunotherapy response prediction

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&lt;0.05 among these groups identified significant separation between CB and no CB (p&lt;0.001, Fisher’s exact test). The SVM nivolumab response prediction algorithm, predicted the remaining 24 samples with an accuracy of more than 85%, as opposed to at random classification (p&lt;0.01). D: TEP RNA profiles potentially enable liquid biopsy-based response prediction to IT. Large-scale validation is ongoing and up to date results of the NSCLC cohort will be presented.

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%&gt;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

Development of bioluminescent chick chorioallantoic membrane (CAM) models for primary pancreatic cancer cells: a platform for drug testing

The aim of the present study was to develop chick-embryo chorioallantoic membrane (CAM) bioluminescent tumor models employing low passage cell cultures obtained from primary pancreatic ductal adenocarcinoma (PDAC) cells. Primary PDAC cells transduced with lentivirus expressing Firefly-luciferase (Fluc) were established and inoculated onto the CAM membrane, with >80% engraftment. Fluc signal reliably correlated with tumor growth. Tumor features were evaluated by immunohistochemistry and genetic analyses, including analysis of mutations and mRNA expression of PDAC pivotal genes, as well as microRNA (miRNA) profiling. These studies showed that CAM tumors had histopathological and genetic characteristic comparable to the original tumors. We subsequently tested the modulation of key miRNAs and the activity of gemcitabine and crizotinib on CAM tumors, showing that combination treatment resulted in 63% inhibition of tumor growth as compared to control (p < 0.01). These results were associated with reduced expression of miR-21 and increased expression of miR-155. Our study provides the first evidence that transduced primary PDAC cells can form tumors on the CAM, retaining several histopathological and (epi)genetic characteristics of original tumors. Moreover, our results support the use of these models for drug testing, providing insights on molecular mechanisms underlying antitumor activity of new drugs/combinations.

Platelets harbor prostate cancer biomarkers and the ability to predict therapeutic response in castration-resistant patients

e583

Background: Novel therapies for castration resistant prostate cancer (CRPC) have been introduced in the clinic with possibilities for individualized treatment plans. Best practice of those expensive drugs requires predictive biomarker monitoring. This study used circulating biomarker analysis to follow cancer-derived transcripts implicated in therapy resistance. Methods: The isolated platelet population of blood samples and QRT-PCR were used to identify selected biomarker transcripts in patients with CRPC prior chemo- or androgen synthesis directed therapies. The association between biomarker status in platelets (positive vs. negative) and therapy response, progression-free survival (PFS) and overall survival (OS) was examined. Results: Fifty patients received either docetaxel (n = 24) or abiraterone (n = 26) therapy, with therapy response rates of 54% and 48%, respectively. Transcripts for the PC-associated biomarkers kallikrein-related peptidase-3 ( KLK3), androgen receptor splice-variant 7 (ARV7), folate hydrolase 1 (FOLH1), and neuropeptide-Y ( NPY) were present within the platelet fraction. Analyzing biomarkers in the chemotherapy group did not add information about PFS, but FOLH1 was associated with short OS (p = 0.00015). In the abiraterone treated cohort, detectable FOLH1 (p = 0.009), KLK3 (p = 0.018), and NPY (p = 0.028) were all associated with short PFS. Patients with biomarker-negative platelets had the best outcome, while FOLH1 and NPY provided independent predictive information regarding PFS and KLK3 (p = 0.001) and FOLH1 (p = 0.002) were associated with short OS. Conclusions: Analyzing tumor-derived biomarkers in platelets of CRPC patients enabled prediction of the outcome after abiraterone therapy with high accuracy. Platelet-based analysis of FOLH1, NPY, and KLK3 may be used for treatment stratification of patients scheduled for treatment with abiraterone.

RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics

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".