Cell adhesion molecule 2 (CADM2) promotes brain metastasis by inducing epithelial-mesenchymal transition (EMT) in human non-small cell lung cancer

Breaking boundaries: role of the brain barriers in metastatic process

Brain metastases (BMs) are the most common intracranial tumors in adults and occur 3-10 times more frequently than primary brain tumors. Despite intensive multimodal therapies, including resection, radiotherapy, and chemotherapy, BMs are associated with poor prognosis and remain challenging to treat. BMs predominantly originate from primary lung (20-56%), breast (5-20%), and melanoma (7-16%) tumors, although they can arise from other cancer types less frequently. The metastatic cascade is a multistep process involving local invasion, intravasation into the bloodstream or lymphatic system, extravasation into normal tissue, and colonization of the distal site. After reaching the brain, circulating tumor cells (CTCs) breach the blood-brain barrier (BBB).The selective permeability of the BBB poses a significant challenge for therapeutic compounds, limiting the treatment efficacy of BMs. Understanding the mechanisms of tumor cell interactions with the BBB is crucial for the development of effective treatments. This review provides an in-depth analysis of the brain barriers, including the BBB, blood-spinal cord barrier, blood-meningeal barrier, blood-arachnoid barrier, and blood-cerebrospinal fluid barrier. It explores the molecular and cellular components of these barriers and their roles in brain metastasis, highlighting the importance of this knowledge for identifying druggable targets to prevent or limit BM formation.

CADM2 participates in endometriosis development by influencing the epithelial-mesenchymal transition

Endometriosis (EM) is a common gynecologic condition that often leads to infertility in women of reproductive age. Cell adhesion molecule 2 (CADM2) is involved in maintaining cell adhesion and polarity, as well as suppressing tumors. However, the role and mechanism of CADM2 in endometriosis is unclear. Therefore, this study evaluated the expression levels of CADM2 and epithelial-mesenchymal transition (EMT)-related marker proteins (E-cadherin, α-SMA, and N-cadherin). Compared to normal endometrial tissue, CADM2 was expressed at low levels in ectopic endometrial tissue from patients with EM. We performed clone formation assays, wound healing assays, and Transwell cell invasion assays to investigate the effects of CADM2 on the biological behavior of endometriosis epithelial cells (11Z) and ectopic endometrial stromal cells (EESCs). The growth, migration, and invasion abilities of these cells were significantly inhibited by overexpression of CADM2. The results were reversed after the knockdown of CADM2. Finally, western blotting (WB) was utilized to detect the effect of CADM2 on EMT in endometriosis cells. CADM2 inhibited EMT in endometriosis cells. In conclusion, our study suggests that CADM2 is a negative regulator of endometriosis development and may inhibit endometriosis development by suppressing EMT.

Changes in the expression of cell interaction-related pathways during brain metastasis in lung adenocarcinoma: Gene expression and immunohistochemical analysis

BACKGROUND

Brain metastasis (BM) is a prevalent prognostic event in the development of lung adenocarcinoma (LUAD) with a poor prognosis. Alterations in gene or protein expression during various phases of BM remain unclear.

METHODS

We performed gene expression and pathway analyses using a metastasis-related gene panel on 12 lung tissues from patients with confirmed BM, 12 lung tissues from patients without BM, and 12 matched brain tissues from patients with confirmed BM during follow-up after LUAD surgery. The results of the gene expression analysis were validated by immunohistochemistry.

RESULTS

Cell interaction-related pathways (such as focal adhesion, extracellular matrix-receptor interaction, and proteoglycans in cancer) showed the greatest differences among the three groups. Expression of the cell interaction-related pathway was highest in the lung sample of BM group and lowest in the matched brain tissue. Using a machine learning model, a signature of 20 genes from cell interaction-related pathways accurately predicted BM (area under the curve score of 0.792 and an accuracy rate of 0.875). Immunohistochemical analysis showed higher expression of proteins associated with cell interaction-related genes and a mesenchymal phenotype in the lung sample of BM group than in those without BM or matched brain tissue.

