Apolipoprotein D Expression in Primary Brain Tumors: Analysis by Quantitative RT-PCR in Formalin-fixed, Paraffin-embedded Tissue

Spatially resolved transcriptomics of benign and malignant peripheral nerve sheath tumors

BACKGROUND

Peripheral nerve sheath tumors (PNSTs) encompass entities with different cellular differentiation and degrees of malignancy. Spatial heterogeneity complicates diagnosis and grading of PNSTs in some cases. In malignant PNST (MPNST) for example, single cell sequencing data has shown dissimilar differentiation states of tumor cells. Here, we aimed at determining the spatial and biological heterogeneity of PNSTs.

METHODS

We performed spatial transcriptomics on formalin-fixed paraffin-embedded diseased peripheral nerve tissue. We used spatial clustering and weighted correlation network analysis to construct niche-similarity networks and gene expression modules. We determined differential expression in primary pathologies, analysed pathways to investigate the biological significance of identified meta-signatures, integrated the transcriptional data with histological features and existing single cell data, and validated expression data by immunohistochemistry.

RESULTS

We identified distinct transcriptional signatures differentiating PNSTs. Immune cell infiltration, APOD and perineurial fibroblast marker expression highlighted the neurofibroma component of hybrid PNSTs (HPNSTs). While APOD was evenly expressed in neurofibromatous tumor tissue in both, HPNST and pure neurofibromas, perineurial fibroblast markers were evenly expressed in HPNST, but restricted to the periphery in plexiform neurofibromas. Furthermore, we provide a spatial cellular differentiation map for MPNST, locating Schwann cell precursors, neural crest-like cells and those with mesenchymal transition.

CONCLUSIONS

This pilot study shows that applying spatial transcriptomics to PNSTs provides important insight into their biology. It helps establishing new markers and provides spatial information about cellular composition and distribution of cellular differentiation states. By integrating morphological and high-dimensional molecular data it can improve PNSTs classification in the future.

Machine learning applications on intratumoral heterogeneity in glioblastoma using single-cell RNA sequencing data

Artificial intelligence is revolutionizing all fields that affect people's lives and health. One of the most critical applications is in the study of tumors. It is the case of glioblastoma (GBM) that has behaviors that need to be understood to develop effective therapies. Due to advances in single-cell RNA sequencing (scRNA-seq), it is possible to understand the cellular and molecular heterogeneity in the GBM. Given that there are different cell groups in these tumors, there is a need to apply Machine Learning (ML) algorithms. It will allow extracting information to understand how cancer changes and broaden the search for effective treatments. We proposed multiple comparisons of ML algorithms to classify cell groups based on the GBM scRNA-seq data. This broad comparison spectrum can show the scientific-medical community which models can achieve the best performance in this task. In this work are classified the following cell groups: Tumor Core (TC), Tumor Periphery (TP) and Normal Periphery (NP), in binary and multi-class scenarios. This work presents the biomarker candidates found for the models with the best results. The analyses presented here allow us to verify the biomarker candidates to understand the genetic characteristics of GBM, which may be affected by a suitable identification of GBM heterogeneity. This work obtained for the four scenarios covered cross-validation results of $93.03\% \pm 5.37\%$, $97.42\% \pm 3.94\%$, $98.27\% \pm 1.81\%$ and $93.04\% \pm 6.88\%$ for the classification of TP versus TC, TP versus NP, NP versus TP and TC (TPC) and NP versus TP versus TC, respectively.

The Lipocalin Apolipoprotein D Functional Portrait: A Systematic Review

Apolipoprotein D is a chordate gene early originated in the Lipocalin protein family. Among other features, regulation of its expression in a wide variety of disease conditions in humans, as apparently unrelated as neurodegeneration or breast cancer, have called for attention on this gene. Also, its presence in different tissues, from blood to brain, and different subcellular locations, from HDL lipoparticles to the interior of lysosomes or the surface of extracellular vesicles, poses an interesting challenge in deciphering its physiological function: Is ApoD a moonlighting protein, serving different roles in different cellular compartments, tissues, or organisms? Or does it have a unique biochemical mechanism of action that accounts for such apparently diverse roles in different physiological situations? To answer these questions, we have performed a systematic review of all primary publications where ApoD properties have been investigated in chordates. We conclude that ApoD ligand binding in the Lipocalin pocket, combined with an antioxidant activity performed at the rim of the pocket are properties sufficient to explain ApoD association with different lipid-based structures, where its physiological function is better described as lipid-management than by long-range lipid-transport. Controlling the redox state of these lipid structures in particular subcellular locations or extracellular structures, ApoD is able to modulate an enormous array of apparently diverse processes in the organism, both in health and disease. The new picture emerging from these data should help to put the physiological role of ApoD in new contexts and to inspire well-focused future research.

