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

Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification

Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community on which methods are the most effective or how to process the data. To circumvent this, we performed a large-scale study using various machine-learning techniques. First, we took a closer look at existing datasets and filtered out some patients to assert data collection quality. The final data collection included platelet RNA samples acquired from 1397 cancer patients (17 types of cancer) and 354 asymptomatic, presumed healthy, donors. Then, we assessed an array of different machine-learning models and techniques (e.g., feature selection of RNA transcripts) in pan-cancer detection and multiclass classification. Our results show that simple logistic regression performs the best, reaching a 68% cancer detection rate at a 99% specificity level, and multiclass classification accuracy of 79.38% when distinguishing between five cancer types. In summary, by revisiting classical machine-learning models, we have exceeded the previously used method by 5% and 9.65% in cancer detection and multiclass classification, respectively. To ease further research, we open-source our code and data processing pipelines (https://gitlab.com/jopekmaksym/improving-platelet-rna-based-diagnostics), which we hope will serve the community as a strong baseline.

The use of platelets as a clinical tool in oncology: opportunities and challenges

Platelets are small circulating anucleated cells mainly involved in thrombosis and hemostasis processes. Moreover, platelets play an active role in tumorigenesis and cancer progression, stimulating angiogenesis and vascular remodelling, and protecting circulating cancer cells from shear forces and immune surveillance. Several reports indicate that platelet number in the blood circulation of cancer patients is associated with prognosis and response to treatment. However, the mechanisms of platelets "education" by cancer cells and the crosstalk between platelets and tumor are still unclear, and the role of "tumor educated platelets" (TEPs) is achieving growing interest in cancer research. TEPs are a biological source of cancer-derived biomarkers, especially RNAs that are protected by platelets membrane from circulating RNases, and could serve as a non-invasive tool for tumor detection, molecular profiling and evolution during therapy in clinical practice. Moreover, short platelet lifespan offers the possibility to get a snapshot assessment of cancer molecular profile, providing a real-time tool. We review and discuss the potential and the clinical utility, in terms of cancer diagnosis and monitoring, of platelet count together with other morphological parameters and of the more recent and innovative TEP profiling.

Liquid biopsy: An arsenal for tumour screening and early diagnosis

Cancer has become the second leading cause of death in the world, and more than 50% of cancer patients are diagnosed at an advanced stage. Early diagnosis of tumours is the key to improving patient quality of life and survival time and reducing the socioeconomic burden. However, there is still a lack of reliable early diagnosis methods in clinical practice. In recent years, liquid biopsy technology has developed rapidly. It has the advantages of noninvasiveness, easy access to sample sources, and reproducibility. It has become the main focus of research on the early diagnosis methods of tumours. This review summarises the research progress of existing liquid biopsy markers, such as circulating tumour DNA, circulating viral DNA, DNA methylation, circulating tumour cells, circulating RNA, exosomes, and tumour education platelets in early diagnosis of tumours, and analyses the current advantages and limitations of various markers, providing a direction for the application and transformation of liquid biopsy research in early diagnosis of clinical tumours.

Extracellular vesicles-derived CXCL4 is a candidate serum tumor biomarker for colorectal cancer

Extracellular vesicles (EVs) were promising circulating biomarkers for multiple diseases, but whether serum EVs-derived proteins could be used as a reliable tumor biomarker for colorectal cancer (CRC) remained inconclusive. In this study, we identified CXCL4 by a 4D data-independent acquisition-based quantitative proteomics assay of serum EVs-derived proteins in 40 individuals and subsequently analyzed serum EVs-derived CXCL4 levels by ELISA in 2 cohorts of 749 individuals. The results revealed that EVs-derived CXCL4 levels were dramatically elevated in CRC patients than in benign colorectal polyp patients or healthy controls (HC). Furthermore, receiver operating characteristic curves revealed that EVs-derived CXCL4 exhibited superior diagnostic performance with area under the curve of 0.948 in the training cohort. Additionally, CXCL4 could effectively distinguish CRC in stage I/II from HC. Notably, CRC patients with high levels of EVs-derived CXCL4 have shorter 2-year progression-free survival than those with low levels. Overall, our findings demonstrated that serum EVs-derived CXCL4 was a candidate diagnostic and prognostic biomarker for CRC.

Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data

Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.

Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer

Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-III respectively. Topological analysis of the protein-protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70 months were identified for hub genes during the Kaplan-Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.

TEP RNA: a new frontier for early diagnosis of NSCLC

BACKGROUND

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer (LC), which is the leading cause of tumor mortality. In recent years, compared with tissue biopsy, which is the diagnostic gold standard for tumor diagnosis, Liquid biopsy (LB) is considered to be a more minimally invasive, sensitive, and safer alternative or auxiliary diagnostic method. However, the current value of LB in early diagnosis of LC is not ideal, so it is particularly important to study the changes in blood composition during the process of tumorigenesis and find more sensitive biomarkers.

PURPOSE

Platelets are a type of abundant blood cells that carry a large amount of RNA. In the LC regulatory network, activated platelets play an important role in the process of tumorigenesis, development, and metastasis. In order to identify predictive liquid biopsy biomarkers for the diagnosis of NSCLC, we summarized the development and function of platelets, the interaction between platelets and tumors, the value of TEP RNA in diagnosis, prognosis, and treatment of NSCLC, and the method for detecting TEP RNA of NSCLC in this article.

CONCLUSION

The application of platelets in the diagnosis and treatment of NSCLC remains at a nascent stage. In addition to the drawbacks of low platelet count and complex experimental processes, the diagnostic accuracy of TEP RNA-seq for cancer in different populations still needs to be improved and validated. At present, a large number of studies have confirmed significant differences in the expression of TEP RNA in platelets between NSCLC patients and healthy individuals. Continuous exploration of the diagnostic value of TEP RNA in NSCLC is of utmost importance. The integration of NSCLC platelet-related markers with other NSCLC markers can improve current tumor diagnosis and prognostic evaluation systems, providing broad prospects in tumor screening, disease monitoring, and prognosis assessment.

Predictive Performance of Cell-Free Nucleic Acid-Based Multi-Cancer Early Detection Tests: A Systematic Review

BACKGROUND

Cancer-screening tests that can detect multiple cancer types, or multi-cancer early detection (MCED) tests, have emerged recently as a potential new tool in decreasing cancer morbidity and mortality. Most MCED assays are based on detecting cell-free tumor DNA (CF-DNA) in the blood. MCEDs offer the potential for screening for cancer organ sites with high mortality, both with and without recommended screening. However, their clinical utility has not been established. Before clinical utility can be established, the clinical validity of MCEDs, i.e., their ability to predict cancer status, must be demonstrated. In this study we performed a systematic review of the predictive ability for cancer of cell-free-nucleic acid-based MCED tests.

CONTENT

We searched PubMed for relevant publications from January 2017 to February 2023, using MeSH terms related to multi-cancer detection, circulating DNA, and related concepts. Of 1811 publications assessed, 61 were reviewed in depth and 20 are included in this review. For almost all studies, the cancer cases were assessed at time of diagnosis. Most studies reported specificity (generally 95% or higher) and overall sensitivity (73% median). The median number of cancer types assessed per assay was 5. Many studies also reported sensitivity by stage and/or cancer type. Sensitivity generally increased with stage.

SUMMARY

To date, relatively few published studies have assessed the clinical validity of MCED tests. Most used cancer cases assessed at diagnosis, with generally high specificity and variable sensitivity depending on cancer type and stage. The next steps should be testing in the intended-use population, i.e., asymptomatic persons.

