Potential Diagnostic Marker Research Articles

Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas.

The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the USs. Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), 3 adenosarcomas, 2 carcinosarcomas, and 1 uterine tumor resembling an ovarian sex-cord tumor (UTROSCT). ESS (including high-grade ESS and low-grade ESS) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A - PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uDEGs were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named MMN-MIL showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Altered N6-methyladenosine methylation level in spermatozoa messenger RNA of the male partners is related to unexplained recurrent pregnancy loss.

Understanding the pathogenesis of unexplained recurrent pregnancy loss is paramount for advancing effective treatments. Various biological processes, including spermatogenesis and embryo development, are tightly regulated by N6-methyladenosine modifications. However, few studies have focused on the impact of sperm N6-methyladenosine modifications on embryonic development. Therefore, we aimed to study altered N6-methyladenosine-mediated messenger RNA methylation modifications in the spermatozoa of male partners from couples experiencing unexplained recurrent pregnancy loss, to identify potential diagnostic markers and explore their potential molecular mechanisms in pregnancy loss and embryogenesis. Methylated RNA immunoprecipitation (MeRIP) sequencing and RNA sequencing were conducted on the spermatozoa of men from couples in the 'unexplained recurrent pregnancy loss' group (n=6), and the fertility control group (n=6). To identify the role of the detected key genes, zebrafish model embryos were studied, and multi-omics (transcriptomics, proteomics, and metabolomics) analyses helped to explore the molecular mechanism of abnormal embryogenesis. Comparing unexplained recurrent pregnancy loss with the fertility control group, 217 N6-methyladenosine peaks were significantly upregulated, and 40 were downregulated in the spermatozoa. The combined analyses of spermatozoa-methylated RNA immunoprecipitation sequencing and RNA sequencing indicated that N6-methyladenosine methylation and the expression of SEMA5A, MT-ATP6, ZNF662, and KDM4C were significantly different. In zebrafish embryos, the altered expression of the four genes increased embryonic mortality and malformations by disturbing several key signaling pathways and zygotic genome activation. This study highlights the paternal epigenome, which could be one of the reasons for faulty embryogenesis leading to pregnancy loss. The N6-methyladenosine modification, the most prevalent RNA modification, contributes to the exploration and understanding of the paternal epigenome in the maintenance of pregnancy and fetal growth and development. The four genes identified in this study may serve as potential diagnostic markers and elucidate novel molecular mechanisms of embryogenesis.

Clinical significance of TROAP in endometrial cancer and the antiproliferative and proapoptotic effects of TROAP knockdown in endometrial cancer cells: integrated utilization of bioinformatic analysis and in vitro test verification.

Trophinin-associated protein (TROAP), a cytoplasmic protein essential for spindle assembly and centrosome integrity during mitosis, has been reported to serve as an oncogene in various tumors. However, its role in endometrial cancer (EC) progression is still undefined. TROAP expression in EC was analyzed via GEPIA and HPA databases. The diagnostic and prognostic values of TROAP were examined by ROC curve analysis and Kaplan-Meier plotter, respectively. Cell proliferation was evaluated using CCK-8 and EdU incorporation assays. Apoptosis was assessed using TUNEL and flow cytometry assays. GSEA was performed to explore TROAP-related pathways in EC. Expression of TROAP, proliferating cell nuclear antigen (PCNA), Ki-67, cleaved-caspase-3 (cl-caspase-3), caspase-3, active β-catenin, and total β-catenin was detected using western blot analysis. TROAP was upregulated in EC. TROAP served as a potential diagnostic and prognostic marker in EC patients. TROAP silencing suppressed proliferation and enhanced apoptosis in EC cells. GSEA revealed that EC and Wnt signaling pathways were related to the expression of TROAP. We further demonstrated that TROAP knockout repressed the Wnt/β-catenin pathway in EC cells. Moreover, SKL2001, a Wnt/β-catenin activator, partially abrogated the effects of TROAP silencing on EC cell proliferation and apoptosis, while the signaling inhibitor XAV-939 had the opposite effect. In conclusion, TROAP knockout retarded proliferation and elicited apoptosis in EC cells by blocking the Wnt/β-catenin pathway.

