Exploration of Pericyte-Derived Factors Implicated in Lung Cancer Brain Metastasis Protection: A Pilot Messenger RNA Sequencing Using the Blood-Brain Barrier In Vitro Model

Do neutrophil extracellular traps implicate in atheromatous plaques from carotid endarterectomy? Re-analyzes of cDNA microarray data by surgeons

Background

Carotid artery stenosis is the cause of 15% of strokes. Neutrophil extracellular traps (NETs) and peptidyl arginine deiminase 4 (PAD4) are believed to be involved in thrombosis. This pilot study described the differential expression profile of NETs between atheromatous plaques and surrounding tissues.

Methods

Microarray datasets of carotid plaques were obtained from Gene Expression Omnibus. The normalized data were processed into comma-separated value matrix files using spreadsheet software. Analyzes of microarray data were conducted using integrated differential expression and pathway analysis.

Result

The clustering results illustrated that the classifications of plaque and control had reasonable biological validity. Pathway analysis revealed the relevance of immune response, cell signaling, and other pathways. Differentially expressed genes were detected between carotid plaques and control specimens. However, enrichment analyzes did not reveal a difference in PAD4 expression between the groups and that NET implication was only found in one cDNA microarray dataset.

Discussion

This pilot study does not necessarily dismiss the possibility of a relationship between NETs and atherothrombotic stroke. Gene expression could differ between endothelial cells and atheromas, and further studies are needed.

Single-Cell Profiling Comparisons of Tumor Microenvironment between Primary Advanced Lung Adenocarcinomas and Brain Metastases and Machine Learning Algorithms in Predicting Immunotherapeutic Responses

Brain metastasis (BM) occurs commonly in patients with lung adenocarcinomas. Limited evidence indicates safety and efficacy of immunotherapy for this metastatic tumor, though immune checkpoint blockade has become the front-line treatment for primary advanced non-small cell lung cancer. We aim to comprehensively compare tumor microenvironments (TME) between primary tumors (PT) and BM at single-cell resolution. Single-cell RNA transcriptomics from tumor samples of PT (N = 23) and BM (N = 16) and bulk sequencing data were analyzed to explore potential differences in immunotherapeutic efficacy between PT and BM of lung adenocarcinomas. Multiple machine learning algorithms were used to develop and validate models that predict responses to immunotherapy using the external cohorts. We found obviously less infiltration of immune cells in BM than PT, characterized specifically by deletion of anti-cancer CD8+ Trm cells and more dysfunctional CD8+ Tem cells in BM tumors. Meanwhile, macrophages and dendritic cells within BM demonstrated more pro-tumoral and anti-inflammatory effects, represented by distinct distribution and function of SPP1+ and C1Qs+ tumor-associated microphages, and inhibited antigen presentation capacity and HLA-I gene expression, respectively. Besides, we also found the lack of inflammatory-like CAFs and enrichment of pericytes within BM tumors, which may be critical factors in shaping inhibitory TME. Cell communication analysis further revealed mechanisms of the immunosuppressive effects associated with the activation of some unfavorable pathways, such as TGFβ signaling, highlighting the important roles of stromal cells in the anti-inflammatory microenvironment, especially specific pericytes. Furthermore, pericyte-related genes were identified to optimally predict immunotherapeutic responses by machine learning models with great predictive performance. Overall, various factors contribute to the immunosuppressive TME within BM tumors, represented by the lack of critical anti-cancer immune cells. Meanwhile, pericytes may help shape the TME and targeting the associated mechanisms may enhance immunotherapy efficacy for BM tumors in patients with lung adenocarcinomas.

Both the Complexity of Tight Junctions and Endothelial Transcytosis Are Increased During BBB Postnatal Development in Rats

The blood-brain barrier (BBB) comprises a single layer of endothelial cells and maintains a safe and homeostatic environment for proper neuronal function and synaptic transmission. BBB is not a discrete physical barrier, but a complex, dynamic, and adaptable interface. BBB continues to mature under the influence of the neural environment within a short period of time after birth. However, the basic mechanism of BBB formation and maintenance remains a mystery. Early studies have identified two structural characteristics of microvascular endothelium: special tight junctions (TJs) and a very low transcellular vesicle transport rate. Previous studies believed that BBB damage was mainly due to the destruction of tight junctions, and the role of vesicle transcytosis was neglected, so there was a lack of research on its impact on blood-brain barrier. It is urgent to get a better clarification of the unique structural and functional characteristics of the BBB endothelium to explain the role of BBB injury in neurological diseases. RNA sequencing was used to study the molecular characterization of cerebral cortex vascular endothelium by isolating them from neonatal, adolescent and adult rats. For investigation the maintenance mechanism of the BBB, we focused on the cellular and molecular regulation of barrier formation and the two characteristics of microvascular endothelial cells. Interestingly, we found that during the development of the blood-brain barrier, although the tight junctions gradually mature, endothelial cell transcytosis is gradually enhanced, resulting in an increase in the permeability of the blood-brain barrier. This study suggested that under physiological conditions, low vesicle transport is playing an important role in maintaining the integrity of the blood-brain barrier. This study not only summarized the unique characteristics of microvascular endothelial cells, but also illustrated a clarified mechanism of the development and maintenance of BBB which can provide new therapeutic opportunities for central nervous system drug delivery. Raw data of RNA sequencing were deposited in NCBI Sequence Read Archive database (PRJNA790676).

RNA Sequencing Data Analysis on the Maser Platform and the Tag-Count Comparison Graphical User Interface

The RNA sequencing (RNA-seq) process that allows for comprehensive transcriptome analysis has become increasingly simple. Analysis and interpretation of RNA-seq output data are indispensable for research, but bioinformatics experts are not always available to assist. Currently, however, even a wet-lab specialist can perform the pipeline analysis of RNA-seq described in this chapter using the Maser platform and the Tag-Count Comparison Graphical User Interface (TCC-GUI). These are free of charge for scientific use.