Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in its late stages when treatment options are limited. Unlike other common cancers, there are no population-wide screening programmes for PDAC. Thus, early disease detection, although urgently needed, remains elusive. Individuals in certain high-risk groups are, however, offered screening or surveillance. Here we explore advances in understanding high-risk groups for PDAC and efforts to implement biomarker-driven detection of PDAC in these groups. We review current approaches to early detection biomarker development and the use of artificial intelligence as applied to electronic health records (EHRs) and social media. Finally, we address the cost-effectiveness of applying biomarker strategies for early detection of PDAC.

Pancreatic cancer (PaCa) is a deadly malignancy that is often diagnosed at an advanced stage, limiting treatment and reducing survival. There is an urgent need for convenient and accurate diagnostic markers for the early detection of PaCa.

In this multicenter case-control study, we performed transcriptome analysis of 673 platelet samples from different in-house and public cohorts. RNA sequencing and RT-qPCR were used to discover and validate potential platelet biomarkers. A multi-gene signature was developed using binomial generalized linear model and independently validated in multicenter cohorts.

Two platelet RNAs, SCN1B and MAGOHB, consistently showed robust altered expression patterns between PaCa and healthy controls across cohorts, as confirmed by both RNA sequencing and RT-qPCR. The diagnostic two-RNA signature, PLA2Sig, demonstrated remarkable performance in detecting PaCa, with area under the receiver operating characteristic curve (AUC) values of 0.808, 0.900, 0.783, and 0.830 across multicenter cohorts. Furthermore, PLA2Sig effectively identified resectable stage I&II PaCa cases with an AUC of 0.812. Notably, PLA2Sig outperformed the traditional serum markers carcinoembryonic antigen and carbohydrate antigen 19-9 in distinguishing PaCa from healthy controls, and is complementary to established blood-based screening biomarkers.

These findings provide preliminary but promising evidence for the potential utility of platelet RNAs as an alternative non-invasive liquid biopsy tool for the early detection of PaCa.

Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), which continues to be the primary cause of cancer-related death worldwide. The new diagnostic biomarkers called tumour-educated platelets (TEPs) show strong prospects for providing vital information about tumor biology, tumor spread pathways, and treatment reaction patterns. Despite lacking a nucleus, platelets exhibit an active RNA profile that develops through interactions with tumor-derived compounds and the tumor microenvironments (TME). This review explains platelet-tumour interaction regulatory mechanisms while focusing on platelet contributions toward cancer development, immune system avoidance, and blood clot formation. The detection and classification of LC show promise through the analysis of RNA molecules extracted from platelets that encompass mRNAs and non-coding RNAs. RNA sequencing technology based on TEP demonstrates excellent diagnostic power by correctly identifying LC patients alongside their oncogenic alterations of EGFR, KRAS, and ALK. Treatment predictions have proven successful using platelet RNA profiles, specifically in immunotherapy and targeted therapy. Integrating next-generation sequencing with machine learning and artificial intelligence enhances TEP-based diagnostic tools, improving detection accuracy. Standardizing platelet extraction methods and vesicle purification from tumor material needs better development for effective and affordable clinical use. Future investigations should combine TEPs with circulating tumor DNA and exosomal RNA markers to enhance both earliest-stage LC diagnosis and patient-specific therapeutic approaches. TEPs introduce a groundbreaking technique in oncology since they can transform non-invasive medical diagnostics and therapeutic monitoring for cancer.

Pancreatic cancer (PC) is a frequent and aggressive digestive system cancer with a very poor prognosis. The best chance for recovery lies in early surgical removal of the tumor. Unfortunately, because PC often develops without noticeable symptoms, diagnosis is frequently delayed. Limited treatment options, the metastasis potential of pancreatic cancer cells, and its generally poor prognosis mean that patients are often diagnosed late, significantly reducing the effectiveness of treatment. Consequently, there's a critical need for new biomarkers and technologies to improve early detection through screening. Recently, the liquid biopsy has developed as a powerful means for detecting and monitoring cancer at the molecular level. Its advantages include the ease and non-invasive nature of sample collection and its ability to reflect the dynamic changes within a tumor. Platelets, the second most numerous type of blood cell, offer a particularly promising source for liquid biopsy. It is known that cancer affects various aspects of platelets, including their number, size, activation state, and the proteins and RNA they contain. However, the full implications of these changes for cancer detection have not yet been fully integrated into routine clinical practice. Platelets have a unique ability to captivate nucleic acids and proteins from their surroundings, and they alter their transcriptome in response to external signals. This leads to the development of tumor-educated platelets (TEPs). Liquid biopsies that utilize TEP biomarkers hold considerable potential for screening, early detection, prognosis, guiding personalized treatment strategies, ongoing monitoring of the disease, and predicting recurrence. Encouraging results from preclinical studies have highlighted the potential of platelets as a novel liquid biopsy source for a wide range of cancers. This review will explore the potential of using platelets as a liquid biopsy method, specifically for pancreatic cancer.

