Elevated expression of FREM1 in breast cancer indicates favorable prognosis and high-level immune infiltration status

A glycolysis-related signature to improve the current treatment and prognostic evaluation for breast cancer

Background

As a heterogeneous malignancy, breast cancer (BRCA) shows high incidence and mortality. Discovering novel molecular markers and developing reliable prognostic models may improve the survival of BCRA.

Methods

The RNA-seq data of BRCA patients were collected from the training set The Cancer Genome Atlas (TCGA)-BRCA and validation set GSE20685 in the Gene Expression Omnibus (GEO) databases. The "GSVA" R package was used to calculate the glycolysis score for each patient, based on which all the patients were divided into different glycolysis groups. The "limma" package was employed to perform differentially expression genes (DEGs) analysis. Key signature genes were selected by performing un/multivariate and least absolute shrinkage and selection operator (LASSO) C regression and used to develop a RiskScore model. The ESTIMATE and MCP-Counter algorithms were used for quantifying immune infiltration level. The functions of the genes were validated using Western blot, colony formation, transwell and wound-healing assay.

Results

The glycolysis score and prognostic analysis showed that high glycolysis score was related to tumorigenesis pathway and a poor prognosis in BRCA as overactive glycolysis inhibited the normal functions of immune cells. Subsequently, we screened five key prognostic genes using the LASSO Cox regression analysis and used them to establish a RiskScore with a high classification efficiency. Based on the results of the RiskScore, it was found that patients in the high-risk group had significantly unfavorable immune infiltration and prognostic outcomes. A nomogram integrating the RiskScore could well predict the prognosis for BRCA patients. Knockdown of PSCA suppressed cell proliferation, invasion and migration of BRCA cells.

Conclusion

This study developed a glycolysis-related signature with five genes to distinguish between high-risk and low-risk BRCA patients. A nomogram developed on the basis of the RiskScore was reliable to predict BRCA survival. Our model provided clinical guidance for the treatment of BRCA patients.

Proteomic characteristics of the aqueous humor in Uyghur patients with pseudoexfoliation syndrome and pseudoexfoliative glaucoma

Pseudoexfoliation syndrome (PEX) is characterized by the deposition of fibrous pseudoexfoliation material (PEXM) in the eye, and secondary glaucoma associated with this syndrome has a faster and more severe clinical course. The incidence of PEX and pseudoexfoliative glaucoma (PEXG) exhibits ethnic clustering; however, few proteomic studies related to PEX and PEXG have been conducted in Asian populations. Therefore, we aimed to conduct proteomic analysis on the aqueous humor (AH) obtained from Uyghur patients with cataracts, those with PEX and cataracts, and those with PEXG and cataracts to better understand the molecular mechanisms of the disease and identify its potential biomarkers. To this end, AH was collected from patients with cataracts (n = 10, control group), PEX with cataracts (n = 10, PEX group), and PEXG with cataracts (n = 10, PEXG group) during phacoemulsification. Label-free quantitative proteomic techniques combined with bioinformatics were used to identify and analyze differentially expressed proteins (DEPs) in the AH of PEX and PEXG groups. Then, independent AH samples (n = 12, each group) were collected to validate DEPs by enzyme-linked immunosorbent assay (ELISA). The PEX group exhibited 25 DEPs, while the PEXG group showed 44 DEPs, both compared to the control group. Subsequently, we found three newly identified proteins in both PEX and PEXG groups, wherein FRAS1-related extracellular matrix protein 2 (FREM2) and osteoclast-associated receptor (OSCAR) exhibited downregulation, whereas coagulation Factor IX (F9) displayed upregulation. Bioinformatics analysis suggested that extracellular matrix interactions, abnormal blood-derived proteins, and lysosomes were mainly involved in the process of PEX and PEXG, and the PPI network further revealed F9 may serve as a potential biomarker for both PEX and PEXG. In conclusion, this study provides new information for understanding the proteomics of AH in PEX and PEXG.

