Metabolomic liquid biopsy dynamics predict early-stage HCC and actionable candidates of human hepatocarcinogenesis
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ORGANISM(S): Homo sapiens (human)
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PROVIDER: S-BSST1808 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Lung cancer is the leading cause of cancer-associated deaths worldwide. Surgery is the standard treatment for early-stage non-small cell lung cancer (NSCLC). However, 30% to 80% of these patients will die within 5 yearS of diagnosis. Circulating cell-free DNA (cfDNA) harbors pathologic characteristics of the original tumor, such as gene mutations or epigenetic alterations. Analysis of cfDNA has revolutionized the clinical care of advanced lung cancer patients undergoing targeted therapies. However, the low concentration of cfDNA in the blood of early-stage NSCLC patients has hampered its use for management of early disease. Continuing development of more specific and sensitive techniques for detection and analysis of cfDNA will soon enable its leverage in early stage and, perhaps, even screening settings. Therefore, cfDNA analysis may become a tool used for routine NSCLC diagnosis and for monitoring tumor burden, as well as for identifying hidden residual disease. In this review, we will focus on the current evidence of cfDNA in patients with early-stage NSCLC, new and upcoming approaches to identify circulating-tumor biomarkers, their clinical applications and future directions.
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Project description:Liquid biopsy-based biomarkers, including microRNAs packaged within extracellular vesicles, are promising tools for patient management. The cytokine tumor necrosis factor-like weak inducer of apoptosis (TWEAK) is related to PCa progression and is found in the semen of patients with PCa. TWEAK can induce the transfer of exo-oncomiRNAs from tumor cells to body fluids, and this process might have utility in non-invasive PCa prognosis. We investigated TWEAK-regulated exo-microRNAs in semen and in post-digital rectal examination urine from patients with different degrees of PCa aggressiveness. We first identified 14 exo-oncomiRNAs regulated by TWEAK in PCa cells in vitro, and subsequently validated those using liquid biopsies from 97 patients with PCa. Exo-oncomiR-221-3p, -222-3p and -31-5p were significantly higher in the semen of high-risk patients than in low-risk peers, whereas exo-oncomiR-193-3p and -423-5p were significantly lower in paired samples of post-digital rectal examination urine. A panel of semen biomarkers comprising exo-oncomiR-221-3p, -222-3p and TWEAK was designed that could correctly classify 87.5% of patients with aggressive PCa, with 85.7% specificity and 76.9% sensitivity with an area under the curve of 0.857. We additionally found that TWEAK modulated two exo-oncomiR-221-3p targets, TCF12 and NLK. Overall, we show that liquid biopsy detection of TWEAK-regulated exo-oncomiRNAs can improve PCa prognosis prediction.
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Project description:MotivationThe analysis of circulating cell-free DNA (cfDNA) holds immense promise as a non-invasive diagnostic tool across various human conditions. However, extracting biological insights from cfDNA fragments entails navigating complex and diverse bioinformatics methods, encompassing not only DNA sequence variation, but also epigenetic characteristics like nucleosome footprints, fragment length, and methylation patterns.ResultsWe introduce Liquid Biopsy Feature extract (LBFextract), a comprehensive package designed to streamline feature extraction from cfDNA sequencing data, with the aim of enhancing the reproducibility and comparability of liquid biopsy studies. LBFextract facilitates the integration of preprocessing and postprocessing steps through alignment fragment tags and a hook mechanism. It incorporates various methods, including coverage-based and fragment length-based approaches, alongside two novel feature extraction methods: an entropy-based method to infer TF activity from fragmentomics data and a technique to amplify signals from nucleosome dyads. Additionally, it implements a method to extract condition-specific differentially active TFs based on these features for biomarker discovery. We demonstrate the use of LBFextract for the subtype classification of advanced prostate cancer patients using coverage signals at transcription factor binding sites from cfDNA. We show that LBFextract can generate robust and interpretable features that can discriminate between different clinical groups. LBFextract is a versatile and user-friendly package that can facilitate the analysis and interpretation of liquid biopsy data.Data and code availability and implementationLBFextract is freely accessible at https://github.com/Isy89/LBF. It is implemented in Python and compatible with Linux and Mac operating systems. Code and data to reproduce these analyses have been uploaded to 10.5281/zenodo.10964406.
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Project description:BackgroundPatients with un-resectable hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) are a diverse group with varying overall survival (OS). Despite the availability of several scoring systems for predicting OS, one of the unsolved problems is identifying patients who might not benefit from TACE. We aim to develop and validate a model for identifying HCC patients who would survive <6 months after their first TACE.MethodsPatients with un-resectable HCC, BCLC stage 0-B, who received TACE as their first and only treatment between 2007 and 2020 were included in this study. Before the first TACE, demographic data, laboratory data, and tumor characteristics were obtained. Eligible patients were randomly allocated in a 2:1 ratio to training and validation sets. The former was used for model development using stepwise multivariate logistic regression, and the model was validated in the latter set.ResultsA total of 317 patients were included in the study (210 for the training set and 107 for the validation set). The baseline characteristics of the two sets were comparable. The final model (FAIL-T) included AFP, AST, tumor sIze, ALT, and Tumor number. The FAIL-T model yielded AUROCs of 0.855 and 0.806 for predicting 6-month mortality after TACE in the training and validation sets, respectively, while the "six-and-twelve" score showed AUROCs of 0.751 (P < 0.001) in the training set and 0.729 (P = 0.099) in the validation sets for the same purpose.ConclusionThe final model is useful for predicting 6-month mortality in naive HCC patients undergoing TACE. HCC patients with high FAIL-T scores may not benefit from TACE, and other treatment options, if available, should be considered.