Liquid biopsy offers a noninvasive method to identify and monitor tumor-derived biomarkers, including circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, microRNAs, and tumor-educated platelets, that provide real-time insights into the biological behavior of gynecological cancers. The detection of these markers has the potential to revolutionize cancer management by enabling earlier detection, providing novel data to personalize treatments, and predicting disease recurrence before clinical imaging and predicting disease recurrence before clinical imaging can confirm progression, thereby also guiding complex clinical decision-making. However, because this new "omics" layer introduces additional complexity, it must be fully understood, from its biological rationale to technical development and clinical integration, to prevent confusion or misapplication. That is why, focusing on 14 critical fields of inquiry, our goal is to map the current state of liquid biopsy from bench to bedside while highlighting practical considerations for clinical integration. Each topic integrates recent advances in assay sensitivity, biomarker variability, and data interpretation, underscoring how standardized protocols and robust analytical methods are pivotal for reliable results. We then translate these findings into disease-specific insights, examining how liquid biopsy could refine early detection, minimal residual disease assessment, and therapy guidance in endometrial, cervical, and ovarian cancers. Although several FDA-approved assays and promising commercial tests illustrate the field's rapid evolution, many translational hurdles remain, including the need for harmonized protocols, larger prospective clinical trials, and cost-effectiveness analyses. Crucially, our synthesis clarifies the pivotal role of interdisciplinary collaboration. Oncologists, laboratory scientists, and industry partners must align on standardized procedures and clinically relevant endpoints. Without such coordination, promising biomarkers may remain confined to research settings, limiting their practical benefit. Taken together, our review offers a translational view designed to contextualize liquid biopsy in gynecological oncology.

The diagnostic potential of tumor-educated platelets (TEPs) across various cancer types has gained increasing recognition; however, the relationship between alternative splicing (AS) events in TEPs and tumor development remains understudied. Early detection of non-small cell lung cancer (NSCLC) in ground-glass opacities (GGOs) is critical for improving patient outcomes, yet current methods lack sufficient accuracy. Our research identified diagnostic-related alternative splicing events (DASEs) in TEPs, revealing several promising biomarkers for NSCLC, specifically in patients presenting with GGOs.

Patients with GGOs from two hospitals were prospectively enrolled [Hospital 1-Platelet (H1-P) and Hospital 2-Tissue (H2-T) in the validation cohort; Hospital 2-Platelet (H2-P) in the test cohort]. Benign/malignant diagnosis of GGOs was confirmed by pathological examination according to the World Health Organization (WHO) classification. TEPs from the H1-P cohort were collected for transcriptome sequencing and AS analysis. Chi-square tests, least absolute shrinkage and selection operator (LASSO) regression analysis, and protein-protein interaction (PPI) network were used for the preliminary screening of DASEs. Pathological tissue from the H2-T cohort was collected to validate the diagnostic efficacy of hub DASEs in NSCLC against the pathological gold standard. Moreover, TEPs from the H2-P cohort were used to assess the predictive performance of hub DASEs for GGOs using receiver operating characteristic (ROC) curves. Decision curve analysis (DCA) was used to determine whether diagnosing NSCLC in the GGOs population via hub DASEs could benefit patients.

A total of 285 patients with GGOs were enrolled, including 151 NSCLC and 128 inflammatory nodules confirmed by pathological examination. Thirteen DASEs were screened with the chi-square test and LASSO regression analysis to identify diagnostic TEP AS markers for GGOs NSCLC. The PPI network identified four hub diagnostic-related alternative splice genes (DASGs) (TMEM219, MPV17, FIBP, and VPS28). Pathological tissues and platelets were collected to validate the four hub DASEs of these four hub DASGs. MXE-32112-TMEM219 yielded an area under the curve (AUC) of 0.82 [95% confidence interval (CI): 0.729-0.902], with a sensitivity of 83.33% and a specificity of 80.00%; RI-3259-VPS28 yielded an AUC of 0.77 (95% CI: 0.677-0.870) with a sensitivity of 93.33% and a specificity of 78.33%; and RI-3641-MPV17 yielded an AUC of 0.82 (95% CI: 0.728-0.901) with a sensitivity of 90.00% and a specificity of 80.00%. The DCA results suggested that using hub DASEs in diagnosing NSCLC in individuals with GGOs could provide benefits.

The specific diagnostic AS events (MXE-32112-TMEM219, RI-3259-VPS28, and RI-3641-MPV17) identified in TEP samples demonstrated high sensitivity and specificity for diagnosing NSCLC in patients with GGOs. These findings suggest that TEP-related AS events may serve as non-invasive biomarkers to guide biopsy decisions for NSCLC in GGOs, reducing unnecessary procedures.