Identification of diagnostic markers for moyamoya disease by combining bulk RNA-sequencing analysis and machine learning

Moyamoya disease (MMD) remains a chronic progressive cerebrovascular disease with unknown etiology. A growing number of reports describe the development of MMD relevant to infection or autoimmune diseases. Identifying biomarkers of MMD is to understand the pathogenesis and development of novel targeted therapy and may be the key to improving the patient's outcome. Here, we analyzed gene expression from two GEO databases. To identify the MMD biomarkers, the weighted gene co-expression network analysis (WGCNA) and the differential expression analyses were conducted to identify 266 key genes. The KEGG and GO analyses were then performed to construct the protein interaction (PPI) network. The three machine-learning algorithms of support vector machine-recursive feature elimination (SVM-RFE), random forest and least absolute shrinkage and selection operator (LASSO) were used to analyze the key genes and take intersection to construct MMD diagnosis based on the four core genes found (ACAN, FREM1, TOP2A and UCHL1), with highly accurate AUCs of 0.805, 0.903, 0.815, 0.826. Gene enrichment analysis illustrated that the MMD samples revealed quite a few differences in pathways like one carbon pool by folate, aminoacyl-tRNA biosynthesis, fat digestion and absorption and fructose and mannose metabolism. In addition, the immune infiltration profile demonstrated that ACAN expression was associated with mast cells resting, FREM1 expression was associated with T cells CD4 naive, TOP2A expression was associated with B cells memory, UCHL1 expression was associated with mast cells activated. Ultimately, the four key genes were verified by qPCR. Taken together, our study analyzed the diagnostic biomarkers and immune infiltration characteristics of MMD, which may shed light on the potential intervention targets of moyamoya disease patients.

Deeply integrating latent consistent representations in high-noise multi-omics data for cancer subtyping

Cancer is a complex and high-mortality disease regulated by multiple factors. Accurate cancer subtyping is crucial for formulating personalized treatment plans and improving patient survival rates. The underlying mechanisms that drive cancer progression can be comprehensively understood by analyzing multi-omics data. However, the high noise levels in omics data often pose challenges in capturing consistent representations and adequately integrating their information. This paper proposed a novel variational autoencoder-based deep learning model, named Deeply Integrating Latent Consistent Representations (DILCR). Firstly, multiple independent variational autoencoders and contrastive loss functions were designed to separate noise from omics data and capture latent consistent representations. Subsequently, an Attention Deep Integration Network was proposed to integrate consistent representations across different omics levels effectively. Additionally, we introduced the Improved Deep Embedded Clustering algorithm to make integrated variable clustering friendly. The effectiveness of DILCR was evaluated using 10 typical cancer datasets from The Cancer Genome Atlas and compared with 14 state-of-the-art integration methods. The results demonstrated that DILCR effectively captures the consistent representations in omics data and outperforms other integration methods in cancer subtyping. In the Kidney Renal Clear Cell Carcinoma case study, cancer subtypes were identified by DILCR with significant biological significance and interpretability.

A Switch-On Affinity-Based Iridium(III) Conjugate Probe for Imaging Mitochondrial Glutathione S-Transferase in Breast Cancer Cells

Glutathione S-transferase is heterogeneously expressed in breast cancer cells and is therefore emerging as a potential diagnostic biomarker for studying the heterogeneity of breast cancers. However, available fluorescent probes for GSTs depend heavily on GSTs-catalyzed glutathione (GSH) nucleophilic substitution reactions, making them susceptible to interference by the high concentration of nucleophilic species in the cellular environment. Moreover, the functions of subcellular GSTs are generally overlooked due to the lack of suitable luminescence probes. Herein, we report a highly selective affinity-based luminescence probe 1 for GST in breast cancer cells through tethering a GST inhibitor, ethacrynic acid, to an iridium(III) complex. Compared to activity-based probes which require the use of GSH, this probe could image GST-pi in the mitochondria by directly adducting to GST-pi (or potentially GST-pi/GS) in living cells. Probe 1 possesses desirable photophysical properties including a lifetime of 911 ns, a Stokes shift of 343 nm, and high photostability. The "turn on" luminescence mode of the probe enables highly selective detection of the GST with a limit of detection of 1.01 μM, while its long emission lifetime allows sensitive detection in organic dye-spiked autofluorescence samples by a time-resolved mode. The probe was further applied to specifically and quantitatively visualize MDA-MB-231 cells via specific binding to mitochondrial GST, and could differentiate breast cell lines based on their expression levels of GST. To the best of our knowledge, this probe is the first affinity-based iridium(III) imaging probe for the subcellular GST. Our work provides a valuable tool for unmasking the diverse roles of a subcellular GST in living systems, as well as for studying the heterogeneity of breast cancers.

