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

Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation

Advances in computer science in combination with the next-generation sequencing have introduced a new era in biology, enabling advanced state-of-the-art analysis of complex biological data. Bioinformatics is evolving as a union field between computer Science and biology, enabling the representation, storage, management, analysis and exploration of many types of data with a plethora of machine learning algorithms and computing tools. In this study, we used machine learning algorithms to detect differentially expressed genes between different types of cancer and showing the existence overlap to final results from RNA-sequencing analysis. The datasets were obtained from the National Center for Biotechnology Information resource. Specifically, dataset GSE68086 which corresponds to PMID:200,068,086. This dataset consists of 171 blood platelet samples collected from patients with six different tumors and healthy individuals. All steps for RNA-sequencing analysis (preprocessing, read alignment, transcriptome reconstruction, expression quantification and differential expression analysis) were followed. Machine Learning- based Random Forest and Gradient Boosting algorithms were applied to predict significant genes. The Rstudio statistical tool was used for the analysis.

Liquid biopsy: paving a new avenue for cancer research

The current constraints associated with cancer diagnosis and molecular profiling, which rely on invasive tissue biopsies or clinical imaging, have spurred the emergence of the liquid biopsy field. Liquid biopsy involves the extraction of circulating tumor cells (CTCs), circulating free or circulating tumor DNA (cfDNA or ctDNA), circulating cell-free RNA (cfRNA), extracellular vesicles (EVs), and tumor-educated platelets (TEPs) from bodily fluid samples. Subsequently, these components undergo molecular characterization to identify biomarkers that are critical for early cancer detection, prognosis, therapeutic assessment, and post-treatment monitoring. These innovative biosources exhibit characteristics analogous to those of the primary tumor from which they originate or interact. This review comprehensively explores the diverse technologies and methodologies employed for processing these biosources, along with their principal clinical applications.

Exploring the potential of multiomics liquid biopsy testing in the clinical setting of lung cancer

The transformative role of artificial intelligence (AI) and multiomics could enhance the diagnostic and prognostic capabilities of liquid biopsy (LB) for lung cancer (LC). Despite advances, the transition from tissue biopsies to more sophisticated, non-invasive methods like LB has been impeded by challenges such as the heterogeneity of biomarkers and the low concentration of tumour-related analytes. The advent of multiomics - enabled by deep learning algorithms - offers a solution by allowing the simultaneous analysis of various analytes across multiple biological fluids, presenting a paradigm shift in cancer diagnostics. Through multi-marker, multi-analyte and multi-source approaches, this review showcases how AI and multiomics are identifying clinically valuable biomarker combinations that correlate with patients' health statuses. However, the path towards clinical implementation is fraught with challenges, including study reproducibility and lack of methodological standardization, thus necessitating urgent solutions to solve these common issues.

DNA Logical Computing on a Transistor for Cancer Molecular Diagnosis

Given the high degree of variability and complexity of cancer, precise monitoring and logical analysis of different nucleic acid markers are crucial for improving diagnostic precision and patient survival rates. However, existing molecular diagnostic methods normally suffer from high cost, cumbersome procedures, dependence on specialized equipment and the requirement of in-depth expertise in data analysis, failing to analyze multiple cancer-associated nucleic acid markers and provide immediate results in a point-of-care manner. Herein, we demonstrate a transistor-based DNA molecular computing (TDMC) platform that enables simultaneous detection and logical analysis of multiple microRNA (miRNA) markers on a single transistor. TDMC can perform not only basic logical operations such as "AND" and "OR", but also complex cascading computing, opening up new dimensions for multi-index logical analysis. Owing to the high efficiency, sensing and computations of multi-analytes can be operated on a transistor at a concentration as low as 2×10-16 M, reaching the lowest concentration for DNA molecular computing. Thus, TDMC achieves an accuracy of 98.4 % in the diagnosis of hepatocellular carcinoma from 62 serum samples. As a convenient and accurate platform, TDMC holds promise for applications in "one-stop" personalized medicine.

Unlocking the intricacies: Exploring the complex interplay between platelets and ovarian cancer

Ovarian cancer, an aggressive malignancy of the female reproductive tract, is frequently linked to an elevated risk of thrombotic events. This association is manifested by a pronounced rise in platelet counts and activation levels. Current research firmly supports the pivotal role of platelets in the oncogenic processes of ovarian cancer, influencing tumor cell proliferation and metastasis. Platelets influence these processes through direct interactions with tumor cells or by secreting cytokines and growth factors that enhance tumor growth, angiogenesis, and metastasis. This review aims to thoroughly dissect the interactions between platelets and ovarian cancer cells, emphasizing their combined role in tumor progression and associated thrombotic events. Additionally, it summarizes therapeutic strategies targeting platelet-cancer interface which show significant promise. Such approaches could not only be effective in managing the primary ovarian tumor but also play a pivotal role in preventing metastasis and attenuating thrombotic complications associated with ovarian cancer.

Prospective, international, multisite comparison of platelet isolation techniques for genome-wide transcriptomics: communication from the SSC of the ISTH

Genome-wide platelet transcriptomics is increasingly used to uncover new aspects of platelet biology and as a diagnostic and prognostic tool. Nevertheless, platelet isolation methods for transcriptomic studies are not standardized, introducing challenges for cross-study comparisons, data integration, and replication. In this prospective multicenter study, called "Standardizing Platelet Transcriptomics for Discovery, Diagnostics, and Therapeutics in the Thrombosis and Hemostasis Community (STRIDE)" by the International Society on Thrombosis and Haemostasis Scientific and Standardization Committees, we assessed how 3 of the most commonly used platelet isolation protocols influence metrics from next-generation bulk RNA sequencing and functional assays. Compared with washing alone, more stringent removal of leukocytes by anti-CD45 beads or PALL filters resulted in a sufficient quantity of RNA for next-generation sequencing and similar quality of RNA sequencing metrics. Importantly, stringent removal of leukocytes resulted in the lower relative expression of known leukocyte-specific genes and the higher relative expression of known platelet-specific genes. The results were consistent across enrolling sites, suggesting that the techniques are transferrable and reproducible. Moreover, all 3 isolation techniques did not influence basal platelet reactivity, but agonist-induced integrin αIIbβ3 activation is reduced by anti-CD45 bead isolation compared with washing alone. In conclusion, the isolation technique chosen influences genome-wide transcriptional and functional assays in platelets. These results should help the research community make informed choices about platelet isolation techniques in their own platelet studies.