DKK1 loss promotes endometrial fibrosis via autophagy and exosome-mediated macrophage-to-myofibroblast transition

IntroductionIntrauterine adhesions (IUA) manifest as endometrial fibrosis, often causing infertility or recurrent miscarriage; however, their pathogenesis remains unclear.ObjectivesThis study assessed the role of Dickkopf WNT signaling pathway inhibitor 1 (DKK1) and autophagy in endometrial fibrosis, using clinical samples as well as in vitro and in vivo experiments.MethodsImmunohistochemistry, immunofluorescence and western blot were used to determine the localization and expression of DKK1 in endometrium; DKK1 silencing and DKK1 overexpression were used to detect the biological effects of DKK1 silencing or expression in endometrial cells; DKK1 gene knockout mice were used to observe the phenotypes caused by DKK1 gene knockout.ResultsIn patients with IUA, DKK1 and autophagy markers were down-regulated; also, α-SMA and macrophage localization were increased in the endometrium. DKK1 conditional knockout (CKO) mice showed a fibrotic phenotype with decreased autophagy and increased localization of α-SMA and macrophages in the endometrium. In vitro studies showed that DKK1 knockout (KO) suppressed the autophagic flux of endometrial stromal cells. In contrast, ectopic expression of DKK1 showed the opposite phenotype. Mechanistically, we discovered that DKK1 regulates autophagic flux through Wnt/β-catenin and PI3K/AKT/mTOR pathways. Further studies showed that DKK1 KO promoted the secretion of interleukin (IL)-8 in exosomes, thereby promoting macrophage proliferation and metastasis. Also, in DKK1 CKO mice, treatment with autophagy activator rapamycin partially restored the endometrial fibrosis phenotype.ConclusionOur findings indicated that DKK1 was a potential diagnostic marker or therapeutic target for IUA.

Brain-Derived Neurotrophic Factor as a Potential Diagnostic Marker in Minimal Hepatic Encephalopathy

Abstract Background Based on the etiology, liver cirrhosis is sub-classified into viral hepatitis (hepatitis B, C, and D), due to toxins (alcohol and drugs), autoimmune hepatitis, Cholestatic (primary biliary cholangitis, and primary sclerosing cholangitis), vascular (Budd-Chiari syndrome, sinusoidal obstruction syndrome, and cardiac cirrhosis), and metabolic causes (hemochromatosis, NASH, Wilson disease, alpha-1 antitrypsin deficiency, cryptogenic cirrhosis). Aim of the Work The aim of the current study is to detect Minimal Hepatic Encephalopathy (MHE) among cirrhotic patients of Child C with no or clinically manifest encephalopathy using Brain-Derived Neurotrophic Factor (BDNF) and study the diagnostic value of BDNF serum marker versus Psychometric Hepatic Encephalopathy Score (PHES) in detecting MHE. Patients and Methods 90 patients were enrolled into a clinical cross-sectional study. All patients gave informed written consent. Patients are divided equally into 3 groups, 30 patients each. Patients are either in-patient or out-patients in Ain shams University Hospitals. Group 1 The Examined Group (EG): includes 30 patients diagnosed as hepatitis C, cirrhotic, Child class C with no overt or clinically manifest encephalopathy. Group 2 The Hepatic Encephalopathy Group (HEG): includes 30 patients diagnosed as hepatitis C, cirrhotic, Child class C with overt or clinically manifest encephalopathy. Group 3 The Control Group (CG): includes 30 healthy individuals (volunteers). Results In the present study among the whole sample (n = 90), there was a significant positive correlation between PHES score & BDNF serum level with Hb, platelet count and albumin. While, there was a significant negative correlation between PHES score and BDNF serum level with AST, ALT, total bilirubin, direct bilirubin, INR and Child’s Score. On the other hand, Stawicka et al. 2021, reported that BDNF had a negative correlation with bilirubin (R = –0.35, p = 0.005) and international normalized ratio (INR) (R = –0.37, p = 0.003), and positive with platelets (R = 0.36, p = 0.004), while no associations with age, sex, body mass index (BMI), waist-hip ratio (WHR), creatinine and ammonia. Conclusion MHE constitutes a significant medical problem in a common patient population. Unfortunately, it is often underdiagnosed, likely related to the notion that testing is time consuming requiring highly specialized personnel. Additionally, the term ‘MHE’ may create the impression that this condition has limited impact on patient’s wellbeing; however, it has been shown that MHE has clinical implications on the patient as well as public safety concerns. Diagnosing and treating MHE is difficult owing to the subclinical nature of the disease. The use of Psychometric Hepatic Encephalopathy Score (PHES) and Brain-Derived Neurotrophic Factor could be of great help in early detection of the condition and to give suitable preventive treatment.

