B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer.

This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.

Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer.

Kinase inhibitors have limited success in cancer treatment because tumors circumvent their action. Using a quantitative proteomics approach, we assessed kinome activity in response to MEK inhibition in triple-negative breast cancer (TNBC) cells and genetically engineered mice (GEMMs). MEK inhibition caused acute ERK activity loss, resulting in rapid c-Myc degradation that induced expression and activation of several receptor tyrosine kinases (RTKs). RNAi knockdown of ERK or c-Myc mimicked RTK induction by MEK inhibitors, and prevention of proteasomal c-Myc degradation blocked kinome reprogramming. MEK inhibitor-induced RTK stimulation overcame MEK2 inhibition, but not MEK1 inhibition, reactivating ERK and producing drug resistance. The C3Tag GEMM for TNBC similarly induced RTKs in response to MEK inhibition. The inhibitor-induced RTK profile suggested a kinase inhibitor combination therapy that produced GEMM tumor apoptosis and regression where single agents were ineffective. This approach defines mechanisms of drug resistance, allowing rational design of combination therapies for cancer.

Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches.

BACKGROUND: High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource for reanalysis. Cost and tissue availability normally preclude processing samples across multiple technologies, making it challenging to directly evaluate performance and whether data from different platforms can be reliably compared or integrated. METHODS: This study describes our experiences of nine new and established mRNA profiling techniques including Lexogen QuantSeq, Qiagen QiaSeq, BioSpyder TempO-Seq, Ion AmpliSeq, Nanostring, Affymetrix Clariom S or U133A, Illumina BeadChip and RNA-seq of formalin-fixed paraffin embedded (FFPE) and fresh frozen (FF) sequential patient-matched breast tumour samples. RESULTS: The number of genes represented and reliability varied between the platforms, but overall all methods provided data which were largely comparable. Crucially we found that it is possible to integrate data for combined analyses across FFPE/FF and platforms using established batch correction methods as required to increase cohort sizes. However, some platforms appear to be better suited to FFPE samples, particularly archival material. CONCLUSIONS: Overall, we illustrate that technology selection is a balance between required resolution, sample quality, availability and cost.

Correction: Tumor Evolution in Two Patients with Basal-like Breast Cancer: A Retrospective Genomics Study of Multiple Metastases.

[This corrects the article DOI: 10.1371/journal.pmed.1002174.].

Tumor Evolution in Two Patients with Basal-like Breast Cancer: A Retrospective Genomics Study of Multiple Metastases.

BACKGROUND: Metastasis is the main cause of cancer patient deaths and remains a poorly characterized process. It is still unclear when in tumor progression the ability to metastasize arises and whether this ability is inherent to the primary tumor or is acquired well after primary tumor formation. Next-generation sequencing and analytical methods to define clonal heterogeneity provide a means for identifying genetic events and the temporal relationships between these events in the primary and metastatic tumors within an individual. METHODS AND FINDINGS: We performed DNA whole genome and mRNA sequencing on two primary tumors, each with either four or five distinct tissue site-specific metastases, from two individuals with triple-negative/basal-like breast cancers. As evidenced by their case histories, each patient had an aggressive disease course with abbreviated survival. In each patient, the overall gene expression signatures, DNA copy number patterns, and somatic mutation patterns were highly similar across each primary tumor and its associated metastases. Almost every mutation found in the primary was found in a metastasis (for the two patients, 52/54 and 75/75). Many of these mutations were found in every tumor (11/54 and 65/75, respectively). In addition, each metastasis had fewer metastatic-specific events and shared at least 50% of its somatic mutation repertoire with the primary tumor, and all samples from each patient grouped together by gene expression clustering analysis. TP53 was the only mutated gene in common between both patients and was present in every tumor in this study. Strikingly, each metastasis resulted from multiclonal seeding instead of from a single cell of origin, and few of the new mutations, present only in the metastases, were expressed in mRNAs. Because of the clinical differences between these two patients and the small sample size of our study, the generalizability of these findings will need to be further examined in larger cohorts of patients. CONCLUSIONS: Our findings suggest that multiclonal seeding may be common amongst basal-like breast cancers. In these two patients, mutations and DNA copy number changes in the primary tumors appear to have had a biologic impact on metastatic potential, whereas mutations arising in the metastases were much more likely to be passengers.

Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer.

A large number of DNA copy number alterations (CNAs) exist in human breast cancers, and thus characterizing the most frequent CNAs is key to advancing therapeutics because it is likely that these regions contain breast tumor 'drivers' (i.e., cancer causal genes). This study aims to characterize the genomic landscape of breast cancer CNAs and identify potential subtype-specific drivers using a large set of human breast tumors and genetically engineered mouse (GEM) mammary tumors. Using a novel method called SWITCHplus, we identified subtype-specific DNA CNAs occurring at a 15% or greater frequency, which excluded many well-known breast cancer-related drivers such as amplification of ERBB2, and deletions of TP53 and RB1. A comparison of CNAs between mouse and human breast tumors identified regions with shared subtype-specific CNAs. Additional criteria that included gene expression-to-copy number correlation, a DawnRank network analysis, and RNA interference functional studies highlighted candidate driver genes that fulfilled these multiple criteria. Numerous regions of shared CNAs were observed between human breast tumors and GEM mammary tumor models that shared similar gene expression features. Specifically, we identified chromosome 1q21-23 as a Basal-like subtype-enriched region with multiple potential driver genes including PI4KB, SHC1, and NCSTN. This step-wise computational approach based on a cross-species comparison is applicable to any tumor type for which sufficient human and model system DNA copy number data exist, and in this instance, highlights that a single region of amplification may in fact harbor multiple driver genes.

Silver-catalyzed C(sp2)-H functionalization/C-O cyclization reaction at room temperature.

Silver-catalyzed C(sp(2))-H functionalization/C-O cyclization has been developed. The scalable reaction proceeds at room temperature in an open flask. The present method exhibits good functional-group compatibility because of the mild reaction conditions. Using a AgNO3 catalyst and a (NH4)2S2O8 oxidant in CH2Cl2/H2O solvent, various lactones are obtained in good to excellent yields. A kinetic isotope effect (KIE) study indicates that the reaction may occur via a radical process.

Copper-catalysed ring-opening trifluoromethylation of cyclopropanols.

A copper-catalysed ring-opening trifluoromethylation reaction of cyclopropanols has been developed. Various ß-trifluoromethyl ketones are obtained in good to excellent yields under mild reaction conditions. The present method also exhibits good functional-group compatibility. The mechanism of this new ring-opening trifluoromethylation reaction was investigated by radical trapping reactions.

Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling.

BACKGROUND: RNA sequencing (RNA-Seq) is often used for transcriptome profiling as well as the identification of novel transcripts and alternative splicing events. Typically, RNA-Seq libraries are prepared from total RNA using poly(A) enrichment of the mRNA (mRNA-Seq) to remove ribosomal RNA (rRNA), however, this method fails to capture non-poly(A) transcripts or partially degraded mRNAs. Hence, a mRNA-Seq protocol will not be compatible for use with RNAs coming from Formalin-Fixed and Paraffin-Embedded (FFPE) samples. RESULTS: To address the desire to perform RNA-Seq on FFPE materials, we evaluated two different library preparation protocols that could be compatible for use with small RNA fragments. We obtained paired Fresh Frozen (FF) and FFPE RNAs from multiple tumors and subjected these to different gene expression profiling methods. We tested 11 human breast tumor samples using: (a) FF RNAs by microarray, mRNA-Seq, Ribo-Zero-Seq and DSN-Seq (Duplex-Specific Nuclease) and (b) FFPE RNAs by Ribo-Zero-Seq and DSN-Seq. We also performed these different RNA-Seq protocols using 10 TCGA tumors as a validation set.The data from paired RNA samples showed high concordance in transcript quantification across all protocols and between FF and FFPE RNAs. In both FF and FFPE, Ribo-Zero-Seq removed rRNA with comparable efficiency as mRNA-Seq, and it provided an equivalent or less biased coverage on gene 3' ends. Compared to mRNA-Seq where 69% of bases were mapped to the transcriptome, DSN-Seq and Ribo-Zero-Seq contained significantly fewer reads mapping to the transcriptome (20-30%); in these RNA-Seq protocols, many if not most reads mapped to intronic regions. Approximately 14 million reads in mRNA-Seq and 45-65 million reads in Ribo-Zero-Seq or DSN-Seq were required to achieve the same gene detection levels as a standard Agilent DNA microarray. CONCLUSIONS: Our results demonstrate that compared to mRNA-Seq and microarrays, Ribo-Zero-Seq provides equivalent rRNA removal efficiency, coverage uniformity, genome-based mapped reads, and consistently high quality quantification of transcripts. Moreover, Ribo-Zero-Seq and DSN-Seq have consistent transcript quantification using FFPE RNAs, suggesting that RNA-Seq can be used with FFPE-derived RNAs for gene expression profiling.