Liquid Biopsy in Neuropsychiatric Disorders: A Step Closer to Precision Medicine

Psychiatric disorders are among the leading causes of disease burden worldwide. Despite their significant impact, their diagnosis remains challenging due to symptom heterogeneity, psychiatric comorbidity, and the lack of objective diagnostic tests and well-defined biomarkers. Leveraging genomic, epigenomic, and fragmentomic technologies, circulating cell-free DNA (ccfDNA)-based liquid biopsies have emerged as a potential non-invasive diagnosis and disease-monitoring tool. ccfDNA is a DNA species released into circulation from all types of cells through passive and active mechanisms and can serve as a biomarker for various diseases, namely, cancer. Despite their potential, the application of ccfDNA in neuropsychiatry remains underdeveloped. In this review, we provide an overview of liquid biopsies and their components, with a particular focus on ccfDNA. With a summary of pre-analytical practices and current ccfDNA technologies, we highlight the current state of research regarding the use of ccfDNA as a biomarker for neuropsychiatric disorders. Finally, we discuss future steps to unlock ccfDNA's potential in clinical practice.

Mining nucleic acid "omics" to boost liquid biopsy in cancer

Treatments for cancer patients are becoming increasingly complex, and there is a growing desire from clinicians and patients for biomarkers that can account for this complexity to support informed decisions about clinical care. To achieve precision medicine, the new generation of biomarkers must reflect the spatial and temporal heterogeneity of cancer biology both between patients and within an individual patient. Mining the different layers of 'omics in a multi-modal way from a minimally invasive, easily repeatable, liquid biopsy has increasing potential in a range of clinical applications, and for improving our understanding of treatment response and resistance. Here, we detail the recent developments and methods allowing exploration of genomic, epigenomic, transcriptomic, and fragmentomic layers of 'omics from liquid biopsy, and their integration in a range of applications. We also consider the specific challenges that are posed by the clinical implementation of multi-omic liquid biopsies.

Research progress on platelets in glioma

ABSTRACT

Gliomas are the most common primary neuroepithelial tumors of the central nervous system in adults, of which glioblastoma is the deadliest subtype. Apart from the intrinsically indestructible characteristics of glioma (stem) cells, accumulating evidence suggests that the tumor microenvironment also plays a vital role in the refractoriness of glioblastoma. The primary functions of platelets are to stop bleeding and regulate thrombosis under physiological conditions. Furthermore, platelets are also active elements that participate in a variety of processes of tumor development, including tumor growth, invasion, and chemoresistance. Glioma cells recruit and activate resting platelets to become tumor-educated platelets (TEPs), which in turn can promote the proliferation, invasion, stemness, and chemoresistance of glioma cells. TEPs can be used to obtain genetic information about gliomas, which is helpful for early diagnosis and monitoring of therapeutic effects. Platelet membranes are intriguing biomimetic materials for developing efficacious drug carriers to enhance antiglioma activity. Herein, we review the recent research referring to the contribution of platelets to the malignant characteristics of gliomas and focusing on the molecular mechanisms mediating the interaction between TEPs and glioma (stem) cells, as well as present the challenges and opportunities in targeting platelets for glioma therapy.

The potential of circulating cell-free RNA in CNS tumor diagnosis and monitoring: A liquid biopsy approach

Early detection of malignancies, through regular cancer screening, has already proven to have potential to increase survival rates. Yet current screening methods rely on invasive, expensive tissue sampling that has hampered widespread use. Liquid biopsy is noninvasive and represents a potential approach to precision oncology, based on molecular profiling of body fluids. Among these, circulating cell-free RNA (cfRNA) has gained attention due to its diverse composition and potential as a sensitive biomarker. This review provides an overview of the processes of cfRNA delivery into the bloodstream and the role of cfRNA detection in the diagnosis of central nervous system (CNS) tumors. Different types of cfRNAs such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) have been recognized as potential biomarkers in CNS tumors. These molecules exhibit differential expression patterns in the plasma, cerebrospinalfluid (CSF) and urine of patients with CNS tumors, providing information for diagnosing the disease, predicting outcomes, and assessing treatment effectiveness. Few clinical trials are currently exploring the use of liquid biopsy for detecting and monitoring CNS tumors. Despite obstacles like sample standardization and data analysis, cfRNA shows promise as a tool in the diagnosis and management of CNS tumors, offering opportunities for early detection, personalized therapy, and improved patient outcomes.

RNAseqCovarImpute: a multiple imputation procedure that outperforms complete case and single imputation differential expression analysis

Missing covariate data is a common problem that has not been addressed in observational studies of gene expression. Here, we present a multiple imputation method that accommodates high dimensional gene expression data by incorporating principal component analysis of the transcriptome into the multiple imputation prediction models to avoid bias. Simulation studies using three datasets show that this method outperforms complete case and single imputation analyses at uncovering true positive differentially expressed genes, limiting false discovery rates, and minimizing bias. This method is easily implemented via an R Bioconductor package, RNAseqCovarImpute that integrates with the limma-voom pipeline for differential expression analysis.

Impact of Molecular Profiling on Therapy Management in Breast Cancer

Breast cancer (BC) remains the most prevalent cancer among women and the leading cause of cancer-related mortality worldwide. The heterogeneity of BC in terms of histopathological features, genetic polymorphisms, and response to therapies necessitates a personalized approach to treatment. This review focuses on the impact of molecular profiling on therapy management in breast cancer, emphasizing recent advancements in next-generation sequencing (NGS) and liquid biopsies. These technologies enable the identification of specific molecular subtypes and the detection of blood-based biomarkers such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and tumor-educated platelets (TEPs). The integration of molecular profiling with traditional clinical and pathological data allows for more tailored and effective treatment strategies, improving patient outcomes. This review also discusses the current challenges and prospects of implementing personalized cancer therapy, highlighting the potential of molecular profiling to revolutionize BC management through more precise prognostic and therapeutic interventions.