Oncogenic miR-1825 promotes head and neck carcinogenesis via targeting FREM1

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignant cancer type worldwide. Although the therapeutic modalities currently used for patients with HNSCC improved in recent decades, HNSCC prognosis is still poor. Therefore, it is an urgent necessity to understand the pathogenesis of HNSCC, to develop novel and effective treatment strategies, and to characterize and identify the oncogenes that are responsible for an aggressive HNSCC phenotype. In this study, we aimed to better understand the roles of miR-1825 in the pathogenesis of HNSCC. We examined the impacts of miR-1825 deregulation on the cancer-associated phenotypes using in vitro tests evaluating cell viability, clonogenicity, cell migration, invasion, apoptosis, and stem cell characteristics. In addition, we investigated the effects of miR-1825 overexpression on the tumor formation capacity of head and neck cancer cells in vivo using nude mice. We searched for potential targets of miR-1825 using microarray analysis and luciferase assay. We found that miR-1825 expression is upregulated in head and neck cells and clinical tumor samples in comparison to corresponding controls, where it potentially acts as an oncogene. We, then, showed that ectopic miR-1825 overexpression promotes cellular phenotypes related to head and neck cancer progression in vitro and has a stimulating potential on cancer formation in vivo. We also identified FREM1 as a direct target of miR-1825 and demonstrated its reduced expression in HNSCC samples using immunohistochemistry analysis. Collectively, we suggest that the miR-1825/FREM1 axis serves as an important mediator of HNSCC development, where miR-1825 acts as an oncogene.

Appearance of tuft cells during prostate cancer progression

Tuft cells are chemosensory epithelial cells that increase in number following infection or injury to robustly activate the innate immune response to alleviate or promote disease. Recent studies of castration resistant prostate cancer and its subtype, neuroendocrine prostate cancer, revealed Pou2f3+ populations in mouse models. The transcription factor Pou2f3 is a master regulator of the tuft cell lineage. We show that tuft cells are upregulated early during prostate cancer development, and their numbers increase with progression. Cancer-associated tuft cells in the mouse prostate express DCLK1, COX1, COX2, while human tuft cells express COX1. Mouse and human tuft cells exhibit strong activation of signaling pathways including EGFR and SRC-family kinases. While DCLK1 is a mouse tuft cell marker, it is not present in human prostate tuft cells. Tuft cells that appear in mouse models of prostate cancer display genotype-specific tuft cell gene expression signatures. Using bioinformatic analysis tools and publicly available datasets, we characterized prostate tuft cells in aggressive disease and highlighted differences between tuft cell populations. Our findings indicate that tuft cells contribute to the prostate cancer microenvironment and may promote development of more advanced disease. Further research is needed to understand contributions of tuft cells to prostate cancer progression.

Establishment of a N1-methyladenosine-related risk signature for breast carcinoma by bioinformatics analysis and experimental validation

OBJECTIVES

Breast carcinoma (BRCA) has resulted in a huge health burden globally. N1-methyladenosine (m¹A) RNA methylation has been proven to play key roles in tumorigenesis. Nevertheless, the function of m¹A RNA methylation-related genes in BRCA is indistinct.