Diagnostic Utility of Free Kappa Light Chain Index in Egyptian Multiple Sclerosis Patients

Abstract Background Multiple sclerosis (MS) is a chronic autoimmune-mediated demyelinating disease of the central nervous system (CNS) that is usually associated with varying degrees of progressive disability. Free Kappa light chain (FKLC) has attracted growing attention as a significant diagnostic marker of MS. Aim of the Work The aim of this work was to study the diagnostic utility of free kappa light chain index in a sample of Egyptian MS patients versus IgG oligo clonal bands (OCBs) in CSF and serum in an attempt to throw light on a new simpler non subjective potential diagnostic marker in MS. Patients and Methods This was a case control study of MS patients carried at Ain Shams University Hospitals during the period from January 2021 till January 2022. Subjects included in this study were 30 patients with symptoms suggestive of MS yet undiagnosed and 20 controls, on the basis of their MRI findings, clinical presentation and according to the revised McDonald criteria 2017. Accordingly, patients were diagnosed as MS including 4 CIS patients, 18 RRMS patients and 3 PPMS patients and non-MS including 2 NMO patients, 1 ADEM patient, 1 APS and 1 SLE patient. They were 8 males and 22 female patients, their age ranged from 20 to 40 years old with mean 30.13 ± 6.85 SD. The control group included 5 males and 15 females; their ages ranged from 20 to 40 years with mean 30.13 ± 6.85 SD. Results We found a statistically significantly higher FKLC index and FKLC IF among MS patients in comparison to both control and non-MS group. it could be used for diagnosis of MS with a diagnostic sensitivity of 100 % and a diagnostic specificity of 100 %. Conclusion The significant association between FKLC index and MS led us to conclude FKLC index can be used as a promising diagnostic marker of MS.

CircCUL1 inhibits trophoblast cell migration and invasion and promotes cell autophagy by sponging hsa-miR-30e-3p in fetal growth restriction via the ANXA1/PI3K/AKT axis.

Fetal growth restriction (FGR) severely affects the health outcome of newborns and represents a major cause of perinatal morbidity. The precise involvement of circCULT1 in the progression of FGR remains unclear. We performed next-generation sequencing and RT-qPCR to identify differentially expressed circRNAs in placental tissues affected by FGR by comparing them with unaffected counterparts. Edu, flow cytometry, and transwell assay were conducted to detect HTR8/SVneo cell's function in regard to cell proliferation, migration, and invasion. The interaction between circCUL1 and hsa-miR-30e-3p was assessed through dual-luciferase reporter assays, validation of the interaction between circCUL1 and ANXA1 was performed using RNA pulldown and immunoprecipitation assays. Western blot analysis was performed to evaluate protein levels of autophagy markers and components of the PI3K/AKT signaling pathway. A knockout (KO) mouse model was established for homologous mmu-circ-0001469 to assess fetal mouse growth and development indicators. Our findings revealed an upregulation of circCUL1 expression in placental tissues from patients with FGR. We found that suppression of circCUL1 increased the trophoblast cell proliferation, migration, and invasion, circCUL1 could interact with hsa-miR-30e-3p. Further, circCUL1 stimulated autophagy, modulating trophoblast cell autophagy via the ANXA1/PI3K/AKT pathway, and a notable disparity was observed, with KO mice displaying accelerated embryo development and exhibiting heavier placentas in comparison to wild-type C57BL/6 mice. By modulating the ANXA1/PI3K/AKT signaling pathway through the interaction with hsa-miR-30e-3p, circCUL1 promotes autophagy while concurrently suppressing trophoblast cell proliferation, migration, and invasion. These findings offer novel insights into potential diagnostic markers and therapeutic targets for FGR research.

Insulin-Like Growth Factor 1 Has the Potential to Be Used as a Diagnostic Tool and Treatment Target for Autism Spectrum Disorders.

