Plasma DNA Methylation-Based Biomarkers for MPNST Detection in Patients With Neurofibromatosis Type 1

Malignant peripheral nerve sheath tumor (MPNST) development is characterized by an altered DNA methylation landscape, which presents a promising area for developing MPNST-specific biomarkers for screening patients with NF1. Genome-wide DNA methylation profiling of a cohort of 13 patients with MPNST (29 samples of tumor and adjacent neurofibroma tissues) and of NF1-MPNST cell lines was performed to identify and validate candidate MPNST-specific CpG sites (CpGs). A logistic regression prediction model was constructed to select MPNST-specific CpGs distinct from adjacent neurofibromas and normal tissues. To test if hypermethylation at selected CpGs can also be detected in plasma from patients with MPNST, cfMBD-seq was applied to profile the cfDNA methylome of blood from patients with MPNST and NF1. Based on stringent feature-selection criteria and predictive modeling, we identified 73 candidate MPNST-specific CpGs (67 with unique CpG island locations) that reliably discriminated MPNSTs from neurofibromas. Validation of five candidate biomarkers confirmed successful MPNST detection (sensitivity: > 88%, specificity: > 91%) in tissues. In plasma samples, 63 of 67 selected genomic regions had greater than 1.2-fold higher methylation in patients with MPNST than those with NF1. Further, we identified 15 CpG islands that consistently separated plasma from patients with confirmed MPNST diagnosis from plasma of individuals with NF1 without a diagnosis of malignant transformation (FDR < 0.1). Our findings confirmed a unique hypermethylation pattern present during malignant transformation. This study highlights the potential to be investigated further as biomarkers in clinical settings for early MPNST detection in patients with NF1.

The multiple roles of interferon regulatory factor family in health and disease

Interferon Regulatory Factors (IRFs), a family of transcription factors, profoundly influence the immune system, impacting both physiological and pathological processes. This review explores the diverse functions of nine mammalian IRF members, each featuring conserved domains essential for interactions with other transcription factors and cofactors. These interactions allow IRFs to modulate a broad spectrum of physiological processes, encompassing host defense, immune response, and cell development. Conversely, their pivotal role in immune regulation implicates them in the pathophysiology of various diseases, such as infectious diseases, autoimmune disorders, metabolic diseases, and cancers. In this context, IRFs display a dichotomous nature, functioning as both tumor suppressors and promoters, contingent upon the specific disease milieu. Post-translational modifications of IRFs, including phosphorylation and ubiquitination, play a crucial role in modulating their function, stability, and activation. As prospective biomarkers and therapeutic targets, IRFs present promising opportunities for disease intervention. Further research is needed to elucidate the precise mechanisms governing IRF regulation, potentially pioneering innovative therapeutic strategies, particularly in cancer treatment, where the equilibrium of IRF activities is of paramount importance.

Potentially functional genetic variants in interferon regulatory factor family genes are associated with colorectal cancer survival

Interferon regulatory factor (IRF) family genes play a critical role in colorectal cancer (CRC) development and impact patient survival. This study evaluated the influence of functional single nucleotide polymorphisms (SNPs) in IRF genes on CRC survival, including functional predictions and experimental validations. Multivariate Cox regression analysis identified three linked SNPs as significant survival predictors, with the rs141112353 T/T genotype in the 3'UTR region of IRF6 significantly associated with decreased survival (HR = 1.60, P = 6E-04). Expression quantitative trait loci (eQTL) analysis indicated that the rs141112353 TA > T alteration reduced IRF6 expression. Dual luciferase assays showed lower activity for the T allele in the presence of hsa-miR-548ap-3p. Data from The Cancer Genome Atlas (TCGA) and other databases confirmed lower IRF6 levels in CRC tissues, correlating with worse survival and inversely with M2 macrophage infiltration. In vitro, IRF6 overexpression inhibited CRC cell proliferation and M2 macrophage polarization by downregulating MIF expression. These findings suggest that the IRF6 rs141112353 TA > T variant significantly affects CRC survival, potentially by enhancing miR-548-ap-3p binding affinity.