METHODS

The RNA sequencing (RNA-seq), copy-number variation (CNV), single-nucleotide variant (SNV), and clinical data of BRCA were acquired via The Cancer Genome Atlas (TCGA) database. In addition, the GSE20685 dataset, the external validation set, was acquired from the Gene Expression Omnibus (GEO) database. 10 m¹A RNA methylation regulators were obtained from the previous literature, and further analyzed through differential expression analysis by rank-sum test, mutation by SNV data, and mutual correlation by Pearson Correlation Analysis. Furthermore, the differentially expressed m¹A-related genes were selected through overlapping m¹A-related module genes obtained by weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) in BRCA and DEGs between high- and low- m¹A score subgroups. The m¹A-related model genes in the risk signature were derived by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. In addition, a nomogram was built through univariate and multivariate Cox analyses. After that, the immune infiltration between the high- and low-risk groups was investigated through ESTIMATE and CIBERSORT. Finally, the expression trends of model genes in clinical BRCA samples were further confirmed by quantitative real-time PCR (RT‒qPCR).

RESULTS

Eighty-five differentially expressed m¹A-related genes were obtained. Among them, six genes were selected as prognostic biomarkers to build the risk model. The validation results of the risk model showed that its prediction was reliable. In addition, Cox independent prognosis analysis revealed that age, risk score, and stage were independent prognostic factors for BRCA. Moreover, 13 types of immune cells were different between the high- and low-risk groups and the immune checkpoint molecules TIGIT, IDO1, LAG3, ICOS, PDCD1LG2, PDCD1, CD27, and CD274 were significantly different between the two risk groups. Ultimately, RT-qPCR results confirmed that the model genes MEOX1, COL17A1, FREM1, TNN, and SLIT3 were significantly up-regulated in BRCA tissues versus normal tissues.

CONCLUSIONS

An m¹A RNA methylation regulator-related prognostic model was constructed, and a nomogram based on the prognostic model was constructed to provide a theoretical reference for individual counseling and clinical preventive intervention in BRCA.

Comprehensive analysis of FRAS1/FREM family as potential biomarkers and therapeutic targets in renal clear cell carcinoma

Background: FRAS1 (Fraser syndrome protein 1), together with FREM1 (the Fras1-related extracellular matrix proteins 1) and FREM2, belonging to the FRAS1/FREM extracellular matrix protein family, are considered to play essential roles in renal organogenesis and cancer progression. However, their roles in kidney renal clear cell carcinoma (KIRC) remain to be elucidated. Methods: FRAS1/FREM RNA expression analysis was performed using TCGA/GTEx databases, and valided using GEO databases and real-time PCR. Protein expression was peformed using CPTAC databases. Herein, we employed an array of bioinformatics methods and online databases to explore the potential oncogenic roles of FRAS1/FREM in KIRC. Results: We found that FRAS1, FREM1 and FREM2 genes and proteins expression levels were significantly decreased in KIRC tissues than in normal tissues. Decreased FRAS1/FREM expression levels were significantly associated with advanced clinicopathological parameters (pathological stage, grade and tumor metastasis status). Notably, the patients with decreased FRAS1/FREM2 expression showed a high propensity for metastasis and poor prognosis. FRAS1/FREM were correlated with various immune infiltrating cells, especially CD4+ T cells and its corresponding subsets (Th1, Th2, Tfh and Tregs). FRAS1 and FREM2 had association with DNA methylation and their single CpG methylation levels were associated with prognosis. Moreover, FRAS1/FREM might exert antitumor effects by functioning in key oncogenic signalling pathways and metabolic pathways. Drug sensitivity analysis indicated that high FRAS1 and FREM2 expression can be a reliable predictor of targeted therapeutic drug response, highlighting the potential as anticancer drug targets. Conclusion: Together, our results indicated that FRAS1/FREM family members could be potential therapeutic targets and valuable prognostic biomarkers of KIRC.

A newly defined basement membrane-related gene signature for the prognosis of clear-cell renal cell carcinoma

Background: Basement membranes (BMs) are associated with cell polarity, differentiation, migration, and survival. Previous studies have shown that BMs play a key role in the progression of cancer, and thus could serve as potential targets for inhibiting the development of cancer. However, the association between basement membrane-related genes (BMRGs) and clear cell renal cell carcinoma (ccRCC) remains unclear. To address that gap, we constructed a novel risk signature utilizing BMRGs to explore the relationship between ccRCC and BMs.