Autism spectrum disorder (ASD), a heterogeneous group of neurodevelopmental disorders, is characterized by social impairment and repetitive and stereotypic behaviors. Because of the lack of approved laboratory diagnostic markers and effective therapeutic medications, it is one of the most challenging diseases. Therefore, it is urgent to explore potential diagnosis markers or therapeutic targets.Insulin-like growth factor 1 (IGF-1) is a neurotrophic growth factor that enhances brain development. IGF-1 levels in body fluids are lower in preschool children with ASD than in typically developing children, which may serve as a potential diagnostic marker. In various ASD models associated with genetic or environmental exposure, IGF-1 treatment can improve core symptoms or pathological changes, including neuronal development, neural cell survival, balance of synaptic excitation and inhibition, neuroimmunology, and oxidative stress status. In March 2023 an IGF-1 derivative was approved as the first drug for treating Rett syndrome, an ASD-related neurodevelopmental disorder, to improve fundamental symptoms such as social communication. Thus, in this review, we present accumulating evidence of altered IGF-1 levels in ASD patients and the possible mechanisms, as well as evidence that IGF-1 treatment improves the pathophysiology in various ASD models. IGF-1 has the potential to be an early diagnosis marker and an effective therapeutic for ASD.

Identification of macrophage differentiation related genes and subtypes linking atherosclerosis plaque processing and metabolic syndrome via integrated bulk and single-cell sequence analysis

Metabolic syndrome(MS) is a separate risk factor for the advancement of atherosclerosis(AS) plaque but mechanism behind this remains unclear. There may be a significant role for the immune system in this process. This study aims to identify potential diagnostic genes in MS patients at a higher risk of developing and progressing to AS. Datasets were retrevied from gene expression omnibus(GEO) database and differentially expressed genes were identified. Hub genes, immune cell dysregulation and AS subtypes were identified using a conbination of muliple bioinformatic analysis, machine learning and consensus clustering. Diagnostic value of hub genes was estimated using a nomogram and ROC analysis. Finally, enrichment analysis, competing endogenous RNA(ceRNA) network, single-cell RNA(scRNA) sequencing analysis and drug-protein interaction prediction was constructed to identify the functional roles, potential regulators and distribution for hub genes. Four hub genes and two macrophage-related subtypes were identified. Their strong diagnostic value was validated and functional process were identified. ScRNA analysis identified the macrophage differentiation regulation function of F13A1. CeRNA network and drug-protein binding modes revealed the potential therapeutic method. Four immune-correlated hub genes(F13A1, MMRN1, SLCO2A1 and ZNF521) were identified with their diagnostic value being assesed, which F13A1 was found strong correlated with macrophage differentiation and could be potential diagnostic and therapeutic marker for AS progression in MS patients.

Pleural pro-gastrin releasing peptide is a potential diagnostic marker for malignant pleural effusion induced by small-cell lung cancer.

Serum pro-gastrin releasing peptide (proGRP) is a well-recognized diagnostic marker for small cell lung cancer (SCLC). Pleural effusion is common in patients with advanced SCLC. The diagnostic accuracy of pleural proGRP for malignant pleural effusion (MPE) has not yet been established. This study aimed to evaluate the diagnostic accuracy of pleural proGRP for MPE. We prospectively recruited patients with undiagnosed pleural effusions from two centers (Hohhot and Changshu). An electrochemiluminescence immunoassay was used to detect pleural fluid proGRP. The diagnostic accuracy of proGRP for MPE was evaluated using a receiver operating characteristic (ROC) curve. In both the Hohhot (n=153) and Changshu (n=58) cohorts, pleural proGRP in MPE patients did not significantly differ from that in patients with benign pleural effusions (BPEs) (Hohhot, P=0.91; Changshu, P=0.12). In the Hohhot and Changshu cohorts, the areas under the curves (AUCs) of proGRP were 0.51 [95% confidence interval (CI): 0.41-0.60] and 0.62 (95% CI: 0.47-0.77), respectively. However, patients with SCLC-induced MPE had significantly higher proGRP levels than those with BPE and other types of MPE (P=0.001 for both). In the pooled cohort, the AUC of proGRP for SCLC-induced MPE was 0.90 (95% CI: 0.78-1.00, P=0.001). At a threshold of 40 pg/mL, proGRP had a sensitivity of 1.00 (95% CI: 0.61-1.00) and specificity of 0.59 (95% CI: 0.52-0.66). The positive likelihood ratio was 2.61 (95% CI: 1.99-3.41), and the negative likelihood ratio was 0. Pleural proGRP has no diagnostic value for MPE, but has high diagnostic accuracy for SCLC-induced MPE. In patients with proGRP levels <40 pg/mL, MPE secondary to SCLC can be excluded.

