Promising Non-invasive Biomarker Research Articles

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.

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.

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.

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.

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.

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.

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...

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.

Serum miRNA-1 may serve as a promising noninvasive biomarker for predicting treatment response in breast cancer patients receiving neoadjuvant chemotherapy

BackgroundMicroRNA-1 (miR-1) is a tumour suppressor that can inhibit cell proliferation and invasion in several cancer types. In addition, miR-1 was found to be associated with drug sensitivity. Circulating miRNAs have been proven to be potential biomarkers with predictive and prognostic value. However, studies of miR-1 expression in the serum of breast cancer (BC) patients are relatively scarce, especially in patients receiving neoadjuvant chemotherapy (NAC).MethodsSerum samples from 80 patients were collected before chemotherapy, and RT-PCR was performed to detect the serum expression of miR-1. The correlation between miR-1 expression in serum and clinicopathological factors, including pathological complete response (pCR), was analyzed by the chi-squared test and logistic regression. KEGG and GSEA analysis were also performed to determine the biological processes and signalling pathways involved.ResultsThe miR-1 high group included more patients who achieved a pCR than did the miR-1 low group (p < 0.001). Higher serum miR-1 levels showed a strong correlation with decreased ER (R = 0.368, p < 0.001) and PR (R = 0.238, p = 0.033) levels. The univariate model of miR-1 for predicting pCR achieved an AUC of 0.705 according to the ROC curve. According to the interaction analysis, miR-1 interacted with Ki67 to predict the NAC response. According to the Kaplan–Meier plot, a high serum miR-1 level was related to better disease-free survival (DFS) in the NAC cohort. KEGG analysis and GSEA results indicated that miR-1 may be related to the PPAR signalling pathway and glycolysis.ConclusionsIn summary, our data suggested that miR-1 could be a potential biomarker for pCR and survival outcomes in patients with BC treated with NAC.

Protocol and rationale of the Australian multicentre registry for serial cardiac computed tomography angiography (ARISTOCRAT): a prospective observational study of the natural history of pericoronary adipose tissue attenuation and radiomics.

Vascular inflammation plays a crucial role in the development of atherosclerosis and atherosclerotic plaque rupture resulting in acute coronary syndrome (ACS). Pericoronary adipose tissue (PCAT) attenuation quantified from routine coronary computed tomography angiography (CCTA) has emerged as a promising non-invasive imaging biomarker of coronary inflammation. However, a detailed understanding of the natural history of PCAT attenuation is required before it can be used as a surrogate endpoint in trials of novel therapies targeting coronary inflammation. This article aims to explore the natural history of PCAT attenuation and its association with changes in plaque characteristics. The Australian natuRal hISTOry of periCoronary adipose tissue attenuation, RAdiomics and plaque by computed Tomographic angiography (ARISTOCRAT) registry is a multi-centre observational registry enrolling patients undergoing clinically indicated serial CCTA in 9 centres across Australia. CCTA scan parameters will be matched across serial scans. Quantitative analysis of plaque and PCAT will be performed using semiautomated software. The primary endpoint is to explore temporal changes in patient-level and lesion-level PCAT attenuation by CCTA and their associations with changes in plaque characteristics. Secondary endpoints include evaluating: (I) impact of statin therapy on PCAT attenuation and plaque characteristics; and (II) changes in PCAT attenuation and plaque characteristics in specific subgroups according to sex and risk factors. ARISTOCRAT will further our understanding of the natural history of PCAT attenuation and its association with changes in plaque characteristics. This study has been prospectively registered with the Australia and New Zealand Clinical Trials Registry (ACTRN12621001018808).

Lipopolysaccharide-binding protein in Crohn's disease patients: a promising noninvasive biomarker monitoring disease activity.