CONCLUSIONS

LUAD acquires the characteristics of the cell interaction-related pathway that leads to the development of BM, with a significant decrease in expression following brain colonization.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

The RNA interactome in the Hallmarks of Cancer

Ribonucleic acid (RNA) molecules are indispensable for cellular homeostasis in healthy and malignant cells. However, the functions of RNA extend well beyond that of a protein-coding template. Rather, both coding and non-coding RNA molecules function through critical interactions with a plethora of cellular molecules, including other RNAs, DNA, and proteins. Deconvoluting this RNA interactome, including the interacting partners, the nature of the interaction, and dynamic changes of these interactions in malignancies has yielded fundamental advances in knowledge and are emerging as a novel therapeutic strategy in cancer. Here, we present an RNA-centric review of recent advances in the field of RNA-RNA, RNA-protein, and RNA-DNA interactomic network analysis and their impact across the Hallmarks of Cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

Liver fibrosis-derived exosomal miR-106a-5p facilitates the malignancy by targeting SAMD12 and CADM2 in hepatocellular carcinoma

The mechanism of hepatocellular carcinoma (HCC) development induced by liver fibrosis is obscure. The objective of this study is to establish miRNAs from exosomes associated with liver fibrosis, and to identify potential biomarkers for the prediction of personalized clinical management effectiveness in HCC. Our research focused on miRNAs from exosomes and mRNA from liver fibrosis, which we found in the gene expression omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) evaluated miRNAs from exosomes associated with liver fibrosis, and Wilcoxon analysis assessed differentially expressed mRNAs (DEGs) across liver fibrosis/normal tissues. Following that, DEGs were assessed through gene set enrichment analysis (GSEA), gene ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, based on the screened targeted genes, including SAMD12 and CADM2, we further elucidated their correlation in HCC patients from the BEST database. The Kaplan-Meier Plotter platform was applied to evaluate the prognostic values of miRNA in HCC. In vitro and vivo experiments validated our findings. Six miRNAs associated with liver fibrosis were evaluated in our investigation. In-depth research presented exosome-derived miR-106a-5p, SAMD12 and CADM2 could exert valuable predictive implications for HCC treatment and illness assessment. Serum miR-106a-5p derived from liver fibrosis was decreased compared with healthy individuals. SAMD12 and CADM2 were diminished in liver cancer cell lines, and their knockdown of them exacerbated the proliferation capacities of liver cells in vitro. Exosome-derived miRNA of liver fibrosis modulated tumorigenesis by targeting SAMD12 and CADM2 in HCC.

Surfaceome Profiling of Cell Lines and Patient-Derived Xenografts Confirm FGFR4, NCAM1, CD276, and Highlight AGRL2, JAM3, and L1CAM as Surface Targets for Rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. The prognosis for patients with high-grade and metastatic disease is still very poor, and survivors are burdened with long-lasting side effects. Therefore, more effective and less toxic therapies are needed. Surface proteins are ideal targets for antibody-based therapies, like bispecific antibodies, antibody-drug conjugates, or chimeric antigen receptor (CAR) T-cells. Specific surface targets for RMS are scarce. Here, we performed a surfaceome profiling based on differential centrifugation enrichment of surface/membrane proteins and detection by LC-MS on six fusion-positive (FP) RMS cell lines, five fusion-negative (FN) RMS cell lines, and three RMS patient-derived xenografts (PDXs). A total of 699 proteins were detected in the three RMS groups. Ranking based on expression levels and comparison to expression in normal MRC-5 fibroblasts and myoblasts, followed by statistical analysis, highlighted known RMS targets such as FGFR4, NCAM1, and CD276/B7-H3, and revealed AGRL2, JAM3, MEGF10, GPC4, CADM2, as potential targets for immunotherapies of RMS. L1CAM expression was investigated in RMS tissues, and strong L1CAM expression was observed in more than 80% of alveolar RMS tumors, making it a practicable target for antibody-based therapies of alveolar RMS.

Genome-wide interrogation of structural variation reveals novel African-specific prostate cancer oncogenic drivers

BACKGROUND

African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation.

METHODS

Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa.

RESULTS

Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7, GTF3C2, NTNG1 and YPEL5. Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2, LSAMP, PTPRD, PDE4D and PACRG having therapeutic implications for African patients.

CONCLUSIONS

In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.

MiR-17-5p Targets and Downregulates CADM2, Activating the Malignant Phenotypes of Colon Cancer Cells

Accumulating studies have demonstrated that CADM2 modulated malignant phenotype of various cancer cells, while its regulatory function and mechanism have not yet been reported. In this study, qRT-PCR was utilized to measure CADM2 mRNA level in normal cells and colon cancer cells, also, IHC and WB were applied to detect CADM2 protein expression in colon tissues, exhibiting low mRNA and protein levels of CADM2 in colon cancer. Applying cell function experiments, the impacts of CADM2 on colon cell phenotypes were examined, and the results illustrated that upregulating CADM2 remarkably repressed proliferation, invasion, migration, cell cycle of colon cancer cells, and facilitated cell apoptosis. Thus, it could be considered that CADM2 served as a tumor repressor gene in colon cancer. Moreover, the outcomes of dual-luciferase assay displayed that miR-17-5p could target CADM2, and overexpressing miR-17-5p could notably inhibit the mRNA and protein expression levels of CADM2. We, therefore, assumed that CADM2 was a downstream target of miR-139-5p. qRT-PCR was conducted to assess miR-17-5p level in colon cancer cells and normal cells, verifying a high miR-17-5p expression in the cancer cells. The effects of miR-17-5p on colon cell phenotypes were examined as well, where we determined that miR-17-5p served as a tumor-promoting factor. Finally, the rescue experiments exhibited that miR-17-5p could activate tumor-promoting phenotypes, while such activating effects could be reversed by upregulating CADM2. In short, the study proved that miR-17-5p facilitated malignant progression of colon cancer through targeting CADM2 at a post-transcriptional level. Our findings offer new insight into molecular therapy of colon cancer patients.

