Global metabolomics revealed deviations from the metabolic aging clock in colorectal cancer patients.

Background: Markers of aging hold promise in the context of colorectal cancer (CRC) care. Utilizing high-resolution metabolomic profiling, we can unveil distinctive age-related patterns that have the potential to predict early CRC development. Our study aims to unearth a panel of aging markers and delve into the metabolomic alterations associated with aging and CRC. Methods: We assembled a serum cohort comprising 5,649 individuals, consisting of 3,002 healthy volunteers, 715 patients diagnosed with colorectal advanced precancerous lesions (APL), and 1,932 CRC patients, to perform a comprehensive metabolomic analysis. Results: We successfully identified unique age-associated patterns across 42 metabolic pathways. Moreover, we established a metabolic aging clock, comprising 9 key metabolites, using an elastic net regularized regression model that accurately estimates chronological age. Notably, we observed significant chronological disparities among the healthy population, APL patients, and CRC patients. By combining the analysis of circulative carcinoembryonic antigen levels with the categorization of individuals into the "hypo" metabolic aging subgroup, our blood test demonstrates the ability to detect APL and CRC with positive predictive values of 68.4% (64.3%, 72.2%) and 21.4% (17.8%, 25.9%), respectively. Conclusions: This innovative approach utilizing our metabolic aging clock holds significant promise for accurately assessing biological age and enhancing our capacity to detect APL and CRC.

Targeted Therapy of Lung Adenocarcinoma by the Nanoplatform Based on Milk Exosomes Loaded with Paclitaxel.

Lung cancer is the most common cancer throughout the world. Currently, most lung cancer therapies are still limited by serious side effects caused. This paper reports a biocompatible drug delivery system that utilizes milk-derived exosomes to deliver paclitaxel to treat lung adenocarcinoma. First, milk-derived exosomes were modified with integrin αVß3, αVß5-binding peptide iRGD so that they could successfully target lung adenocarcinoma cells. Then, iRGD modified exosomes were loaded with paclitaxel (PAC) via electroporation and used for tumor therapy. These modified exosomes proved effective in killing lung adenocarcinoma cells, and the exosome-based nanoplatform showed no obvious toxicity to normal cells. Further more, the exosome-based nanoplatform could effectively penetrate the interior of the 3D tumor sphere, reaching more tumor cells and demonstrating that it is a promising tool for lung adenocarcinoma therapy.

Multi-Omics Signatures Link to Ticagrelor Effects on Vascular Function in Patients With Acute Coronary Syndrome.

BACKGROUND: Long-term antiplatelet agents including the potent P2Y12 antagonist ticagrelor are indicated in patients with a previous history of acute coronary syndrome. We sought to compare the effect of ticagrelor with that of aspirin monotherapy on vascular endothelial function in patients with prior acute coronary syndrome. METHODS: This was a prospective, single center, parallel group, investigator-blinded randomized controlled trial. We randomized 200 patients on long-term aspirin monotherapy with prior acute coronary syndrome in a 1:1 fashion to receive ticagrelor 60 mg BD (n=100) or aspirin 100 mg OD (n=100). The primary end point was change from baseline in brachial artery flow-mediated dilation at 12 weeks. Secondary end points were changes to platelet activation marker (CD41_62p) and endothelial progenitor cell (CD34/133) count measured by flow cytometry, plasma level of adenosine, IL-6 (interleukin-6) and EGF (epidermal growth factor), and multi-omics profiling at 12 weeks. RESULTS: After 12 weeks, brachial flow-mediated dilation was significantly increased in the ticagrelor group compared with the aspirin group (ticagrelor: 3.48±3.48% versus aspirin: -1.26±2.85%, treatment effect 4.73 [95% CI, 3.85-5.62], P<0.001). Nevertheless ticagrelor treatment for 12 weeks had no significant effect on platelet activation markers, circulating endothelial progenitor cell count or plasma level of adenosine, IL-6, and EGF (all P>0.05). Multi-omics pathway assessment revealed that changes in the metabolism and biosynthesis of amino acids (cysteine and methionine metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis) and phospholipids (glycerophosphoethanolamines and glycerophosphoserines) were associated with improved brachial artery flow-mediated dilation in the ticagrelor group. CONCLUSIONS: In patients with prior acute coronary syndrome, ticagrelor 60 mg BD monotherapy significantly improved brachial flow-mediated dilation compared with aspirin monotherapy and was associated with significant changes in metabolomic and lipidomic signatures. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03881943.