Hypertension in an ageing population: Diagnosis, mechanisms, collateral health risks, treatments, and clinical challenges

Ageing population is considerably increasing worldwide, which is considered to reflect an improved quality of life. However, longevity in the human lifespan has increased the burden of late-life illnesses including cancer, neurodegeneration, and cardiovascular dysfunction. Of these, hypertension is the most common condition with huge health risks, with an increased prevalence among the elderly. In this review, we outline the current guidelines for defining hypertension and examine the detailed mechanisms underlying the relationship between hypertension and ageing-related outcomes, including sodium sensitivity, arterial stiffness, endothelial dysfunction, isolated systolic hypertension, white coat effect, and orthostatic hypertension. As hypertension-related collateral health risk increases among the elderly, the available management strategies are necessary to overcome the clinical treatment challenges faced among elderly population. To improve longevity and reduce adverse health effects, potential approaches producing crucial information into new era of medicine should be considered in the prevention and treatment of hypertension among elderly population. This review provides an overview of mechanisms underlying hypertension and its related collateral health risk in elderly population, along with multiple approaches and management strategies to improve the clinical challenges among elderly population.

Development and validation of a combined hypoxia- and metabolism-related prognostic signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Hypoxia and metabolism are closely correlated with the progression of cancer. We aimed to construct a combined hypoxia- and metabolism-related genes (HMRGs) prognostic signature to predict survival and immunotherapy responses in patients with clear cell renal cell carcinoma (ccRCC).

Methods

The RNA-seq profiles and clinical data of ccRCC were acquired from the TCGA and the ArrayExpress (E-MTAB-1980) databases. Least absolute shrinkage and selection operator (LASSO) and univariate and multivariate Cox regression analyses were applied to establish a prognostic signature. The E-MTAB-1980 cohort was selected for validation. The effectiveness and reliability of the signature were further evaluated by Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) curves. Further analyses, including functional enrichment, ssGSEA algorithm, CIBERSORT algorithm, and expression of immune checkpoints, were explored to investigate immune status and immunotherapy responses.

Results

We constructed a prognostic eight-gene signature with IRF6, TEK, PLCB2, ABCB1, TGFA, COL4A5, PLOD2, and TUBB6. Patients were divided into high-risk and low-risk groups based on the medium-risk score. The K-M analysis revealed that patients in the high-risk group had an apparently poor prognosis compared to those in the low-risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p < 0.005). The area under ROC curve (AUC) of the prognostic signature was 0.8 at 1 year, 0.77 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.82 at 1 year, 0.74 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis confirmed the risk score as a separate prognostic factor in ccRCC patients (p < 0.001). The results of ssGSEA showed not only a high degree of immune cell infiltration but also high scores of immune-related functions in the high-risk group. The CIBERSORT analysis further confirmed that the abundance of immune cells was apparently different between the two risk groups. The risk score was significantly correlated with the expression of cytotoxic T lymphocyte-associated antigen-4 (CTLA4), lymphocyte-activation gene 3 (LAG3), and programmed cell death protein 1 (PD-1).

Conclusion

The HMRGs signature could be used to predict clinical prognosis, evaluate the efficacy of immunotherapy, and guide personalized immunotherapy in ccRCC patients.

KIF20A as a potential biomarker of renal and bladder cancers based on bioinformatics and experimental verification

BACKGROUND

Bladder cancer (BC) is a malignant tumor that occurs in the bladder wall and often appears in elderly individuals. Renal cancer (RC) arises from the renal tubular epithelium, but its molecular mechanism remains unclear.