The impact of platelets on the metastatic potential of tumour cells

In cancer, activation of platelets by tumor cells is critical to disease progression. Development of precise antiplatelet targeting may improve outcomes from anticancer therapy. Alongside a distinct shift in functionality such as pro-metastatic and pro-coagulant properties, platelet production is often accelerated significantly early in carcinogenesis and the cancer-associated thrombocytosis increases the risk of metastasis formation and thromboembolic events. Tumor-activated platelets facilitate the proliferation of migrating tumor cells and shield them from immune surveillance and physical stress during circulation. Additionally, platelet-tumor cell interactions promote tumor cell intravasation, intravascular arrest, and extravasation through a repertoire of adhesion molecules, growth factors and angiogenic factors. Particularly, the presence of circulating tumor cell (CTC) clusters in association with platelets is a negative prognostic indicator. The contribution of platelets to the metastatic process is an area of intense investigation and this review provides an overview of the advances in understanding platelet-tumor cell interactions and their contribution to disease progression. Also, we review the potential of targeting platelets to interfere with the metastatic process.

Green manure application improves insect resistance of subsequent crops through the optimization of soil nutrients and rhizosphere microbiota

Green manure (GM) enhances organic agriculture by improving soil quality and microbiota, yet its effects on plant resistance are unclear. Investigating the GM crop hairy vetch-maize rotation system, a widely adopted GM practice in China, we aimed to determine maize resistance to fall armyworm (FAW), Spodoptera frugiperda (Smith), a major pest. Greenhouse experiments with three fertilization treatments (chemical fertilizer, GM, and a combination) revealed that GM applications significantly improved maize resistance to FAW, evidenced by reduced larval feeding preference and pupal weight. GM also enriched soil nutrients, beneficial rhizobacteria, and resistance-related compounds, such as salicylic acid, jasmonic acid, and 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), in maize. The results suggest that GM-amended soils and microbial communities may have an underestimated role in regulating host plant adaptation to pests by increasing plant resistance. This study can provide information for developing and implementing environmentally friendly and sustainable cropping systems with enhanced resistance to pests and diseases.

Clinical application of liquid biopsy in colorectal cancer: detection, prediction, and treatment monitoring

Colorectal cancer (CRC) is one of the most prevalent malignancies affecting the gastrointestinal tract and is ranked third among cancers with the highest incidence and second-highest mortality rate worldwide. CRC exhibits a slow progression providing a wide treatment window. The currently employed CRC screening methods have shown great potential to prevent CRC and reduce CRC-related morbidity and mortality. The diagnosis of CRC is achieved by colonoscopy and tissue biopsy, with studies showing that liquid biopsy is more effective in detecting and diagnosing early CRC patients. Increasing number of studies have shown that the tumor components shed into circulating blood can be detected in liquid form, and can be applied in the clinical management of CRC. Analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), or tumor-associated platelets (TEPs) in the blood can be used for early screening and diagnosis of CRC, aid tumor staging, treatment response monitoring, and prediction of CRC recurrence and metastasis in a minimally invasive manner. This chapter provides an updated review of CTCs, ctDNA, and TEPs as novel biomarkers for CRC, highlighting their strengths and limitations.

PKCα Induced the Generation of Extracellular Vesicles in Activated Platelets to Promote Breast Cancer Metastasis

Platelet extracellular vesicles (PEVs) play an important role in tumor development. However, the mechanisms underlying their biogenesis have not been fully elucidated. Protein kinase Cα (PKCα) is an important regulator of platelet activation, but the effect of PKCα on EV generation is unclear. We used small-particle flow cytometry and found that the number of PEVs was increased in patients with breast cancer compared to those with benign breast disease. This was accompanied by increased levels of activated PKCα in breast cancer platelets. Treating platelets with the PKCα agonist phorbol 12-myristate 13-acetate (PMA) increased the phosphorylation PKCα and induced PEV production, while the PKCα inhibitor GÖ6976 showed the opposite effects. Notably, incubating platelets from patients with benign tumors with the culture supernatant of MDA-MB-231 cells induced PKCα phosphorylation in the platelets. Mass spectrometry and coimmunoprecipitation assays showed that Dynamin 2 (DNM2), a member of the guanosine-triphosphate-binding protein family, might cooperate with activated PKCα to regulate PEV production by breast cancer platelets. Similar results were observed in a mouse model of lung metastasis. In addition, PEVs were engulfed by breast cancer cells and promoted cancer cell migration and invasion via miR-1297 delivery. These findings suggested that PKCα cooperates with DNM2 to induce PEV generation, and PEV release might triggered by factors in the breast cancer environment.

Immunological Signatures for Early Detection of Human Head and Neck Squamous Cell Carcinoma through RNA Transcriptome Analysis of Blood Platelets

Although there has been a reduction in head and neck squamous cell carcinoma occurrence, it continues to be a serious global health concern. The lack of precise early diagnostic biomarkers and postponed diagnosis in the later stages are notable constraints that contribute to poor survival rates and emphasize the need for innovative diagnostic methods. In this study, we employed machine learning alongside weighted gene co-expression network analysis (WGCNA) and network biology to investigate the gene expression patterns of blood platelets, identifying transcriptomic markers for HNSCC diagnosis. Our comprehensive examination of publicly available gene expression datasets revealed nine genes with significantly elevated expression in samples from individuals diagnosed with HNSCC. These potential diagnostic markers were further assessed using TCGA and GTEx datasets, demonstrating high accuracy in distinguishing between HNSCC and non-cancerous samples. The findings indicate that these gene signatures could revolutionize early HNSCC identification. Additionally, the study highlights the significance of tumor-educated platelets (TEPs), which carry RNA signatures indicative of tumor-derived material, offering a non-invasive source for early-detection biomarkers. Despite using platelet and tumor samples from different individuals, our results suggest that TEPs reflect the transcriptomic and epigenetic landscape of tumors. Future research should aim to directly correlate tumor and platelet samples from the same patients to further elucidate this relationship. This study underscores the potential of these biomarkers in transforming early diagnosis and personalized treatment strategies for HNSCC, advocating for further research to validate their predictive and therapeutic potential.