Methods: We gathered transcriptome and clinical data from The Cancer Genome Atlas (TCGA) and randomly separated the data into training and test sets to look for new potential biomarkers and create a predictive signature of BMRGs for ccRCC. We applied univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to establish the model. The risk signature was further verified and evaluated through principal component analysis (PCA), the Kaplan-Meier technique, and time-dependent receiver operating characteristics (ROC). A nomogram was constructed to predict the overall survival (OS). The possible biological pathways were investigated through functional enrichment analysis. In this study, we also determined tumor mutation burden (TMB) and performed immunological analysis and immunotherapeutic drug analysis between the high- and low-risk groups.

Results: We identified 33 differentially expressed genes and constructed a risk model of eight BMRGs, including COL4A4, FREM1, CSPG4, COL4A5, ITGB6, ADAMTS14, MMP17, and THBS4. The PCA analysis showed that the signature could distinguish the high- and low-risk groups well. The K-M and ROC analysis demonstrated that the model could predict the prognosis well from the areas under the curves (AUCs), which was 0.731. Moreover, the nomogram showed good predictability. Univariate and multivariate Cox regression analysis validated that the model results supported the hypothesis that BMRGs were independent risk factors for ccRCC. Furthermore, immune cell infiltration, immunological checkpoints, TMB, and the half-inhibitory concentration varied considerably between high- and low-risk groups.

Conclusion: Employing eight BMRGs to construct a risk model as a prognostic indicator of ccRCC could provide us with a potential progression trajectory as well as predictions of therapeutic response.

A novel pyroptosis-related indicator of immune infiltration features and prognosis in breast cancer

Breast cancer is the most common malignancy in women, and there is evidence for the dual role of cell pyroptosis in tumor development. However, little is known about the relationship between cell pyroptosis and breast cancer and its prognostic value. We aimed to construct a prognostic model using cell-pyroptosis-related genes to provide innovative insights into the prognosis and treatment of breast cancer. We screened candidate genes for pyroptosis using public databases and identified 10 cell pyroptosis signature genes with the random forest method. Finally, a nomogram for predicting 1-, 3-, and 5-year survival probabilities was constructed. The differences in immune cell distributions between survival periods were similar across the breast cancer datasets. The 10 identified key pyroptosis factors showed a significant correlation with Her2, tumor–node–metastasis (TNM) stage, and survival of breast cancer. The risk scores correlated positively with the infiltration features of naive B cells, CD8+ T cells, atpdelnd mast cells, while they correlated negatively with those of M0 macrophages and dendritic cells. In conclusion, our findings confirm that cell pyroptosis is closely associated with breast cancer. Importantly, the prognostic complex values generated from the 10 cell-pyroptosis-related genes based on various clinical features may provide an important basis for future studies on the prognosis of breast cancer.

Characterization of Butyrate-Resistant Colorectal Cancer Cell Lines and the Cytotoxicity of Anticancer Drugs against These Cells

Colorectal cancer (CRC) is the third most common cancer worldwide. The gut microbiota plays a critical role in homeostasis and carcinogenesis. Butyrate, a short-chain fatty acid produced by the gut microbiota, plays a role in intestinal homeostasis and acts as an anticancer agent by inhibiting growth and inducing apoptosis. However, microbiota studies have revealed an abnormally high abundance of butyrate-producing bacteria in patients with CRC and indicated that it leads to chemoresistance. We characterized butyrate resistance in HCT-116 and PMF-K014 CRC cells after treatment with a maximum butyrate concentration of 3.2 mM. The 50% inhibitory concentration of butyrate was increased in butyrate-resistant (BR) cells compared with that in parental (PT) cells. The mechanism of butyrate resistance was initially investigated by determining the expression of butyrate influx- and drug efflux-related genes. We found the increased expression of influx- and efflux-related genes in BR cells compared with that in PT cells. Proteomic data showed both identical and different proteins in PT and BR cells. Further analysis revealed the crossresistance of HCT-116 cells to metformin and oxaliplatin and that of PMF-K014 cells to 5-fluorouracil. Our findings suggest that the acquisition of butyrate resistance induces the development of chemoresistance in CRC cells, which may play an important role in CRC development, treatment, and metastasis.

