Promising Non-invasive Biomarker Research Articles

Magnetic 3D macroporous MOF oriented urinary exosome metabolomics for early diagnosis of bladder cancer

Bladder cancer (BCa) exhibits the escalating incidence and mortality due to the untimely and inaccurate early diagnosis. Urinary exosome metabolites, carrying critical tumor cell information and directly related to bladder, emerge as promising non-invasive diagnostic biomarkers of BCa. Herein, the magnetic 3D ordered macroporous zeolitic imidazolate framework-8 (magMZIF-8) is synthesized and used for efficient urinary exosome isolation. Notably, beyond retaining the single crystals and micropores of conventional ZIF-8, MZIF-8 is further enhanced with highly oriented and ordered macropores (150 nm) and the large specific surface area (973 m2·g–1), which could enable the high purity and yield separation of exosomes via leveraging the combination of size exclusion, affinity, and electrostatic interactions between magMZIF-8 and the surfaces of exosome. Furthermore, the magnetic and hydrophilic properties of magMZIF-8 will further simplify the process and enhance the efficiency of separation. After conditional optimization, a 50 mL of urine is sufficient for exosome metabolomics analysis, and the time for isolating exosomes from 42 urine samples was 2 hours only. Incorporating machine learning algorithms with LC-MS/MS analysis of the metabolic patterns obtained from isolated exosomes, early-stage BCa patients were differentiated from healthy controls, with area under the curve (AUC) value of 0.844–0.9970 in the training set and 0.875-1.00 in the test set, signifying its potential as a reliable diagnostic tool. This study offers a promising approach for the non-invasive and efficient diagnosis of BCa on a large scale via exosome metabolomics.Graphical

Diagnostic Potential of NEAT1, hsa-let-7a-5p, and miR-506-3p in Early-stage Parkinson's Disease.

Parkinson's disease (PD) is a multifaceted disease that is influenced by both genetic and environmental parameters. Non-coding RNAs have been shown to be ideal biomarkers for several diseases, including PD. This study was conducted to evaluate the expression levels of NEAT1, hsa-let-7a-5p, and miR-506-3p in individuals with PD to assess their efficacy for early-stage PD diagnosis. Twenty-four patients with PD and 29 healthy individuals participated in this study. The IntaRNA tool was used to predict potential base pairings between NEAT1 and let-7a-5p, and NEAT1 and miR-506-3p. RT-qPCR was employed to measure the relative expression of tyrosine hydroxylase (TH), as well as nuclear enriched abundant transcript 1 (NEAT1), hsa-let-7a-5p, and miR-506-3p levels in both groups. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic value. The PD group exhibited significantly elevated NEAT1 expression levels compared to the healthy control group. While the PD group exhibited an insignificant decreased TH expression level relative to the healthy group. Furthermore, the levels of hsa-let-7a-5p and miR-506-3p expression were seen to be decreased in patients with PD in comparison to the control group. Integration of NEAT1, hsa-let-7a-5p, and miR-506-3p levels significantly enhanced diagnostic capabilities and increased the AUC to 0.9501 (95% confidence interval: 0.8978-1.000, p < .0001). The elevated NEAT1 expression and the decreased expression of hsalet- 7a-5p and miR-506-3p in PD patients indicate that these factors might contribute to the disease's pathogenesis. Combining the ROC curves of NEAT1 and hsa-let-7a-5p with miR-506-3p showed improved sensitivity and specificity, facilitating more accurate PD diagnosis. More importantly, they may contribute as promising non-invasive biomarkers for PD diagnosis.

Urinary Neutrophil Gelatinase-Associated Lipocalin Values in Preterm Neonates: A Systematic Review and Meta-analysis.

