An extracellular vesicle-related gene expression signature identifies high-risk patients in medulloblastoma

CTC, ctDNA, and Exosome in Thyroid Cancers: A Review

Thyroid cancer has become more common in recent years all around the world. Many issues still need to be urgently addressed in the diagnosis, treatment, and prognosis of thyroid cancer. Liquid biopsy (mainly circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and circulating exosomes) may provide a novel and ideal approach to solve these issues, allows us to assess the features of diseases more comprehensively, and has a function in a variety of malignancies. Recently, liquid biopsy has been shown to be critical in thyroid cancer diagnosis, treatment, and prognosis in numerous previous studies. In this review, by testing CTCs, ctDNA, and exosomes, we focus on the possible clinical role of liquid biopsy in thyroid cancer, including diagnostic and prognostic biomarkers and response to therapy. We briefly review how liquid biopsy components have progressed in thyroid cancer by consulting the existing public information. We also discuss the clinical potential of liquid biopsy in thyroid cancer and provide a reference for liquid biopsy research. Liquid biopsy has the potential to be a useful tool in the early detection, monitoring, or prediction of response to therapies and prognosis in thyroid cancer, with promising clinical applications.

Group-specific cellular metabolism in Medulloblastoma

BACKGROUND

Cancer metabolism influences multiple aspects of tumorigenesis and causes diversity across malignancies. Although comprehensive research has extended our knowledge of molecular subgroups in medulloblastoma (MB), discrete analysis of metabolic heterogeneity is currently lacking. This study seeks to improve our understanding of metabolic phenotypes in MB and their impact on patients' outcomes.

METHODS

Data from four independent MB cohorts encompassing 1,288 patients were analysed. We explored metabolic characteristics of 902 patients (ICGC and MAGIC cohorts) on bulk RNA level. Moreover, data from 491 patients (ICGC cohort) were searched for DNA alterations in genes regulating cell metabolism. To determine the role of intratumoral metabolic differences, we examined single-cell RNA-sequencing (scRNA-seq) data from 34 additional patients. Findings on metabolic heterogeneity were correlated to clinical data.

RESULTS

Established MB groups exhibit substantial differences in metabolic gene expression. By employing unsupervised analyses, we identified three clusters of group 3 and 4 samples with distinct metabolic features in ICGC and MAGIC cohorts. Analysis of scRNA-seq data confirmed our results of intertumoral heterogeneity underlying the according differences in metabolic gene expression. On DNA level, we discovered clear associations between altered regulatory genes involved in MB development and lipid metabolism. Additionally, we determined the prognostic value of metabolic gene expression in MB and showed that expression of genes involved in metabolism of inositol phosphates and nucleotides correlates with patient survival.

CONCLUSION

Our research underlines the biological and clinical relevance of metabolic alterations in MB. Thus, distinct metabolic signatures presented here might be the first step towards future metabolism-targeted therapeutic options.

Intratumoral heterogeneity of MYC drives medulloblastoma metastasis and angiogenesis

BACKGROUND

Intratumoral heterogeneity is crucially involved in metastasis, resistance to therapy, and cancer relapse. Amplifications of the proto-oncogene MYC display notable heterogeneity at the single-cell level and are associated with a particularly dismal prognosis in high-risk medulloblastomas (MBs). The aim of this study was to establish the relevance of interclonal cross-talk between MYC-driven and non-MYC-driven MB cells.

METHODS

We used fluorescence in situ hybridization, single-cell transcriptomics, and immunohistochemistry, in vitro isogenic cell models, non-targeted proteomics, mass spectrometry-based metabolite quantification, HUVECs tube formation assay, and orthotopic in vivo experiments to investigate interclonal cross-talk in MB.

RESULTS

We found that the release of lactate dehydrogenase A (LDHA) from MYC-driven cells facilitates metastatic seeding and outgrowth, while secretion of dickkopf WNT signaling pathway inhibitor 3 from non-MYC-driven cells promotes tumor angiogenesis. This tumor-supporting interaction between both subclones was abrogated by targeting the secretome through pharmacological and genetic inhibition of LDHA, which significantly suppressed tumor cell migration.