METHODS

We downloaded RC datasets (GSE14762 and GSE53757) and a BC dataset (GSE121711) to screen differentially expressed genes (DEGs). We also performed weighted gene coexpression network analysis (WGCNA). We created a protein-protein interaction (PPI) network and performed functional enrichment analysis, such as gene set enrichment analysis (GSEA). Heatmaps were made for gene expression. Survival analysis and immunoinfiltration analysis were performed. Comparative toxicogenomics database (CTD) analysis was performed to find the relationship between disease and hub genes. Western blotting was performed to verify the role of KIF20A in apoptosis.

RESULTS

A total of 764 DEGs were identified. The GSEA showed that the DEGs were mainly enriched in organic acid metabolism, drug metabolism, mitochondria, and metabolism of cysteine and methionine. The PPI network in GSE121711 showed that KIF20A was a hub gene of renal clear cell carcinoma. Where the expression level of KIF20A was higher, the prognosis of patients was worse. CTD analysis showed that KIF20A was associated with inflammation, proliferation, and apoptosis. KIF20A expression in the RC group was upregulated, as shown by western blotting. The core proteins (including pRB Ser 780, CyclinA, E2F1, CCNE1, and CCNE2) in the pRB Ser 780/CyclinA signaling pathway were also upregulated in the RC group.

CONCLUSIONS

KIF20A might be a novel biomarker for researching renal and bladder cancers.

Identification of prognostic and therapeutic biomarkers in type 2 papillary renal cell carcinoma

BACKGROUND

Papillary renal cell carcinoma (PRCC) can be divided into type 1 (PRCC1) and type 2 (PRCC2) and PRCC2 share a more invasive phenotype and worse prognosis. This study aims to identify potential prognostic and therapeutic biomarkers in PRCC2.

METHODS

A cohort from The Cancer Genome Atlas and two datasets from Gene Expression Omnibus were examined. Common differentially expressed genes (DEGs) were screened and potential biomarkers were explored by using Kaplan-Meier method and cox regression analysis. Functional enrichment analysis was utilized to evaluate the potential biological functions. Tumor infiltrating immune cells were estimated by CIBERSORT algorithm. Ninety-two PRCC2 samples from Fudan University Shanghai Cancer Center were obtained, and immunostaining was performed to validate prognostic and therapeutic significance of the potential biomarker.

RESULTS

PRCC2 has worse overall survival and shares distinct molecular characteristics from PRCC1. There was significant higher expression level of Targeting protein for Xklp2 (TPX2) in PRCC2 compared with normal tissues. Higher expression level of TPX2 was significantly associated with worse overall survival in PRCC2 and kinesin family genes expression were found significantly elevated in high risk PRCC2. Abundance of tumor infiltrating M1 macrophage was significantly higher in PRCC2 and it was also associated with worse overall survival. In the FUSCC cohort, higher TPX2 expression was significantly correlated with worse overall and progression-free survival. Retrospective analysis indicated that mTOR inhibitor (everolimus) had greater efficacy in the high-risk group than in the low-risk group (overall response rate: 28.6% vs. 16.7%) and that everolimus had greater efficacy than sunitinib in the high-risk group (overall response rate: 28.6% vs. 20%).

CONCLUSIONS

TPX2 was a prognostic and therapeutic biomarker in PRCC2. Higher abundance of tumor infiltrating M1 macrophage was significantly associated with worse overall survival in PRCC2. mTOR inhibitors may have good efficacy in patients with high-risk PRCC2.

Expression, regulating mechanism and therapeutic target of KIF20A in multiple cancer

Kinesin family member 20A (KIF20A) is a member of the kinesin family. It transports chromosomes during mitosis, plays a key role in cell division. Recently, studies proved that KIF20A was highly expressed in cancer. High expression of KIF20A was correlated with poor overall survival (OS). In this review, we summarized all the cancer that highly expressed KIF20A, described the role of KIF20A in cancer. We also organized phase I and phase II clinical trials of KIF20A peptides vaccine. All results indicated that KIF20A was a promising therapeutic target for multiple cancer.