Extracellular Vesicles as a Novel Liquid Biopsy-Based Diagnosis for the Central Nervous System, Head and Neck, Lung, and Gastrointestinal Cancers: Current and Future Perspectives

Simple Summary

To improve clinical outcomes, early diagnosis is mandatory in cancer patients. Several diagnostic approaches have been proposed, however, the main drawback relies on the invasive procedures required. Extracellular vesicles (EVs) are bilayer lipid membrane structures released by almost all cells and transferred to remote sites via the bloodstream. The observation that their cargo reflects the cell of origin has opened a new frontier for non-invasive biomarker discovery in oncology. Moreover, since EVs can be recovered from different body fluids, their impact as a Correctdiagnostic tool has gained particular interest. Hence, in the last decade, several studies using different biological fluids have been performed, showing the valuable contributions of EVs as tumour biomarkers, and their improved diagnostic power when combined with currently available tumour markers. In this review, the most relevant data on the diagnostic relevance of EVs, alone or in combination with the well-established tumour markers, are discussed.

Abstract

Early diagnosis, along with innovative treatment options, are crucial to increase the overall survival of cancer patients. In the last decade, extracellular vesicles (EVs) have gained great interest in biomarker discovery. EVs are bilayer lipid membrane limited structures, released by almost all cell types, including cancer cells. The EV cargo, which consists of RNAs, proteins, DNA, and lipids, directly mirrors the cells of origin. EVs can be recovered from several body fluids, including blood, cerebral spinal fluid (CSF), saliva, and Broncho-Alveolar Lavage Fluid (BALF), by non-invasive or minimally invasive approaches, and are therefore proposed as feasible cancer diagnostic tools. In this review, methodologies for EV isolation and characterization and their impact as diagnostics for the central nervous system, head and neck, lung, and gastrointestinal cancers are outlined. For each of these tumours, recent data on the potential clinical applications of the EV’s unique cargo, alone or in combination with currently available tumour biomarkers, have been deeply discussed.

Clinical Significance of Extracellular Vesicles in Plasma from Glioblastoma Patients

PURPOSE

Glioblastoma (GBM) is the most common primary brain tumor. The identification of blood biomarkers reflecting the tumor status represents a major unmet need for optimal clinical management of patients with GBM. Their high number in body fluids, their stability, and the presence of many tumor-associated proteins and RNAs make extracellular vesicles potentially optimal biomarkers. Here, we investigated the potential role of plasma extracellular vesicles from patients with GBM for diagnosis and follow-up after treatment and as a prognostic tool.

EXPERIMENTAL DESIGN

Plasma from healthy controls (n = 33), patients with GBM (n = 43), and patients with different central nervous system malignancies (n = 25) were collected. Extracellular vesicles were isolated by ultracentrifugation and characterized in terms of morphology by transmission electron microscopy, concentration, and size by nanoparticle tracking analysis, and protein composition by mass spectrometry. An orthotopic mouse model of human GBM confirmed human plasma extracellular vesicle quantifications. Associations between plasma extracellular vesicle concentration and clinicopathologic features of patients with GBM were analyzed. All statistical tests were two-sided.

RESULTS

GBM releases heterogeneous extracellular vesicles detectable in plasma. Plasma extracellular vesicle concentration was higher in GBM compared with healthy controls (P < 0.001), brain metastases (P < 0.001), and extra-axial brain tumors (P < 0.001). After surgery, a significant drop in plasma extracellular vesicle concentration was measured (P < 0.001). Plasma extracellular vesicle concentration was also increased in GBM-bearing mice (P < 0.001). Proteomic profiling revealed a GBM-distinctive signature.

CONCLUSIONS

Higher extracellular vesicle plasma levels may assist in GBM clinical diagnosis: their reduction after GBM resection, their rise at recurrence, and their protein cargo might provide indications about tumor, therapy response, and monitoring.

Multiple similarly effective solutions exist for biomedical feature selection and classification problems

Binary classification is a widely employed problem to facilitate the decisions on various biomedical big data questions, such as clinical drug trials between treated participants and controls, and genome-wide association studies (GWASs) between participants with or without a phenotype. A machine learning model is trained for this purpose by optimizing the power of discriminating samples from two groups. However, most of the classification algorithms tend to generate one locally optimal solution according to the input dataset and the mathematical presumptions of the dataset. Here we demonstrated from the aspects of both disease classification and feature selection that multiple different solutions may have similar classification performances. So the existing machine learning algorithms may have ignored a horde of fishes by catching only a good one. Since most of the existing machine learning algorithms generate a solution by optimizing a mathematical goal, it may be essential for understanding the biological mechanisms for the investigated classification question, by considering both the generated solution and the ignored ones.