Acute kidney injury (AKI) is common in hospitalized preterm neonates. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) is a promising noninvasive AKI biomarker. However, normal values of uNGAL in preterm neonates without AKI are poorly characterized. The objective of this study was to evaluate the current literature to determine normal uNGAL values for preterm neonates without AKI. Systematic review and meta-analysis of all articles published before November 2021 evaluating uNGAL values in preterm neonates without AKI. Of 1,607 studies evaluated for eligibility, 11 were included in the final meta-analysis (210 males, 202 females). uNGAL values were higher in the preterm neonates <29 weeks and ranged between 20.7 and 782.65 ng/mL. Meta mean estimates of gestational age (GA), birthweight, and neutrophil gelatinase-associated lipocalin were 29.4 weeks (95% confidence interval [CI]: 28.8-30.0), 1,241 g (95% CI: 1,111-1,372), and 148.9 ng/mL (95% CI: 48-231), respectively. In limited studies, a wide range of uNGAL values in preterm neonates without AKI are reported. Future studies should identify normal uNGAL values in preterm neonates using larger cohorts by GA and birthweight. · Urinary NGAL is a promising noninvasive biomarker of neonatal AKI.. · A wide range of uNGAL is reported in preterm neonates but the baseline values are not well defined.. · Urine NGAL values are higher in extremely preterm compared with preterm neonates..

Circulating tumour DNA in patients with hepatocellular carcinoma across tumour stages and treatments

ObjectiveCirculating tumour DNA (ctDNA) is a promising non-invasive biomarker in cancer. We aim to assess the dynamic of ctDNA in patients with hepatocellular carcinoma (HCC).DesignWe analysed 772 plasmas from 173...

Application of serum tumor specific protein 70 for prognostic stratification in acute myeloid leukemia

Objective: To assess the value of serum tumor specific protein 70 (SP70) for prognostic stratification in acute myeloid leukemia (AML). Methods: A cohort study design was adopted. 129 newly diagnosed AML patients from September 2022 to January 2024 at the Hematology Department of the First Affiliated Hospital of Nanjing Medical University were included, as well as a control group consisted of 120 healthy individuals and 7 cases with benign hematologic diseases during the same period (total 127 cases). Clinical data were collected from Electronic Medical Records. According to the 2023 edition of the Chinese Leukemia Diagnosis and Treatment Guidelines, AML patients with good or moderate prognosis were categorized as low-to-intermediate risk, while those with poor prognosis were high-risk group. Univariate and multivariate logistic regression analyses were used to identify variables significantly associated with AML prognostic risk. ROC analysis was used to evaluate diagnostic performance. A nomogram for predicting patient prognostic risk was constructed by R 4.0.2 software, and the internal validation was performed using bootstrapping. Results: Among 129 AML patients, there were 71 males (55.0%) and 58 females (45.0%), with 42 (32.6%) classified as high-risk and 87 (67.4%) as low-intermediate risk. The high-risk group had a significantly higher median age [62 (48, 67) years] compared to the low-intermediate risk group [50 (35, 63) years, Z=-2.381, P=0.017], and a significantly higher proportion of males (30 patients, 71.4%) compared to the low-intermediate risk group (41 patients, 47.1%, χ2=6.760, P=0.009). Multivariate logistic regression analysis indicated that serum SP70 (OR=2.54, 95%CI: 1.68-3.84, P<0.001), hemoglobin (HB) (OR=0.96, 95%CI: 0.93-0.99, P<0.05), and bone marrow blast (BM blast) (OR=1.07, 95%CI: 1.02-1.13, P<0.05) were independent risk factors for high-risk prognosis in AML patients. ROC analysis showed that the area under the curve (AUC) for SP70 predicting high-risk patients was 0.908 (cut-off value of 5.74 ng/ml, 95%CI: 0.845-0.952, sensitivity 90.5%, specificity 82.8%). The combined model of serum SP70, HB, and BM blasts had an AUC of 0.931 (95%CI: 0.890-0.973); C-index=0.925 (95%CI: 0.876-0.963),with no statistically significant difference compared to serum SP70 alone (Z=1.693,P>0.05). Conclusion: Serum SP70 may be a promising non-invasive molecular biomarker for prognostic stratification in AML.

