Diagnostic Biomarkers Research Articles

Relationship of Signaling Pathways between RKIP Expression and the Inhibition of EMT-Inducing Transcription Factors SNAIL1/2, TWIST1/2 and ZEB1/2

Untreated primary carcinomas often lead to progression, invasion and metastasis, a process that involves the epithelial-to-mesenchymal transition (EMT). Several transcription factors (TFs) mediate the development of EMT, including SNAIL1/SNAIL2, TWIST1/TWIST2 and ZEB1/ZEB2, which are overexpressed in various carcinomas along with the under expression of the metastasis suppressor Raf Kinase Inhibitor Protein (RKIP). Overexpression of RKIP inhibits EMT and the above associated TFs. We, therefore, hypothesized that there are inhibitory cross-talk signaling pathways between RKIP and these TFs. Accordingly, we analyzed the various properties and biomarkers associated with the epithelial and mesenchymal tissues and the various molecular signaling pathways that trigger the EMT phenotype such as the TGF-β, the RTK and the Wnt pathways. We also presented the various functions and the transcriptional, post-transcriptional and epigenetic regulations for the expression of each of the EMT TFs. Likewise, we describe the transcriptional, post-transcriptional and epigenetic regulations of RKIP expression. Various signaling pathways mediated by RKIP, including the Raf/MEK/ERK pathway, inhibit the TFs associated with EMT and the stabilization of epithelial E-Cadherin expression. The inverse relationship between RKIP and the TF expressions and the cross-talks were further analyzed by bioinformatic analysis. High mRNA levels of RKIP correlated negatively with those of SNAIL1, SNAIL2, TWIST1, TWIST2, ZEB1, and ZEB2 in several but not all carcinomas. However, in these carcinomas, high levels of RKIP were associated with good prognosis, whereas high levels of the above transcription factors were associated with poor prognosis. Based on the inverse relationship between RKIP and EMT TFs, it is postulated that the expression level of RKIP in various carcinomas is clinically relevant as both a prognostic and diagnostic biomarker. In addition, targeting RKIP induction by agonists, gene therapy and immunotherapy will result not only in the inhibition of EMT and metastases in carcinomas, but also in the inhibition of tumor growth and reversal of resistance to various therapeutic strategies. However, such targeting strategies must be better investigated as a result of tumor heterogeneities and inherent resistance and should be better adapted as personalized medicine.

The GFAP proteoform puzzle: How to advance GFAP as a fluid biomarker in neurological diseases.

Glial fibrillary acidic protein (GFAP) is a well-established biomarker of reactive astrogliosis in the central nervous system because of its elevated levels following brain injury and various neurological disorders. The advent of ultra-sensitive methods for measuring low-abundant proteins has significantly enhanced our understanding of GFAP levels in the serum or plasma of patients with diverse neurological diseases. Clinical studies have demonstrated that GFAP holds promise both as a diagnostic and prognostic biomarker, including but not limited to individuals with Alzheimer's disease. GFAP exhibits diverse forms and structures, herein referred to as its proteoform complexity, encompassing conformational dynamics, isoforms and post-translational modifications (PTMs). In this review, we explore how the proteoform complexity of GFAP influences its detection, which may affect the differential diagnostic performance of GFAP in different biological fluids and can provide valuable insights into underlying biological processes. Additionally, proteoforms are often disease-specific, and our review provides suggestions and highlights areas to focus on for the development of new assays for measuring GFAP, including isoforms, PTMs, discharge mechanisms, breakdown products, higher-order species and interacting partners. By addressing the knowledge gaps highlighted in this review, we aim to support the clinical translation and interpretation of GFAP in both CSF and blood and the development of reliable, reproducible and specific prognostic and diagnostic tests. To enhance disease pathology comprehension and optimise GFAP as a biomarker, a thorough understanding of detected proteoforms in biofluids is essential.

Multiomics Profiling Distinguishes Sebaceous Carcinoma from Benign Sebaceous Neoplasms and Provides Insight into the Genetic Evolution of Sebaceous Carcinogenesis.