Following STRIDE-II recommendations, the discovery of novel noninvasive biomarkers, beyond the use of C-reactive protein (CRP) and fecal calprotectin, remains a medical need to further improve the monitoring of patients with inflammatory bowel disease (IBD). This study aims to evaluate the potential of serum lipopolysaccharide-binding protein (LBP) in monitoring IBD activity. This retrospective cross-sectional study included 69 IBD patients (43 Crohn's disease and 26 ulcerative colitis) and 82 controls. Serum LBP levels were measured by ELISA. Clinical, biological and endoscopic parameters were analyzed for IBD patients with no reports of missing data. Statistical tests, including nonparametric tests and receiver operating characteristic (ROC) curve analysis, were used to evaluate the diagnostic accuracy of LBP. IBD patients displayed a significantly higher LBP median [29.6 μg/ml (19.8-38.8) in Crohn's disease and 22.8 (13.7-38.8) in ulcerative colitis] than controls [5.8 (4.7-7.3), P < 0.001] with little overlapping distributions. In Crohn's disease patients, LBP levels gradually increased with endoscopic activity scores demonstrating a 1.7-fold rise in active patients compared to remitter patients ( P = 0.02). LBP level exhibited a positive correlation with CRP ( ρ = 0.75, P < 0.001) as well as fecal calprotectin ( ρ = 0.42, P < 0.01), both of which further increased when excluding cases that did not match endoscopic activity. LBP might be a promising noninvasive biomarker for monitoring disease activity, especially in Crohn's disease patients. In clinical situations where current biomarkers lack sensitivity, LBP could be discriminative and help filling the gap for reliable therapeutic decisions.

FinaleToolkit: Accelerating Cell-Free DNA Fragmentation Analysis with a High-Speed Computational Toolkit.

Cell-free DNA (cfDNA) fragmentation pattern represents a promising non-invasive biomarker for disease diagnosis and prognosis. Numerous fragmentation features, such as end motif and window protection score (WPS), have been characterized in cfDNA genomic sequencing. However, the analytical tools developed in these studies are often not released to the liquid biopsy community or are inefficient for genome-wide analysis in large datasets. To address this gap, we have developed FinaleToolkit, a fast and memory efficient Python package designed to generate comprehensive fragmentation features from large cfDNA genomic sequencing data. For instance, FinaleToolkit can generate genome-wide WPS features from a ~100X cfDNA whole-genome sequencing (WGS) dataset in 1.2 hours using 16 CPU cores, offering up to a ~50-fold increase in processing speed compared to original implementations in the same dataset. We have benchmarked FinaleToolkit against original studies or implementations where possible, confirming its efficacy. Furthermore, FinaleToolkit enabled the genome-wide analysis of fragmentation patterns over arbitrary genomic intervals, significantly boosting the performance for cancer early detection. FinaleToolkit is open source and thoroughly documented with both command line interface and Python application programming interface (API) to facilitate its widespread adoption and use within the research community: https://github.com/epifluidlab/FinaleToolkit.

Application of ctDNA sequencing in patients with metastasized lung cancer.

e20033 Background: Circulating tumor DNA (ctDNA) is a form of cell-free DNA (cfDNA) found in blood that originates from tumor cells, which has emerged as a promising non-invasive biomarker in monitoring cancer prognosis and precision medicine with the advancement of deep sequencing. Here we compared the mutational landscape between solid tumor and cfDNA in metastasis-free and metastasized lung cancer patients using targeted NGS to investigate the feasibility of ctDNA sequencing in monitoring cancer prognosis. Methods: Blood-derived cfDNA samples and formalin-fixed paraffin embedded tissue were collected from 217 Chinese patients with metastatic lung cancer (n = 39) or metastasis-free lung cancer (n = 178). Blood samples were collected after surgery. Panel sequencing targeting 680 cancer-related genes was performed on both samples. Somatic single nucleotide variations and indels were analyzed. Results: Among the 178 metastasis-free patients, 89.3% of the patients have at least one mutation both detected in tumor and blood samples. On average, 50.4% of tumor mutations were detected in blood for each patients. EGFR, TP53, CSMD3, LRP1B and SYNE1 were the top five most frequently mutated genes, with the proportion of tumor mutation found in blood of 89.1%, 80.2%, 70.0%, 61.3% and 64.3% respectively. In the metastasized cohort, all 39 individuals have at least one tumor mutations found in blood, achieving a concordance of 100%. On average, 59.9% of tumor mutations were detected in blood for each patients. Notably, the proportion of tumor mutations detected in blood for each patients is significantly higher than the metastasis-free cohort (unpaired T-test, p = 0.0167). EGFR, TP53, RBM10, PIK3CA and CSMD3 were the top five most frequently mutated genes, with the proportion of tumor mutation found in blood of 93.5%, 80.8%, 57.1%, 83.3% and 42.9% respectively. Moreover, the proportion of patients having EGFR p.L858R mutation in metastasized cohort was higher than the metastasis-free cohort (54.3% vs 32.8%). While within the metastasized cohort, blood samples detected a higher proportion of EGFR p.T790M (12.9% vs 7.69%) but a lower proportion of EGFR exon19 deletion (p.E746_A750del, 19.4% vs 27.7%) comparing to tumor sample, which can indicate drug resistance. Conclusions: We demonstrated a high mutation detection concordance between tumor and blood using targeted NGS, with an exceptional performance especially in driver oncogenes like EGFR and TP53. Our findings showed that metastasized lung cancer patients exhibit a higher positive concordance rate compared to metastasis-free cohort using ctDNA. We also showed a varied mutational landscape between ctDNA and tumor sequencing in metastasized lung cancer patients. Overall, this study not only reaffirms the viability of using blood as an alternative of tissue biopsy, but also provides new insights on application of ctDNA monitoring lung cancer metastasis and its clinically targetable mutations.