Clinical evaluation and MR imaging are currently the cornerstone of brain tumor progression monitoring. However, this is complicated by the occurrence of treatment effects such as pseudoprogression and radionecrosis. While essential for patient management, the distinction from true progression remains a significant challenge. Moreover, MR imaging provides limited real-time insights into tumor heterogeneity, genetic divergence, and treatment resistance. Although surgical histopathological biopsies can yield additional valuable information, they are not always conclusive, invasive, and therefore, not suitable for longitudinal measurements. In the era of precision medicine, there is a critical need for minimally invasive, accurate, and cost-effective monitoring methods for both primary brain tumors and brain metastases. Liquid biopsies have emerged as a potential candidate. Various analytes, including circulating nucleic acids, extracellular vesicles, platelet RNAs, and circulating tumor cells, can be obtained from whole blood and its derivatives, as well as other body fluids such as cerebrospinal fluid. In this narrative review, we outline the potential of liquid biopsies for the management of gliomas and brain metastases in adults and emphasize their utility in monitoring disease progression and treatment response. We discuss the most studied biofluids and analytes, along with their respective advantages and downsides. Furthermore, we address key considerations for future research and biobanking to pave the way for clinical implementation.

Platelets, traditionally recognized for their role in hemostasis, have emerged as pivotal players in cancer biology. They actively contribute to tumor proliferation, angiogenesis, immune evasion, and metastasis and thus play a significant role in cancer progression. Tumor-educated platelets (TEPs) acquire protumorigenic phenotypes through RNA, protein, and receptor profile alterations driven by interactions with tumors and their microenvironment. These modifications enable TEPs to enhance tumor growth and dissemination and to play a critical role throughout the metastatic process. Moreover, TEPs are promising biomarkers that can easily be analyzed in liquid biopsies. Since they dynamically mirror tumor activity through transcriptomic and proteomic changes, their analysis offers a non-invasive method for determining cancer detection and diagnosis, patient prognosis, therapy monitoring, and personalization of treatment. Their demonstrated accuracy in identifying cancer types and predicting treatment responses underscores their ability to provide real-time insights into tumor biology, including in urological malignancies. Their diagnostic potential and their accessibility as blood-sourced biomarkers position TEPs as transformative tools in advancing personalized oncology. Here, we focus on the role of TEPs in urological tumors, exploring their applications in early cancer detection, disease monitoring, and the design of tailored therapeutic strategies.

Breast cancer (BC) is the most commonly occurring type of cancer in women, being a major cancer-related cause of mortality worldwide. With the advancement in current therapeutic options, including hormone therapy and targeted therapies, there is a need for more accurate and less invasive options to monitor cancer progression in patients. Liquid biopsy has evolved rapidly, being able to detect small quantities of nucleic acids or cell-free DNA in the blood of BC patients. This method addresses three major issues of needle biopsy: firstly, it is more permissive by being less invasive and does not require needling the organs; secondly, it covers for the heterogeneous nature of the tumor of origin, which could lead to an otherwise inaccurate representation of the cancer-driving mutations; thirdly, it better represents the type of tumor that the primary tumor is going to evolve into before it starts to metastasize. This current review will address the current advancements in liquid biopsy in the context of BC, highlighting the pros and challenges.

Background/Objectives: Ovarian cancer (OC) remains one of the most lethal gynecologic malignancies, largely due to the challenges of early detection. While next-generation sequencing (NGS) has been explored for screening, its high cost limits large-scale implementation. To develop a more accessible diagnostic solution, we designed a qPCR-based algorithm optimized for early OC detection, with a focus on high-grade serous ovarian cancer (HGSOC), the most aggressive subtype. Methods: Peripheral blood samples from 19 ovarian cancer patients, 37 benign tumor patients, and 34 asymptomatic controls were analyzed using RNA sequencing to identify splice junction-based biomarkers with minimal expression in benign samples but elevated in OC. Results: A final panel of 10 markers was validated via qPCR, demonstrating strong agreement with sequencing data (R2 = 0.44-0.98). The classification algorithm achieved 94.1% sensitivity and 94.4% specificity (AUC = 0.933). Conclusions: By leveraging platelet RNA profiling, this approach offers high specificity, accessibility, and potential for early OC detection. Future studies will focus on expanding histologic diversity and refining biomarker panels to further enhance diagnostic performance.

Selective screening of the population based on NSCLC risk is an effective technique for minimising overdiagnosis and overtreatment. Platelets and the components can be used as liquid-biopsy markers, potentially assessing the risk of NSCLC, which are easily deployed in clinical applications. Platelet RNA sequencing datasets were analysed to identify specific genes derived from NSCLC patients and healthy donors. Then, expressions of the selected gene were validated in a clinical trial. Not only the availability of the specific gene in differentiating NSCLC patients from healthy donors but also from patients with benign nodules was estimated respectively. Finally, the values of the specific TEP-gene in metastasis and survival prognosis were also evaluated. FLNA was selected based on the GSE datasets, of which mRNA expression levels were higher in platelets from NSCLC patients than in healthy donors and also higher than in benign patients. To discriminate the malignant patients from the healthy individuals, FLNA got an AUC for the ROC curve of 0.716. When discriminating from the benign individuals, FLNA got an AUC of 0.705. In addition, an AUC of 0.595 was found when the metastatic group was distinguished from the non-metastatic group using the relative quantitative results of FLNA, and it seemed that the high-FLNA-expression group had a poorer long-term survival rate than the low-expression group. These findings suggested that high expression of FLNA in TEPs may indicate the incidence and metastasis of NSCLC and serve as a biomarker for high-risk estimation for NSCLC.