Critical Factors in the Analytical Work Flow of Circulating Tumor DNA-Based Molecular Profiling

BACKGROUND

Liquid biopsy testing, especially molecular tumor profiling of circulating tumor DNA (ctDNA) in cell-free plasma, has received increasing interest in recent years as it serves as a reliable alternative for the detection of tumor-specific aberrations to guide treatment decision-making in oncology. Many (commercially available) applications have been developed, however, broad divergences in (pre)analytical work flows and lack of universally applied guidelines impede routine clinical implementation. In this review, critical factors in the blood-based ctDNA liquid biopsy work flow are evaluated.

CONTENT

In the preanalytical phase, several aspects (e.g., blood collection tubes [BCTs], plasma processing, and extraction method) affect the quantity and quality of the circulating cell-free DNA (ccfDNA) applicable for subsequent molecular analyses and should meet certain standards to be applied in diagnostic work flows. Analytical considerations, such as analytical input and choice of assay, might vary based on the clinical application (i.e., screening, primary diagnosis, minimal residual disease [MRD], response monitoring, and resistance identification). In addition to practical procedures, variant interpretation and reporting ctDNA results should be harmonized. Collaborative efforts in (inter)national consortia and societies are essential for the establishment of standard operating procedures (SOPs) in attempts to standardize the plasma-based ctDNA analysis work flow.

SUMMARY

Development of universally applicable guidelines regarding the critical factors in liquid biopsy testing are necessary to pave the way to clinical implementation for routine diagnostics.

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.

A brain metastasis liquid biopsy: Where are we now?

Brain metastases remain a challenging and feared complication for patients with cancer and research in this area has lagged behind research into metastases to other organs. Due to their location and the risks associated with neurosurgical biopsies, the biology underpinning brain metastases response to treatment and evolution over time remains poorly understood. Liquid biopsies are proposed to overcome many of the limitations present with tissue biopsies, providing a better representation of tumor heterogeneity, facilitating repeated sampling, and providing a noninvasive assessment of tumor biology. Several different liquid biopsy approaches have been investigated including circulating tumor cells, circulating tumor DNA, extracellular vesicles, and tumor-educated platelets; however, these have generally been less effective in assessing brain metastases compared to metastases to other organs requiring improved techniques to investigate these approaches, studies combining different liquid biopsy approaches and/or novel liquid biopsy approaches. Through this review, we highlight the current state of the art and define key unanswered questions related to brain metastases liquid biopsies.

Recent Developments in Blood Biomarkers in Neuro-oncology

PURPOSE OF REVIEW

Given the invasive and high-risk nature of brain surgery, the need for non-invasive biomarkers obtained from the peripheral blood is greatest in tumors of the central nervous system (CNS). In this comprehensive review, we highlight recent advances in blood biomarker development for adult and pediatric brain tumors.

RECENT FINDINGS

We summarize recent blood biomarker development for CNS tumors across multiple key analytes, including peripheral blood mononuclear cells, cell-free DNA, cell-free RNA, proteomics, circulating tumor cells, and tumor-educated platelets. We also discuss methods for enhancing blood biomarker detection through transient opening of the blood-brain barrier. Although blood-based biomarkers are not yet used in routine neuro-oncology practice, this field is advancing rapidly and holds great promise for improved and non-invasive management of patients with brain tumors. Prospective and adequately powered studies are needed to confirm the clinical utility of any blood biomarker prior to widespread clinical implementation.

Megakaryocyte- and erythroblast-specific cell-free DNA patterns in plasma and platelets reflect thrombopoiesis and erythropoiesis levels