Promotion of BST2 expression by the transcription factor IRF6 affects the progression of endometriosis

Background

Endometriosis (EM) is a benign, multifactorial, immune-mediated inflammatory disease that is characterized by persistent activation of the NF-κB signaling pathway and some features of malignancies, such as proliferation and lymphangiogenesis. To date, the pathogenesis of EM is still unclear. In this study, we investigated whether BST2 plays a role in the development of EM.

Methods

Bioinformatic analysis was performed with data from public databases to identify potential candidate targets for drug treatment. Experiments were conducted at the cell, tissue, and mouse EM model levels to characterize the aberrant expression patterns, molecular mechanisms, biological behaviors of endometriosis as well as treatment outcomes.

Results

BST2 was significantly upregulated in ectopic endometrial tissues and cells compared with control samples. Functional studies indicated that BST2 promoted proliferation, migration, and lymphangiogenesis and inhibited apoptosis in vitro and in vivo. The transcription factor (TF) IRF6 induced high BST2 expression by directly binding the BST2 promoter. The underlying mechanism by which BST2 functions in EM was closely related to the canonical NF-κB signaling pathway. New lymphatic vessels may serve as a channel for the infiltration of immune cells into the endometriotic microenvironment; these immune cells further produce the proinflammatory cytokine IL-1β, which in turn further activates the NF-κB pathway to promote lymphangiogenesis in endometriosis.

Conclusion

Taken together, our findings provide novel insight into the mechanism by which BST2 participates in a feedback loop with the NF-κB signaling pathway and reveal a novel biomarker and potential therapeutic target for endometriosis.

Construction of an interferon regulatory factors-related risk model for predicting prognosis, immune microenvironment and immunotherapy in clear cell renal cell carcinoma

Background

Interferon regulatory factors (IRFs) played complex and essential roles in progression, prognosis, and immune microenvironment in clear cell renal cell carcinoma (ccRCC). The purpose of this study was to construct a novel IRFs-related risk model to predict prognosis, tumor microenvironment (TME) and immunotherapy response in ccRCC.

Methods

Multi-omics analysis of IRFs in ccRCC was performed based on bulk RNA sequencing and single cell RNA sequencing data. According to the expression profiles of IRFs, the ccRCC samples were clustered by non-negative matrix factorization (NMF) algorithm. Then, least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were applied to construct a risk model to predict prognosis, immune cells infiltration, immunotherapy response and targeted drug sensitivity in ccRCC. Furthermore, a nomogram comprising the risk model and clinical characteristics was established.

Results

Two molecular subtypes with different prognosis, clinical characteristics and infiltration levels of immune cells were identified in ccRCC. The IRFs-related risk model was developed as an independent prognostic indicator in the TCGA-KIRC cohort and validated in the E-MTAB-1980 cohort. The overall survival of patients in the low-risk group was better than that in the high-risk group. The risk model was superior to clinical characteristics and the ClearCode34 model in predicting the prognosis. In addition, a nomogram was developed to improve the clinical utility of the risk model. Moreover, the high-risk group had higher infiltration levels of CD8⁺ T cell, macrophages, T follicular helper cells and T helper (Th1) cells and activity score of type I IFN response but lower infiltration levels of mast cells and activity score of type II IFN response. Cancer immunity cycle showed that the immune activity score of most steps was remarkably higher in the high-risk group. TIDE scores indicated that patients in the low-risk group were more likely responsive to immunotherapy. Patients in different risk groups showed diverse drug sensitivity to axitinib, sorafenib, gefitinib, erlotinib, dasatinib and rapamycin.

Conclusions

In brief, a robust and effective risk model was developed to predict prognosis, TME characteristics and responses to immunotherapy and targeted drugs in ccRCC, which might provide new insights into personalized and precise therapeutic strategies.