A "quasi" confocal droplet reader based on laser-induced fluorescence (LIF) cytometry for highly-sensitive and contamination-free detection.

Highly-sensitive and contamination-free droplet digital PCR (ddPCR) is an enabling technology and widely needed for accurate quantification of nucleic acid in clinical applications. In this paper, a novel droplet reader was developed by combining a "quasi" confocal laser-induced fluorescence (LIF) cytometry with a delicate microfluidic chip design. The droplets with a size of 90 µm was illuminated at an out-of-focus position by two aligned laser beams to generate maximum fluorescent signal. Additionally, the lateral offset position of the microfluidic chip should be precisely tuned so that the bandwidth of the FAM and VIC channels were configured at the matching sizes. Then, PMT gain voltages and pneumatic pressures were optimized for better droplet detection efficiencies. An aerosol adsorption experiment was performed to demonstrate that there was no aerosol contamination, and detected copy numbers of both mutants and wild types scaled linearly with the expected input copy numbers (r2>0.998) with a LoB of 0.0 copies and LoD of 3.0 copies. The results demonstrated that this droplet reader with the delicate chip is a convenient, highly-sensitive and contamination-free to detect fluorescence signals inside droplets after ddPCR, which is highly promising for broad applications of ddPCR in clinical diagnosis.

A density-watershed algorithm (DWA) method for robust, accurate and automatic classification of dual-fluorescence and four-cluster droplet digital PCR data.

Droplet digital PCR (ddPCR) is a single-molecule amplification technology with broad applications in precision medicine and clinical diagnosis. Dual-fluorescence and four-cluster ddPCR (two/four-ddPCR) assay is an effective way to quantify copy numbers. Currently, two/four-ddPCR data are usually classified with manual thresholds. For clinical applications, automatic and accurate methods are required to avoid subjectivity in diagnosis. Although there are some automatic classification algorithms, their accuracy and robustness still need to be improved to meet the needs of clinical diagnosis. Therefore, a new method is in high demand to automatically classify two/four-ddPCR data in an accurate and robust way. Here, a novel density-watershed algorithm (DWA) method was developed for the accurate, automatic and unsupervised classification of two/four-ddPCR data. First, data gridding was applied to a scatter plot of the fluorescence signal intensity to calculate data densities. Based on the data densities, the watershed algorithm was used to divide the gridded scatter plot into isolated regions automatically. Next, an optimal cluster pattern was determined based on these isolated regions, and excess regions were merged. Finally, the two/four-ddPCR data were classified based on the merged regions, and DNA template copy numbers were calculated accordingly. Using the DWA method for the quantification of both wild types and mutants of epidermal growth factor receptor (EGFR) L858R and T790M, the classification results were highly consistent with expectations, and significantly better than commonly-used automatic algorithms for now. The computed template copy numbers scaled proportionally to the relative concentration of input templates (r2 > 0.998) in four orders of magnitude with a good reproducibility, and achieved a limit of detection over 40 times lower than the commonly-used automatic algorithms. Furthermore, the DWA method was validated on 254 clinical DNA samples derived from frozen tissues, formalin-fixed paraffin-embedded tissues and peripheral blood. In most cases, the DWA method derived accurate and valid classification results. This highly effective DWA method may be widely used for automatically classifying two/four-ddPCR data, and it will greatly promote the application of ddPCR in clinical diagnosis.

Rapid and efficient isolation and detection of extracellular vesicles from plasma for lung cancer diagnosis.

Extracellular vesicles (EVs) are cell-derived nanoscale vesicles that provide promising biomarkers for the non-invasive diagnosis of cancer because they carry important cancer-related DNA, RNA and protein biomarkers. However, the clinical application of EVs is limited by tedious and non-standardized isolation methods that require bulky instrumentation. Here, we propose an easy-to-operate, simple dielectrophoretic (DEP) method for EV isolation with higher recovery efficiency (>83%) and higher purity than ultracentrifugation (UC). The DEP chip reduces the isolation procedure from 8 h to 30 min. To facilitate subsequent analysis, our DEP chip achieved integration of EV isolation and in situ lysis of EVs for the first time. Our chip also achieved on-chip siRNA delivery to EVs isolated by DEP. We found that EVs isolated from the plasma of lung cancer patients contained higher levels of miR-21, miR-191 and miR-192 compared to those from healthy people. With on-chip detection, EGFR in EVs could distinguish lung cancer patients from healthy people. Overall, this study provides an efficient and practical approach to the isolation and detection of EVs, which could be used for the early diagnosis of lung cancer.