In the tumor context, platelets play a significant role in primary tumor progression, dissemination and metastasis. Analysis of this interaction in various cancers, such as non-small cell lung cancer (NSCLC), demonstrate that platelets can both transfer and receive biomolecules (e.g. RNA and proteins) to and from the tumor at different stages, becoming tumor-educated platelets. To investigate how platelets are able to transfer oncogenic material, we developed in vitro platelet-like particles (PLPs), from a differentiated MEG-01 cell line, that stably carry RNA and protein of the KRASG12D oncogene in fusion with GFP. We co-cultured these PLPs with NSCLC H1975 tumor cells to assess their ability to transfer this material. We observed that the generated platelets were capable of stably expressing the oncogene and transferring both its RNA and protein forms to tumor cells using qPCR and imaging techniques. Additionally, we found that coculturing PLPs loaded with GFP-KRASG12D with tumor cells increased their proliferative capacity at specific PLP concentrations. In conclusion, our study successfully engineered an MEG-01 cell line to produce PLPs carrying oncogenic GFP-KRASG12D simulating the tumor microenvironment, demonstrating the efficient transfer of this oncogene to tumor cells and its significant impact on enhancing proliferation.

The Liquid Biopsy (LB) represents an ideal surrogate of tumor Tissue Biopsy (TB) when the aim is to obtain useful information on patient prognosis and personalized therapy. This technique renders it possible to isolate circulating tumor cells, circulating tumor DNA and other molecules from biological fluids. The most commonly used fluid for liquid biopsy is blood, but depending on the case it could be necessary to isolate the tumor components from other biological fluids such as urine, pleural effusion, cerebrospinal fluid, and others. The main advantages of liquid biopsy are the minimally invasive nature of the procedure and the possibility of analyzing all tumor clones. Limitations include difficulties in the isolation of tumor components and the requirement for highly sensitive analysis methods to avoid the risk of technical artifacts. In our review we will focus on describing circulating tumor biomarkers to illustrate the variety of information that can be obtained from biological fluids, particularly blood. We will then discuss the advanced biotechnological techniques suitable for the identification and analysis of Circulating Tumor DNA (ctDNA), examining both the potential and limitations of analytical methods and the clinical applicability of liquid biopsy for cancer diagnosis, monitoring, and therapeutic prediction. Additionally, we will explore strategies to enhance this valuable alternative to the more invasive tissue biopsy, with a dedicated focus on ongoing clinical studies, currently approved tests, and guideline recommendations.

Brain metastases are the most commonly diagnosed type of central nervous system tumor, yet the mechanisms of their occurrence are still widely unknown. Lung cancer, breast cancer, and melanoma are the most common etiologies, but renal and colorectal cancers have also been described as metastasizing to the brain. Regardless of their origin, there are common mechanisms for progression to all types of brain metastases, such as the creation of a suitable tumor microenvironment in the brain, priming of tumor cells, adaptations to survive spreading in lymphatic and blood vessels, and development of mechanisms to penetrate the blood-brain barrier. However, there are complex genetic and molecular interactions that are specific to every type of primary tumor, making the understanding of the metastatic progression of tumors to the brain a challenging field of study. In this review, we aim to summarize current knowledge on the pathophysiology of brain metastases, from specific genetic characteristics of commonly metastatic tumors to the molecular and cellular mechanisms involved in progression to the central nervous system. We also briefly discuss current challenges in targeted therapies for brain metastases and how there is still a gap in knowledge that needs to be overcome to improve patient outcomes.

Circulating tumor DNA (ctDNA) analysis has emerged as a minimally invasive tool for detecting minimal residual disease (MRD) in colorectal cancer (CRC) patients. This enables dynamic risk stratification, earlier recurrence detection and optimized post-surgical treatment. Two primary methodologies have been developed for ctDNA-based MRD detection: tumor-informed strategies, which identify tumor-specific mutations through initial tissue sequencing to guide ctDNA monitoring, and tumor-agnostic approaches, which utilize predefined panels to detect common cancer-associated genomic or epigenomic alterations directly from plasma without prior tissue analysis. The debate over which is superior in terms of sensitivity, specificity, cost-effectiveness and clinical feasibility remains unsolved.

This review summarizes studies published up to November 2024, exploring the utility and performance of tumor-informed and tumor-agnostic approaches for ctDNA analysis in CRC. We evaluate the strengths and limitations of each methodology, focusing on sensitivity, specificity and clinical outcomes.

Both strategies demonstrate clinical utility in post-operative risk stratification and guiding adjuvant chemotherapy decisions in CRC patients. Tumor-informed approaches generally exhibit superior sensitivity and specificity for recurrence prediction, attributed to their personalized tumor profile designs. However, these methods are limited by the need for prior tissue sequencing and higher associated costs. In contrast, tumor-agnostic approaches offer broader applicability due to their reliance on plasma-only analysis, although with relatively lower sensitivity. Technological advancements, including fragmentomics and multi-omic integrations, are expanding the capabilities of ctDNA-based MRD detection, enhancing the performance of both approaches.