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Project description:PurposeThis study explored the potential feasibility of cell-free DNA (cfDNA) in monitoring treatment response through the measurement of chromosomal instabilities using I-scores in the context of radiation therapy (RT) for other solid tumors.Materials and methodsThis study enrolled 23 patients treated with RT for lung, esophageal, and head and neck cancer. Serial cfDNA monitoring was performed before RT, 1 week after RT, and 1 month after RT. Low-depth whole-genome sequencing was done using Nano kit and NextSeq 500 (Illumina Inc.). To measure the extent of genome-wide copy number instability, I-score was calculated.ResultsPretreatment I-score was elevated to more than 5.09 in 17 patients (73.9%). There was a significant positive correlation between the gross tumor volume and the baseline I-score (Spearman rho = 0.419, p = 0.047). The median I-scores at baseline, post-RT 1 week (P1W), and post-RT 1 month (P1M) were 5.27, 5.13, and 4.79, respectively. The I-score at P1M was significantly lower than that at baseline (p = 0.002), while the difference between baseline and P1W was not significant (p = 0.244).ConclusionWe have shown the feasibility of cfDNA I-score to detect minimal residual disease after RT in patients with lung cancer, esophageal cancer, and head and neck cancer. Additional studies are ongoing to optimize the measurement and analysis of I-scores to predict the radiation response in cancer patients.
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Project description:Lung cancer remains the leading cause of cancer death worldwide, with the majority of cases diagnosed in an advanced stage. Early-stage disease non-small cell lung cancer (NSCLC) has a better outcome, nevertheless the 5-year survival rates drop from 60% for stage IIA to 36% for stage IIIA disease. Early detection and optimized perioperative systemic treatment are frontrunner strategies to reduce this burden. The rapid advancements in molecular diagnostics as well as the growing availability of targeted therapies call for the most efficient detection of actionable biomarkers. Liquid biopsies have already proven their added value in the management of advanced NSCLC but can also optimize patient care in early-stage NSCLC. In addition to having known diagnostic benefits of speed, accessibility, and enhanced biomarker detection compared to tissue biopsy, liquid biopsy could be implemented for screening, diagnostic, and prognostic purposes. Furthermore, liquid biopsy can optimize therapeutic management by overcoming the issue of tumor heterogeneity, monitoring tumor burden, and detecting minimal residual disease (MRD), i.e., the presence of tumor-specific ctDNA, post-operatively. The latter is strongly prognostic and is likely to become a guidance in the postsurgical management. In this review, we present the current evidence on the clinical utility of liquid biopsy in early-stage lung cancer, discuss a selection of key trials, and suggest future applications.
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Project description: Not available
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Project description:PurposeWe used ultraperformance liquid chromatography coupled with quadrupole/time-of-flight tandem mass spectrometry (UPLC-Q/TOF-MS/MS) to analyze the metabolic profile of reflex tears obtained from patients with dry eye disorders.MethodsWe performed a cross-sectional study involving 113 subjects: 85 patients diagnosed with dry eye syndrome (dry eye group) and 28 healthy volunteers (control group). Reflex tears (20-30 μl) were collected from the tear meniscus of both eyes of each subject using a Schirmer I test strip. MS data were acquired with a standard workflow by UPLC-Q/TOF-MS/MS. Metabolites were quantitatively analyzed and matched with entries in the Metlin, Massbank, and HMDB databases. Least absolute shrinkage and selection operator (LASSO) regression was conducted to detect important metabolites. Multiple logistic regression was used to identify the significant metabolic biomarker candidates for dry eye syndrome. Open database sources, including the Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst, were used to identify metabolic pathways.ResultsAfter the LASSO regression and multiple logistic regression analysis, 4 of 20 metabolic biomarker candidates were significantly correlated with Ocular Surface Disease Index score, 42 of 57 with fluorescein breakup time, and 26 of 57 with fluorescein staining. By focusing on the overlap of these three sets, 48 of 51 metabolites contributed to the incidence of dry eye and there were obvious changes in different age groups. Metabolic pathway analysis revealed that the main pathways were glucose metabolism, amino acid metabolism, and glutathione metabolism.ConclusionDry eye syndrome induces changes in the metabolic profile of tears, and the trend differs with age. This evidence reveals the relationship between changes in metabolites, symptoms of dry eye syndrome, and age.
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