Gut microbiota as a prognostic biomarker for unresectable hepatocellular carcinoma treated with anti-PD-1 therapy.

To investigate the relationship between the gut microbiome and the response to anti-PD-1-based combination therapy in unresectable hepatocellular carcinoma (HCC). We aimed to identify potential non-invasive biomarkers and new strategies to modulate immunotherapy in HCC. In this study, fresh stool samples and clinical data were collected from unresectable HCC patients treated with anti-PD-1-based combination therapy at the Cancer Hospital of the Chinese Academy of Medical Sciences between January 2020 and December 2021. The patients were divided into two groups based on their response to treatment: the treatment responder group (R group) and the treatment non-responder group (NR group). The composition and diversity of the gut microbiome were bioinformatically analyzed by using the Whole Genome Shotgun strategy, including taxonomic composition analysis, Alpha diversity analysis, Beta diversity analysis, and differentially enriched bacterial taxa analysis. Differentially enriched bacterial taxa between R and NR groups were identified based on the magnitude of the linear discriminant analysis effect size (LEfSe) and analyzed for their impact on the survival of the patient. A total of 45 eligible patients with unresectable HCC treated with anti-PD-1-based combination therapy participated in this study. The gut microbiological composition and Alpha diversity of patients were not statistically different, but there was a statistically significant difference in Beta diversity between the R and NR groups. (PERMANOVA tests, P = 0.006). We further identified 56 enriched bacterial taxa in the R group and 44 enriched bacterial taxa in the NR group based on the LEfSe analysis (LDA >2.66, P< 0.05). Patients with a high abundance of Collinsella genus, Ruminococcus_AM4211, and Ruminococcus_AF25_28AC had a longer median PFS and median OS compared to those with low abundance (P < 0.05). On the contrary, the median PFS and OS of patients with a high abundance of Bacteroides_AF20_13LB and Veillonella_atypica were significantly shorter than those of patients with low abundance (P < 0.05). The multivariate analysis showed that the abundance of Bacteroides_AF20_13LB and Ruminococcus_ AF25_28AC was independent related factors for PFS, and the abundance of Bacteroides_AF20_13LB was an independent related factor of OS. The enrichment of specific gut microbiota affected clinical efficacy and survival benefits in HCC treated with anti-PD-1 therapy and may be a promising non-invasive gut microbial biomarker and a new strategy for modulating immunotherapy in HCC.

Fecal calprotectin measurement as a biomarker of severe disease phenotype in celiac disease and non-celiac enteropathies

BackgroundFecal calprotectin (FC) is a non-invasive biomarker of gut inflammation, but its role in celiac disease (CD) and non-celiac enteropathies (NCEs) is undefined. AimsTo retrospectively evaluate FC in patients with CD and NCEs as a tool for assessing disease activity and predicting long-term outcomes. MethodsPatients with uncomplicated and complicated CD, and NCEs with data on FC, evaluated at our center between June-2008 and December-2023, were enrolled. The relationship between elevated FC (>50 mg/kg) and disease activity was statistically analysed and Cox regression adjusted for age and sex was used to compare development of complications and mortality in patients with elevated and normal FC. Results177 patients (109F, mean age at diagnosis 39±20 years, 132 CD, 17 complicated CD, 28 NCEs) were enrolled. 55 patients had elevated FC, which was associated with lack of clinical and histological response to therapy (both p < 0.001). During a median follow-up of 103 months (IQR 54–176), 22 patients developed complications (15.4 %) and 21 died (11.9 %). Elevated FC was significantly more common in complicated CD (70.6 %) and NCEs (67.9 %) than in uncomplicated CD (18.2 %), p < 0.001. Elevated FC was independently predictive of developing complications (HR 4.8,95 %CI 1.4–17.7, p = 0.01) and mortality (HR 4.8,95 %CI 1.6–14.3, p < 0.01). ConclusionFC is a promising non-invasive biomarker for assessing disease severity and long-term outcomes in CD and NCEs.