While tumor-informed strategies currently offer higher precision in MRD detection, tumor-agnostic approaches are gaining traction due to their convenience and improving performance metrics. The integration of novel technologies in ongoing clinical trials may redefine the optimal approach for MRD detection in CRC, paving the way for more personalized and adaptive patient management strategies.

Platelets have important roles in hemostasis but also actively participate in cancer metastasis and inflammatory processes. They are produced by large precursor cells, the megakaryocytes, residing mainly in the bone marrow. Clinically, elevated platelet counts and/or increased platelet-to-lymphocyte ratio are being explored as biomarkers of metastatic disease and to predict survival or response to therapy in certain cancers. Multiple mechanisms have been put forward on how platelets promote hematogenous metastasis stemming mainly from murine experimental models. Research is now beginning to explore the potential roles of megakaryocytes in solid cancer, myeloma, and lymphoma. Here, we review mechanisms on how platelets and megakaryocytes contribute to cancer progression and metastasis but also discuss potential cancer-suppressing functions mainly related to the regulation of vascular intratumor integrity. Recent developments in cancer immune checkpoint therapy are reviewed with a focus on the potential roles of platelets. Moreover, we review studies exploring platelets for targeted drug delivery systems in cancer therapy.

DNA-based molecular computing systems for biomarkers have emerged as powerful tools for intelligent diagnostics. However, with the variety of feature biomarkers expanding, current molecular computing systems suffer from the use of a large number of oligonucleotides and limited encoding capability. Here, the study develops an alternative molecular computing approach termed Digital DNA Strand Displacement (DDSD) which recognizes targets and operates target valence through DNA polymerase-based extension and strand release. DDSD significantly reduced the number of used oligonucleotide species, provided robust molecular classifiers. In clinical blood samples, a 96% accuracy rate is achieved with a DDSD-based binary classifier for distinguishing bacterial and viral infections, a 100% accuracy rate is achieved with a multiclass classifier for identifying pathogen types, surpassing existing classifier systems. Moreover, DDSD can be readily expanded. Cascade DDSD is developed, enabling simultaneous computing of up to 14 valence states with a maximum valence of 25. Multiway junction DDSD is implemented to achieve high-valence computing by compact DNA nanostructures rather than split DNA computing units, reducing the potential leakage. The implementation of DDSD enhances the capability of valence-based intelligent molecular diagnostics and multiplexed biomarker detection.

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.

Tumor metastasis leads to circulating tumor cells (CTCs) that separate from primary malignant tumors and enter blood circulation. CTCs survive and engage with other cells to cope with obstacles, including shear stress, disease, immune attacks, and drugs. Platelets are the best partners for CTCs. Platelets provide a good protective layer for CTCs to ensure that are not monitored and cleared by the native immune system, and protected from shear stress and survive better. Here, we review current reports on platelet-CTC interaction and the clinical relevance of their combination and summarize new techniques for CTC capture and treatment based on platelet-CTC interaction. We discuss current data, identify its shortcomings, and suggest future developments.

Platelets, anucleate blood cells essential for hemostasis, are increasingly recognized for their role in cancer, challenging the traditional notion of their sole involvement in blood coagulation. It has been demonstrated that platelets establish bidirectional communication with tumor cells, contributing to tumor progression and metastasis through diverse molecular mechanisms such as modulation of proliferation, angiogenesis, epithelial-mesenchymal transition, resistance to anoikis, immune evasion, extravasation, chemoresistance, among other processes. Reciprocally, cancer significantly alters platelets in their count and composition, including mRNA, non-coding RNA, proteins, and lipids, product of both internal synthesis and the uptake of tumor-derived molecules. This phenomenon gives rise to tumor-educated platelets (TEPs), which are emerging as promising tools for the development of liquid biopsies. In this review, we provide a detailed overview of the dynamic roles of platelets in tumor development and progression as well as their use in diagnosis and prognosis. We also provide our view on current limitations, challenges and future research areas, including the need to design more efficient strategies for their isolation and analysis, as well as the validation of their sensitivity and specificity through large-scale and rigorous clinical trials. This research will not only enable the evaluation of their clinical viability but could also open new opportunities to enhance diagnostic accuracy and develop personalized treatments in oncology.

Blood platelets are anucleate cells essential for normal blood hemostasis. To maintain a normal platelet count of 150 000 to 400 000 per μL of blood, 1011 platelets must be released each day from precursor cells called megakaryocytes. In this review, we aim to provide an overview of platelet production and evaluate the proposed mechanisms of platelet generation. We will discuss novel cytoskeletal mechanisms of platelet production, including microtubule and actin-based systems. We present new evidence that supports a cytoplasmic trigger for platelet production, discuss centrosome clustering as a new mechanism to trigger proplatelet production, and review new data supporting the bone marrow as the major location of platelet production.