Exploring the protective effect and molecular mechanism of betulin in Alzheimer's disease based on network pharmacology, molecular docking and experimental validation.

Alzheimer's disease (AD) is a neurodegenerative disorder that impairs learning and memory, with high rates of mortality. Birch bark has been traditionally used in the treatment of various skin ailments. Betulin (BT) is a key compound of birch bark that exhibits diverse pharmacological benefits and therapeutic potential in AD. However, the therapeutic effects and molecular mechanisms of BT in AD remain unclear. The present study aimed to predict the potential therapeutic targets of BT in the treatment of AD, and to determine the specific underlying molecular mechanisms through network pharmacology analysis and experimental validation. PharmMapper was used to predict the target genes of BT, and four disease databases were searched to screen for AD targets. The intersection targets were identified using the jveen website. Drug­disease target protein­protein interaction networks and hub genes were obtained and visualized using the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape. The Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and AutoDock was used for molecular docking analysis of BT and hub genes. Subsequently, the network­predicted mechanisms of BT in AD were verified in vitro. A total of 495 BT and 1,386 AD targets were identified, and 120 were identified as potential targets of BT in the treatment of AD. The results of the molecular docking analysis revealed a strong binding affinity between BT and the hub genes. In addition, enrichment analyses of GO and KEGG pathways indicated that the neuroprotective effects of BT mainly involved the 'PI3K­Akt signaling pathway'. The results of in vitro experiments demonstrated that pretreatment with BT for 2 h may ameliorate formaldehyde (FA)­induced cytotoxicity and morphological changes in HT22 cells, and decrease FA­induced Tau hyperphosphorylation and reactive oxygen species levels. Furthermore, the PI3K/AKT signaling pathway was activated and the expression levels of downstream proteins, namely GSK3ß, Bcl­2 and Bax, were modified following pre­treatment with BT. Overall, the results of network pharmacology and in vitro analyses revealed that BT may reduce FA­induced AD­like pathology by modulating the PI3K/AKT signaling pathway, highlighting it as a potential multi­target drug for the treatment of AD.

Characterization of cell lines derived from breast cancers and normal mammary tissues for the study of the intrinsic molecular subtypes.

Five molecular subtypes (luminal A, luminal B, HER2-enriched, basal-like, and claudin-low) with clinical implications exist in breast cancer. Here, we evaluated the molecular and phenotypic relationships of (1) a large in vitro panel of human breast cancer cell lines (BCCLs), human mammary fibroblasts (HMFs), and human mammary epithelial cells (HMECs); (2) in vivo breast tumors; (3) normal breast cell subpopulations; (4) human embryonic stem cells (hESCs); and (5) bone marrow-derived mesenchymal stem cells (hMSC). First, by integrating genomic data of 337 breast tumor samples with 93 cell lines we were able to identify all the intrinsic tumor subtypes in the cell lines, except for luminal A. Secondly, we observed that the cell lines recapitulate the differentiation hierarchy detected in the normal mammary gland, with claudin-low BCCLs and HMFs cells showing a stromal phenotype, HMECs showing a mammary stem cell/bipotent progenitor phenotype, basal-like cells showing a luminal progenitor phenotype, and luminal B cell lines showing a mature luminal phenotype. Thirdly, we identified basal-like and highly migratory claudin-low subpopulations of cells within a subset of triple-negative BCCLs (SUM149PT, HCC1143, and HCC38). Interestingly, both subpopulations within SUM149PT were enriched for tumor-initiating cells, but the basal-like subpopulation grew tumors faster than the claudin-low subpopulation. Finally, claudin-low BCCLs resembled the phenotype of hMSCs, whereas hESCs cells showed an epithelial phenotype without basal or luminal differentiation. The results presented here help to improve our understanding of the wide range of breast cancer cell line models through the appropriate pairing of cell lines with relevant in vivo tumor and normal cell counterparts.