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.

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood

INTRODUCTION

We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood.

MATERIALS AND METHODS

We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47).

RESULTS

A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%.

CONCLUSION

A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

Prospects of liquid biopsy in the prognosis and clinical management of gastrointestinal cancers

Gastrointestinal (GI) cancers account for one-fourth of the global cancer incidence and are incriminated to cause one-third of cancer-related deaths. GI cancer includes esophageal, gastric, liver, pancreatic, and colorectal cancers, mostly diagnosed at advanced stages due to a lack of accurate markers for early stages. The invasiveness of diagnostic methods like colonoscopy for solid biopsy reduces patient compliance as it cannot be frequently used to screen patients. Therefore, minimally invasive approaches like liquid biopsy may be explored for screening and early identification of gastrointestinal cancers. Liquid biopsy involves the qualitative and quantitative determination of certain cancer-specific biomarkers in body fluids such as blood, serum, saliva, and urine to predict disease progression, therapeutic tolerance, toxicities, and recurrence by evaluating minimal residual disease and its correlation with other clinical features. In this review, we deliberate upon various tumor-specific cellular and molecular entities such as circulating tumor cells (CTCs), tumor-educated platelets (TEPs), circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), exosomes, and exosome-derived biomolecules and cite recent advances pertaining to their use in predicting disease progression, therapy response, or risk of relapse. We also discuss the technical challenges associated with translating liquid biopsy into clinical settings for various clinical applications in gastrointestinal cancers.

Pathformer: a biological pathway informed transformer for disease diagnosis and prognosis using multi-omics data

MOTIVATION

Multi-omics data provide a comprehensive view of gene regulation at multiple levels, which is helpful in achieving accurate diagnosis of complex diseases like cancer. However, conventional integration methods rarely utilize prior biological knowledge and lack interpretability.

RESULTS

To integrate various multi-omics data of tissue and liquid biopsies for disease diagnosis and prognosis, we developed a biological pathway informed Transformer, Pathformer. It embeds multi-omics input with a compacted multi-modal vector and a pathway-based sparse neural network. Pathformer also leverages criss-cross attention mechanism to capture the crosstalk between different pathways and modalities. We first benchmarked Pathformer with 18 comparable methods on multiple cancer datasets, where Pathformer outperformed all the other methods, with an average improvement of 6.3%-14.7% in F1 score for cancer survival prediction, 5.1%-12% for cancer stage prediction, and 8.1%-13.6% for cancer drug response prediction. Subsequently, for cancer prognosis prediction based on tissue multi-omics data, we used a case study to demonstrate the biological interpretability of Pathformer by identifying key pathways and their biological crosstalk. Then, for cancer early diagnosis based on liquid biopsy data, we used plasma and platelet datasets to demonstrate Pathformer's potential of clinical applications in cancer screening. Moreover, we revealed deregulation of interesting pathways (e.g. scavenger receptor pathway) and their crosstalk in cancer patients' blood, providing potential candidate targets for cancer microenvironment study.

AVAILABILITY AND IMPLEMENTATION

Pathformer is implemented and freely available at https://github.com/lulab/Pathformer.

Circulating tumor cells et al.: towards a comprehensive liquid biopsy approach in breast cancer

Liquid biopsy has emerged as a crucial tool in managing breast cancer (BC) patients, offering a minimally invasive approach to detect circulating tumor biomarkers. Until recently, the majority of the studies in BC focused on evaluating a single liquid biopsy analyte, primarily circulating tumor DNA and circulating tumor cells (CTCs). Despite the proven prognostic and predictive value of CTCs, their low abundance when detected using enrichment methods, especially in the early stages, poses a significant challenge. It is becoming evident that combining diverse circulating biomarkers, each representing different facets of tumor biology, has the potential to enhance the management of patients with BC. This article emphasizes the importance of considering these biomarkers as complementary/synergistic rather than competitive, recognizing their ability to contribute to a comprehensive disease profile. The review provides an overview of the clinical significance of simultaneously analyzing CTCs and other biomarkers, including cell-free circulating DNA, extracellular vesicles, non-canonical CTCs, cell-free RNAs, and non-malignant cells. Such a comprehensive liquid biopsy approach holds promise not only in BC but also in other cancer types, offering opportunities for early detection, prognostication, and therapy monitoring. However, addressing associated challenges, such as refining detection methods and establishing standardized protocols, is crucial for realizing the full potential of liquid biopsy in transforming our understanding and approach to BC. As the field evolves, collaborative efforts will be instrumental in unlocking the revolutionary impact of liquid biopsy in BC research and management.

Plasma Circular RNAs as Biomarkers for Breast Cancer

Breast cancer (BC) is currently the most common neoplasm, the second leading cause of cancer death in women worldwide, and is a major health problem. The discovery of new biomarkers is crucial to improve our knowledge of breast cancer and strengthen our clinical approaches to diagnosis, prognosis, and follow-up. In recent decades, there has been increasing interest in circulating RNA (circRNA) as modulators of gene expression involved in tumor development and progression. The study of circulating circRNAs (ccircRNAs) in plasma may provide new non-invasive diagnostic, prognostic, and predictive biomarkers for BC. This review describes the latest findings on BC-associated ccircRNAs in plasma and their clinical utility. Several ccircRNAs in plasma have shown great potential as BC biomarkers, especially from a diagnostic point of view. Mechanistically, most of the reported BC-associated ccircRNAs are involved in the regulation of cell survival, proliferation, and invasion, mainly via MAPK/AKT signaling pathways. However, the study of circRNAs is a relatively new area of research, and a larger number of studies will be crucial to confirm their potential as plasma biomarkers and to understand their involvement in BC.

