Comparative transcriptome analysis reveals involvement of TLR-2 signaling in the pathogenesis of intracranial aneurysm

Molecular Subtypes and Machine Learning-Based Predictive Models for Intracranial Aneurysm Rupture

BACKGROUND

The determination of biological mechanisms and biomarkers related to intracranial aneurysm (IA) rupture is of utmost significance for the development of effective preventive and therapeutic strategies in the clinical field.

METHODS

GSE122897 and GSE13353 datasets were downloaded from Gene Expression Omnibus. Data extracted from GSE122897 were used for analyzing differential gene expression, and consensus clustering was performed to identify stable molecular subtypes. Clinical characteristics were compared between subgroups, and fast gene set enrichment analysis and weighted gene coexpression network analysis were performed. Hub genes were identified via least absolute shrinkage and selection operator analysis. Predictive models were constructed based on hub genes using the Light Gradient Boosting Machine, eXtreme Gradient Boosting, and logistic regression algorithm. Immune cell infiltration in IA samples was analyzed using Microenvironment Cell Population counter, CIBERSORT, and xCell algorithm. The correlation between hub genes and immune cells was analyzed. The predictive model and immune cell infiltration were validated using data from the GSE13353 dataset.

RESULTS

A total of 43 IA samples were classified into 2 subgroups based on gene expression profiles. Subgroup I had a higher risk of rupture, while 70% of subgroup II remained unruptured. In subgroup I, specific genes were associated with inflammation and immunity, and weighted gene coexpression network analysis revealed that the black module genes were linked to IA rupture. We identified 4 hub genes (spermine synthase, macrophage receptor with collagenous structure, zymogen granule protein 16B, and LIM and calponin-homology domains 1), which constructed predictive models with good diagnostic performance in differentiating between ruptured and unruptured IA samples. Monocytic lineage was found to be a significant factor in IA rupture, and the 4 hub genes were linked to monocytic lineage (P < 0.05).

CONCLUSIONS

We reveal a new molecular subtype that can reflect the actual pathological state of IA rupture, and our predictive models constructed by machine learning algorithms can efficiently predict IA rupture.

Dysregulated Genes and Signaling Pathways in the Formation and Rupture of Intracranial Aneurysm

Intracranial aneurysm (IA) has the potential to rupture. Despite scientific advances, we are still not in a position to screen patients for IA and identify those at risk of rupture. It is critical to comprehend the molecular basis of disease to facilitate the development of novel diagnostic strategies. We used transcriptomics to identify the dysregulated genes and understand their role in the disease biology. In particular, RNA-Seq was performed in tissue samples of controls, unruptured IA, and ruptured IA. Dysregulated genes (DGs) were identified and analyzed to understand the functional aspects of molecules. Subsequently, candidate genes were validated at both transcript and protein level. There were 314 DGs in patients with unruptured IA when compared to control samples. Out of these, SPARC and OSM were validated as candidate molecules in unruptured IA. PI3K-AKT signaling pathway was found to be an important pathway for the formation of IA. Similarly, 301 DGs were identified in the samples of ruptured IA when compared with unruptured IAs. CTSL was found to be a key candidate molecule which along with Hippo signaling pathway may be involved in the rupture of IA. We conclude that activation of PI3K-AKT signaling pathway by OSM along with up-regulation of SPARC is important for the formation of IA. Further, regulation of Hippo pathway through PI3K-AKT signaling results in the down-regulation of YAP1 gene. This along with up-regulation of CTSL leads to further weakening of aneurysm wall and its subsequent rupture.