The prevalence of Alzheimer's disease (AD) is increasing as society ages. The details of AD pathogenesis have not been fully elucidated, and a comprehensive gene expression analysis of the process leading up to the onset of AD would be helpful for understanding the mechanism. We performed an RNA sequencing analysis on a cohort of 1227 Japanese blood samples, representing 424 AD patients, 543 individuals with mild cognitive impairment (MCI), and 260 cognitively normal (CN) individuals. A total of 883 and 1169 statistically significant differentially expressed genes (DEGs) were identified between CN and MCI (CN-MCI) and between MCI and AD (MCI-AD), respectively. Pathway analyses using these DEGs, followed by protein-protein interaction network analysis, revealed key roles of ribosomal function in MCI progression, whereas immune responses, cell cycle, and protein processing in endoplasmic reticulum were involved in AD progression. Our findings indicate that the onset of AD might be associated with gene expression changes in the immune system, cell cycle, and protein processing following alterations in the expression of ribosomal protein genes during the MCI stage, although validation using brain tissue samples will be necessary in the future. Given the known effectiveness of delaying MCI progression in preventing AD, the genes related to ribosomal function might emerge as biomarkers for early diagnosis.

Platelets are enriched in miRNAs and harbor Ago2 as the principal RNA silencing Argonaute. However, roles in thrombopoiesis and platelet function remain poorly understood. We generated megakaryocyte/platelet-specific Ago2-deleted (Ago2 KO) mice and assessed proteomic and functional effects. We predicted platelet hyperreactivity with Ago2 deletion due to large-scale upregulated protein expression. Platelet counts were normal. Mean volumes were increased, associated with larger, though fewer megakaryocytes. Ago2-deleted platelets from male mice showed hyperreactivity to thromboxane but not to other agonists compared to controls, whereas Ago2-deleted platelets from female mice showed normal reactivity. Ago2 KO mice displayed normal hemostasis and clot dynamics. Proteomes of Ago2-deleted and wild type platelets were mostly similar. However, Ago1 - undetectable in wild type platelets - was upregulated in Ago2-deleted platelets in both males and females, confirmed by immunoblotting. Female Ago2-deleted platelets selectively showed downregulation of a protein cohort established in breast cancer cells to be transcriptionally regulated by estrogen receptor-beta coupled to Ago2, whereas male Ago2-deleted platelets did not. Thus, Ago2 is important for platelet development and function, putatively partially rescued by upregulation of Ago1. Platelet reactivity controlled by Ago2 reflects sex-specific regulation of gene expression potentially at both transcriptional and translational levels in megakaryocytes and platelets.

Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are among the most challenging malignancies due to their high mortality rates and complex neurological effects. Despite advancements in surgery and chemoradiotherapy, the prognosis for glioblastoma multiforme (GBM) and brain metastases remains poor, underscoring the need for innovative diagnostic strategies. This review highlights recent advancements in imaging techniques, liquid biopsies, and artificial intelligence (AI) applications addressing current diagnostic challenges. Advanced imaging techniques, including diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS), improve the differentiation of tumor progression from treatment-related changes. Additionally, novel positron emission tomography (PET) radiotracers, such as 18F-fluoropivalate, 18F-fluoroethyltyrosine, and 18F-fluluciclovine, facilitate metabolic profiling of high-grade gliomas. Liquid biopsy, a minimally invasive technique, enables real-time monitoring of biomarkers such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs), circulating tumor cells (CTCs), and tumor-educated platelets (TEPs), enhancing diagnostic precision. AI-driven algorithms, such as convolutional neural networks, integrate diagnostic tools to improve accuracy, reduce interobserver variability, and accelerate clinical decision-making. These innovations advance personalized neuro-oncological care, offering new opportunities to improve outcomes for patients with central nervous system tumors. We advocate for future research integrating these tools into clinical workflows, addressing accessibility challenges, and standardizing methodologies to ensure broad applicability in neuro-oncology.

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.

(Tumor-educated platelets) TEPs have emerged as active players in all steps of tumorigenesis, confrontation of platelets with tumor cells via transfer of tumor-associated biomolecules and results in the sequestration of such biomolecules. The current study was aimed to examine whether TEPs lncRNA-STARD4-AS1 and ELOA-AS1 might be potential biomarkers for NSCLC.

TEPs were obtained by low-speed centrifugation. Quantitative real-time PCR was used to determine the expression level of TEPs-STARD4-AS1, ELOA-AS1 in the training cohort and the validation cohort. ROC curve was generated to evaluate their diagnostic value. Correlations between TEPs-STARD4-AS1, ELOA-AS1 and clinical parameters were further analyzed.

Our results showed that the level of TEPs-STARD4-AS1 and ELOA-AS1 significantly upregulated in patients with NSCLC compared with healthy controls in the two cohorts. By ROC analysis, we found that TEPs-STARD4-AS1, ELOA-AS1 could offer valuable diagnostic performance for NSCLC patients (AUCSTARD4-AS1 = 0.800/0.774, and AUCELOA-AS1 = 0.754/0.718 for diagnosing adenocarcinoma and squamous cell carcinoma cases from controls, respectively). The combination of TEP-STARD4-AS1 and ELOA-AS1 improved the diagnostic efficiency of NSCLC. Clinicopathological analysis further revealed that TEPs-STARD4-AS1 level significantly correlated with tumor-node-metastasis (TNM) stage (p = 0.011), while TEPs-ELOA-AS1 expression significantly correlated with tumor-node-metastasis (TNM) stage and (p = 0.019) distant metastasis (p = 0.004).