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.

Structural Features and Physiological Associations of Human 14-3-3ζ Pseudogenes

There are about 14,000 pseudogenes that are mutated or truncated sequences resembling functional parent genes. About two-thirds of pseudogenes are processed, while others are duplicated. Although initially thought dead, emerging studies indicate they have functional and regulatory roles. We study 14-3-3ζ, an adaptor protein that regulates cytokine signaling and inflammatory diseases, including rheumatoid arthritis, cancer, and neurological disorders. To understand how 14-3-3ζ (gene symbol YWHAZ) performs diverse functions, we examined the human genome and identified nine YWHAZ pseudogenes spread across many chromosomes. Unlike the 32 kb exon-to-exon sequence in YWHAZ, all pseudogenes are much shorter and lack introns. Out of six, four YWHAZ exons are highly conserved, but the untranslated region (UTR) shows significant diversity. The putative amino acid sequence of pseudogenes is 78-97% homologous, resulting in striking structural similarities with the parent protein. The OMIM and Decipher database searches revealed chromosomal loci containing pseudogenes are associated with human diseases that overlap with the parent gene. To the best of our knowledge, this is the first report on pseudogenes of the 14-3-3 family protein and their implications for human health. This bioinformatics-based study introduces a new insight into the complexity of 14-3-3ζ's functions in biology.

Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors

Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The complexity of biological systems and the explosive growth of biomarker data have driven machine learning to become a powerful tool for mining and processing big data from disease diagnosis sensors. With the development of bioinformatics and artificial intelligence (AI), machine learning models formed by data mining have been able to guide more sensitive and accurate molecular computing. This review presents an overview of big data collection approaches and fundamental machine learning algorithms and discusses recent advances in machine learning and molecular computational disease diagnostic sensors. More specifically, we highlight existing modular workflows and key opportunities and challenges for machine learning to achieve disease diagnosis through big data mining.

Comparison of platelet proteomic profiles between children and adults reveals origins of functional differences

BACKGROUND

Platelets are blood cells responsible for the prevention of blood loss upon vessel wall disruption. It has been demonstrated that platelet functioning differs significantly between adult and pediatric donors. This study aimed to identify potential differences between the protein composition of platelets of pediatric, adolescent, and adult donors.

METHODS

Platelet functional testing was conducted with live cell flow cytometry. Using a straightforward approach to platelet washing based on the sequential platelets centrifugation-resuspension, we were able to obtain stable and robust proteomics results, which corresponded to previously published data.

RESULTS

We have identified that pediatric donors' platelets have increased amounts of proteins, responsible for mitochondrial activity, proteasome activity, and vesicle transport. Flow cytometry analysis of platelet intracellular signaling and functional responses revealed that platelets of the pediatric donors have diminished granule secretion and increased quiescent platelet calcium concentration and decreased calcium mobilization in response to ADP. We could explain the observed changes in calcium responses by the increased mitochondria protein content, and the changes in granule secretion could be explained by the differences in vesicle transport protein content.

CONCLUSIONS

Therefore, we can conclude that the age-dependence of platelet functional responses originates from the difference in platelet protein content.

IMPACT

Platelets of infants are known to functionally differ from the platelet of adult donors, although the longevity and persistivity of these differences are debatable. Pediatric donor platelets have enhanced amounts of mitochondrial, proteasomal, and vesicle transport proteins. Platelets of the pediatric donors had increased cytosolic calcium in the resting state, what is explained by the increased numbers of mitochondrial proteins. Infants had decreased platelet granule release, which resolved upon adolescence. Thus, platelets of the infants should be assessed differently from adult platelets. Differences in platelet proteomic contents persisted in adolescent groups, yet, no significant differences in platelet function were observed.

PD-L1 mRNA derived from tumor-educated platelets as a potential immunotherapy biomarker in non-small cell lung cancer

Background

To date, the role of programmed death ligand-1 (PD-L1) messenger RNA (mRNA) derived from tumor-educated platelets (TEPs) has not been well investigated in patients with advanced non-small cell lung cancer (NSCLC). A few reports have examined whether mRNA in TEPs can predict the clinical responses of patients with advanced NSCLC following immunotherapy. This study aimed to identify novel biomarkers to improve the clinical benefits and outcomes of NSCLC patients.

Methods

Advanced NSCLC patients receiving a combination of immunotherapy and chemotherapy, or immunotherapy alone as a first- or second-line treatment at the Fudan University Shanghai Cancer Center were enrolled in this study. All the patients had wild-type epidermal growth factor receptor/anaplastic lymphoma kinase. The patients were enrolled in clinical trials for immune checkpoint inhibitors (ICIs), including nivolumab, pembrolizumab, atezolizumab, durvalumab, tremelimumab, and camrelizumab. Tumoral PD-L1 expression was tested by immunohistochemistry (PD-L1 22C3 pharmDx kit, Agilent, Santa Clara, CA, USA) in archived tissue samples, when available, to calculate the tumor proportion scores (TPSs). RNA and exosomal RNA of blood were isolated before immunotherapy using the Yunying RNA extraction kit (Yunying Medicine, Shanghai, China). The concentration and quality of the RNA was determined using a Qubit fluorometer (Life Technologies, Carlsbad, CA, USA). Finally, we analyzed the predictive value of TEP-derived PD-L1 mRNA expression and association with the level of the tumoral PD-L1 expression.