Advancements and Challenges in Biomarkers for Colorectal Cancer Detection: A Comprehensive Review

This study provides an overview of the current landscape of biomarkers for colorectal cancer (CRC) detection, focusing on genetic, proteomic, circulating microRNA (miRNA), and metabolomic biomarkers. CRC remains a significant global health challenge, ranking among the most prevalent cancers worldwide and being a leading cause of cancer-related deaths. Despite advancements in screening methods such as colonoscopy, sigmoidoscopy, and fecal occult blood tests (FOBT), the asymptomatic nature of early-stage CRC often results in late diagnoses, negatively impacting patient outcomes. Genetic biomarkers like APC, KRAS, TP53, and microsatellite instability (MSI) play critical roles in CRC pathogenesis and progression. These biomarkers, detectable through polymerase chain reaction, next-generation sequencing, and other advanced techniques, guide early detection and personalized treatment decisions. Proteomic biomarkers such as CEA, CA 19-9, and novel signatures offer insights into CRC’s physiological changes and disease status, aiding prognosis and treatment response assessments through enzyme-linked immunosorbent assay and mass spectrometry. Circulating miRNAs, including miR-21 and miR-92a, present promising non-invasive biomarkers that can be detected in blood and stool samples, reflecting CRC presence, progression, and therapeutic response. Metabolomic biomarkers, encompassing amino acids, lipids, and TCA cycle intermediates, provide further insights into CRC-associated metabolic alterations, which are crucial for early detection and treatment monitoring using mass spectrometry and nuclear magnetic resonance. Despite these advancements, challenges such as biomarker validation, standardization, and clinical utility remain. Future research directions include integrating multi-omics approaches and leveraging technologies like liquid biopsies and AI for enhanced biomarker discovery and clinical application. By addressing these challenges and advancing research in biomarker development, CRC screening and management could potentially be revolutionized, improving patient outcomes and reducing the global burden of this disease.

Application of graft-derived cell-free DNA for solid organ transplantation.

Monitoring the status of grafts and the occurrence of postoperative complications, such as rejection, is crucial for ensuring the success and long-term survival of organ transplants. Traditional histopathological examination, though effective, is an invasive procedure and poses risks of complications, making frequent use impractical. In recent years, graft-derived cell-free DNA (gd-cfDNA) has emerged as a promising non-invasive biomarker. It not only provides early warnings of rejection and other types of graft injury but also offers important information about the effectiveness of immunosuppressive therapy and prognosis. gd-cfDNA shows potential in the monitoring of organ transplants. The early, real-time information on graft injury provided by gd-cfDNA facilitates timely individualized treatment and improves patient outcomes. However, the progress of research on gd-cfDNA varies across different organs. Therefore, this article will comprehensively review the application and findings of gd-cfDNA in monitoring various solid organs, discussing the advantages, limitations, and some future research directions to aid in its clinical application.

Surface protein analysis of breast cancer exosomes using visualized strategy on centrifugal disk chip

Breast cancer, the most common cancer among women worldwide, lacks specific tumor markers for accurate diagnosis. Recent advances have highlighted tumor-derived exosomes as a promising non-invasive biomarker for cancer detection. Continuous monitoring of surface protein markers on exosomes in the blood could offer valuable insights for breast cancer diagnosis. However, integrating the isolation and detection of exosomes from whole blood is bulky, time-consuming, and requires professional operations. To address this difficulty, we developed a method of integrated centrifugal disk chip (CD chip) exosome enrichment directly from whole blood followed by a colorimetric visualization strategy for multiplex analysis. The disc consists of multi-chambers and multi-microchannels with immediate smartphone-enabled processing of colorimetric results. The combination of CEA + CA125 + EGFR on-chip detection could significantly differentiate the different stages of cancer in tumor-bearing mice and successfully distinguish between breast cancer patients and healthy individuals. Crucially, small volumes (100 μL) of blood samples were adequate. In addition, the chip was simple and fast, with results within 10 min, which provides immediate exosomal information through consecutive blood sampling, which could potentially result in a more timely and well-informed clinical breast cancer diagnosis.