Sebaceous carcinoma is the third most common nonkeratinocyte skin cancer in the United States with 1,000 cases per year. The clinicopathologic features of sebaceous carcinoma and benign sebaceous neoplasms (adenomas, sebaceomas) can overlap, highlighting the need for molecular biomarkers to improve classification. This study describes the genomic and transcriptomic landscape of sebaceous neoplasms in order to understand tumor etiology and biomarkers relevant for diagnosis and treatment. We performed whole-genome sequencing (WGS) and whole-transcriptome sequencing (WTS) of sebaceous neoplasms from six academic and two federal healthcare facilities in the United States diagnosed between January 1, 1999, and December 31, 2021. We evaluated 98 sebaceous neoplasms: 64 tumors (32 adenomas, 2 sebaceomas, 5 atypical sebaceous neoplasms, 25 carcinomas) had sufficient material for WGS, 96 tumors (42 adenomas, 11 sebaceomas, 8 atypical sebaceous neoplasms, 35 carcinomas) had sufficient material for WTS, and 62 tumors (31 adenomas, 2 sebaceomas, 5 atypical sebaceous neoplasms, 24 carcinomas) had sufficient material for combined WGS and WTS. Overall, we found decreased cholesterol biosynthesis and increased TP53 mutations, copy number gains (chromosome 6, 8q, and/or 18), and tumor mutation burden-high (>10 mutations/MB) in carcinomas compared to adenomas. Although diminished compared to adenomas, most carcinomas still had higher cholesterol biosynthesis than nonmalignant skin. Multiomics profiling also supported a precancerous model of tumor evolution with sebaceomas and atypical sebaceous neoplasms being likely intermediate lesions. The study findings highlight key diagnostic biomarkers for sebaceous carcinoma and suggest that immunotherapy and modulation of cholesterol biosynthesis could be effective treatment strategies.

Intratumoral and fecal microbiota reveals microbial markers associated with gastric carcinogenesis

BackgroundThe relationship between dysbiosis of the gastrointestinal microbiota and gastric cancer (GC) has been extensively studied. However, microbiota alterations in GC patients vary widely across studies, and reproducible diagnostic biomarkers for early GC are still lacking in multiple populations. Thus, this study aimed to characterize the gastrointestinal microbial communities involved in gastric carcinogenesis through a meta-analysis of multiple published and open datasets.MethodsWe analyzed 16S rRNA sequencing data from 1,642 gastric biopsy samples and 394 stool samples across 11 independent studies. VSEARCH, QIIME and R packages such as vegan, phyloseq, cooccur, and random forest were used for data processing and analysis. PICRUSt software was employed to predict functions.ResultsThe α-diversity results indicated significant differences in the intratumoral microbiota of cancer patients compared to non-cancer patients, while no significant differences were observed in the fecal microbiota. Network analysis showed that the positive correlation with GC-enriched bacteria increased, and the positive correlation with GC-depleted bacteria decreased compared to healthy individuals. Functional analyses indicated that pathways related to carbohydrate metabolism were significantly enriched in GC, while biosynthesis of unsaturated fatty acids was diminished. Additionally, we investigated non-Helicobacter pylori (HP) commensals, which are crucial in both HP-negative and HP-positive GC. Random forest models, constructed using specific taxa associated with GC identified from the LEfSe analysis, revealed that the combination of Lactobacillus and Streptococcus included alone could effectively discriminate between GC patients and healthy individuals in fecal samples (area under the curve (AUC) = 0.7949). This finding was also validated in an independent cohort (AUC = 0.7712).ConclusionsThis study examined the intratumoral and fecal microbiota of GC patients from a dual microecological perspective and identified Lactobacillus, Streptococcus, Roseburia, Faecalibacterium and Phascolarctobacterium as intratumoral and intestinal-specific co-differential bacteria. Furthermore, it confirmed the validity of the combination of Lactobacillus and Streptococcus as GC-specific microbial markers across multiple populations, which may aid in the early non-invasive diagnosis of GC.

Polymeric immunoglobulin receptor promotes Th2 immune response in the liver by increasing cholangiocytes derived IL-33: a diagnostic and therapeutic biomarker of biliary atresia