Results

In total, 72 patients were enrolled in this study. Most of the patients were male (n=54, 75.0%), had adenocarcinoma (n=49, 68.1%). We found there was no significant correlation between the TEP-derived mRNA of PD-L1 and tumoral PD-L1 expression based on the results of the Pearson Correlation test (r=-0.19, P=0.233). Based on the median of PD-L1 mRNA, 72 patients were divided into a high PD-L1 group and a low PD-L1 group. We found that 19 patients (44.4%) responded to immunotherapy [partial response or progression-free survival (PFS) >6 months] in the high PD-L1 group, but only five patients (13.9%) responded to immunotherapy in the low PD-L1 group (P<0.01). The median PFS of the low PD-L1 group was lower than that of the high PD-L1 group (2.8 vs. 8.3 months, P<0.001). For the patients who were treated with immunotherapy alone (n=64), a similar PFS advantage was observed in the high PD-L1 group (2.8 vs. 8.0 months, P=0.002).

Conclusions

This article presented the first data on TEP-derived PD-L1 mRNA in advanced NSCLC patients following immunotherapy and showed the potential advantage of using it as the surrogate biomarker for predicting the PFS and overall survival of patients following immunotherapy.

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.

Research progress on the correlation between platelet aggregation and tumor progression

Platelets are generally considered as the main functional unit of the coagulation system. However, more and more studies have confirmed that platelets also have an important relationship with tumor progression. Tumor cells can utilize platelets to promote their own infiltration and hematogenous metastasis, and platelets are activated and aggregated in this process. Therefore, platelet aggregation may be a concomitant marker of tumor progression. This is of great significance for predicting tumor metastasis before timely treatments.

Heterogeneity of platelets and their responses

There has been increasing recognition of heterogeneity in blood platelets and their responses, particularly in recent years, where next-generation technologies and advanced bioinformatic tools that interrogate "big data" have enabled large-scale studies of RNA and protein expression across a growing list of disease states. However, pioneering platelet biologists and clinicians were already hypothesizing upon and investigating heterogeneity in platelet (and megakaryocyte) activity and platelet metabolism and aggregation over half a century ago. Building on their foundational hypotheses, in particular Professor Marian A. Packham's pioneering work and a State of the Art lecture in her memoriam at the 2023 International Society on Thrombosis and Haemostasis Congress by Anandi Krishnan, this review outlines the key features that contribute to the heterogeneity of platelets between and within individuals. Starting with important epidemiologic factors, we move stepwise through successively smaller scales down to heterogeneity revealed by single-cell technologies in health and disease. We hope that this overview will urge future scientific and clinical studies to recognize and account for heterogeneity of platelets and aim to apply methods that capture that heterogeneity. Finally, we summarize other exciting new data presented on this topic at the 2023 International Society on Thrombosis and Haemostasis Congress.

N-acetyl-aspartate metabolism at the interface of cancer, immunity, and neurodegeneration

N-acetyl-L-aspartic acid (NAA) is a prominent amino acid derivative primarily associated with vertebrate brain metabolism. This review delineates the critical role of NAA across various cell types and its significance in pathophysiological contexts, including Canavan disease and cancer metabolism. Although traditionally linked with myelination and aspartoacylase-driven carbon donation, its significance as a carbon source for myelination remains debated. Evidence suggests that intact NAA might substantially impact cellular signaling, particularly processes such as histone acetylation. Beyond the brain, NAA metabolism's relevance is evident in diverse tissues, such as adipocytes, immune cells, and notably, cancer cells. In several cancer types, there is an observed upregulation of NAA synthesis accompanied by a simultaneous downregulation of its degradation. This pattern highlights the potential signaling role of intact NAA in disease.

Platelet RNA sequencing reveals profile of caffeic acid affecting hemostasis in mice

Background

Caffeic acid (CA) is a naturally occurring phenolic compound with diverse pharmacologic properties. CA plays a crucial role in hemostasis by increasing platelet count. However, the mechanism by which CA regulates platelets to promote hemostasis remains unclear.

Objectives

We aim to identify the potential target pathways and genes by which CA regulates platelets to promote hemostasis.

Methods

We performed RNA sequencing (RNA-seq) analysis of mouse platelet pools in both the CA-gavaged group and phosphate-buffered saline-gavaged group.

Results

The 12,934 expressed transcripts had been annotated after platelet RNA-seq. Compared with the phosphate-buffered saline group, 987 differentially expressed genes (DEGs) were identified, of which 466 were downregulated and 521 were upregulated in CA group. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome gene set enrichment analysis demonstrated that upregulated DEGs were enriched in the pathways of hemostasis, platelet activation, signaling, aggregation, and degranulation. Moreover, Kyoto Encyclopedia of Genes and Genomes and Reactome gene set enrichment analysis revealed that 5 of the 25 cosignificantly upregulated DEGs were essential in CA-mediated platelet regulation to promote hemostasis.

Conclusion

Our findings of platelet RNA-seq analysis demonstrate that CA regulates the gene expression of hemostasis and platelet activation-related pathways to increase platelet count and promote hemostasis. It will also provide reference molecular resources for future research on the function and mechanism by which CA regulates platelets to promote hemostasis.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Tumor-derived cell-free DNA and circulating tumor cells: partners or rivals in metastasis formation?

The origin of metastases is a topic that has sparked controversy. Despite recent advancements, metastatic disease continues to pose challenges. The first admitted model of how metastases develop revolves around cells breaking away from the primary tumor, known as circulating tumor cells (CTCs). These cells survive while circulating through the bloodstream and subsequently establish themselves in secondary organs, a process often referred to as the "metastatic cascade". This intricate and dynamic process involves various steps, but all the mechanisms behind metastatic dissemination are not yet comprehensively elucidated. The "seed and soil" theory has shed light on the phenomenon of metastatic organotropism and the existence of pre-metastatic niches. It is now established that these niches can be primed by factors secreted by the primary tumor before the arrival of CTCs. In particular, exosomes have been identified as important contributors to this priming. Another concept then emerged, i.e. the "genometastasis" theory, which challenged all other postulates. It emphasizes the intriguing but promising role of cell-free DNA (cfDNA) in metastasis formation through oncogenic formation of recipient cells. However, it cannot be ruled out that all these theories are intertwined. This review outlines the primary theories regarding the metastases formation that involve CTCs, and depicts cfDNA, a potential second player in the metastasis formation. We discuss the potential interrelationships between CTCs and cfDNA, and propose both in vitro and in vivo experimental strategies to explore all plausible theories.

