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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., Competing Interests: T.W. and R.J.A.N. received funding from Illumina and are shareholders in GRAIL Inc., (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)

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., (© 2017 Wiley Periodicals, Inc.)

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., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)