Circulating tumor DNA as a predictor of treatment response to neoadjuvant chemotherapy in stage 2/3 rectal cancer without high risks: Subset analysis from the COPEC trial.

e15623 Background: Circulating tumor DNA (ctDNA) serves as a valuable tool for minimal residual disease (MRD) assessment. It has been reported as a promising noninvasive biomarker for the dynamic monitoring of treatment response of metastatic colorectal cancers to chemotherapy and locally advanced rectal cancers (LARC) to neoadjuvant chemoradiotherapy. However, the potential role of ctDNA in neoadjuvant chemotherapy (NCT) in LARC remains unexplored. The present study aims to investigate the value of ctDNA in NCT based on a prospective, multicentered, non-inferior, randomized, controlled trial (ClinicalTrials.gov ID, NCT04922853). The COPEC trial enrolls stage 2/3 LARC with low or intermediate and is designed to determine the optimal time (after 2 or 4 cycles of CAPOX) to evaluate treatment response based on pathological regression grades. Methods: Colonoscopy biopsy was taken before neoadjuvant therapy. Peripheral blood samples were collected before neoadjuvant (baseline, BL), one cycle (C1) and two cycles (4-cycle group, C2) after NCT, before surgery (BS), and within one month after surgery (postoperative, OP). All tissue biopsy and plasma specimens were analyzed by NGS assays using the MinerVA platform (Genecast Biotechnology Co., Ltd). MRI tumor regression grade (mrTRG) was assessed after 2 and 4 cycles (4-cycle group) of NCT. The primary outcome was the accuracy of ctDNA in the prediction of pathological tumor regression grade (pTRG). Results: A total of 151 LARC patients were enrolled, including 82 in the 2-cycle group and 69 in the 4-cycle group. The ctDNA was detectable in 87.4% (132/151), 39.6% (55/139), 29.0% (18/62), 38.4% (58/151), and 4.4% (6/138) at BL, C1, C2, BS and OP, respectively. The ctDNApositivity rates were significantly lower in good responders determined by mrTRG (mrTRG 1-3) compared to mrTRG 4-5 group at C1 (29% vs. 63.89%, p &lt; 0.001), C2 (20% vs.56.25%, p = 0.011), and BS time points (23.85% vs. 74.36%, p &lt; 0.001). Furthermore, the ctDNA-positivity rates at C1 in the good response group determined by TRG (pTRG 0-1) were 6.25%, significantly lower than that in the pTRG 2-3 group (49.53%). At neither C2 nor BS time point, patients in the pTRG 0-1 subgroup were detected as ctDNA positive while the ctDNA positivity rates for patients in pTRG 2-3 subgroup were 39.13% and 50%, respectively. Additionally, the mean of hGE/ml was 0.045 in pTRG 0-1 group at C1, significantly lower comparing to 1.337 in pTRG 2-3 group (p &lt; 0.001). Conclusions: We find that dynamic monitoring of ctDNA status was a useful tool in early predicting the effect of (treatment response to) NCT in LARC patients with low/intermediate risks. The monitoring of ctDNA status can supplement MRI in determining the NCT response and could potentially help identify poor responders to discontinue the treatment with inadequate efficacy. Clinical trial information: NCT04922853 .