Liquid biopsy in colorectal cancer

Liquid biopsy refers to a set of pathological samples retrieved from non-solid sources, such as blood, cerebrospinal fluid, urine, and saliva through non-invasive or minimally invasive approaches. In the recent decades, an increasing number of studies have focused on clinical applications and improving technological investigation of liquid biopsy biosources for diagnostic goals particularly in cancer. Materials extracted from these sources and used for medical evaluations include cells like circulating tumor cells (CTCs), tumor-educated platelets (TEPs), cell-free nucleic acids released by cells, such as circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), cell-free RNA (cfRNA), and exosomes. Playing significant roles in the pathogenesis of human malignancies, analysis of these sources can provide easier access to genetic and transcriptomic information of the cancer tissue even better than the conventional tissue biopsy. Notably, they can represent the inter- and intra-tumoral heterogeneity and accordingly, liquid biopsies demonstrate strengths for improving diagnosis in early detection and screening, monitoring and follow-up after therapies, and personalization of therapeutical strategies in various types of human malignancies. In this review, we aim to discuss the roles, functions, and analysis approaches of liquid biopsy sources and their clinical implications in human malignancies with a focus on colorectal cancer.

TEP SNORD12B, SNORA63, and SNORD14E as novel biomarkers for hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC)

PURPOSE

The alterations of RNA profile in tumor-educated platelets (TEPs) have been described as a novel biosource for cancer diagnostics. This study aimed to explore the potential snoRNAs in TEP as biomarkers for diagnostics of hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC).

METHODS

Platelets were isolated using low-speed centrifugation and subjected to a quantitative polymerase chain reaction (qPCR) for snoRNAs detection.

RESULTS

Down-regulated SNORD12B and SNORD14E as well as up-regulated SNORA63 were identified in TEP from HBV-related HCC, which could act as diagnostic biomarkers for HBV-related HCC as well as the early disease. Besides, TEP SNORD12B, SNORD14E, and SNORA63 facilitate the diagnostic performance of AFP and achieve favorable diagnostics efficiency for HBV-related HCC when combined with platelet parameters.

CONCLUSIONS

Aberrant expression of SNORD12B, SNORA63, and SNORD14E in TEPs could serve as the novel and non-invasive biomarkers for HBV-related HCC diagnosis.

Tumor-educated platelets

Beyond traditional roles in homeostasis and coagulation, growing evidence suggests that platelets also reflect malignant transformation in cancer. Platelets are present in the tumor microenvironment where they interact with cancer cells. This interaction results in direct and indirect "education" as evident by platelet alterations in adhesion molecules, glycoproteins, nucleic acids, proteins and various receptors. Subsequently, these tumor-educated platelets (TEPs) circulate throughout the body and play pivotal roles in promotion of tumor growth and dissemination. Accordingly, platelet status can be considered a unique blood-based biomarker that can potentially predict prognosis and therapeutic success. Recently, liquid biopsies including TEPs have received much attention as safe, minimally invasive and sensitive alternatives for patient management. Herein, we provide an overview of TEPs and explore their benefits and limitations in cancer.

The dynamic role of platelets in cancer progression and their therapeutic implications

Systemic antiplatelet treatment represents a promising option to improve the therapeutic outcomes and therapeutic efficacy of chemotherapy and immunotherapy due to the critical contribution of platelets to tumour progression. However, until recently, targeting platelets as a cancer therapeutic has been hampered by the elevated risk of haemorrhagic and thrombocytopenic (low platelet count) complications owing to the lack of specificity for tumour-associated platelets. Recent work has advanced our understanding of the molecular mechanisms responsible for the contribution of platelets to tumour progression and metastasis. This has led to the identification of the biological changes in platelets in the presence of tumours, the complex interactions between platelets and tumour cells during tumour progression, and the effects of platelets on antitumour therapeutic response. In this Review, we present a detailed picture of the dynamic roles of platelets in tumour development and progression as well as their use in diagnosis, prognosis and monitoring response to therapy. We also provide our view on how to overcome challenges faced by the development of precise antiplatelet strategies for safe and efficient clinical cancer therapy.

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.

A Comprehensive Review of the Potential Role of Liquid Biopsy as a Diagnostic, Prognostic, and Predictive Biomarker in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most lethal malignant diseases, with a mortality rate being close to incidence. Due to its heterogeneity and plasticity, as well as the lack of distinct symptoms in the early phases, it is very often diagnosed at an advanced stage, resulting in poor prognosis. Traditional tissue biopsies remain the gold standard for making a diagnosis, but have an obvious disadvantage in their inapplicability for frequent sampling. Blood-based biopsies represent a non-invasive method which potentially offers easy and repeated sampling, leading to the early detection and real-time monitoring of the disease and hopefully an accurate prognosis. Given the urgent need for a reliable biomarker that can estimate a patient's condition and response to an assigned treatment, blood-based biopsies are emerging as a potential new tool for improving patients' survival and surveillance. In this article, we discuss the current advances and challenges in using liquid biopsies for pancreatic cancer, focusing on circulating tumour DNA (ctDNA), extracellular vesicles (EVs), and circulating tumour cells (CTCs), and compare the performance and reliability of different biomarkers and combinations of biomarkers.

Decoding the role of platelets in tumour metastasis: enigmatic accomplices and intricate targets for anticancer treatments

The canonical role of platelets as central players in cardiovascular disease by way of their fundamental role in mediating thrombosis and haemostasis is well appreciated. However, there is now a large body of experimental evidence demonstrating that platelets are also pivotal in various physiological and pathophysiological processes other than maintaining haemostasis. Foremost amongst these is the emerging data highlighting the key role of platelets in driving cancer growth, metastasis and modulating the tumour microenvironment. As such, there is significant interest in targeting platelets therapeutically for the treatment of cancer. Therefore, the purpose of this review is to provide an overview of how platelets contribute to the cancer landscape and why platelets present as valuable targets for the development of novel cancer diagnosis tools and therapeutics.