Proteomics of autism and Alzheimer's mouse models reveal common alterations in mTOR signaling pathway

Autism spectrum disorder (ASD) and Alzheimer's disease (AD) are two different neurological disorders that share common clinical features, such as language impairment, executive functions, and motor problems. A genetic convergence has been proposed as well. However, the molecular mechanisms of these pathologies are still not well understood. Protein S-nitrosylation (SNO), the nitric oxide (NO)-mediated posttranslational modification, targets key proteins implicated in synaptic and neuronal functions. Previously, we have shown that NO and SNO are involved in the InsG3680(+/+) ASD and P301S AD mouse models. Here, we performed large-scale computational biology analysis of the SNO-proteome followed by biochemical validation to decipher the shared mechanisms between the pathologies. This analysis pointed to the mammalian target of rapamycin complex 1 (mTORC1) signaling pathway as one of the shared molecular mechanisms. Activation of mTOR in the cortex of both mouse models was confirmed by western blots that showed increased phosphorylation of RPS6, a major substrate of mTORC1. Other molecular alterations affected by SNO and shared between the two mouse models, such as synaptic-associated processes, PKA signaling, and cytoskeleton-related processes were also detected. This is the first study to decipher the SNO-related shared mechanisms between SHANK3 and MAPT mutations. Understanding the involvement of SNO in neurological disorders and its intersection between ASD and AD might help developing an effective novel therapy for both neuropathologies.

Tumor Nonimmune-Microenvironment-Related Gene Expression Signature Predicts Brain Metastasis in Lung Adenocarcinoma Patients after Surgery: A Machine Learning Approach Using Gene Expression Profiling

Simple Summary

It is important to be able to predict brain metastasis in lung adenocarcinoma patients; however, research in this area is still lacking. Much of the previous work on tumor microenvironments in lung adenocarcinoma with brain metastasis concerns the tumor immune microenvironment. The importance of the tumor nonimmune microenvironment (extracellular matrix (ECM), epithelial–mesenchymal transition (EMT) feature, and angiogenesis) has been overlooked with regard to brain metastasis. We evaluated tumor nonimmune-microenvironment-related gene expression signatures that could predict brain metastasis after the surgical resection of lung adenocarcinoma using a machine learning approach. We identified a tumor nonimmune-microenvironment-related 17-gene expression signature, and this signature showed high brain metastasis predictive power in four machine learning classifiers. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. Our tumor nonimmune-microenvironment-related gene expression signatures are important biological markers that can predict brain metastasis and provide patient-specific treatment options.

Abstract

Using a machine learning approach with a gene expression profile, we discovered a tumor nonimmune-microenvironment-related gene expression signature, including extracellular matrix (ECM) remodeling, epithelial–mesenchymal transition (EMT), and angiogenesis, that could predict brain metastasis (BM) after the surgical resection of 64 lung adenocarcinomas (LUAD). Gene expression profiling identified a tumor nonimmune-microenvironment-related 17-gene expression signature that significantly correlated with BM. Of the 17 genes, 11 were ECM-remodeling-related genes. The 17-gene expression signature showed high BM predictive power in four machine learning classifiers (areas under the receiver operating characteristic curve = 0.845 for naïve Bayes, 0.849 for support vector machine, 0.858 for random forest, and 0.839 for neural network). Subgroup analysis revealed that the BM predictive power of the 17-gene signature was higher in the early-stage LUAD than in the late-stage LUAD. Pathway enrichment analysis showed that the upregulated differentially expressed genes were mainly enriched in the ECM–receptor interaction pathway. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. The tumor nonimmune-microenvironment-related gene expression signatures found in this study are important biological markers that can predict BM and provide patient-specific treatment options.

The Immune Microenvironment in Brain Metastases of Non-Small Cell Lung Cancer

Brain metastasis of non-small cell lung cancer is associated with poor survival outcomes and poses rough clinical challenges. At the era of immunotherapy, it is urgent to perform a comprehensive study uncovering the specific immune microenvironment of brain metastases of NSCLC. The immune microenvironment of brain is distinctly different from microenvironments of extracranial lesions. In this review, we summarized the process of brain metastases across the barrier and revealed that brain is not completely immune-privileged. We comprehensively described the specific components of immune microenvironment for brain metastases such as central nervous system-derived antigen-presenting cells, microglia and astrocytes. Besides, the difference of immune microenvironment between brain metastases and primary foci of lung was particularly demonstrated.