#1536 Serum soluble LYVE1 is a promising non-invasive biomarker of renal fibrosis: a population-based retrospective cross-sectional study

Abstract Background and Aims Diagnosis of renal fibrosis can only be verified by kidney biopsy, but biomarkers for non-invasive evaluation remain unsatisfactory. Patients with fibrosis often have abnormalities of the lymphatic vascular system and associated immune function. We describe here a lymphatic marker as a candidate biomarker for fibrosis. Method After assessing and grading the fibrosis scores, testing serum soluble lymphatic vessel endothelial hyaluronan receptor1 (sLYVE1) level, and collecting clinical information, the association between sLYVE1 and renal fibrosis was analyzed. Logistic regression analysis was used to screen variables. Diagnosis models with or without sLYVE1 were built, and nomograms were plotted. Calibration curve, C-index, and DCA were performed to assess the models. Results A total of 298 patients were enrolled in the study, of which 199 were included in the training cohort and 99 patients in the validation cohort. Serum sLYVE1 levels markedly elevated with increasing fibrosis grade (p &amp;lt; 0.05). ROC analysis of sLYVE1 showed an AUC of 0.791 and 0.846 with optimal cut-off value of 405.25 ng/mL and 498.55 ng/mL for the prediction of moderate-to-severe renal fibrosis (MSF) and severe renal fibrosis (SF), respectively (Fig. 1). The diagnostic nomogram model without sLYVE1 (model 1) included traditional clinical determinants (C-index: 0.658 for MSF; 0.603 for SF). A combination of model 1 and sLYVE1 (model 2) improved predictive performance (C-index: 0.847 for MSF; 0.856 for SF) (Figs 2 and 3). Calibration curve and DCA demonstrated a better consistency accuracy and clinical benefit of model 2 than model 1. Conclusion Serum sLYVE1 may be identified as a potential biomarker of renal fibrosis. Models incorporating sLYVE1 may be beneficial for a more accurate non-invasive diagnosis of renal fibrosis.

#1393 Urinary soluble CD163 correlates with glomerular inflammation in proliferative lupus nephritis

Abstract Background and Aims Clinical distinction between histologic activity and chronicity in lupus nephritis remains challenging. We sought to evaluate the utility of urinary soluble protein CD613 (usCD163) as a potential biomarker to reflect histologic activity in lupus nephritis (LN). Method Forty-three patients with LN with concurrent determination of usCD163 at the moment of kidney biopsy were included in the study. A first morning void prior to the kidney biopsy was collected and usCD163 was measured by a commercial ELISA assay (EUROIMMUN, Lubeck, DE). Urine CD163 values were normalized to urine creatinine and expressed as ng per mmol of urine creatinine. Results The study cohort had a mean age at the moment of kidney biopsy of 35.3 ± 12.3 years, 81.4% being females. The mean eGFR and 24-h proteinuria were 77.1 ± 33.7 ml/min/1.73 m2 and 3.28 ± 3.23 g/day, respectively. In terms of histological findings, the majority of patients had proliferative LN (class III—34.9%, class IV—34.9%, class IV+V—9.3%), while the median activity and chronicity index were 7 (IQR: 3-11) and 3 (IQR: 1-5), respectively. The median usCD163 normalized to urine creatinine was 616.4 ng/mmol (IQR: 117.6-2363.7). usCD163 significantly correlated with 24-h proteinuria (r = 0.46, p = 0.002), albumin/creatinine ratio (r = 0.61, p &amp;lt; 0.001) and C3 level (r = −0.32, p = 0.03), but not with hematuria (r = 0.26, p = 0.09) or eGFR (r = −0.27, p = 0.07). Regarding the histological parameters, usCD163 significantly correlated with the activity index (AI) and the individual active lesions (with the exception of fibrinoid necrosis), but not with chronicity index or any chronic lesion (Fig. 1). In addition, the level of usCD163 was higher in patients with proliferative LN compared to those with class II or isolated class V LN (Fig. 2). When evaluating the capacity of different variables to discriminate patients with a high AI (≥9), usCD163 outperformed classical clinical or immunological variables, with an area under the curve of 0.71 (95% CI, 0.55-0.86; p = 0.01). At a cutoff of 313 ng/mmol (Youden Index = 0.42), usCD163 had a sensitivity of 88.2% and specificity of 46% to identify patients with a high AI. Patients with an elevated level of usCD163 (≥313 ng/mmol) had higher 24-h proteinuria (4.41 ± 3.4 vs. 1.36 ± 1.74 g/day, p &amp;lt; 0.001), higher AI [10 (IQR: 6-12) vs. 3.5 (IQR: 0-6), p &amp;lt; 0.001] and more frequently class IV LN (48.1% vs. 12.5%, p = 0.02), compared to those with low levels of usCD163. In addition, 4 patients underwent repeat kidney biopsy post-induction therapy. In these patients, serial monitoring showed a normalization of usCD163 levels that paralleled a decrease in both proteinuria and AI. Conclusion Urinary soluble CD163 is a promising non-invasive biomarker for glomerular inflammation and could be used to evaluate histologic activity in patients with LN.