A Transcriptomic Comparative Study of Cranial Vasculature

In genetic studies of cerebrovascular diseases, the optimal vessels to use as controls remain unclear. Our goal is to compare the transcriptomic profiles among 3 different types of control vessels: superficial temporal artery (STA), middle cerebral arteries (MCA), and arteries from the circle of Willis obtained from autopsies (AU). We examined the transcriptomic profiles of STA, MCA, and AU using RNAseq. We also investigated the effects of using these control groups on the results of the comparisons between aneurysms and the control arteries. Our study showed that when comparing pathological cerebral arteries to control groups, all control groups presented similar responses in the activation of immunological processes, the regulation of intracellular signaling pathways, and extracellular matrix productions, despite their intrinsic biological differences. When compared to STA, AU exhibited upregulation of stress and apoptosis genes, whereas MCA showed upregulation of genes associated with tRNA/rRNA processing. Moreover, our results suggest that the matched case-control study design, which involves control STA samples collected from the same subjects of matched aneurysm samples in our study, can improve the identification of non-inherited disease-associated genes. Given the challenges associated with obtaining fresh intracranial arteries from healthy individuals, our study suggests that using MCA, AU, or paired STA samples as controls are feasible strategies for future large-scale studies investigating cerebral vasculopathies. However, the intrinsic differences of each type of control should be taken into consideration when interpreting the results. With the limitations of each control type, it may be most optimal to use multiple tissues as controls.

Transcriptomic Studies on Intracranial Aneurysms

Intracranial aneurysm (IA) is a relatively common vascular malformation of an intracranial artery. In most cases, its presence is asymptomatic, but IA rupture causing subarachnoid hemorrhage is a life-threating condition with very high mortality and disability rates. Despite intensive studies, molecular mechanisms underlying the pathophysiology of IA formation, growth, and rupture remain poorly understood. There are no specific biomarkers of IA presence or rupture. Analysis of expression of mRNA and other RNA types offers a deeper insight into IA pathobiology. Here, we present results of published human studies on IA-focused transcriptomics.

Toll-Like Receptor Signaling Pathways: Novel Therapeutic Targets for Cerebrovascular Disorders

Toll-like receptors (TLRs), a class of pattern recognition proteins, play an integral role in the modulation of systemic inflammatory responses. Cerebrovascular diseases (CVDs) are a group of pathological conditions that temporarily or permanently affect the brain tissue mostly via the decrease of oxygen and glucose supply. TLRs have a critical role in the activation of inflammatory cascades following hypoxic-ischemic events and subsequently contribute to neuroprotective or detrimental effects of CVD-induced neuroinflammation. The TLR signaling pathway and downstream cascades trigger immune responses via the production and release of various inflammatory mediators. The present review describes the modulatory role of the TLR signaling pathway in the inflammatory responses developed following various CVDs and discusses the potential benefits of the modulation of different TLRs in the improvement of functional outcomes after brain ischemia.

[Over-expression of miR-144 inhibits invasion of liver cancer SMMC-7721 cells in vitro by suppressing TLR/MyD88 pathway]

OBJECTIVE

To investigate the effects of over-expression of miR-144 on invasion of SMMC-7721 cells and Toll-like receptor (TLR)/myeloid differentiation factor 88 (MyD88) pathway in hepatocellular carcinoma cells.

METHODS

The expressions of miR-144 was examined in normal human hepatocyte line HL-7702 and hepatocarcinoma cell line SMMC-7721 using realtime quantitative PCR (qRT-PCR). SMMC-7721 cells were divided into blank group, miR-144 NC group and miR-144 mimics group, and the expressions of miR-144 in each group were detected with qRT-PCR. Cell count kit-8 (CCK8) was used to assess the survival of SMMC-7721 cells, and the cell invasion was evaluated using Transwell assay. The expressions of matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9) and TLR/MyD88 pathway-related proteins in the cells were detected with Western blotting; the effect of 40 μ mol/L MyD88 inhibitor on TLR/MyD88 pathway-related proteins was examined in SMMC-7721 cells.

RESULTS

Compared with normal human hepatocytes, SMMC-7721 cells expressed a significantly lower level of miR-144 (P < 0.05). CCK-8 assay showed that test showed that miR-144 over-expression significantly decreased the cell survival rate (P < 0.05), lowered the number of invasive cells, and decreased the expression of MMP-2 and MMP-9 in SMMC-7721 cells (P < 0.05). The expressions of Toll-like receptor 4 (TLR4), MyD88, phosphorylated nuclear factor-kappa B (pNF-κB) and NF-κB protein decreased significantly in miR-144 mimics group and TJ-M2010-2 group (P < 0.05) and were comparable between the two groups (P > 0.05).

CONCLUSIONS

Overexpression of miR-144 decreases SMMC-7721 cell survival and invasion by inhibiting TLR/MyD88 pathway.