Biliary atresia (BA) is a devastating neonatal cholangiopathy with an unclear pathogenesis, and prompt diagnosis of BA is currently challenging. Proteomic and immunoassay analyses were performed with serum samples from 250 patients to find potential BA biomarkers. The expression features of polymeric immunoglobulin receptor (PIGR) were investigated using human biopsy samples, three different experimental mouse models, and cultured human biliary epithelial cells (BECs). Chemically modified small interfering RNA and adenovirus expression vector were applied for invivo silencing and overexpressing PIGR in a rotavirus-induced BA mouse model. Luminex-based multiplex cytokine assays and RNA sequencing were used to explore the molecular mechanism of PIGR involvement in the BA pathogenesis. Serum levels of PIGR, poliovirus receptor (PVR), and aldolase B (ALDOB) were increased in BA patients and accurately distinguished BA from infantile hepatitis syndrome (IHS). Combined PIGR and PVR analysis distinguished BA from IHS with an area under the receiver operating characteristic curve of 0.968 and an accuracy of 0.935. PIGR expression was upregulated in the biliary epithelium of BA patients; Th1 cytokines TNF-α and IFN-γ induced PIGR expression in BECs via activating NF-κB pathway. Silencing PIGR alleviated symptoms, reduced IL-33 expression, and restrained hepatic Th2 inflammation in BA mouse model; while overexpressing PIGR increased liver fibrosis and IL-33 expression, and boosted hepatic Th2 inflammation in BA mouse model. PIGR expression promotes the proliferation and epithelial-mesenchymal transition, and reduced the apoptosis of BECs. PIGR participated in BA pathogenesis by promoting hepatic Th2 inflammation via increasing cholangiocytes derived IL-33; PIGR has the value as a diagnostic and therapeutic biomarker of BA. This study was financially supported by the National Natural Science Foundation of China (82170529), the National Key R&D Program (2021YFC2701003), and the National Natural Science Foundation of China (82272022).

Gut microbiome and metabolome profiling in coal workers' pneumoconiosis: potential links to pulmonary function.

The findings have significant implications for the early diagnosis and treatment of coal workers' pneumoconiosis, highlighting the potential of gut microbiota as diagnostic biomarkers. They pave the way for new research into gut microbiota-based therapeutic strategies, potentially focusing on modifying gut microbiota to mitigate disease progression.

Prognosis prediction of PDAC via detection of O-glycan altered extracellular vesicles in perioperative sera.

Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignancy due to the difficulty in diagnosis and poor prognosis because of the high recurrence rate, necessitating reliable biomarkers to improve the diagnosis and prognosis. However, the existing markers have limitations. We previously identified extracellular vesicles (EVs) recognized by O-glycan-binding lectins (Amaranthus caudatus agglutinin [ACA]) as a novel diagnostic biomarker for PDAC using an EV-counting system (ExoCounter). This retrospective study analyzed changes in ACA-positive EVs in perioperative PDAC serum and its association with prognosis using ExoCounter. Absolute EV levels in the pre- and postoperative sera of 44 patients who underwent curative pancreatectomy for PDAC were quantified using ExoCounter. The carbohydrate antigen 19-9 levels declined in most samples postoperatively, and presented no correlation with poor prognosis. In contrast, ACA-positive EVs increased in serum at 7 days postoperatively in 27 of 44 patients (61.4%). We therefore divided participants with ACA-positive EVs before and after surgery into elevation and decline groups. The overall survival (OS) and recurrence-free survival (RFS) of patients with higher ACA-positive EVs were significantly shorter than those with lower ACA-positive EVs (26.1 months vs. not reached, P = 0.018; 11.9 vs. 38.6 months, P = 0.013). Multivariable analysis revealed that ACA-positive EV elevation in postoperative serum was an independent prognostic factor for poor OS (hazard ratio [HR] = 3.891, P = 0.023) and RFS (HR = 2.650, P = 0.024). The detection of ACA-positive EVs in perioperative serum may be used to predict the prognosis of PDAC in the early postoperative period.

Identification and validation of endoplasmic reticulum stress-related genes in patients with steroid-induced osteonecrosis of the femoral head