Circulating cell-free DNA (cfDNA) fragments are a biological analyte with extensive utility in diagnostic medicine. Understanding the source of cfDNA and mechanisms of release is crucial for designing and interpreting cfDNA-based liquid biopsy assays. Using cell type-specific methylation markers as well as genome-wide methylation analysis, we determine that megakaryocytes, the precursors of anuclear platelets, are major contributors to cfDNA (~26%), while erythroblasts contribute 1-4% of cfDNA in healthy individuals. Surprisingly, we discover that platelets contain genomic DNA fragments originating in megakaryocytes, contrary to the general understanding that platelets lack genomic DNA. Megakaryocyte-derived cfDNA is increased in pathologies involving increased platelet production (Essential Thrombocythemia, Idiopathic Thrombocytopenic Purpura) and decreased upon reduced platelet production due to chemotherapy-induced bone marrow suppression. Similarly, erythroblast cfDNA is reflective of erythrocyte production and is elevated in patients with thalassemia. Megakaryocyte- and erythroblast-specific DNA methylation patterns can thus serve as biomarkers for pathologies involving increased or decreased thrombopoiesis and erythropoiesis, which can aid in determining the etiology of aberrant levels of erythrocytes and platelets.

Liquid biopsy: creating opportunities in brain space

In recent years, liquid biopsy has emerged as an alternative method to diagnose and monitor tumors. Compared to classical tissue biopsy procedures, liquid biopsy facilitates the repetitive collection of diverse cellular and acellular analytes from various biofluids in a non/minimally invasive manner. This strategy is of greater significance for high-grade brain malignancies such as glioblastoma as the quantity and accessibility of tumors are limited, and there are collateral risks of compromised life quality coupled with surgical interventions. Currently, blood and cerebrospinal fluid (CSF) are the most common biofluids used to collect circulating cells and biomolecules of tumor origin. These liquid biopsy analytes have created opportunities for real-time investigations of distinct genetic, epigenetic, transcriptomics, proteomics, and metabolomics alterations associated with brain tumors. This review describes different classes of liquid biopsy biomarkers present in the biofluids of brain tumor patients. Moreover, an overview of the liquid biopsy applications, challenges, recent technological advances, and clinical trials in the brain have also been provided.

Characterization of all small RNAs in and comparisons across cultured megakaryocytes and platelets of healthy individuals and COVID-19 patients

BACKGROUND

The small noncoding RNAs (sncRNAs) in megakaryocytes (MKs) and platelets are not well characterized. Neither is the impact of SARS-CoV-2 infection on the sncRNAs of platelets.

OBJECTIVES

To investigate the sorting of MK sncRNAs into platelets, and the differences in the platelet sncRNAomes of healthy donors (HDs) and COVID-19 patients.

METHODS

We comprehensively profiled sncRNAs from MKs cultured from cord blood-derived CD34+ cells, platelets from HDs, and platelets from patients with moderate and severe SARS-CoV-2 infection. We also comprehensively profiled Argonaute (AGO)-bound sncRNAs from the cultured MKs.

RESULTS

We characterized the sncRNAs in MKs and platelets and can account for ∼95% of all sequenced reads. We found that MKs primarily comprise microRNA isoforms (isomiRs), tRNA-derived fragments (tRFs), rRNA-derived fragments (rRFs), and Y RNA-derived fragments (yRFs) in comparable abundances. The platelets of HDs showed a skewed distribution by comparison: 56.7% of all sncRNAs are yRFs, 34.4% are isomiRs, and <2.0% are tRFs and rRFs. Most isomiRs in MKs and platelets are either noncanonical, nontemplated, or both. When comparing MKs and platelets from HDs, we found numerous isomiRs, tRFs, rRFs, and yRFs showing opposite enrichments or depletions, including molecules from the same parental miRNA arm, tRNA, rRNA, or Y RNA. The sncRNAome of platelets from patients with COVID-19 is skewed compared to that of HDs with only 19.8% of all sncRNAs now being yRFs, isomiRs increasing to 63.6%, and tRFs and rRFs more than tripling their presence to 6.1%.

CONCLUSION

The sncRNAomes of MKs and platelets are very rich and more complex than it has been believed. The evidence suggests complex mechanisms that sort MK sncRNAs into platelets. SARS-CoV-2 infection acutely alters the contents of platelets by changing the relative proportions of their sncRNAs.

Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentation facilitates multi-cancer early detection

Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.