Systematic analysis of expression profiles and prognostic significance for MMDS-related iron-sulfur proteins in renal clear cell carcinoma

Mitochondrial metabolism disorders play an important role in the occurrence and development of tumors, and iron-sulfur protein is an important molecule for maintaining the normal function of mitochondria. However, the relationship between the expression, prognostic value, and immune infiltration of MMDS-related iron-sulfur protein genes in kidney renal clear cell carcinoma (KIRC) remains unclear. Based on online databases bioinformatics analysis was performed to evaluate the expression differences, survival impacts, immune infiltration, and prognostic significance of multiple mitochondrial dysfunction syndrome (MMDS)-related iron-sulfur protein genes in KIRC patients. For example, the protein-protein interaction (PPI) network was constructed using STRING and GEPIA database; Survival impacts were constructed by TCGA database; Immune infiltration was analyzed using TIMER database. There were significant differences in the mRNA expression levels of ISCA1, ISCA2, C1ORF69 and NFU1 in KIRC among different tumor grades and individual cancer stages. Furthermore, KIRC with high transcription levels of ISCA1, ISCA2, C1ORF69 and NFU1 (p < 0.01) was significantly associated with long overall survival (OS) and disease-free survival (DFS). In addition, overexpression of four genes, NFU1, ISCA1, ISCA2, and C1ORF69 in KIRC indicated a better prognosis. Further studies showed that immune cells had a significantly positive correlation with iron-sulfur protein family genes, including CD8+ T cells, CD4+ T cells and B cells. More importantly, the results of immunohistochemistry showed that the expression of NFU1, ISCA1, ISCA2 and C1ORF69 in normal tissues was higher than that in renal clear cell carcinoma tissues. In this study, we systematically analyzed the expression and prognostic value of iron-sulfur protein family genes in KIRC. More importantly, NFU1, ISCA1, ISCA2, and C1ORF69 are expected to become potential therapeutic targets for KIRC, as well as potential prognostic markers for improving the survival rate and prognostic accuracy of KIRC.

The convergence of tumor suppressors on the type I interferon pathway in clear cell renal cell carcinoma and its therapeutic implications

In clear cell renal cell carcinoma (ccRCC), the von Hippel-Lindau tumor suppressor gene/hypoxia inducible factor (VHL/HIF) axis lays the groundwork for tumorigenesis and is the target of many therapeutic agents. HIF activation alone, however, is largely insufficient for kidney tumor development, and secondary mutations in PBRM1, BAP1, SETD2, KDM5C, or other tumor suppressor genes are strong enablers of tumorigenesis. Interestingly, it has been discovered that VHL loss and subsequent HIF activation results in upregulation of a negative feedback loop mediated by ISGF3, a transcription factor activated by type I interferon (IFN). Secondary mutations in the aforementioned tumor suppressor genes all partially disable this negative feedback loop to facilitate tumor growth. The convergence of several cancer genes on this pathway suggests that it plays an important role in ccRCC development and maintenance. Tumors with secondary mutations that dampen the negative feedback loop may be exquisitely sensitive to its reactivation, and pharmacological activation of ISGF3 either alone or in combination with other therapies could be an effective method to treat patients with ccRCC. In this review, we examine the relevance of the type I IFN pathway to ccRCC, synthesize our current knowledge of the ccRCC tumor suppressors in its regulation, and explore how this may impact the future treatment of patients with ccRCC.