Steroid-induced osteonecrosis of the femoral head (SONFH) is a debilitating condition caused by long-term corticosteroid use, leading to impaired blood flow and bone cell death. The disruption of cellular processes and promotion of apoptosis by endoplasmic reticulum stress (ERS) is implicated in the pathogenesis of SONFH. We identified ERS-associated genes in SONFH and investigated their potential as therapeutic targets. We analysed the GSE123568 GEO dataset to identify differentially expressed genes (DEGs) related to ERS in SONFH. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, identified hub genes by protein-protein interaction (PPI) analyses, and evaluated their functions by gene set enrichment analysis (GSEA). We constructed mRNA–miRNA networks, identified potential therapeutics, and assessed immune cell infiltration. We performed cross-validation using the GEO dataset GSE74089, qRT-PCR on clinical samples from patients with SONFH and controls, and a receiver operating characteristic (ROC) curve analysis to assess the diagnostic performance of the hub genes. We identified 195 ERS-related genes in SONFH, which were primarily involved in oxidative stress, immune responses, and metabolic pathways. The PPI network suggested CXCL8, STAT3, IL1B, TLR4, PTGS2, TLR2, CASP1, CYBB, CAT, and HOMX1 to be key hub genes, which were shown by GSEA to be involved in biological pathways related to metabolism, immune modulation, and cellular integrity. We also identified 261 microRNAs (miRNAs) as well as drugs such as dibenziodolium and N-acetyl-L-cysteine that modulated inflammatory responses in SONFH. Twenty-two immune cell subtypes showed significant correlations, such as a positive correlation between activated mast cells and Tregs, and patients with SONFH had fewer dendritic cells than controls. The hub genes CYBB and TLR4 showed significant correlations with M1 macrophages and CD8 T cells, respectively. Cross-validation and qRT-PCR confirmed the upregulation of STAT3, IL1B, TLR2, and CASP1 in patients with SONFH, validating the bioinformatics findings. An ROC curve analysis confirmed the diagnostic potential of the hub genes. The top 10 hub genes show promise as ERS-related diagnostic biomarkers for SONFH. We discovered that 261 miRNAs, including hsa-miR-23, influence these genes and identified potential therapeutics such as dibenziodolium and simvastatin. Immune profiling indicated altered immune functions in SONFH, with significant correlations among immune cell types. Validation confirmed the upregulation of STAT3, IL1B, TLR2 and CASP1, which had diagnostic potential. The findings suggest potential diagnostic markers and therapeutic targets for SONFH.

Abstract A061: DKK3 in pancreatic cancer – Elucidating the roles of a double-edged sword

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains a highly challenging disease with a poor prognosis due to lack of diagnostic biomarkers and high tumor heterogeneity. Therefore, it is crucial to meticulously examine the intricate molecular mechanisms in PDAC. We previously identified DKK3 (Dickkopf-3) as a novel factor promoting organ regeneration during pancreatitis and established a previously unknown link between DKK3 and the Wnt and Hedgehog signaling. Given that pancreatitis is a significant risk factor for pancreatic cancer, we were motivated to investigate the potential role of DKK3 in PDAC development. We utilized PDAC mouse models driven by LSL-KrasG12D/+; Ptf1aCre/+ with wildtype, homozygous/heterozygous DKK3 deletion in both epithelial and stromal compartment while employing in vitro and ex vivo systems to examine the stage and compartment-specific roles of the same. Through a comprehensive and time-resolved analysis of tumor characteristics, we discovered that the loss of DKK3 led to rapid oncogenic transformation, marked by a significant increase in metaplasia and desmoplasia starting at an early stage (10 weeks). Ex vivo acinar-to-ductal metaplasia assay and rescue experiments with wildtype and DKK3-null acinar cells revealed that secreted DKK3 operates as a tumor suppressive roadblock in PDAC-initiating steps. This advanced preneoplastic stage translated into accelerated progression toward invasive tumors at 36 weeks, a shortened overall survival, and a higher liver metastasis incidence in the DKK3-null animals at the endpoint. Interestingly, transcriptomic analyses further validated our observation and revealed the involvement PI3-AKT signaling pathway as an underlying mechanism. Further characterization of isolated tumor cells confirmed our observations, revealing prominent mesenchymal features and enhanced migratory capacities upon loss of DKK3. Interestingly, DKK3-null PDACs exhibited a pronounced stroma remodeling with a myofibroblastic cancer-associated fibroblast-enriched environment, as well as an immunosuppressive stroma with abundant regulatory T cells and cytotoxic T cell depletion, as substantiated by coculture experiments. Intriguingly, while displaying similar phenotypic features to DKK3-null tumors, Dkk3+/- heterozygotes exhibited the most aggressive outcome. To further dissect this finding, we conducted a set of in silico approaches and immunostainings revealing persistent stromal DKK3 expression in DKK3- proficient PDACs. This suggested a possible dual role of DKK3 that could operate either as a friend or a foe depending on its spatiotemporal expression in PDAC. In line, in vitro systems demonstrated a distinct oncogenic effect of DKK3 on endpoint tumor cells, particularly promoting malignant cell migration. In summary, we propose that epithelial DKK3 exerts cell-autonomous tumor suppressive functions during the onset of PDAC, while stromal DKK3 acts as an oncogenic cue driving cancer progression. These findings highlight DKK3 as a promising biomarker and a novel therapeutic target for PDAC tumors. Citation Format: Dharini Srinivasan, Frank Arnold, Elodie Roger, Anna Härle, Michael K Melzer, Chantal Allgöwer, Patrick C Hermann, Lukas Perkhofer, Johann Gout, Alexander Kleger. DKK3 in pancreatic cancer – Elucidating the roles of a double-edged sword [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A061.