Proteomic study of pilocytic astrocytoma pediatric brain tumor intracystic fluid

Liquid chromatography in coupling with high-resolution ESI-LTQ-Orbitrap mass spectrometry was applied for a proteomic study of pediatric pilocytic astrocytoma brain tumor intracystic fluid by an integrated top-down/bottom-up platform. Both of the proteomic strategies resulted complementary and support each other in contributing to a wide characterization of the protein and peptide content of the tumor fluid. Top-down approach allowed to identify several proteins and peptides involved in different biological activities together with the characterization of interesting proteoforms such as fibrinopeptide A and its truncated form, fibrinopeptide B, complement C3f fragments, β-thymosin peptides, ubiquitin, several apolipoproteins belonging to A and C families, apolipoprotein J and D, and cystatin C. Of particular interest resulted the identification of a N-terminal truncated cystatin C proteoform, likely involved in immune response mechanism modulations and the identification of oxidized and glycosylated apolipoproteins including disulfide bridge dimeric forms. The bottom-up approach confirmed some of the experimental data findings together with adding the characterization of high-molecular-mass proteins in the samples. These data could contribute to elucidate the molecular mechanisms involved in onset and progression of the disease and cyst development.

Apolipoprotein D as a novel marker in human end-stage heart failure: a preliminary study

Apolipoprotein D (Apo D) is reported to be in close association with developing and mature blood vessels, and involved in enhanced smooth muscle cell migration after injury. This study was designed to clarify the expression pattern of Apo D and the possibility of Apo D as a new marker in human end-stage heart failure. Individual RNA samples obtained from independent left ventricular tissue of six heart failure patients derived from cardiomyopathies of different aetiologies during cardiac transplantation and six non-failing control subjects were hybridized to the gene microarray containing, in total, 35 000 well-characterized Homo sapiens genes. Apo D was one of the highly expressed genes (3.3-fold upregulated) detected by microarray, which was further confirmed by quantitative real-time reverse transcriptase polymerase chain reaction (RT-PCR) (5.88-fold upregulated) in failing hearts compared with non-failing hearts. Both Western blotting and immunohistochemistry analyses also demonstrated the higher levels of Apo D protein in failing hearts. Importantly, we observed elevated levels of plasma Apo D in heart failure patients compared with non-failing control subjects. We demonstrated, for the first time to our knowledge, that Apo D was highly expressed in the mRNA and protein levels in human failing hearts compared with non-failing hearts. Furthermore, our finding of elevated plasma Apo D levels in patients with heart failure provides clues that Apo D may act not only as a cardiac molecular marker but also as a circulating biomarker in patients with heart failure.

Exploring the Distinctive Biological Characteristics of Pilocytic and Low-Grade Diffuse Astrocytomas Using Microarray Gene Expression Profiles

Although World Health Organization (WHO) grade I pilocytic astrocytomas and grade II diffuse astrocytomas have been classified for decades as different clinicopathologic entities, few, if any, data are available on the biologic features explaining these differences. Although more than 50 microarray-related studies have been carried out to characterize the molecular profiles of astrocytic tumors, we have identified only 11 that provide sound data on low-grade astrocytomas. We have incorporated these data into a comparative analysis for the purpose of identifying the most relevant molecular markers characterizing grade I pilocytic and grade II diffuse astrocytomas. Our analysis has identified various interesting genes that are differentially expressed in either grade I or grade II astrocytomas when compared with normal tissue and/or high-grade (WHO grade III and IV) astrocytomas. A large majority of these genes encode adhesion, extracellular matrix, and invasion-related proteins. Interestingly, a group of 6 genes (TIMP4, C1NH, CHAD, THBS4, IGFBP2, and TLE2) constitute an expression profile characteristic of grade I astrocytomas as compared with all other categories of tissue (normal brain, grade II, and high-grade astrocytomas). The end products (proteins) of these genes act as antimigratory compounds, a fact that could explain why pilocytic astrocytomas behave as compact (well-circumscribed) tumors as opposed to all the other astrocytic tumor types that diffusely invade the brain parenchyma. Having validated these molecular markers by means of real-time reverse transcriptase-polymerase chain reaction, an integrated model was proposed illustrating how and why pilocytic astrocytomas constitute a distinct biologic and pathologic entity when compared with diffuse astrocytomas.