Branching Copy-Number Evolution and Parallel Immune Profiles across the Regional Tumor Space of Resected Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal disease. The only option for curative treatment is resection of the tumor followed by standard adjuvant chemotherapy. Yet, early relapse due to chemoresistance is almost inevitable. Herein, we delineated the genetic intratumor heterogeneity in resected PDAC, with the aim to identify evolutionary patterns that may be associated with overall survival (OS) following treatment with curative intent. Potential relationships with the adjacent immune microenvironment were also examined. The genetic and immune landscapes of the regional tumor space were analyzed in nine patients with resected PDAC. Targeted deep sequencing and genome wide SNP array were followed by clonal deconvolution and phylogenetic analysis. A mathematical complexity score was developed to calculate the network extent of each phylogeny. Spatial variation in abundancy and tumor nest infiltration of immune cells was analyzed by double IHC staining. Copy-number heterogeneity was denoted as the major contributing factor to the branching architectures of the produced phylogenetic trees. Increased tree complexity was significantly inversely associated with OS, and larger regional maximum aberrations (higher treetops) were associated with increased PD-L1 expression on tumor cells. Contrastingly, an FREM1 gene amplification, found in one patient, coincided with a particularly vigorous immune response. Findings from this limited case series suggest that complex evolutionary patterns may be associated with a shorter survival in surgically treated patients with PDAC. Some hypothesis-generating associations with the surrounding immune microenvironment were also detected.

IMPLICATIONS

Evolutionary copy-number patterns may be associated with survival in patients with resected PDAC.

Circular RNA UBAP2 facilitates the cisplatin resistance of triple-negative breast cancer via microRNA-300/anti-silencing function 1B histone chaperone/PI3K/AKT/mTOR axis

Circular RNAs (CircRNAs) have attracted increasing attention in the diagnosis and treatment of human cancers. CircUBAP2 has been identified to promote the progression of triple-negative breast cancer (TNBC), but the function of circUBAP2 in the cisplatin (DDP) resistance of TNBC remains obscure. Our investigation showed that circUBAP2 was significantly upregulated in DDP-resistant TNBC and TNBC sensitivity to DDP could be enhanced by silencing of circUBAP2. Moreover, circUBAP2 was revealed to be a ceRNA for miR-300 to upregulate the expression of anti-silencing function 1B histone chaperone (ASF1B). The effect of circUBAP2/miR-300/ASF1B axis on DDP resistance of TNBC was evaluated by rescue experiments, which demonstrated that circUBAP2 inhibited TNBC sensitivity to DDP through miR-300/ASF1B axis. Furthermore, it was discovered that ASF1B activated PI3K/AKT/mTOR signaling to facilitate the DDP resistance of TNBC cells. In summary, this research revealed a novel regulatory mechanism that circUBAP2 functioned as ceRNA of miR-300 to upregulate ASF1B, which further triggered the PI3K/AKT/mTOR (PAM) signaling to enhance the DDP resistance of TNBC.

Bioinformatics Analyses Identify the Therapeutic Potential of ST8SIA6 for Colon Cancer

Sialylation of glycoproteins is modified by distinct sialyltransferases such as ST3Gal, ST6Gal, ST6GalNAc, or ST8SIA with α2,3-, α2,6-, or α2,8-linkages. Alteration of these sialyltransferases causing aberrant sialylation is associated with the progression of colon cancer. However, among the ST8- sialyltransferases, the role of ST8SIA6 in colon cancer remains poorly understood. In this study, we explored the involvement of ST8SIA6 in colon cancer using multiple gene databases. The relationship between ST8SIA6 expression and tumor stages/grades was investigated by UALCAN analysis, and Kaplan–Meier Plotter analysis was used to analyze the expression of ST8SIA6 on the survival outcome of colon cancer patients. Moreover, the biological functions of ST8SIA6 in colon cancer were explored using LinkedOmics and cancer cell metabolism gene DB. Finally, TIMER and TISMO analyses were used to delineate ST8SIA6 levels in tumor immunity and immunotherapy responses, respectively. ST8SIA6 downregulation was associated with an advanced stage and poorly differentiated grade; however, ST8SIA6 expression did not affect the survival outcomes in patients with colon cancer. Gene ontology analysis suggested that ST8SIA6 participates in cell surface adhesion, angiogenesis, and membrane vesicle trafficking. In addition, ST8SIA6 levels affected immunocyte infiltration and immunotherapy responses in colon cancer. Collectively, these results suggest that ST8SIA6 may serve as a novel therapeutic target towards personalized medicine for colon cancer.