High expression of cell adhesion molecule 2 unfavorably impacts survival in non-small cell lung cancer patients with brain metastases

Background

Lung cancer is one kind of malignant tumor with a high risk for morbidity and mortality compared to other solid organ malignancies. Brain metastases occur in 30-55% of non-small cell lung cancer (NSCLC) patients. Prognosis of NSCLC patients with brain metastases is very poor. Our previous study showed that cell adhesion molecule 2 (CADM2) could regulate the development of brain metastasis in NSCLC cells. Therefore, the objective of the study is to evaluate the effect of CADM2 on the prognosis of NSCLC patients with brain metastases.

Methods

The expression of CADM2 was detected by quantitative real-time polymerase chain reaction (qRT-PCR) in the tissue of the primary tumor. Patients were followed up and overall survival (OS) was calculated. The relationships between CADM2 and clinicopathological features were analyzed using the chi-square test. Kaplan-Meier analysis was carried out to demonstrate the influence of CADM2 on the OS of patients. Univariate and multivariate Cox analyses were used to determine the prognosis of NSCLC patients with brain metastases.

Results

A total of 139 NSCLC patients with brain metastases from the Affiliated Cancer Hospital & Institute of Guangzhou Medical University, treated between January 2015 and December 2017 were evaluated retrospectively. The expression level of CADM2 in patients ranged from 1 to 17.2677, with a median of 6.0772. Chi-square analysis showed that CADM2 gene expression level was not significantly associated with gender, age, tumor location, histological subtype, tumor T stage, extracranial metastasis, or smoking status. However, CADM2 expression was notably associated with risk for lymph node metastasis. The results of the Kaplan-Meier analysis showed that high expression [CADM2 messenger RNA (mRNA) ≥6.0772] of CADM2 was markedly associated with poor prognosis. Univariate and multivariate Cox analyses demonstrated that CADM2 was an independent risk factor for survival in NSCLC patients with brain metastases (P<0.05).

Conclusions

CADM2 expression is up-regulated and closely associated with disease progression and poor prognosis in NSCLC patients with brain metastases. CADM2 expression warrants special consideration given its potential prognostic significance that might help inform clinical decision making.

The metastasizing mechanisms of lung cancer: Recent advances and therapeutic challenges

Lung cancer is one of the common malignant tumors that threaten human life with serious incidence and high mortality. According to the histopathological characteristics, lung cancer is mainly divided into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC accounts for about 80-85% of lung cancers. In fact, lung cancer metastasis is a major cause of treatment failure in clinical patients. The underlying reason is that the mechanisms of lung cancer metastasis are still not fully understood. The metastasis of lung cancer cells is controlled by many factors, including the interaction of various components in the lung cancer microenvironment, epithelial-mesenchymal transition (EMT) transformation, and metastasis of cancer cells through blood vessels and lymphatics. The molecular relationships are even more intricate. Further study on the mechanisms of lung cancer metastasis and in search of effective therapeutic targets can bring more reference directions for clinical drug research and development. This paper focuses on the factors affecting lung cancer metastasis and connects with related molecular mechanisms of the lung cancer metastasis and mechanisms of lung cancer to specific organs, which mainly reviews the latest research progress of NSCLC metastasis. Besides, in this paper, experimental models of lung cancer and metastasis, mechanisms in SCLC transfer and the challenges about clinical management of lung cancer are also discussed. The review is intended to provide reference value for the future research in this field and promising treatment clues for clinical patients.

The UFSP2/UFMylation Pathway Is Involved in Silica-Induced Pulmonary Injury

Silicosis is an irreversible occupational pulmonary disease that is characterized as progressed pulmonary fibrosis. In this study, we investigated the changes of UFSP2 and the related UFMylation in silica-induced pulmonary injury mice models. The experimental silicosis models were prepared by intratracheal injection of silica particles, and the lung samples were harvested at the first or the seventh day after treatment. We found that the UFSP2 expression in the 1-day models was comparable, whereas it was upregulated in the 7-day models. Consistently, the UFMylation in the lung tissues of the 7-day models was activated. In addition, we observed the CADM2, an adhesion molecule, was reported to associate with epithelial-mesenchymal transition, was upregulated in the lungs of 7-day models. In contrast, it remained comparable in the 1-day models. Our data indicated that the UFSP2/UFMylation pathway and the CADM2 might be involved in the silica-induced pulmonary injury.