Investigating the Role of Inflammatory Response in Polycystic Ovary Syndrome Using Integrated RNA-Seq Analysis.

An important factor in the pathogenesis of polycystic ovary syndrome (PCOS) is chronic low-grade inflammation. However, the exact pathophysiology of PCOS is currently unknown, which makes clinical diagnosis and the development of effective treatments more difficult. We aimed to investigate the role of the inflammatory response in initiating and progressing PCOS. 13 control granulosa cell samples and 15 granulosa cell samples from patients with PCOS were obtained from the GSE102293, GSE34526, and GSE5850 datasets. The gene set variation analysis (GSVA) method was used to calculate the inflammatory response score. Subsequently, the genes associated with inflammation in the hub were identified using differential expression analysis and weighted gene co-expression network analysis (WGCNA). The findings were confirmed by analysis of independent datasets and examination of clinical samples by qRT-PCR analysis. A consensus cluster analysis was conducted to categorize the PCOS samples into subtypes related to inflammation. Functional enrichment and analysis of immune cell infiltration were conducted to explore the potential mechanisms involved. Additionally, the CMap database was utilized to predict potential drugs, and the results were confirmed through molecular docking. During the training cohort analysis, we identified five distinct genes (TGFBR2, ICAM3, WIPF1, SLC11A1, and NCF2) that could serve as potential diagnostic markers for PCOS. The expression levels of these genes were confirmed through validation in both the test set and clinical samples. In training cohort, two distinct inflammatory patterns (C1 and C2) were identified, and the C2 subtype exhibited activated immune- and inflammation-related pathways. Esmolol was shown to have potential as a drug to treat PCOS and it showed good results for molecular binding at TGFBR2, ICAM3, WIPF1, SLC11A1, and NCF2 proteins. Five diagnostic biomarkers and two inflammation-related molecular types associated with PCOS were identified, and esmolol was a potential drug for PCOS treatment. Our findings provided new diagnostic markers and potential small-molecule drugs for PCOS diagnosis and prevention.

Prognostic model development and clinical correlation of eight key genes in skin cutaneous melanoma

Cutaneous melanoma (SKCM) is a challenging and increasingly prevalent cancer with limited effective treatments. In our extensive study of 342 SKCM samples, we developed a prognostic model identifying eight key genes—CASPASE7CLEAVEDD198, FOXO3A, Melanoma gp100, CD171, 1433ZETA, SRC, P21, and CABL—linked to SKCM prognosis. Statistical analysis indicated significant differences in clinical outcomes between low and high-risk groups, corroborated by principal component analysis (PCA). Survival analysis and receiver operating characteristic (ROC) curve analysis confirmed the model's predictive accuracy for SKCM prognosis. Additionally, we observed notable correlations between the expression levels of genes related to prognosis and clinical characteristics. Our research offers crucial insights into SKCM prognosis, suggesting potential diagnostic markers and personalized treatment targets.

Rebound Tremor Frequency as a Potential Diagnostic Marker for Delayed Therapy Escape after Thalamic Deep Brain Stimulation for Essential Tremor-Insights from a Cross-Sectional Study.

Delayed therapy escape (DTE) is frequent after thalamic deep brain stimulation for essential tremor, leading to reduced quality of life, often with ataxic symptoms, and early recognition is challenging. Our goal was to examine whether a low-frequency rebound tremor of the left hand after switching off stimulation is useful as a diagnostic marker for DTE. In this cross-sectional study with additional retrospective analysis, we examined 31 patients with bilateral thalamic DBS ≥ 12 months for essential tremor, using quantitative assessments including video-based motion capture, Fahn-Tolosa-Marin Tremor Rating Scale (FTMTRS), and scale for the assessment and rating of ataxia (SARA). If available, preoperative (preOP) and 12-month postoperative assessments were included in the analysis. Evaluations occurred with DBS activated (ON) and deactivated (OFF). A higher ratio FTMTRS nowON/preOP indicated DTE. Preoperative FTMTRS scores were available for 16 patients, including 5 patients with DTE. The receiver operating characteristic analysis found an area under the curve of 0.86 (p = 0.024) for identification of DTE by low-frequency rebound tremor (i.e., OFF) on the left. In conclusion, it could serve as a potential diagnostic marker.