Identification and evaluation of a serum microRNA panel to diagnose colorectal cancer patients.

Screening plays a crucial role in the early detection of colorectal cancer, greatly reducing mortality rates. The objective of this study was to identify a non-invasive diagnostic method utilizing serum microRNA expression for the diagnosis of colorectal cancer patients. The study consisted of three stages. In the first stage, 129 patients with colorectal cancer and 129 normal subjects were recruited as the training set for the development of a blood miRNA panel. The second stage involved recruiting 200 patients from each group as the validation cohort. Finally, a blinded study was conducted in the third stage, with 260 patients recruited to determine the predictive value of our miRNA panel. Serum samples were prospectively collected from colorectal cancer patients and normal subjects between 2017 and 2021 at Queen Mary Hospital in Hong Kong. Quantitative PCR was utilized to detect the serum levels of candidate microRNAs, and a multiple linear regression model was employed to formulate a serum microRNA panel for diagnosing colorectal cancer patients. The performance of the panel was evaluated using ROC analysis. Our study showed that the values of three pairs of serum microRNAs, namely miR-106b-5p/miR-1246, miR-106b-5p/miR-16 and miR-106b-5p/miR-21-5p, exhibited statistically significant differences between colorectal cancer patients and normal subjects. A serum microRNA panel formulated from these three pairs of microRNAs demonstrated high accuracy in diagnosing colorectal cancer patients from normal subjects, with an AUC of approximately 0.9. The serum miRNA test proved to be a feasible and promising non-invasive biomarker for the diagnosis of colorectal cancer patients in comparison to normal subjects.

5-Hydroxymethylcytosines in circulating cell-free DNA as a diagnostic biomarker for nasopharyngeal carcinoma

ObjectiveTo evaluate the diagnostic value of 5-hydroxymethylcytosines (5hmC) in circulating cell-free DNA (cfDNA) for nasopharyngeal carcinoma (NPC) and to develop a diagnostic model. MethodsGenome-wide 5hmC profiles in cfDNA from 174 NPC patients and 146 non-cancer individuals were analyzed using the 5hmC-Seal technique. A cfDNA 5hmC-based diagnostic model to identify NPC patients was developed using least absolute shrinkage and selection operator (LASSO) logistic regression, and performance was evaluated with receiver operating characteristic (ROC) curves and confusion matrices. ResultsThe 5hmC-Seal data from patients with NPC showed a different genome-wide distribution than non-tumor samples. Our initial analysis revealed a 12-gene-based 5hmC marker panel to be an accurate diagnostic model effectively distinguishing between NPC samples and non-cancerous samples (training set: area under curve (AUC)= 0.97 [95 % CI: 0.94–0.99]; and test set: AUC= 0.93 [95 % CI: 0.88–0.98]) superior to EBV DNA testing. The diagnostic score performed well in differentiating the non-cancer subjects from early-stage NPC (training set: AUC=0.99 [95 % CI: 0.98–1]; test set: AUC=0.98 [95 % CI: 0.95–1]), and advanced-stage NPC (training set: AUC=0.96 [95 % CI: 0.93–0.99]; test set: AUC=0.93 [95 % CI: 0.88–0.98]). Notably, in EBV-negative patients, the diagnostic scores showed excellent capacity for distinguishing EBV-negative patients with NPC from non-cancer subjects in both the training set (AUC= 0.94 [95 % CI: 0.88–1]) and test set (AUC=0.91 [95 % CI: 0.81–1]). Conclusion5hmC modifications in cfDNA are promising noninvasive biomarkers for NPC, offering high sensitivity and specificity, particularly for early-stage and EBV-negative NPC.

A novel tumor-derived exosomal gene signature predicts prognosis in patients with pancreatic cancer.