The coming of age of liquid biopsy in neuro-oncology

The clinical role of liquid biopsy in oncology is growing significantly. In gliomas and other brain tumours, targeted sequencing of cell-free DNA (cfDNA) from CSF may help differential diagnosis when surgery is not recommended and be more representative of tumour heterogeneity than surgical specimens, unveiling targetable genetic alterations. Given the invasive nature of lumbar puncture to obtain CSF, the quantitative analysis of cfDNA in plasma is a lively option for patient follow-up. Confounding factors may be represented by cfDNA variations due to concomitant pathologies (inflammatory diseases, seizures) or clonal haematopoiesis. Pilot studies suggest that methylome analysis of cfDNA from plasma and temporary opening of the blood-brain barrier by ultrasound have the potential to overcome some of these limitations. Together with this, an increased understanding of mechanisms modulating the shedding of cfDNA by the tumour may help to decrypt the meaning of cfDNA kinetics in blood or CSF.

Superresolution Fluorescence Microscopy of Platelet Subcellular Structures as a Potential Tumor Liquid Biopsy

Blood-based tumor liquid biopsies are promising as an alternative or complement to tissue biopsies due to their noninvasiveness, convenience, and safety, and there is still a great demand for the discovery of new biomarkers for these biopsies. Here, nanoscale distribution patterns of subcellular structures in platelets, as imaged by structured illumination superresolution fluorescence microscopy, as a new type of potential biomarker for tumor liquid biopsies are presented. A standardized protocol for platelet sample preparation and developed an automated high-throughput image analysis workflow is established. The diagnostic capability based on the statistical analysis of 280 000 superresolution images of individual platelets from a variety of tumor patients, benign mass patients, and healthy volunteers (n = 206) is explored. These results suggest that the nanoscale distribution patterns of α-granules in platelets have the potential to be biomarkers for several cancers, including glioma and cervical, endometrial, and ovarian cancers, facilitating not only diagnosis but also therapeutic monitoring. This study provides a promising novel type of platelet parameter for tumor liquid biopsies at the subcellular level rather than the existing cellular or molecular level and opens up a new avenue for clinical applications of superresolution imaging techniques.

Clinical Cytometry for Platelets and Platelet Disorders

Clinical flow cytometry tests for inherited and acquired platelet disorders are useful diagnostic tools but are not widely available. Flow cytometric methods are available to detect inherited glycoprotein deficiencies, granule release (secretion defects), drug-induced thrombocytopenias, presence of antiplatelet antibodies, and pharmacodynamic inhibition by antiplatelet agents. New tests take advantage of advanced multicolor cytometers and allow identification of novel platelet subsets by high-dimensional immunophenotyping. Studies are needed to evaluate the value of these new tests for diagnosis and monitoring of therapy in patients with platelet disorders.

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.

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.

Tumor educated platelet: the novel BioSource for cancer detection

Platelets, involved in the whole process of tumorigenesis and development, constantly absorb and enrich tumor-specific substances in the circulation during their life span, thus called "Tumor Educated Platelets" (TEPs). The alterations of platelet mRNA profiles have been identified as tumor markers due to the regulatory mechanism of post-transcriptional splicing. Small nuclear RNAs (SnRNAs), the important spliceosome components in platelets, dominate platelet RNA splicing and regulate the splicing intensity of pre-mRNA. Endogenous variation at the snRNA levels leads to widespread differences in alternative splicing, thereby driving the development and progression of neoplastic diseases. This review systematically expounds the bidirectional tumor-platelets interactions, especially the tumor induced alternative splicing in TEP, and further explores whether molecules related to alternative splicing such as snRNAs can serve as novel biomarkers for cancer diagnostics.

Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection

Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.

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.