Stress Reactivity, Susceptibility to Hypertension, and Differential Expression of Genes in Hypertensive Compared to Normotensive Patients

Although half of hypertensive patients have hypertensive parents, known hypertension-related human loci identified by genome-wide analysis explain only 3% of hypertension heredity. Therefore, mainstream transcriptome profiling of hypertensive subjects addresses differentially expressed genes (DEGs) specific to gender, age, and comorbidities in accordance with predictive preventive personalized participatory medicine treating patients according to their symptoms, individual lifestyle, and genetic background. Within this mainstream paradigm, here, we determined whether, among the known hypertension-related DEGs that we could find, there is any genome-wide hypertension theranostic molecular marker applicable to everyone, everywhere, anytime. Therefore, we sequenced the hippocampal transcriptome of tame and aggressive rats, corresponding to low and high stress reactivity, an increase of which raises hypertensive risk; we identified stress-reactivity-related rat DEGs and compared them with their known homologous hypertension-related animal DEGs. This yielded significant correlations between stress reactivity-related and hypertension-related fold changes (log2 values) of these DEG homologs. We found principal components, PC1 and PC2, corresponding to a half-difference and half-sum of these log2 values. Using the DEGs of hypertensive versus normotensive patients (as the control), we verified the correlations and principal components. This analysis highlighted downregulation of β-protocadherins and hemoglobin as whole-genome hypertension theranostic molecular markers associated with a wide vascular inner diameter and low blood viscosity, respectively.

TILRR (Toll-like Interleukin-1 Receptor Regulator), an Important Modulator of Inflammatory Responsive Genes, is Circulating in the Blood

Purpose

TILRR (Toll-like interleukin-1 receptor regulator), a variant of FREM1 (Fras-related extracellular matrix 1), is a modulator of many genes in NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) signaling and inflammatory responses. It enhanced the expression of multiple genes in the NF-κB signaling pathway and promoted the production of multiple pro-inflammatory cytokines/chemokines. TILRR is an extracellular matrix protein and expressed in cells and tissues, and has never been considered to exist in the blood. The study aimed to identify circulating TILRR protein in human plasma as a biomarker of systemic inflammation.

Methods and Results

We developed a multiplex bead array method (Bio-Plex) using 4 monoclonal antibodies targeting different protein domains of FREM1/TILRR to investigate whether TILRR can be detected in blood plasma. The results of the multiplex bead array method were validated by Western blot analysis of affinity-purified TILRR from patient plasma samples. We subsequently analyzed 640 plasma samples from women enrolled in the Pumwani Sex Worker cohort (PSWC) (Nairobi, Kenya). Our study showed that TILRR exists in all patient plasma samples, but its quantities vary greatly among the patients, ranging from 2.38 ng/mL to 5196.79 ng/mL. The plasma TILRR below 2.38 ng/mL can only be detected by affinity purification and Western blot analysis.

Conclusion

Our in-house developed multiplex bead array method can successfully quantify TILRR protein in plasma samples. Because TILRR is an important modulator of many inflammation-responsive genes, it may be an inflammation biomarker in blood and play a role in modulating systemic inflammation.