The Protective Effect of Mangiferin on Formaldehyde-Induced HT22 Cell Damage and Cognitive Impairment.

Formaldehyde (FA) has been found to induce major Alzheimer's disease (AD)-like features including cognitive impairment, Aß deposition, and Tau hyperphosphorylation, suggesting that it may play a significant role in the initiation and progression of AD. Therefore, elucidating the mechanism underlying FA-induced neurotoxicity is crucial for exploring more comprehensive approaches to delay or prevent the development of AD. Mangiferin (MGF) is a natural C-glucosyl-xanthone with promising neuroprotective effects, and is considered to have potential in the treatment of AD. The present study was designed to characterize the effects and mechanisms by which MGF protects against FA-induced neurotoxicity. The results in murine hippocampal cells (HT22) revealed that co-treatment with MGF significantly decreased FA-induced cytotoxicity and inhibited Tau hyperphosphorylation in a dose-dependent manner. It was further found that these protective effects were achieved by attenuating FA-induced endoplasmic reticulum stress (ERS), as indicated by the inhibition of the ERS markers, GRP78 and CHOP, and downstream Tau-associated kinases (GSK-3ß and CaMKII) expression. In addition, MGF markedly inhibited FA-induced oxidative damage, including Ca2+ overload, ROS generation, and mitochondrial dysfunction, all of which are associated with ERS. Further studies showed that the intragastric administration of 40 mg/kg/day MGF for 6 weeks significantly improved spatial learning ability and long-term memory in C57/BL6 mice with FA-induced cognitive impairment by reducing Tau hyperphosphorylation and the expression of GRP78, GSK-3ß, and CaMKII in the brains. Taken together, these findings provide the first evidence that MGF exerts a significant neuroprotective effect against FA-induced damage and ameliorates mice cognitive impairment, the possible underlying mechanisms of which are expected to provide a novel basis for the treatment of AD and diseases caused by FA pollution.

Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes.

PURPOSE: To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based "intrinsic" subtypes luminal A, luminal B, HER2-enriched, and basal-like. METHODS: A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. RESULTS: The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%. CONCLUSION: Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.

Genomic analysis identifies unique signatures predictive of brain, lung, and liver relapse.

The ability to predict metastatic potential could be of great clinical importance, however, it is uncertain if predicting metastasis to specific vital organs is feasible. As a first step in evaluating metastatic predictions, we analyzed multiple primary tumors and metastasis pairs and determined that >90% of 298 gene expression signatures were found to be similarly expressed between matched pairs of tumors and metastases; therefore, primary tumors may be a good predictor of metastatic propensity. Next, using a dataset of >1,000 human breast tumor gene expression microarrays we determined that HER2-enriched subtype tumors aggressively spread to the liver, while basal-like and claudin-low subtypes colonize the brain and lung. Correspondingly, brain and lung metastasis signatures, along with embryonic stem cell, tumor initiating cell, and hypoxia signatures, were also strongly expressed in the basal-like and claudin-low tumors. Interestingly, low "Differentiation Scores," or high expression of the aforementioned signatures, further predicted for brain and lung metastases. In total, these data identify that depending upon the organ of relapse, a combination of gene expression signatures most accurately predicts metastatic behavior.

Basal-like Breast cancer DNA copy number losses identify genes involved in genomic instability, response to therapy, and patient survival.