Pancreatic cancer is a devastating disease with poor prognosis. Accumulating evidence has shown that exosomes and their cargo have the potential to mediate the progression of pancreatic cancer and are promising non-invasive biomarkers for the early detection and prognosis of this malignancy. This study aimed to construct a gene signature from tumor-derived exosomes with high prognostic capacity for pancreatic cancer using bioinformatics analysis. Gene expression data of solid pancreatic cancer tumors and blood-derived exosome tissues were downloaded from The Cancer Genome Atlas (TCGA) and ExoRBase 2.0. Overlapping differentially expressed genes (DEGs) in the two datasets were analyzed, followed by functional enrichment analysis, protein-protein interaction networks, and weighted gene co-expression network analysis (WGCNA). Using the least absolute shrinkage and selection operator (LASSO) regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was constructed based on the TCGA dataset, which was validated by an external validation dataset, GSE62452. The prognostic power of this gene signature and its relationship with various pathways and immune cell infiltration were analyzed. A total of 166 overlapping DEGs were identified from the two datasets, which were markedly enriched in functions and pathways associated with the cell cycle. Two key modules and corresponding 70 exosomal DEGs were identified using WGCNA. Using LASSO Cox regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was built using six exosomal DEGs (ARNTL2, FHL2, KRT19, MMP1, CDCA5, and KIF11), which showed high predictive performance for prognosis in both the training and validation datasets. In addition, this prognostic signature is associated with the differential activation of several pathways, such as the cell cycle, and the infiltration of some immune cells, such as Tregs and CD8+ T cells. This study established a six-exosome gene signature that can accurately predict the prognosis of pancreatic cancer.

Using Urine Biomarkers to Differentiate Bladder Dysfunctions in Women with Sensory Bladder Disorders.

Sensory bladder disorders encompass several distinct conditions with overlapping symptoms, which pose diagnostic challenges. This study aimed to evaluate urine biomarkers for differentiating between various sensory bladder disorders, including non-Hunner's interstitial cystitis (NHIC), detrusor overactivity (DO), hypersensitive bladder (HSB), and urodynamically normal women. A retrospective analysis of 191 women who underwent a videourodynamic study (VUDS) was conducted, with some also receiving cystoscopic hydrodistention to confirm the presence of NHIC. Participants were categorized into four groups: DO (n = 51), HSB (n = 29), NHIC (n = 81), and normal controls (n = 30). The urine levels of inflammatory and oxidative stress biomarkers were measured. The DO patients exhibited elevated IP-10 levels, while the HSB patients had decreased TAC and 8-OHdG levels. The NHIC patients showed lower IL-2 and higher TNF-α levels. A TNF-α ≥ 1.05 effectively identified NHIC, with an AUROC of 0.889, a sensitivity of 98.8%, and a specificity of 81.3%. An IP-10 ≥ 6.31 differentiated DO with an AUROC of 0.695, a sensitivity of 56.8%, and a specificity of 72.3%. An 8-OHdG ≤ 14.705 and a TAC ≤ 528.7 identified HSB with AUROCs of 0.754 and 0.844, respectively. The combination of 8-OHdG and TAC provided an AUROC of 0.853 for HSB. These findings suggest that TNF-α, IP-10, TAC, 8-OHdG, and IL-2 are promising non-invasive biomarkers for distinguishing between these conditions, which may improve diagnosis and management.

Immune checkpoint inhibitor-associated nephritis-treatment standard.