Immunological Signatures for Early Detection of Human Head and Neck Squamous Cell Carcinoma through RNA Transcriptome Analysis of Blood Platelets.

Although there has been a reduction in head and neck squamous cell carcinoma occurrence, it continues to be a serious global health concern. The lack of precise early diagnostic biomarkers and postponed diagnosis in the later stages are notable constraints that contribute to poor survival rates and emphasize the need for innovative diagnostic methods. In this study, we employed machine learning alongside weighted gene co-expression network analysis (WGCNA) and network biology to investigate the gene expression patterns of blood platelets, identifying transcriptomic markers for HNSCC diagnosis. Our comprehensive examination of publicly available gene expression datasets revealed nine genes with significantly elevated expression in samples from individuals diagnosed with HNSCC. These potential diagnostic markers were further assessed using TCGA and GTEx datasets, demonstrating high accuracy in distinguishing between HNSCC and non-cancerous samples. The findings indicate that these gene signatures could revolutionize early HNSCC identification. Additionally, the study highlights the significance of tumor-educated platelets (TEPs), which carry RNA signatures indicative of tumor-derived material, offering a non-invasive source for early-detection biomarkers. Despite using platelet and tumor samples from different individuals, our results suggest that TEPs reflect the transcriptomic and epigenetic landscape of tumors. Future research should aim to directly correlate tumor and platelet samples from the same patients to further elucidate this relationship. This study underscores the potential of these biomarkers in transforming early diagnosis and personalized treatment strategies for HNSCC, advocating for further research to validate their predictive and therapeutic potential.

Expression of Intragenic LCAL4 Long Non-Coding RNAs as a Potential Diagnostic and Prognostic Marker in Female Breast Cancer.

In breast cancer early detection is associated with reduced mortality and it is essential to identify new biomarkers for early detection and appropriate management of cancer patients with the best response to treatment. Long non-coding RNAs (LncRNAs) have attracted much attention as potential diagnostic, prognostic, or predictive biomarkers due to their high specificity, easy access to non-invasive methods, and their aberrant expression under various pathological and physiological conditions. Have attracted the aim of this study is to investigate the expression profile of intragenic non-coding LncRNAs LCAL4 as a biomarker as potential diagnostic and prognostic biomarkers in cancer. In this research, 62 tissue samples were obtained from patients undergoing therapeutic surgery in Khatam al-Anbia Hospital and the normal peripheral tissue that was removed for prevention was used as a control by Real-time PCR method. The expression pattern of LCAL4 long non-coding RNA gene is significantly different between two groups of healthy control samples and samples obtained from patients with different breast cancer subtypes, Also its expression between samples obtained from different subgroups and different stages showed significant differences. The studied LncRNAs can act as a factor to identify tumor tissue from healthy tissue, and the diagnosis of cancer grades can be different depending on the type of LncRNA. These results can be proposed in the introduction of LncRNA LCAL4 as a new marker in the diagnosis of breast cancer. In addition, by interpreting the results, it can be concluded that these LncRNAs can be considered as influential factors in the process of breast cancer.

Decreased Extracellular Vesicle Vasorin in Severe Preeclampsia Plasma Mediates Endothelial Dysfunction.