Our data suggested that TEPs-STARD4-AS1 and ELOA-AS1 are promising non-invasive circulating diagnostic markers for NSCLC.

Accurately differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC) is essential for therapeutic decision-making. This study aimed to explore the value of Fluor 18 (18F)-conjugated fibroblast-activation protein inhibitor (FAPI-42) positron emission tomography-computed tomography (PET/CT) in distinguishing HCC from ICC preoperatively.

Patients with suspected intrahepatic lesions who underwent 18F-FAPI-42 PET/CT were retrospectively assessed and placed into an HCC group and an ICC group based on postoperative pathology. Clinical indicators and PET/CT metabolic parameters were documented. Univariate and multivariate logistic regression analyses identified the independent predictive factors. The receiver operating characteristic curve and the area under the receiver operating curve (AUC) were used to determine the diagnostic efficacy.

A total of 48 patients (age 55.4±10.8 years; 35 males and 13 females), including 28 in the HCC and 20 in the ICC group, were included. Univariate analysis revealed significant differences in clinical indicators such as gender, platelet count, and hepatitis B surface antigen, carbohydrate antigen 19-9 (CA19-9), and alpha fetoprotein (AFP) levels between the groups (P<0.05). Metabolic parameters including the maximum standardized uptake value (SUVmax), the total lesion-FAPI (TL-FAPI), and the target-to-background ratio (TBR) were statistically different between groups (P<0.01), and patients with ICC had higher values than those with HCC, while the FAPI tumor volume (FAPI-TV) was not statistically different (P>0.05). Multivariate binary logistic regression analysis identified the SUVmax (P=0.003) as an independent predictor for ICC, and the AUC of the regression-based diagnostic model for predicting ICC was 0.914 at an optimal cutoff value of 12.13, with a sensitivity of 85.0% and a specificity of 89.3%.

SUVmax is an independent predictor for ICC. With the optimal cutoff value of 12.13, 18F-FAPI-42 PET/CT indicates good diagnostic efficacy in distinguishing between HCC and ICC.

Multi-cancer early detection (MCED) tests are already being marketed as noninvasive, convenient opportunities to test for multiple cancer types with a single blood sample. The technology varies-involving detection of circulating tumor DNA, fragments of DNA, RNA, or proteins unique to each targeted cancer. The priorities and tradeoffs of reaching diagnostic resolution in the setting of possible false positives and negatives remain under active study. Given the well-established role of imaging in lesion detection and characterization for most cancers, radiologists have an essential role to play in selecting diagnostic pathways, determining the validity of test results, resolving false-positive MCED test results, and evaluating tradeoffs for clinical policy. Appropriate access to and use of imaging tests will also factor into clinical guidelines. Thus, all clinicians potentially involved with MCED tests for cancer screening will need to weigh the benefits and harms of MCED testing, including consideration of how the tests will be used alongside or in place of other screening options, how diagnostic confirmation tests should be selected, and what the implications are for policy and reimbursement decisions. Further, patients will need regular support to make informed decisions about screening using MCED tests in the context of their personal cancer risks, health-related values, and access to care.

Breast cancer, a complex and heterogeneous ailment impacting numerous women worldwide, persists as a prominent cause of cancer-related fatalities. MicroRNAs (miRNAs), small non-coding RNAs, have garnered significant attention for their involvement in breast cancer's progression. These molecules post-transcriptionally regulate gene expression, influencing crucial cellular processes including proliferation, differentiation, and apoptosis. This review provides an overview of the current research on the role of miRNAs in breast cancer. It discusses the role of miRNAs in breast cancer, including the different subtypes of breast cancer, their molecular characteristics, and the mechanisms by which miRNAs regulate gene expression in breast cancer cells. Additionally, the review highlights recent studies identifying specific miRNAs that are dysregulated in breast cancer and their potential use as diagnostic and prognostic biomarkers. Furthermore, the review explores the therapeutic potential of miRNAs in breast cancer treatment. Preclinical studies have shown the effectiveness of miRNA-based therapies, such as antagomir and miRNA mimic therapies, in inhibiting tumor growth and metastasis. Emerging areas, including the application of artificial intelligence (AI) to advance miRNA research and the "One Health" approach that integrates human and animal cancer insights, are also discussed. However, challenges remain before these therapies can be fully translated into clinical practice. In conclusion, this review emphasizes the significance of miRNAs in breast cancer research and their potential as innovative diagnostic and therapeutic tools. A deeper understanding of miRNA dysregulation in breast cancer is essential for their successful application in clinical settings. With continued research, miRNA-based approaches hold promise for improving patient outcomes in this devastating disease.