Over the last 13 years, the use of immune checkpoint inhibitor (ICI) therapy has grown remarkably, owing to their unprecedented anti-tumor efficacy in certain tumor groups. With increased use of ICIs, we are seeing immune-related adverse events (irAEs) more frequently. Renal irAEs, such as ICI-associated acute kidney injury (ICI-AKI), are reported in 2%-5% of patients treated with ICIs, with acute tubulointerstitial nephritis (ATIN) as the most common histopathologic lesion, though various forms of glomerulonephritis have also been reported. Modifiable risk factors for ICI-AKI include concurrent use of ATIN-associated drugs, like proton pump inhibitors, non-steroidal anti-inflammatory drugs and antibiotics, and dual ICI therapy with both Cytotoxic T-lymphocyte Associated Protein 4 (CTLA-4) and Programmed Cell Death Protein 1 and its ligand (PD1/PDL-1) blockade. Kidney biopsies remain the diagnostic modality of choice, though several promising non-invasive biomarkers, which have not yet been broadly clinically validated have emerged. The treatment of ICI-AKI involves holding ICIs, discontinuation of ATIN-associated drugs and initiation of immunosuppression with corticosteroids as first-line therapy. With prompt treatment initiation, most patients achieve full or partial renal recovery, allowing for re-challenge with ICI. However, a subset of patients will require additional steroid-sparing therapies for corticosteroid-dependent or refractory ICI-AKI. Here we review developments in our understanding of the pathophysiology of ICI-AKI, the approach to diagnosis (with a focus on the emergence of novel diagnostic tools), prognostic factors and the current evidence for establishing treatment standards for ICI-AKI. As the evidence base remains largely retrospective, we identify questions that would benefit from future prospective studies in the diagnosis, management and prognostication of ICI-AKI.

Determination of global DNA methylation level by methylation-sensitive comet assay in patients with urinary bladder cancer.

DNA methylation is an important mechanism in the regulation of gene expression and maintenance of genomic integrity. Aberrant DNA methylation is an early event in carcinogenesis. DNA methyltransferase inhibitors are used to restore aberrant DNA methylation and inhibit tumor growth. Evaluation of DNA methylation level is important for an effective anti-cancer therapy. In the present study, the determination of global DNA methylation levels in patients with urinary bladder cancer was proposed. The methylation-sensitive comet assay determined the global DNA methylation level at the level of single cells. McrBC enzyme, a methylation-sensitive restriction endonuclease was used for enzymatic digestion to generate additional breaks at methylated sites. % DNA methylation level was significantly higher in patients with bladder cancer compared to the control group. The clinical performance of % DNA methylation analysis by methylation-sensitive comet assay was evaluated by ROC curve. Using the cut-off value of 6,5% DNA methylation, 92% sensitivity, and 42% specificity were obtained. In conclusion, global DNA methylation measured by methylation-sensitive comet assay may be a promising non-invasive biomarker that reduces interventional tests required in the diagnosis and follow-up of urinary bladder cancer.

I-Biomarker CaDx: A circulating miRNA-based multi-cancer detection test with generative and explainable AI for colorectal cancer.

64 Background: Colorectal cancer (CRC), the second most deadly cancer, underscores the critical need for early detection to significantly improve treatment outcomes and survival rates. Colonoscopy, flexible sigmoidoscopy, and the fecal immunochemical tests (FIT), often fail to capture early disease, significantly decreasing the survival chance. Circulating miRNA is a promising non-invasive biomarker for various cancers, including CRC. The i-Biomarker CaDx (patent pending) is an innovative multi-cancer early detection and diagnosis platform, covering 32 cancer types with an impressive accuracy rate of 99-100%. This study focuses on the effectiveness of i-Biomarker CaDx for CRC, employing significant data collection and leveraging insights from Generative AI (GenAI) and Explainable Artificial Intelligence (XAI). Methods: We collected various available datasets (e.g. GSE106817, etc.) encompassing 305 colorectal cancer patients and a matching number of healthy controls. Microarray was employed to profile circulating miRNAs. We used various classification paradigms, e.g., decision trees, neural networks, etc. Hyperparameter optimization was conducted, and the best-performing classifiers were amalgamated in the final model, weighted by their respective efficacies. We assessed i-Biomarker CaDx's performance through cross-validation and independent test sets. The XAI provided detailed insights into miRNA variations associated with personalized diagnostic. GenAI integrated the test into the screening and early detection best practice workflows and performs Functional Analysis. Results: i-Biomarker CaDx shows exceptional diagnostic accuracy of 99-100%, surpassing conventional colorectal cancer diagnostic methods like colonoscopy, flexible sigmoidoscopy, and FIT. It can also be used for personalized treatment response monitoring. I-Biomarker effectively deciphers intricate miRNA relationships relevant to colorectal cancer using XAI. Thus, our analyses shed light on miRNA patterns and their associations with colorectal cancer, enhancing the understanding of the underlying molecular complexities of the disease. It goes further by explaining the personalized cellular and molecular mechanisms involved, and it will be integrated into the corresponding medical workflows. Conclusions: Our AI-powered multi-cancer early diagnostic platform demonstrates outstanding performance in detecting CRC, surpassing traditional diagnostic methods like colonoscopy, flexible sigmoidoscopy, and FIT. XAI allows for in-depth exploration of miRNA alterations and their impact on CRC, enriching our interpretations at both the population and individual levels. These findings underscore the substantial potential of i-Biomarker CaDx as a transformative, non-invasive diagnostic tool for CRC.