Emerging Applications of Liquid Biopsies in Ovarian Cancer

Liquid biopsy is a new diagnostic tool in precision oncology that can be used as a complementary or alternative method to surgical biopsies. It is a cutting-edge sampling technique that examines distinct cancer components, such as exosomes and circulating tumor cells discharged into the peripheral circulation, to identify tumor biomarkers through various methods, including polymerase chain reaction (PCR). Liquid biopsy has several benefits, including its non-invasiveness and practicality, which permit serial sampling and long-term monitoring of dynamic tumor changes. Ovarian cancer (OC), the most lethal gynecologic malignancy in the world, is typically diagnosed at stages II and III, which makes recovery and treatment extremely difficult. Relapsed OC and chemotherapy resistance of ovarian tumor cells are other clinical challenges. Although liquid biopsy is not a routinely used diagnostic test, it should be utilized in the diagnosis and prognosis of OC for early detection and treatment. It is less intrusive than conventional tissue biopsies, allowing for the continuous collection of serial blood samples to track cancer development in real time. Before therapeutic application, more investigation is required to pinpoint the particular release processes, the source tissue, and the biological significance of the bulk of liquid biopsy contents.

High levels of PD-L1 on platelets of NSCLC patients contributes to the pharmacological activity of Atezolizumab

Several studies have associated platelets (PLTs) to NSCLC prognosis. To understand the role of PLTs in immunotherapy-treated patients, we used blood samples of NSCLC patients at different TNM stage. We found that PLTs count and the expression of PD-L1 (pPD-L1) were significantly higher in NSCLC patients at Stage IV than Stage I-III and healthy subjects. The presence of high pPD-L1 was associated to upregulated genes for the extracellular matrix organization and tumor immunosuppression. When patients' survival was correlated to the levels of pPD-L1, longer survival rate was observed, but not when progression disease occurred. The in vitro stimulation of pPD-L1 with Atezolizumab induced CXCL4 release, accompanied by higher levels of TGFβ at the time of drug resistance when the levels of CD16, CD32 and CD64 significantly increased. Leiden-clustering method defined the phenotype of PLTs which showed that the ezrin-radixin-moesin (ERM) family proteins, underlying the PD-L1 signalosome, were involved in high pPD-L1 and higher survival rate. These data imply that Stage IV NSCLC patients characterized by high pPD-L1 are associated with longer progression-free survival rate because the blockade of pPD-L1 by Atezolizumab avoids the exacerbation of a T cell-mediated immune-suppressive environment. pPD-L1 could be an easy-to-use clinical approach to predict ICI responsiveness.

Increased expression of individual genes in whole blood is associated with late-stage lung cancer at and close to diagnosis

Lung cancer (LC) mortality rates are still increasing globally. As survival is linked to stage, there is a need to identify markers for earlier LC diagnosis and individualized treatment. The whole blood transcriptome of LC patients represents a source of potential LC biomarkers. We compared expression of > 60,000 genes in whole blood specimens taken from LC cases at diagnosis (n = 128) and controls (n = 62) using genome-wide RNA sequencing, and identified 14 candidate genes associated with LC. High expression of ANXA3, ARG1 and HP was strongly associated with lower survival in late-stage LC cases (hazard ratios (HRs) = 2.81, 2.16 and 2.54, respectively). We validated these markers in two independent population-based studies with pre-diagnostic whole blood specimens taken up to eight years prior to LC diagnosis (n = 163 cases, 184 matched controls). ANXA3 and ARG1 expression was strongly associated with LC in these specimens, especially with late-stage LC within two years of diagnosis (odds ratios (ORs) = 3.47 and 5.00, respectively). Additionally, blood CD4 T cells, NK cells and neutrophils were associated with LC at diagnosis and improved LC discriminative ability beyond candidate genes. Our results indicate that in whole blood, increased expression levels of ANXA3, ARG1 and HP are diagnostic and prognostic markers of late-stage LC.

Cell-free multi-omics analysis reveals potential biomarkers in gastrointestinal cancer patients' blood

During cancer progression, tumorigenic and immune signals are spread through circulating molecules, such as cell-free DNA (cfDNA) and cell-free RNA (cfRNA) in the blood. So far, they have not been comprehensively investigated in gastrointestinal cancers. Here, we profile 4 categories of cell-free omics data from patients with colorectal cancer and patients with stomach adenocarcinoma and then assay 15 types of genomic, epigenomic, and transcriptomic variations. We find that multi-omics data are more appropriate for detection of cancer genes compared with single-omics data. In particular, cfRNAs are more sensitive and informative than cfDNAs in terms of detection rate, enriched functional pathways, etc. Moreover, we identify several peripheral immune signatures that are suppressed in patients with cancer. Specifically, we establish a γδ-T cell score and a cancer-associated-fibroblast (CAF) score, providing insights into clinical statuses like cancer stage and survival. Overall, we reveal a cell-free multi-molecular landscape that is useful for blood monitoring in personalized cancer treatment.

Liquid Biopsy in Head and Neck Cancer: Its Present State and Future Role in Africa

The rising mortality and morbidity rate of head and neck cancer (HNC) in Africa has been attributed to factors such as the poor state of health infrastructures, genetics, and late presentation resulting in the delayed diagnosis of these tumors. If well harnessed, emerging molecular and omics diagnostic technologies such as liquid biopsy can potentially play a major role in optimizing the management of HNC in Africa. However, to successfully apply liquid biopsy technology in the management of HNC in Africa, factors such as genetic, socioeconomic, environmental, and cultural acceptability of the technology must be given due consideration. This review outlines the role of circulating molecules such as tumor cells, tumor DNA, tumor RNA, proteins, and exosomes, in liquid biopsy technology for the management of HNC with a focus on studies conducted in Africa. The present state and the potential opportunities for the future use of liquid biopsy technology in the effective management of HNC in resource-limited settings such as Africa is further discussed.

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.