Accurate and highly sensitive detection of Alzheimer's disease-related extracellular vesicles via förster resonance energy transfer

Alzheimer's disease (AD) is the most common neurodegenerative disease in the world and poses a huge challenge to global healthcare. Early and accurate detection of amyloid-β (1-42) (Aβ42), a key biomarker of AD, is crucial for effective diagnosis and intervention of AD. Specific or overexpressed proteins on extracellular vesicles (EVs) describe a close correlation with the occurrence and development of diseases. EVs are a very promising non-invasive biomarker for the diagnosis of AD and other diseases. As a sensitive, simple and rapid analytical method, fluorescence resonance energy transfer (FRET) has been widely applied in the detection of EVs. Herein, we developed a dual labelling strategy for simultaneously detecting EV membrane proteins of Aβ42 and CD63 based on FRET pair consisting of Au nanoclusters (AuNCs) and polydopamine nanospheres (PDANSs). The constructed nanoprobe, termed EVMPFAP assay, could specifically measure the Aβ42 and CD63 on EVs with excellent sensitivity, high specificity and satisfactory accuracy. The limit of detection of EVMPFAP assay was 1.4 × 103 particles mL−1 and the linear range was from 104 to 108 particles mL−1. EVMPFAP assay was successfully used to analyze plasma EVs to distinguish AD and healthy mice. We expect that EVMPFAP assay can be routinely applied for early diagnosis and development-monitoring of AD, thus facilitating the fight against AD.

Multiarmed DNA jumper and metal-organic frameworks–functionalized paper-based bioplatform for small extracellular vesicle–derived miRNAs assay

Small extracellular vesicle–derived microRNAs (sEV-miRNAs) have emerged as promising noninvasive biomarkers for early cancer diagnosis. Herein, we developed a molecular probe based on three-dimensional (3D) multiarmed DNA tetrahedral jumpers (mDNA-Js)-assisted DNAzyme activated by Na+, combined with a disposable paper-based electrode modified with a Zr-MOF–rGO–Au NP nanocomplex (ZrGA) to fabricate a novel biosensor for sEV-miRNAs Assay. Zr-MOF tightly wrapped by rGO was prepared via a one-step method, and it effectively aids electron transfer and maximizes the effective reaction area. In addition, the mechanically rigid, and nanoscale-addressable mDNA-Js assembled from the bottom up ensure the distance and orientation between fixed biological probes as well as avoid probe entanglement, considerably improving the efficiency of molecular hybridization. The fabricated bioplatform achieved the sensitive detection of sEV-miR-21 with a detection limit of 34.6 aM and a dynamic range from100 aM to 0.2 µM. In clinical blood sample tests, the proposed bioplatform showed results highly consistent with those of qRT-PCRs and the signal increased proportionally with the NSCLC staging. The proposed biosensor with a portable wireless USB-type analyzer is promising for the fast, easy, low-cost, and highly sensitive detection of various nucleic acids and their mutation derivatives, making it ideal for POC biosensing.