Preeclampsia (PE) is a serious pregnancy complication affecting 5-8% of pregnancies globally. It is a leading cause of maternal and neonatal morbidity and mortality. Despite its prevalence, the underlying mechanisms of PE remain unclear. This study aimed to determine the potential role of vasorin (VASN) in PE pathogenesis by investigating its levels in extracellular vesicles (EV) and its effects on vascular function. We conducted unbiased proteomics on urine-derived EV from severe PE (sPE) and normotensive pregnant women (NTP), identifying differential protein abundances. Out of one hundred and twenty proteins with ≥ ±1.5-fold regulation at P<0.05 between sPE and NTP, we focused on Vasorin (VASN), which is downregulated in sPE in urinary EV, in plasma EV and in the placenta and is a known regulator of vascular function. We generated EV with high VASN content from both human and murine placenta explants (Plex EV), which recapitulated disease-state-dependent effects on vascular function observed when treating murine aorta rings (MAR) or human aortic endothelial cells (HAEC) with murine or human plasma-derived EV. In normal murine pregnancy, VASN increases with gestational age (GA), and VASN is decreased in plasma EV, in placenta tissue and in Plex EV after intravenous administration of adenovirus encoding short FMS-like tyrosine kinase 1 (sFLT-1), a murine model of PE (murine-PE). VASN is decreased in plasma EV, in placenta tissue and in EV isolated from conditioned media collected from placenta explants (Plex EV) in patients with sPE as compared to NTP. Human sPE and murine-PE plasma EV and Plex EV impair migration, tube formation, and induces apoptosis in human aortic endothelial cells (HAEC) and inhibit acetylcholine-induced vasorelaxation in murine vascular rings (MAR). VASN over-expression counteracts the effects of sPE EV treatment in HAEC and MAR. RNA sequencing revealed that over-expression or knock down of VASN in HAEC results in contrasting effects on transcript levels of hundreds of genes associated with vasculogenesis, endothelial cell proliferation, migration and apoptosis. The data suggest that VASN, delivered to the endothelium via EV, regulates vascular function and that the loss of EV VASN may be one of the mechanistic drivers of PE. What is NewVASN in circulating plasma EV in sPE is reduced compared with VASN content in plasma EV of gestational age-matched pregnant women.VASN is encapsulated and transported in EV and plays a pro-angiogenic role during pregnancy.VASN should be explored both for its pro-angiogenic mechanistic role and as a novel biomarker and potential predictive diagnostic marker for the onset and severity of PE.What Are the Clinical Implications?VASN plays a role in maintaining vascular health and the normal adaptive cardiovascular response in pregnancy. A decrease of VASN is observed in sPE patients contributing to cardiovascular maladaptation.Strategies to boost diminished VASN levels and/or to pharmacologically manipulate mechanisms downstream of VASN may be explored for potential therapeutic benefit in PE.The decrease in EV-associated VASN could potentially be used as a (predictive) biomarker for PE.

A CEBPB/miR-32–5p/GATA6 axis promotes vascular calcification in type 2 diabetes

Vascular calcification in diabetes patients is a major independent risk factor for developing diabetic cardiovascular complications. However, the mechanisms by which diabetes leads to vascular calcification are complex and not yet fully understood. Our previous study revealed that miR-32–5p is a potential new diagnostic marker for coronary artery calcification. In this study, we found that miR-32–5p levels were significantly greater in the plasma of type 2 diabetes patients with coronary artery calcification and were positively correlated with the coronary artery calcification score. In type 2 diabetic mice, miR-32–5p levels were also elevated in the aorta, and knockout of miR-32–5p inhibited the osteogenic differentiation of vascular smooth muscle cells in vivo. Furthermore, overexpression of miR-32–5p promoted vascular smooth muscle cell calcification, while antagonism of miR-32–5p inhibited vascular smooth muscle cell calcification under high-glucose conditions. GATA binding protein 6 (GATA6) was identified as the key target gene through which miR-32–5p promotes vascular smooth muscle cell calcification. Overexpression of GATA6 antagonized the effects of miR-32–5p on vascular calcification. Additionally, high glucose levels were shown to induce the upregulation of miR-32–5p by activating CCAAT/enhancer binding protein beta (CEBPB). These results suggest that miR-32–5p is an important procalcification factor in vascular calcification associated with type 2 diabetes and identify the CEBPB/miR-32–5p/GATA6 axis as a potential biomarker and therapeutic target for preventing and treating vascular calcification in type 2 diabetes.

Postprandial Plasma Glucose between 4 and 7.9 h May Be a Potential Diagnostic Marker for Diabetes.

Postprandial glucose levels between 4 and 7.9 h (PPG4-7.9h) correlate with mortality from various diseases, including hypertension, diabetes, cardiovascular disease, and cancer. This study aimed to assess if predicted PPG4-7.9h could diagnose diabetes. Two groups of participants were involved: Group 1 (4420 participants) had actual PPG4-7.9h, while Group 2 (8422 participants) lacked this measure but had all the diabetes diagnostic measures. Group 1 underwent multiple linear regression to predict PPG4-7.9h using 30 predictors, achieving accuracy within 11.1 mg/dL in 80% of the participants. Group 2 had PPG4-7.9h predicted using this model. A receiver operating characteristic curve analysis showed that predicted PPG4-7.9h could diagnose diabetes with an accuracy of 87.3% in Group 2, with a sensitivity of 75.1% and specificity of 84.1% at the optimal cutoff of 102.5 mg/dL. A simulation on 10,000 random samples from Group 2 revealed that 175 participants may be needed to investigate PPG4-7.9h as a diabetes diagnostic marker with a power of at least 80%. In conclusion, predicted PPG4-7.9h appears to be a promising diagnostic indicator for diabetes. Future studies seeking to ascertain its definitive diagnostic value might require a minimum sample size of 175 participants.