Plasma miR-122-5p and miR-142-5p and their role in chemoresistance of colon cancer patients.

Chemoresistance represents a major issue affecting cancer therapy efficacy. Because microRNAs (miRNAs) regulate gene expression on multiple levels, their role in chemoresistance development is reasonably certain. In our previous study, miR-122-5p and miR-142-5p were identified as diagnostic, prognostic, and predictive biomarkers for primary and metastatic rectal cancer. The aim of the present study was to investigate whether these miRNAs can also reflect the disease course of colon cancer (CC) patients. Further, we focused on a deeper understanding of their involvement in 5-fluorouracil (5-FU) chemoresistance development. The expression analysis of both miRNAs was analysed in repeated whole plasma samplings (n=3, approximately every 6 months) of CC patients (n=49) by RT-qPCR. Expression levels of both miRNAs were determined in the 5-FU sensitive and resistant CC cell lines. From RNA-seq profiles of both sensitive and 5-FU resistant DLD-1 cell lines, the expression levels of miR-122-5p and miR-142-5p validated target genes were detected and compared. Significant differences in the expression levels of both miRNAs between T0 and T1 or T2 samplings were observed. Further, an association between the occurrence of relapse and miR-122-5p expression levels was noticed. Patients who did not relapse had higher expression of miR-122-5p at T1 (p=0.01; 3.16-fold change) and T2 (p=0.04; 2.79-fold change) samplings in comparison with T0 sampling. Out of all miR-122-5p validated targets (n=102), 25 genes were significantly differentially expressed between sensitive and 5-FU-resistant cell lines. Our data suggest that miR-122-5p may represent a predictive marker of tumour relapse in CC patients. In vitro data suggests that this aspect may be linked to the potential therapeutic targets of miR-122-5p related to 5-FU-based chemoresistance. However, deeper mechanistic studies are still needed for progress toward personalized medicine.

Integrated DNA methylation analysis of peripheral blood from asbestos exposed populations and patients with malignant mesothelioma reveals novel methylation driver genes of diagnostic and prognostic relevance

Effective biomarkers are paramount importance for the early detection and prognosis prediction of malignant mesothelioma (MM) which mainly caused by asbestos exposure, and DNA methylation has been demonstrated to be a potentially powerful diagnostic tool. To elucidate the relationship between asbestos exposure and alterations in DNA methylation patterns, as well as the potential diagnostic and prognostic value of differentially methylated regions and CpG sites (DMRs/DMCs) in the progression of MM. The current study employed reduced representation bisulfite sequencing (RRBS) to examine the genome-wide DNA methylation profiles in the peripheral blood of individuals exposed to asbestos and those diagnosed with MM, in comparison to the controls, and DMRs/DMCs were subsequently validated by targeted bisulfite sequencing (TBS). Our results suggested that there were 12 DMRs/DMCs exhibiting a consistent change trend of DNA methylation in both RRBS and TBS results. Significant correlations were observed between DNA methylation levels of DMRs/DMCs and the duration of occupational asbestos exposure. The evaluation of the receiver operating characteristic (ROC) curve suggested that the DNA methylation status of FHIT, CCR12P and CDH15 may serve as diagnosis indicator in distinguishing MM patients from healthy controls and those exposed to asbestos. Our findings offer a foundation for the role of DNA methylation in the development of MM induced by asbestos exposure. The potential significance of FHIT, CCR12P and CDH15 DNA methylation alterations in the pathogenesis and advancement of MM disease suggests their potential as diagnostic and prognostic biomarkers.

An abnormal metabolism-related gene, ALG3, is a potential diagnostic and prognostic biomarker for lung adenocarcinoma.

To explore the abnormal metabolism-related genes that affect the prognosis of patients with lung adenocarcinoma (LUAD), and analyze the relationship with immune infiltration and competing endogenous RNA (ceRNA) network. Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples. In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. In the model, the survival rate of LUAD patients in the high-risk subgroup was lower than that in the low-risk group. In addition, the risk score of the constructed LUAD prognostic model can be used as an independent prognostic factor for patients. According to the analysis of CIBERSORT algorithm, the risk score is related to the infiltration of multiple immune cells. The potential ceRNA network of model genes in LUAD was constructed through the starBase database. IHC experiments revealed that ALG3 expression was upregulated in LUAD. The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD.

Identification of the shared gene MXD3 signatures and biological mechanism in patients with hip pain and prostate cancer.