Breast cancer is a heterogeneous disease with known expression-defined tumor subtypes. DNA copy number studies have suggested that tumors within gene expression subtypes share similar DNA Copy number aberrations (CNA) and that CNA can be used to further sub-divide expression classes. To gain further insights into the etiologies of the intrinsic subtypes, we classified tumors according to gene expression subtype and next identified subtype-associated CNA using a novel method called SWITCHdna, using a training set of 180 tumors and a validation set of 359 tumors. Fisher's exact tests, Chi-square approximations, and Wilcoxon rank-sum tests were performed to evaluate differences in CNA by subtype. To assess the functional significance of loss of a specific chromosomal region, individual genes were knocked down by shRNA and drug sensitivity, and DNA repair foci assays performed. Most tumor subtypes exhibited specific CNA. The Basal-like subtype was the most distinct with common losses of the regions containing RB1, BRCA1, INPP4B, and the greatest overall genomic instability. One Basal-like subtype-associated CNA was loss of 5q11-35, which contains at least three genes important for BRCA1-dependent DNA repair (RAD17, RAD50, and RAP80); these genes were predominantly lost as a pair, or all three simultaneously. Loss of two or three of these genes was associated with significantly increased genomic instability and poor patient survival. RNAi knockdown of RAD17, or RAD17/RAD50, in immortalized human mammary epithelial cell lines caused increased sensitivity to a PARP inhibitor and carboplatin, and inhibited BRCA1 foci formation in response to DNA damage. These data suggest a possible genetic cause for genomic instability in Basal-like breast cancers and a biological rationale for the use of DNA repair inhibitor related therapeutics in this breast cancer subtype.

Assessment of Topoisomerase II α status in breast cancer by quantitative PCR, gene expression microarrays, immunohistochemistry, and fluorescence in situ hybridization.

Anthracyclines are frequently used for the treatment of breast cancer and topoisomerase II alpha (TOP2A) is considered to be the molecular target. Numerous studies have evaluated the predictive value of TOP2A using different methodological approaches and inconsistent results have been reported. Indeed, the correlation between techniques for the assessment of TOP2A status has not been well evaluated. In this study, we determined TOP2A status in 61 breast tumor samples by real-time PCR, DNA microarrays, immunohistochemistry (IHC), and fluorescence in situ hybridization (FISH), and then evaluated these results with clinical-pathological features and breast cancer intrinsic subtypes. First, we observed a statistical significant correlation of TOP2A gene expression between real-time PCR and microarrays (Pearson coefficient, 0.816; P < 0.001), and both predicted TOP2A IHC results fairly well (area under the curve > 0.74). In contrast, poor agreement between FISH and IHC data was observed (k: 0.134). Secondly, TOP2A expression was found significantly associated with cell proliferation, and with the highly proliferative Luminal B, Her2-enriched and Basal-like intrinsic subtypes. In conclusion, TOP2A expression in breast cancer was associated with high proliferation and aggressive tumor subtypes and appears to be independent of its amplification status. All of these features should be taken into consideration when assessing the predictive value of TOP2A for anthracycline-based chemotherapy.

MapSplice: accurate mapping of RNA-seq reads for splice junction discovery.

The accurate mapping of reads that span splice junctions is a critical component of all analytic techniques that work with RNA-seq data. We introduce a second generation splice detection algorithm, MapSplice, whose focus is high sensitivity and specificity in the detection of splices as well as CPU and memory efficiency. MapSplice can be applied to both short (<75 bp) and long reads (≥ 75 bp). MapSplice is not dependent on splice site features or intron length, consequently it can detect novel canonical as well as non-canonical splices. MapSplice leverages the quality and diversity of read alignments of a given splice to increase accuracy. We demonstrate that MapSplice achieves higher sensitivity and specificity than TopHat and SpliceMap on a set of simulated RNA-seq data. Experimental studies also support the accuracy of the algorithm. Splice junctions derived from eight breast cancer RNA-seq datasets recapitulated the extensiveness of alternative splicing on a global level as well as the differences between molecular subtypes of breast cancer. These combined results indicate that MapSplice is a highly accurate algorithm for the alignment of RNA-seq reads to splice junctions. Software download URL: http://www.netlab.uky.edu/p/bioinfo/MapSplice.

Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features.