Platelets possess cancer-induced reprogramming properties, thereby contributing to RNA profile alterations and further cancer progression, while the former is considered a promising biosource for cancer detection. Hence, tumor-educated platelets (TEP) are considered a prospective novel method for early breast cancer (BC) screening. Our study integrated the data from 276 patients with untreated BC, 95 with benign disease controls, 214 healthy controls, and 2 who underwent mastectomy in Chinese and European cohorts to develop a 10-biomarker diagnostic model. The model demonstrated high diagnostic performance for BC in an independent test set (n = 177) with an area under the curve of 0.957. The sensitivity for BC diagnosis was 89.2%, with 100% specificity in asymptomatic controls, while that for the symptomatic group, including benign tumors and inflammatory diseases, was 62.1%. The model demonstrated substantial accuracy for stages 0-III BC (80% for stage 0 [n = 5], 83.3% for stage I [n = 12], 94.6% for stage II [n = 37], and 88.9% for stage III [n = 9]) and precisely helped determine residual cancer in two patients who underwent mastectomy. Moreover, our developed classifiers distinguish different BC subtypes properly. In summary, we created and tested a new TEP-RNA-based BC diagnostic model that was confirmed valid and demonstrated high efficiency in detecting early-stage BC and heterogeneous subtypes, including recurrent tumors. However, these results warrant more validation in larger population-based prospective studies before clinical implementation.

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.

Glioma is a malignancy with challenging clinical treatment and poor prognosis. Platelets are closely associated with tumor growth, propagation, invasion, and angiogenesis. However, the role of platelet-related genes in glioma treatment and prognosis remains unclear.

A prognostic risk model was established using nine platelet-related prognostic signature genes (CAPG, CLIC1, GLB1, GNG12, KIF20A, PDIA4, SULF2, TAGLN2, and WEE1), and the risk score of samples were calculated. Subsequently, the glioma samples were divided into high- and low-risk groups based on the median values of risk scores. scRNA-seq analysis revealed that the prognostic genes were primarily located in astrocytes and natural killer cells. The immune infiltration proportions of most immune cells differed significantly between high- and low-risk groups. Moreover, we found AZD7762 as a potential candidate for glioma treatment.

Nine platelet-related prognostic genes identified as prognostic signatures for glioma were closely associated with the TME and may aid in directing the clinical treatment and prognosis of gliomas.

Cancer has a high mortality rate across the globe, and tissue biopsy remains the gold standard for tumor diagnosis due to its high level of laboratory standardization, good consistency of results, relatively stable samples, and high accuracy of results. However, there are still many limitations and drawbacks in the application of tissue biopsy in tumor. The emergence of liquid biopsy provides new ideas for early diagnosis and prognosis of tumor. Compared with tissue biopsy, liquid biopsy has many advantages in the diagnosis and treatment of various types of cancer, including non-invasive, quickly and so on. Currently, the application of liquid biopsy in tumor detection has received widely attention. It is now undergoing rapid progress, and it holds significant potential for future applications. Around now, liquid biopsies encompass several components such as circulating tumor cells, circulating tumor DNA, exosomes, microRNA, circulating RNA, tumor platelets, and tumor endothelial cells. In addition, advances in the identification of liquid biopsy indicators have significantly enhanced the possibility of utilizing liquid biopsies in clinical settings. In this review, we will discuss the application, advantages and challenges of liquid biopsy in some common tumors from the perspective of diverse systems of tumors, and look forward to its future development prospects in the field of cancer diagnosis and treatment.

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.

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.

Despite numerous therapeutic advancements, such as immune checkpoint inhibitors, lung cancer continues to be the leading cause of cancer-related mortality. Therefore, the identification of cancer at an early stage is becoming a significant subject in contemporary oncology. Despite significant advancements in early detection tactics in recent decades, they continue to provide challenges because of the inconspicuous symptoms observed during the early stages of the primary tumor. Presently, tumor biomarkers and imaging techniques are extensively employed across different forms of cancer. Nevertheless, every approach has its own set of constraints. In certain instances, the detriments outweigh the advantages. Hence, there is an urgent need to enhance early detection methods. Currently, liquid biopsy is considered more flexible and not intrusive method in comparison to conventional test for early detection. Circulating tumor cells (CTCs) are crucial components of liquid biopsy and have a pivotal function in the spread and formation of secondary tumors. These indicators show great promise in the early identification of cancer. This study presents a comprehensive examination of the methodologies employed for the isolation and enrichment of circulating tumor cells (CTCs) in lung cancer. Additionally, it explores the formation of clusters of CTCs, which have a pivotal function in facilitating the effective dissemination of cancer to distant organs. In addition, we discuss the importance of CTCs in the detection, treatment, and prognosis of lung cancer.

Liver cancer ranks as the sixth most common cancer globally, with hepatocellular carcinoma (HCC) accounting for approximately 75%-85% of cases. Most patients present with moderately advanced disease, while those with advanced HCC face limited and ineffective treatment options. Despite diagnostic efforts, no ideal tumor marker exists to date, highlighting the urgent clinical need for improved early detection of HCC. A key research objective is the development of assays that target specific pathways involved in HCC progression. This review explores the pathological origin and development of HCC, providing insights into the mechanistic rationale, clinical statistics, and the advantages and limitations of commonly used diagnostic tumor markers. Additionally, it discusses the potential of emerging biomarkers for early diagnosis and offers a brief overview of relevant assay methodologies. This review aims to summarize existing markers and investigate new ones, providing a basis for subsequent 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.