Prostate cancer (PRAD) is recognized as having a significant effect on systemic illnesses. This study examined possible immune cells, metabolic pathways, and genes that may explain the interaction between PRAD and hip pain. We used information retrieved from the Cancer Genome Atlas and the Gene Expression Omnibus databases. To find common genes, we utilized differential expression analysis and weighted gene co-expression network analysis. The genes that were shared were subjected to pathway enrichment studies using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Additionally, hub genes were analyzed using LASSO regression, and a receiver operating characteristic curve was generated based on the screening outcomes. The genes for the nodes were chosen in a protein-protein interaction network that was built. Single-sample gene-set enrichment analysis was performed to identify the differentially expressed genes. Immunohistochemistry staining confirmed hub gene expression, and single-sample gene-set enrichment analysis assessed immune cell infiltration. We concluded by comparing MAX dimerization protein 3 (MXD3) and MAX interactor 1 (MXI1) expression in tumor tissues using Uniform Manifold Approximation and Projection and violin plots in the Tumor lmmune Single-cell Hub database. After analyzing the intersection of the differentially expressed genes and weighted gene co-expression network analysis-significant module genes, we determined that MXD3 was the best shared diagnostic biomarker for PRAD and hip pain. One potential predictor of PRAD development was the MXI1 node gene, which was found in the protein-protein interaction network. The analyses revealed that MXD3 had a relatively positive correlation with neutrophil and T-helper cell infiltration levels, whereas MXI1 had a negative correlation with mast and Tgd cell levels. Tumors had lower levels of MXI1 expression and higher levels of MXD3 expression compared to normal tissues. Endothelial cells, induced pluripotent stem cells, and smooth muscle cells were all found to express MXI1. This is the first study to investigate the close genetic link between hip pain and PRAD using bioinformatics technologies. The 2 most significant genes involved in crosstalk between PRAD and hip pain were MXD3 and MXI1. The immunological responses triggered by T cells, mast cells, and neutrophils may be crucial in the relationship between PRAD and hip pain.

No replicating evidence for anti-amyloid-β autoantibodies in cerebral amyloid angiopathy-related inflammation.

Elevated levels of anti-amyloid-β (anti-Aβ) autoantibodies in cerebrospinal fluid (CSF) have been proposed as a diagnostic biomarker for cerebral amyloid angiopathy-related inflammation (CAA-RI). We aimed to independently validate the immunoassay for quantifying these antibodies and evaluate its diagnostic value for CAA-RI. We replicated the immunoassay to detect CSF anti-Aβ autoantibodies using CSF from CAA-RI patients and non-CAA controls with unrelated disorders and further characterized its performance. Moreover, we conducted a literature review of CAA-RI case reports to investigate neuropathological and CSF evidence of the nature of the inflammatory reaction in CAA-RI. The assay demonstrated a high background signal in CSF, which increased and corresponded with higher total immunoglobulin G (IgG) concentration in CSF (rsp = 0.51, p = 0.02). Assay levels were not elevated in CAA-RI patients (n = 6) compared to non-CAA controls (n = 20; p = 0.64). Literature review indicated only occasional presence of B-lymphocytes and plasma cells (i.e., antibody-producing cells), alongside the abundant presence of activated microglial cells, T-cells, and other monocyte lineage cells. CSF analysis did not convincingly indicate intrathecal IgG production. We were unable to reproduce the reported elevation of anti-Aβ autoantibody concentration in CSF of CAA-RI patients. Our findings instead support nonspecific detection of IgG levels in CSF by the assay. Reviewed CAA-RI case reports suggested a widespread cerebral inflammatory reaction. In conclusion, our findings do not support anti-Aβ autoantibodies as a diagnostic biomarker for CAA-RI.

Identification of mitochondria-related genes as diagnostic biomarkers for diabetic nephropathy and their correlation with immune infiltration: New insights from bioinformatics analysis