Contents in tumor-educated platelets as the novel biosource for cancer diagnostics

Liquid biopsy, a powerful non-invasive test, has been widely used in cancer diagnosis and treatment. Platelets, the second most abundant cells in peripheral blood, are becoming one of the richest sources of liquid biopsy with the capacity to systematically and locally respond to the presence of cancer and absorb and store circulating proteins and different types of nucleic acids, thus called "tumor-educated platelets (TEPs)". The contents of TEPs are significantly and specifically altered, empowering them with the potential as cancer biomarkers. The current review focuses on the alternation of TEP content, including coding and non-coding RNA and proteins, and their role in cancer diagnostics.

Dissecting order amidst chaos of programmed cell deaths: construction of a diagnostic model for KIRC using transcriptomic information in blood-derived exosomes and single-cell multi-omics data in tumor microenvironment

Background

Kidney renal clear cell carcinoma (KIRC) is the most frequently diagnosed subtype of renal cell carcinoma (RCC); however, the pathogenesis and diagnostic approaches for KIRC remain elusive. Using single-cell transcriptomic information of KIRC, we constructed a diagnostic model depicting the landscape of programmed cell death (PCD)-associated genes, namely cell death-related genes (CDRGs).

Methods

In this study, six CDRG categories, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA sequencing (RNA-seq) data of blood-derived exosomes from the exoRBase database, RNA-seq data of tissues from The Cancer Genome Atlas (TCGA) combined with control samples from the GTEx databases, and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were downloaded. Next, we intersected the differentially expressed genes (DEGs) of the KIRC cohort from exoRBase and the TCGA databases with CDRGs and DEGs obtained from single-cell datasets, further screening out the candidate biomarker genes using clinical indicators and machine learning methods and thus constructing a diagnostic model for KIRC. Finally, we investigated the underlying mechanisms of key genes and their roles in the tumor microenvironment using scRNA-seq, single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq), and the spatial transcriptomics sequencing (stRNA-seq) data of KIRC provided by the GEO database.

Result

We obtained 1,428 samples and 216,155 single cells. After the rational screening, we constructed a 13-gene diagnostic model for KIRC, which had high diagnostic efficacy in the exoRBase KIRC cohort (training set: AUC = 1; testing set: AUC = 0.965) and TCGA KIRC cohort (training set: AUC = 1; testing set: AUC = 0.982), with an additional validation cohort from GEO databases presenting an AUC value of 0.914. The results of a subsequent analysis revealed a specific tumor epithelial cell of TRIB3^high subset. Moreover, the results of a mechanical analysis showed the relatively elevated chromatin accessibility of TRIB3 in tumor epithelial cells in the scATAC data, while stRNA-seq verified that TRIB3 was predominantly expressed in cancer tissues.

Conclusions

The 13-gene diagnostic model yielded high accuracy in KIRC screening, and TRIB3^high tumor epithelial cells could be a promising therapeutic target for KIRC.

A narrative review for platelets and their RNAs in cancers: New concepts and clinical perspectives

Recent years have witnessed a growing body of evidence suggesting that platelets are involved in several stages of the metastatic process via direct or indirect interactions with cancer cells, contributing to the progression of neoplastic malignancies. Cancer cells can dynamically exchange components with platelets in and out of blood vessels, and directly phagocytose platelets to hijack their proteome, transcriptome, and secretome, or be remotely regulated by metabolites or microparticles released by platelets, resulting in phenotypic, genetic, and functional modifications. Moreover, platelet interactions with stromal and immune cells in the tumor microenvironment lead to alterations in their components, including the ribonucleic acid (RNA) profile, and complicate the impact of platelets on cancers. A deeper understanding of the roles of platelets and their RNAs in cancer will contribute to the development of anticancer strategies and the optimization of clinical management. Encouragingly, advances in high-throughput sequencing, bioinformatics data analysis, and machine learning have allowed scientists to explore the potential of platelet RNAs for cancer diagnosis, prognosis, and guiding treatment. However, the clinical application of this technique remains controversial and requires larger, multicenter studies with standardized protocols. Here, we integrate the latest evidence to provide a broader insight into the role of platelets in cancer progression and management, and propose standardized recommendations for the clinical utility of platelet RNAs to facilitate translation and benefit patients.