CONCLUSION

Our study reveals the functional relevance of clonal diversity and highlights the therapeutic potential of targeting the secretome to interrupt interclonal communication and progression in high-risk MB.

Weighted Gene Co-Expression Network Analysis and Support Vector Machine Learning in the Proteomic Profiling of Cerebrospinal Fluid from Extraventricular Drainage in Child Medulloblastoma

Medulloblastoma (MB) is the most common pediatric malignant central nervous system tumor. Overall survival in MB depends on treatment tuning. There is aneed for biomarkers of residual disease and recurrence. We analyzed the proteome of waste cerebrospinal fluid (CSF) from extraventricular drainage (EVD) from six children bearing various subtypes of MB and six controls needing EVD insertion for unrelated causes. Samples included total CSF, microvesicles, exosomes, and proteins captured by combinatorial peptide ligand library (CPLL). Liquid chromatography-coupled tandem mass spectrometry proteomics identified 3560 proteins in CSF from control and MB patients, 2412 (67.7%) of which were overlapping, and 346 (9.7%) and 805 (22.6%) were exclusive. Multidimensional scaling analysis discriminated samples. The weighted gene co-expression network analysis (WGCNA) identified those modules functionally associated with the samples. A ranked core of 192 proteins allowed distinguishing between control and MB samples. Machine learning highlighted long-chain fatty acid transport protein 4 (SLC27A4) and laminin B-type (LMNB1) as proteins that maximized the discrimination between control and MB samples. Machine learning WGCNA and support vector machine learning were able to distinguish between MB versus non-tumor/hemorrhagic controls. The two potential protein biomarkers for the discrimination between control and MB may guide therapy and predict recurrences, improving the MB patients' quality of life.

The Growing Relevance of Immunoregulation in Pediatric Brain Tumors

Pediatric brain tumors are genetically heterogeneous solid neoplasms. With a prevailing poor prognosis and widespread resistance to conventional multimodal therapy, these aggressive tumors are the leading cause of childhood cancer-related deaths worldwide. Advancement in molecular research revealed their unique genetic and epigenetic characteristics and paved the way for more defined prognostication and targeted therapeutic approaches. Furthermore, uncovering the intratumoral metrics on a single-cell level placed non-malignant cell populations such as innate immune cells into the context of tumor manifestation and progression. Targeting immune cells in pediatric brain tumors entails unique challenges but promising opportunities to improve outcome. Herein, we outline the current understanding of the role of the immune regulation in pediatric brain tumors.

Evaluation of exosome derivatives as bio-informational reprogramming therapy for cancer

Exosomes are nanoparticle sized (100 ± 50 nm) extracellular vesicles (ECVs) that play important roles in cell-to-cell communication. They do this by utilizing their natural ability to shuttle signaling molecules across the cellular microenvironment and promote paracrine signaling. Currently, exosomes are being explored for their potential as therapeutic agents for various degenerative diseases including cancer. The rationale behind their therapeutic ability is that they can transfer signaling biomolecules, and subsequently induce metabolic and physiological changes in diseased cells and tissues. In addition, exosomes can be used as a drug delivery system and may be very effective at reducing toxicity and increasing bioavailability of therapeutic molecules and drugs. Although exosomes were first believed to be a waste product of the cell, current research has demonstrated that these particles can serve as modulators of the immune system, act as cancer biomarkers, cause re-differentiation of cancer cells, and induce apoptosis in diseased cells. Extensive research has been performed specifically using amniotic fluid-derived extracellular vesicles, named "cytosomes". While the use of cytosomes in clinical application is still in the early stages, researchers have shown great potential for these EVs in regenerative medicine as immune modulators, in controlling microbial infection and by inducing tissue repair through the activation of endogenous, tissue-specific stem cells. This review emphasizes the capabilities of specific subsets of extracellular vesicles that can potentially be used for cancer therapy, principally as a source of bi-informational reprogramming for malignant cells.