BackgroundDiabetic nephropathy (DN) is a common and severe microvascular complication of diabetes. Mitochondrial dysfunction and immune inflammation are important factors in the pathogenesis of DN. However, the specific mechanisms and their intricate interactions in DN remain unclear. Besides, there are no effective specific predictive or diagnostic biomarkers for DN so far. Therefore, this study aims to elucidate the role of mitochondrial-related genes and their possibility as predictive or diagnostic biomarkers, as well as their crosstalk with immune infiltration in the progression of DN. MethodsBased on the GEO database and limma R package, the differentially expressed genes (DEGs) of DN were identified. Mitochondrial-related DEGs (MitoDEGs) were then obtained by intersecting these DEGs with mitochondria-related genes from the MitoCarta 3.0 database. Subsequently, the candidate hub genes were further screened by gene co-expression network analysis (WGCNA), and verified mRNA levels of these genes by real-time quantitative PCR (qRT-PCR) in high-glucose-treated human proximal tubular (HK-2) cells. The verified hub genes were utilized to construct a combined diagnostic model for DN, with its diagnostic efficacy assessed across the GSE30122 and GSE96804 datasets. Additionally, the immune infiltration pattern in DN was assessed with the CIBERSORT algorithm, and the Nephroseq v5 database was used to analyze the correlation between hub genes and clinical features of DN. ResultsSeven mitochondria-related candidate hub genes were screened from 56 MitoDEGs. Subsequently, the expression levels of six of them, namely EFHD1, CASP3, AASS, MPC1, NT5DC2, and BCL2A1, exhibited significant inter-group differences in the HK-2 cell model. The diagnostic model based on the six genes demonstrated good diagnostic efficacy in both training and validation sets. Furthermore, correlation analysis indicated that EFHD1 and AASS, downregulated in DN, are positively correlated with eGFR and negatively with serum creatinine. Conversely, CASP3, NT5DC2, and BCL2A1, upregulated in DN, show opposite correlations. In addition, spearman analysis revealed that the six hub genes were significantly associated with the infiltration of immune cells, including M1 and M2 macrophages, mast cells, resting NK cells, gamma delta T cells, and follicular helper T cells. ConclusionThis study elucidated the characteristics of mitochondria-related genes and their correlation with immune cell infiltration in DN, providing new insights for exploring the pathogenesis of DN and facilitating the identification of new potential biomarkers and therapeutic targets.

The Prominence of the Broad-Spectrum Protease inhibitor gene A2ML1 as a potential biomarker in cervical cancer diagnostics using Immunotherapeutic and Multi-Omics approaches

One of the venereal tumors that threaten human life is cervical cancer. A2ML1 is detected in advanced-stage cancer patients and is found to be strongly associated with cervical cancer. A2ML1 was shown to be substantially expressed in cervical cancer in this study, which used data from the TCGA database. Those with high A2ML1 expression had a lower chance of survival than patients with low A2ML1 expression. Both univariate and multivariate Cox regression analyses were utilized to investigate the relationship between clinical variables and overall survival rates. An investigation into the link between A2ML1 and immune infiltration was subsequently conducted. Utilizing the immune cell database, research was conducted to investigate the dispersion of 24 immune cells and their correlation to A2ML1 expression. In addition to this, the favorable correlation between immune cells and A2ML1 was validated using all three immune cell methodologies. The Genomics of Drug Sensitivity in Cancer database was used to confirm the idea that there is a link between A2ML1 expression and the efficacy of chemotherapy or immunotherapy. The findings demonstrated that A2ML1 is a potential biomarker for cervical cancer diagnostics. This biomarker may be used to chaperone immunotherapy, as well as to explain the elucidates of cervical cancer caused by the immunological microenvironment.

Evaluation of Serum Proteome Sample Preparation Methods to Support Clinical Proteomics Applications.

Serum contains several proteins that are associated with disease-related processes. Mass spectrometry (MS)-based proteomics approaches greatly facilitate serum protein biomarker development. However, the serum proteome complexity presents a technical challenge for the accurate, sensitive, and reproducible quantification of proteins by MS. Thus, efficient sample preparation methods are of critical importance for serum proteome analyses. In this study, we evaluated the technical performance of two serum proteome sample preparation methods using sera from patients with high-grade serous ovarian cancer and patients with benign nongynecological conditions with a goal of providing insight into their compatibility with clinical proteomics workflows. One method entailed the use of immobilized trypsin (SMART Digest Trypsin) with RapiGest SF, an acid-labile surfactant designed to enhance the in-solution enzymatic digestion of proteins. The other method incorporated a commercially available sample preparation kit, iST-BCT, which contains standardized reagents. Significantly higher protein sequence coverage, albeit with lower digestion efficiency, was obtained with the immobilized trypsin + RapiGest SF workflow, whereas the iST-BCT workflow was quicker and had marginally better reproducibility. Protein relative abundance analysis revealed that the serum proteomes clustered primarily by the sample processing workflow and secondarily by disease state. We conducted a time course study to determine whether differences in the relative abundance of diagnostic high-grade serous ovarian cancer serum protein biomarker candidates were biased according to the duration of enzymatic digestion. Our results highlight the importance of optimizing enzymatic digestion kinetics according to the peptide targets of interest while considering the sensitivity of the downstream analytical method utilized in clinical proteomics workflows designed to measure biomarkers.