Machine learning models predicts risk of proliferative lupus nephritis.

This study aims to develop and validate machine learning models to predict proliferative lupus nephritis (PLN) occurrence, offering a reliable diagnostic alternative when renal biopsy is not feasible or safe. This study retrospectively analyzed clinical and laboratory data from patients diagnosed with SLE and renal involvement who underwent renal biopsy at West China Hospital of Sichuan University between 2011 and 2021. We randomly assigned 70% of the patients to a training cohort and the remaining 30% to a test cohort. Various machine learning models were constructed on the training cohort, including generalized linear models (e.g., logistic regression, least absolute shrinkage and selection operator, ridge regression, and elastic net), support vector machines (linear and radial basis kernel functions), and decision tree models (e.g., classical decision tree, conditional inference tree, and random forest). Diagnostic performance was evaluated using ROC curves, calibration curves, and DCA for both cohorts. Furthermore, different machine learning models were compared to identify key and shared features, aiming to screen for potential PLN diagnostic markers. Involving 1312 LN patients, with 780 PLN/NPLN cases analyzed. They were randomly divided into a training group (547 cases) and a testing group (233 cases). we developed nine machine learning models in the training group. Seven models demonstrated excellent discriminatory abilities in the testing cohort, random forest model showed the highest discriminatory ability (AUC: 0.880, 95% confidence interval(CI): 0.835-0.926). Logistic regression had the best calibration, while random forest exhibited the greatest clinical net benefit. By comparing features across various models, we confirmed the efficacy of traditional indicators like anti-dsDNA antibodies, complement levels, serum creatinine, and urinary red and white blood cells in predicting and distinguishing PLN. Additionally, we uncovered the potential value of previously controversial or underutilized indicators such as serum chloride, neutrophil percentage, serum cystatin C, hematocrit, urinary pH, blood routine red blood cells, and immunoglobulin M in predicting PLN. This study provides a comprehensive perspective on incorporating a broader range of biomarkers for diagnosing and predicting PLN. Additionally, it offers an ideal non-invasive diagnostic tool for SLE patients unable to undergo renal biopsy.

Analysis of potential diagnostic markers and therapeutic targets for rheumatoid arthritis with comorbid depression immunologic indicators

ObjectiveDepression can impact the severity of rheumatoid arthritis (RA). This study aimed to investigate the relationship between Th1, Th2, Th17, Treg cell subsets, and their associated cytokines (e.g., IL-2, IL-4, IL-6, IL-10, IL-17, IFN-γ, and TNF-α), and the occurrence of RA both with and without comorbid depression. The objective is to identify potential biological markers, therapeutic targets, and the therapeutic effects of RA with comorbid depression. Results53 RA patients,46 RA with comorbid depression patients and 51 healthy subjects were included in the RA,RD and HC group from August 2021 and October 2022. Among RA patients, 46.46 % were comorbid with depression. IL-6 concentrations were significantly higher in RD group than in RA group.Comparison between the HC and RA and RD groups revealed that Th1 %, Th17 %, Th1, Th17, Th1/Th2, Th17/Treg and Th1/Treg were significantly higher in the RA and RD groups, and conversely, Th2 %, Treg%, Th2 and Treg were significantly lower than in the HC group.The RA group compared to the RD group found that Th17 %, Th17 and Th17/Treg were significantly higher in the RD group than in the RA group, however, Th1 %, Treg and Th2/Treg were significantly lower than in the RA group. The total HAMD score had a medium strength positive correlation with IL-6. ConclusionThese findings suggest that elevated the autoimmunity status was overactivated in RA with or without depression activates patients, IL-6 may be a predictor of the severity of RA with comorbid depression, IL-6 concentrations and an imbalance in the Th17/Treg may underlie the comorbidity of RA and depression, offering potential targets for therapeutic intervention, prompting further evaluation of the role of indirect inflammatory markers in RA with comorbid depression, highlighting the need for additional research to clarify the complex relationship between inflammation and psychological health.