LncRNA ENSMUST_147219 mediates the progression of ischemic acute kidney injury by targeting the miR-221-5p/IRF6 axis

Although previous studies have revealed that long noncoding RNAs (lncRNAs) regulate the progression of ischemic acute kidney injury (AKI), the exact role and mechanism of lncRNA ENSMUST_147219 in ischemic AKI are not clear. In the present study, lncRNA ENSMUST_147219 was induced by ischemic injury in vitro and in vivo. Functionally, lncRNA ENSMUST_147219 mediated apoptosis in mouse proximal tubule‐derived cell line (BUMPT). Mechanistically, lncRNA ENSMUST_147219 sponged the microRNA (miR)-221-5p to upregulate the expression of interferon regulatory factor 6 (IRF6) to drive apoptosis. Finally, knockdown of lncRNA ENSMUST_147219 markedly attenuated the ischemic AKI by targeting the miR-221-5p/IRF6 axis. Collectively, our data demonstrated that lncRNA ENSMUST_147219 promoted the development of ischemic AKI by regulating the miR-221-5p/IRF6 pathway, which could be considered a new therapeutic target for ischemic AKI.

Decreased interferon regulatory factor 6 expression due to DNA hypermethylation predicts an unfavorable prognosis in clear cell renal cell carcinoma

Background: Emerging evidences have indicated that IRF6, as a member of the Interferon regulatory factors (IRFs) family, plays important roles in a variety of tumors. However, the expression status of IRF6 and its prognostic value in clear cell renal cell carcinoma (ccRCC) remain unclear. Methods: In this study, we used TCGA-KIRC, GEO and TIP databases and immunohistochemistry staining to determine the expression profile, clinico-pathological features and prognostic value of IRF6 in ccRCC. MSP and demethylation analysis were utilized to verify the regulatory effect of DNA methylation on IRF6 expression. Results: Our results found that IRF6 expression was downregulated in ccRCC tissues and cell lines, and decreased IRF6 expression was associated with worse clinicopathological features and poorer prognosis. Besides, the results of multivariate Cox regression analysis also confirmed that decreased IRF6 expression was an independently risk factor predictor of shorter Overall Survival (OS) (HR: 0.8524, 95%CI: 0.7614-0.9543, P=0.0056) and Disease Free Survival (DFS) (HR: 0.7024, 95%CI: 0.6087-0.8104, P<0.0001) in ccRCC patients. Moreover, the results of MSP and demethylation analysis validated that decreased IRF6 expression was caused by DNA hypermethylation. Furthermore, our results showed that IRF6 expression was associated with the infiltration levels of multiple immune cells in ccRCC. Conclusions: These findings demonstrated that IRF6 expression was significantly reduced in ccRCC and DNA hypermethylation played an important role in decreased IRF6 expression. In addition, the decrease of IRF6 was related to the unfavorable prognosis of ccRCC patients and the alterations of tumor immune cells infiltration.

Improving MRI-based analysis of brain structural changes in patients with hypertension via a privileged information learning algorithm

Hypertension can lead to changes in the brain structure and function, and different blood pressure levels (2017ACC/AHA) have different effects on brain structure. It is important to analyze these changes by machine learning methods, and various characteristics can provide rich information for the analysis of these changes. However, multiple feature extraction involves complex data processing. How to make a single feature achieve the same diagnosis effect as multiple features do is worth of study. Kernel ridge regression (KRR) is a kind of machine learning method, which shows faster learning speed and generalization ability in classification tasks. In order to knowledge transfer, we use privileged information (PI) to transfer information of multiple types of feature to single feature. This allows only one feature type to be used during the test stage. In the process of feature fusion, we need to consider all the samples' attribution making the classifier better. In this work, we propose a multi-kernel KRR+ framework based on self-paced learning to analyze the changes of the brain structure in patients with different blood pressure levels. Specifically, one kind of a feature is taken as main feature, and other features are input into the multi-kernel KRR as PI. These two inputs are fed into the final KRR classifier together. In addition, a self-paced learning method is introduced into sample selecting to avoid training the classifier using samples with a large loss value firstly, which improves the generalization performance of the classifier. Experimental results show that the proposed method can make full use of the information of various features and achieve better classification performance. This shows self-paced learning based KRR can help analyze brain structure of patients with different blood pressure levels. The discriminative features may help clinicians to make judgments of hypertension degrees on brain MRI images.