MiR-381-3p/TET3 axis promotes cervical cancer: A bioinformatic integrative analysis

Cervical cancer (CC) is a global public health problem. Epigenetic factors, such as microRNAs, play a key role in the development of CC. Although a previous study reported that miR-381-3p inhibits CC by downregulating fibroblast growth factor 7, its role in CC remains largely unknown. This study aimed to fill the gap by analyzing the role of miR-381-3p in CC. Expression analysis was performed using databases including The Cancer Genome Atlas, Gene Expression Omnibus, and the Human Protein Atlas. Receiver operating characteristics and Kaplan–Meier curves were plotted using GraphPad Prism and Kaplan–Meier Plotter databases. Target messenger RNAs were identified using the miRDB and miRPathDB databases. Kyoto Encyclopedia of Genes and Genomes, Gene Ontology Biological Process, and Gene Set Enrichment Analysis were performed using Enrichr and WebGestalt databases. Mutation analysis was conducted using the cBioPortal database. In this study, we found that miR-381-3p expression is low in CC. Moreover, we identified a total of 1,191 potential targets of miR-381-3p that may be involved in key signaling pathways in this cancer. Interestingly, our results identified ten-eleven translocation 3 (TET3) as a potential target, with evidence suggesting that TET3 expression is increased in CC. This increase in TET3 expression may be useful as a diagnostic and prognostic biomarker. In addition, four mutations were identified in the TET3 protein. TET3 expression increases in patients with International federation of gynecology and obstetrics stage II CC and in those with lymph node metastasis. Mechanistically, TET3 expression may be induced by a gain in copy number, human papillomavirus infection, aberrant methylation, and activation of the transcription factor activator protein 2α. Finally, we identified 145 genes that are regulated by TET3 in CC, which are involved in key pathways and biological processes associated with CC, such as the cell cycle, DNA replication, mitogen-activated protein kinase signaling pathway, and basal transcription factors. In conclusion, we identified the miR-381-3p/TET3 axis as a key player in the carcinogenic process of CC.

Somatic mutations in 3929 HPV positive cervical cells associated with infection outcome and HPV type

Invasive cervical cancers (ICC), caused by HPV infections, have a heterogeneous molecular landscape. We investigate the detection, timing, and HPV type specificity of somatic mutations in 3929 HPV-positive exfoliated cervical cell samples from individuals undergoing cervical screening in the U.S. using deep targeted sequencing in ICC cases, precancers, and HPV-positive controls. We discover a subset of hotspot mutations rare in controls (2.6%) but significantly more prevalent in precancers, particularly glandular precancer lesions (10.2%), and cancers (25.7%), supporting their involvement in ICC carcinogenesis. Hotspot mutations differ by HPV type, and HPV18/45-positive ICC are more likely to have multiple hotspot mutations compared to HPV16-positive ICC. The proportion of cells containing hotspot mutations is higher (i.e., higher variant allele fraction) in ICC and mutations are detectable up to 6 years prior to cancer diagnosis. Our findings demonstrate the feasibility of using exfoliated cervical cells for detection of somatic mutations as potential diagnostic biomarkers.

Platinum-perovskite nanocomposite-based Exosensor for specific detection of prostate cancer in clinical settings.

Exosomes, extracellular vesicles (EVs) with an average size of 50-150nm, transfer various biomolecules and exchange signaling molecules between cells in a paracrine manner. Molecular investigations have revealed that EVs can reflect real-time metabolic changes in normal- and cancer-origin cells and thus harbor valid diagnostic biomarkers. Despite these advantages, the detection of low concentrations of cancer cell EVs in biological fluids is still a great challenge. Here, a new electrochemical Exosensor based on platinum-perovskite is developed for the direct detection of EVs using a biotinylated monoclonal CD63 antibody as a capture element. The label-free method exhibited higher sensitivity with a lower limit of quantification of 2000 EVs/µL with a dynamic linear range (LDR) of 2000 to 14,000 EVs/μL compared with other available methods. To enhance the selectivity of detection, EVs were simultaneously sandwiched between secondary antibodies of PSA (prostate-specific antigen), as an FDA-approved prostate cancer biomarker. Data indicated that this Exosensor can distinguish normal and cancer EVs in samples from healthy individuals and prostate cancer patients. Taken together, this technology offers a unique approach to label-free quantification of EVs and cancer detection in the early stages.