Gut microbes on the risk of advanced adenomas

BackgroundMore than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC.ObjectiveTo analyze the characteristic microbes in AA.MethodsFecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and β diversity. α diversity included box diagram, and β diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed.ResultsThe abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively.ConclusionPrevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.

The diagnostic value of serum exosomal SNORD116 and SNORA21 for NSCLC patients.

Non-small cell lung cancer (NSCLC) is a widespread and serious global malignancy. This study aimed to examine the clinical relevance of serum exosomal SNORD116 and SNORA21 as novel diagnostic biomarkers for NSCLC. Serum exosomes from 226 healthy controls and 305 NSCLC patients were isolated by ultracentrifugation. Characterization of exosomes was conducted by qNano, transmission electron microscopy (TEM) and Western immunoblotting. RT-PCR revealed snoRNAs that were differentially expressed. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance. In NSCLC patients, the levels of serum exosomal SNORD116 and SNORA21 were significantly reduced compared to those in healthy controls (P < 0.0001 for both). ROC curves showed AUC values of 0.738 and 0.761. By combining SNORD116 and SNORA21 with traditional blood biomarkers CYFRA21-1 and carcinoembryonic antigen (CEA), the AUC increased to 0.917. Moreover, these two exosomal snoRNAs distinguished between patients with metastatic NSCLC (n = 132) and those with non-metastatic NSCLC (n = 173) significantly (P < 0.0001 for both). The ROC curves gave AUC values of 0.743 and 0.694, respectively. The combined analysis raised the AUC to 0.751. The diagnostic power of these two exosomal snoRNAs combined with CYFRA21-1 and CEA increased to 0.784. This study demonstrated that serum exosomal SNORD116 and SNORA21 can be used as potential promising non-invasive diagnostic biomarkers for NSCLC.

Vaginal microbiome dysbiosis as a novel noninvasive biomarker for detection of chronic endometritis in infertile women.

To identify the vaginal microbial signature in women with chronic endometritis (CE) and investigate the potential of vaginal microbiome characterization as a novel diagnostic tools for CE. A cross-sectional study was conducted to compare the characteristics of the vaginal microbiome in 98 women who underwent endometrial biopsy for routine clinical inspection of infertility (49 women diagnosed with CE and 49 with non-CE). The vaginal microbiome was analyzed using 16S ribosomal RNA gene amplicon sequencing. The study included an analysis of diversity, bacterial abundance, and microbial function. In addition, microbial markers were identified, and a CE classifier was developed. The relative abundances of genera, including Bifidobacterium, Prevotella and Gardnerella, were found to be different between the two groups. Analysis of the Kyoto Encyclopedia of Genes and Genomes pathways reported differential expression in metabolism-related pathways in the two groups. We identified four microbial markers of CE (Enterobacter, Prevotella, Faecalibacterium, and Phascolarctobacterium) and developed a predictive classifier for diagnosing CE, achieving an area under the curve of 83.26%. The results of the current study revealed that, compared with the non-CE controls, patients with CE have a different vaginal microbiota, highlighting the diagnostic significance of the vaginal microbiome as a promising noninvasive biomarker in detecting CE.