Algorithmically Deduced FREM2 Molecular Pathway Is a Potent Grade and Survival Biomarker of Human Gliomas

Gliomas are the most common malignant brain tumors with high mortality rates. Recently we showed that the FREM2 gene has a role in glioblastoma progression. Here we reconstructed the FREM2 molecular pathway using the human interactome model. We assessed the biomarker capacity of FREM2 expression and its pathway as the overall survival (OS) and progression-free survival (PFS) biomarkers. To this end, we used three literature and one experimental RNA sequencing datasets collectively covering 566 glioblastomas (GBM) and 1097 low-grade gliomas (LGG). The activation level of deduced FREM2 pathway showed strong biomarker characteristics and significantly outperformed the FREM2 expression level itself. For all relevant datasets, it could robustly discriminate GBM and LGG (p < 1.63 × 10-13, AUC > 0.74). High FREM2 pathway activation level was associated with poor OS in LGG (p < 0.001), and low PFS in LGG (p < 0.001) and GBM (p < 0.05). FREM2 pathway activation level was poor prognosis biomarker for OS (p < 0.05) and PFS (p < 0.05) in LGG with IDH mutation, for PFS in LGG with wild type IDH (p < 0.001) and mutant IDH with 1p/19q codeletion(p < 0.05), in GBM with unmethylated MGMT (p < 0.05), and in GBM with wild type IDH (p < 0.05). Thus, we conclude that the activation level of the FREM2 pathway is a potent new-generation diagnostic and prognostic biomarker for multiple molecular subtypes of GBM and LGG.

The Potential Role of FREM1 and Its Isoform TILRR in HIV-1 Acquisition through Mediating Inflammation

FREM1 (Fras-related extracellular matrix 1) and its splice variant TILRR (Toll-like interleukin-1 receptor regulator) have been identified as integral components of innate immune systems. The potential involvement of FREM1 in HIV-1 (human immunodeficiency virus 1) acquisition was suggested by a genome-wide SNP (single nucleotide polymorphism) analysis of HIV-1 resistant and susceptible sex workers enrolled in the Pumwani sex worker cohort (PSWC) in Nairobi, Kenya. The studies showed that the minor allele of a FREM1 SNP rs1552896 is highly enriched in the HIV-1 resistant female sex workers. Subsequent studies showed that FREM1 mRNA is highly expressed in tissues relevant to mucosal HIV-1 infection, including cervical epithelial tissues, and TILRR is a major modulator of many genes in the NF-κB signal transduction pathway. In this article, we review the role of FREM1 and TILRR in modulating inflammatory responses and inflammation, and how their influence on inflammatory responses of cervicovaginal tissue could enhance the risk of vaginal HIV-1 acquisition.

Silencing of cluster determinant 36 transmitted by gold nanoparticles inhibits the occurrence and progression of breast cancer by down-regulating the peroxisome proliferative activated receptor signaling pathway

Breast cancer is the most commonly diagnosed tumor in women worldwide. Although a range of therapeutic strategies have been developed in recent years, the outcome for patients is often poor. The purpose of this study was to explore the molecular mechanisms of the membrane glycoprotein CD36 in breast cancer. Cells from breast cancer cell lines were transfected with gold nanoparticles protected by liposomes, as gene vectors. Cell counting kit 8 assays were performed to determine cell variability, EdU straining assays were used to evaluate cell proliferation, and colony formation assays were performed to detect cell colony ability. The number of cells involved in migration and invasion was counted using Transwell assays. Lymphangiogenesis formation was assessed using lymphangiogenesis formation assay. Xenograft tumor mice were established, to analyze the effects of CD36. Quantitative real-time polymerase chain reaction (qRT-PCR), western blotting, and immunohistochemistry (IHC) were performed to estimate the expression of genes. Silencing of CD36 inhibited cell variability, proliferation, colony formation, lymphangiogenesis, and repressed cell migration and invasion in vitro. Overexpression of PPAR reversed the effects of the silencing of CD36, and the effects of PPAR upregulation were blocked by PPAR inhibitor. In vivo, tumor growth and lymphangiogenesis and PPAR activation were suppressed by the silencing of CD36. Silencing of CD36 also inhibited the variability, proliferation, colony formation, lymphangiogenesis, migration and invasion of breast cancer cells by suppressing PPAR signaling pathway activation. The CD36 gene was transfected with gold nanoparticles which improved the efficiency of gene transfection. The use of gold nanoparticles provides a new way to study the effects of genes on tumor cells.