Diagnostic Accuracy of Liquid Biopsy in Endometrial Cancer

Is There a Role for Machine Learning in Liquid Biopsy for Brain Tumors? A Systematic Review

The paucity of studies available in the literature on brain tumors demonstrates that liquid biopsy (LB) is not currently applied for central nervous system (CNS) cancers. The purpose of this systematic review focused on the application of machine learning (ML) to LB for brain tumors to provide practical guidance for neurosurgeons to understand the state-of-the-art practices and open challenges. The herein presented study was conducted in accordance with the PRISMA-P (preferred reporting items for systematic review and meta-analysis protocols) guidelines. An online literature search was launched on PubMed/Medline, Scopus, and Web of Science databases using the following query: "((Liquid biopsy) AND (Glioblastoma OR Brain tumor) AND (Machine learning OR Artificial Intelligence))". The last database search was conducted in April 2023. Upon the full-text review, 14 articles were included in the study. These were then divided into two subgroups: those dealing with applications of machine learning to liquid biopsy in the field of brain tumors, which is the main aim of this review (n = 8); and those dealing with applications of machine learning to liquid biopsy in the diagnosis of other tumors (n = 6). Although studies on the application of ML to LB in the field of brain tumors are still in their infancy, the rapid development of new techniques, as evidenced by the increase in publications on the subject in the past two years, may in the future allow for rapid, accurate, and noninvasive analysis of tumor data. Thus making it possible to identify key features in the LB samples that are associated with the presence of a brain tumor. These features could then be used by doctors for disease monitoring and treatment planning.

Platelet-Based Liquid Biopsies through the Lens of Machine Learning

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

Minimally invasive approaches for the early detection of endometrial cancer

Endometrial cancer (EC) is one of the most common gynecologic cancers and its incidence is rising globally. Although advanced EC has a poor prognosis; diagnosing EC at an earlier stage could improve long-term patient outcomes. However, there is no consensus on the early detection strategies for EC and the current diagnostic practices such as transvaginal ultrasound, hysteroscopy and endometrial biopsy are invasive, costly and low in specificity. Thus, accurate and less invasive screening tests that detect EC in women with early stages of the disease are needed. Current research has revolutionized novel EC early detection methodologies in many aspects. This review aims to comprehensively characterizes minimally invasive screening techniques that can be applied to EC in the future, and fully demonstrate their potential in the early detection of EC.

Fertility-Sparing Strategies for Early-Stage Endometrial Cancer: Stepping towards Precision Medicine Based on the Molecular Fingerprint

Endometrial cancer represents the fifth most common cancer in women, and the most common gynecological malignancy in developed countries [...].

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

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

Bioplatforms in liquid biopsy: advances in the techniques for isolation, characterization and clinical applications

Tissue biopsy analysis has conventionally been the gold standard for cancer prognosis, diagnosis and prediction of responses/resistances to treatments. The existing biopsy procedures used in clinical practice are, however, invasive, painful and often associated with pitfalls like poor recovery of tumor cells and infeasibility for repetition in single patients. To circumvent these limitations, alternative non-invasive, rapid and economical, yet sturdy, consistent and dependable, biopsy techniques are required. Liquid biopsy is an emerging technology that fulfills these criteria and potentially much more in terms of subject-specific real-time monitoring of cancer progression, determination of tumor heterogeneity and treatment responses, and specific identification of the type and stages of cancers. The present review first briefly revisits the state-of-the-art technique of liquid biopsy and then proceeds to address in detail, the advances in the potential clinical applications of four major biological agencies present in liquid biopsy samples (circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs)). Finally, the authors conclude with the limitations that need to be addressed in order for liquid biopsy to effectively replace the conventional invasive biopsy methods in the clinical settings.

Platelet detection as a new liquid biopsy tool for human cancers

Cancer is still a leading cause of death worldwide and liquid biopsy is a powerful tool that can be applied to different stages of cancer screening and treatment. However, as the second most abundant cell type in the bloodstream, platelets are isolated through well-established and fast methods in clinic but their value as a BioSource of cancer biomarkers is relatively recent. Many studies demonstrated the bidirectional interaction between cancer cells and platelets. Platelets transfer various proteins (e.g., growth factors, cytokine, chemokines) and RNAs (e.g., mRNA, lncRNA, miRNA, circRNA) into the tumor cells and microenvironment, leading the stimulation of tumor growth and metastasis. In turn, the platelet clinical characteristics (e.g., count and volume) and contents (e.g., RNA and protein) are altered by the interactions with cancer cells and this enables the early cancer detection using these features of platelets. In addition, platelet-derived microparticles also demonstrate the prediction power of being cancer biomarkers. In this review, we focus on the clinical applications of platelet detection using the platelet count, mean platelet volume, platelet RNA and protein profiles for human cancers and discuss the gap in bringing these implementations into the clinic.

PltDB: a blood platelets-based gene expression database for disease investigation

MOTIVATION

Molecular profiling of blood-based liquid biopsies is a promising disease detection method, which overcomes the limitations of invasive diagnostic strategies. Recently, gene expression profiling of platelets reportedly provides valuable resource for developing new biomarkers for the detection of diseases, including cancer. However, there is no database containing RNAs in platelets.

RESULTS

In this study, we constructed PltDB (http://www.pltdb-hust.com), a platelets-based gene expression database featuring integration and visualization of RNA expression profiles based on RNA-seq and microarray data spanning both normal individuals and patients with different diseases. PltDB currently contains the expression landscape of mRNAs, lncRNAs, circRNAs, and miRNAs in platelets from patients with different disease types and healthy controls. Moreover, PltDB provides users with the tools for visualizing results of comparison and correlation analysis and for downloading expression profiles and analysis results. A submission interface for the scientific community is also embraced for uploading novel RNA expression profiles derived from platelet samples. PltDB will offer a comprehensive review of the clinical use of platelets, overcome technical problems when analyzing data from diverse studies and serve as a powerful platform for developing new blood biomarkers.

AVAILABILITY

PltDB is accessible at http://www.pltdb-hust.com.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.