Some breast cancers have been shown to contain a small fraction of cells characterized by CD44(+)/CD24(-/low) cell-surface antigen profile that have high tumor-initiating potential. In addition, breast cancer cells propagated in vitro as mammospheres (MSs) have also been shown to be enriched for cells capable of self-renewal. In this study, we have defined a gene expression signature common to both CD44(+)/CD24(-/low) and MS-forming cells. To examine its clinical significance, we determined whether tumor cells surviving after conventional treatments were enriched for cells bearing this CD44(+)/CD24(-/low)-MS signature. The CD44(+)/CD24(-/low)-MS signature was found mainly in human breast tumors of the recently identified "claudin-low" molecular subtype, which is characterized by expression of many epithelial-mesenchymal-transition (EMT)-associated genes. Both CD44(+)/CD24(-/low)-MS and claudin-low signatures were more pronounced in tumor tissue remaining after either endocrine therapy (letrozole) or chemotherapy (docetaxel), consistent with the selective survival of tumor-initiating cells posttreatment. We confirmed an increased expression of mesenchymal markers, including vimentin (VIM) in cytokeratin-positive epithelial cells metalloproteinase 2 (MMP2), in two separate sets of postletrozole vs. pretreatment specimens. Taken together, these data provide supporting evidence that the residual breast tumor cell populations surviving after conventional treatment may be enriched for subpopulations of cells with both tumor-initiating and mesenchymal features. Targeting proteins involved in EMT may provide a therapeutic strategy for eliminating surviving cells to prevent recurrence and improve long-term survival in breast cancer patients.

Identification of Differential Genes of DNA Methylation Associated With Alzheimer's Disease Based on Integrated Bioinformatics and Its Diagnostic Significance.

Background: Alzheimer's disease (AD) is a common neurodegenerative disease. The pathogenesis is complex and has not been clearly elucidated, and there is no effective treatment. Recent studies have demonstrated that DNA methylation is closely associated with the pathogenesis of AD, which sheds light on investigating potential biomarkers for the diagnosis of early AD and related possible therapeutic approaches. Methods: Alzheimer's disease patients samples and healthy controls samples were collected from two datasets in the GEO database. Using LIMMA software package in R language to find differentially expressed genes (DEGs). Afterward, DEGs have been subjected to enrichment analysis of GO and KEGG pathways. The PPI networks and Hub genes were created and visualized based on the STRING database and Cytoscape. ROC curves were further constructed to analyze the accuracy of these genes for AD diagnosis. Results: Analysis of the GSE109887 and GSE97760 datasets showed 477 significant DEGs. GO and KEGG enrichment analysis showed terms related to biological processes related to these genes. The top ten Hub genes were found on the basis of the PPI network using the CytoHubba plugin, and the AUC areas of these top ranked genes were all greater than 0.7, showing satisfactory diagnostic accuracy. Conclusion: The study identified the top 10 Hub genes associated with AD-related DNA methylation, of which RPSA, RPS23, and RPLP0 have high diagnostic accuracy and excellent AD biomarker potential.

The potential diagnostic accuracy of urine formaldehyde levels in Alzheimer's disease: A systematic review and meta-analysis.

Background: Formaldehyde (FA), a toxic aldehyde, has been shown to be associated with a variety of cognitive disorders, including Alzheimer's disease (AD). There is increasing evidence that FA levels are significantly increased in AD patients and may be involved in the pathological process of AD. The aim of this study was to assess the potential diagnostic value of urine FA levels in AD using meta-analysis techniques. Methods: Original reports of morning urine FA levels in AD patients and healthy controls (HCs) were included in the meta-analysis. Standardized mean differences (SMD) were calculated using a random-effects model, heterogeneity was explored using methodological, age, sex difference and sensitivity analyses, and receiver operating characteristic (ROC) curves were constructed to assess the diagnostic value of urine FA levels in AD. Results: A total of 12 studies were included, and the urine FA levels of 874 AD patients and 577 HCs were reviewed. Compared with those in HCs, the FA levels were significantly increased in AD patients. The heterogeneity of the results did not affect their robustness, and results of the area under the curve (AUC) suggested that urine FA levels had good potential diagnostic value. Conclusion: Urine FA levels are involved in AD disease progression and are likely to be useful as a potential biomarker for clinical auxiliary diagnosis. However, further studies are needed to validate the results of this study.