Biomarkers最新文献

Background and objectives: Prior studies have shown that small non-coding RNAs (sncRNAs) are associated with cancer occurrence or development. Recently, a newly discovered class of small ncRNAs known as PIWI-interacting RNAs (piRNAs) have been found to play a vital role in physiological processes and cancer initiation. This study aims to utilize piRNAs as innovative, noninvasive diagnostic biomarkers for breast cancer. Our objective is to develop computational methods that leverage piRNA attributes for breast cancer prediction and its application in diagnostics.

Methods: We created a set of piRNA sequence descriptors using information extracted from the piRNA sequences. To ensure accuracy, we found a path to convert non-standard piRNA to standard names to enable precise identification of these sequences. Using these descriptors, we applied machine-learning (ML) techniques in WEKA (Waikato Environment for Knowledge Analysis) to a dataset of piRNA to assess the predictive accuracy of the following classifiers: Logistic Regression model, Sequential Minimal Optimization (SMO), Random Forest classifier, and Logistic Model Tree (LMT). Furthermore, we performed Shapley additive explanations (SHAP) Analysis to understand which descriptors were the most relevant to the prediction accuracy. The ML models were then validated on an independent dataset to evaluate their effectiveness in predicting breast cancer.

Results: The top three performing classifiers in WEKA were Logistic Regression, SMO, and LMT. The Logistic Regression model achieved an accuracy of 90.7% in predicting breast cancer, while SMO and LMT attained 89.7% and 85.65%, respectively.

Conclusions: Our study demonstrates the effectiveness of using ML-based piRNA classifiers in diagnosing breast cancer and contributes to the growing body of evidence supporting piRNAs as biomarkers in cancer diagnosis. However, additional research is needed to validate these findings and further assess the clinical applicability of this approach.

Background: Despite the current diagnostic and therapeutic methods for colorectal cancer (CRC), patients are often diagnosed at advanced stages of colorectal cancer. Recently, numerous investigations have highlighted the role of lncRNAs in cancer development and progression. This study investigated less well-characterized genes in the colorectal cancer metastasis process.

Materials and methods: Genes expression profiles from CRC patients were downloaded from the TCGA database by the TCGAbiolinks R package. Differential gene expression analysis of miRNA, lncRNAs, and mRNAs was conducted for the M1 and M0 compared to control samples. Then, the DIANA lncbase3 tool was used to find M1-specific miRNA-LncRNA interactions. In addition, the expression of selected genes was evaluated by Real-time RT-PCR in forty-one CRC tissues.

Results: Our analysis showed that the expression levels of 77 lncRNAs, 12 miRNAs, and 627 mRNA were significantly changed only in metastatic tumors. In experimental study, significant overexpression of LncRNAs LINC00839, LINC01006, BACE1-AS and G2E3-AS1 was confirmed in metastatic tumors. Also, ROC analysis showed that these lncRNAs, especially lncRNAs G2E3-AS1 and BACE1-AS, are good prognostic biomarkers for metastatic colorectal tumors.

Conclusion: We demonstrated that the lncRNAs G2E3-AS1 and BACE1-AS expression upregulated in CRC tissues can be good potential biomarkers for metastatic colorectal cancer.

Introduction: Adults who switch from smoking cigarettes to use of electronic nicotine delivery systems (ENDS) may reduce their exposure to harmful and potentially harmful constituents (HPHCs). This study assessed changes in exposure to HPHCs, assessed via biomarkers of exposure (BOEs), among adults who switched to a new ENDS product.

Methods: Adults who smoke cigarettes (N = 89) were randomized to: (1) switch completely to using JUUL2 Virginia Tobacco (N = 24) or Polar Menthol (N = 24); (2) continue smoking usual brand (UB) cigarettes (N = 21); or (3) abstain from all tobacco/nicotine products (N = 20) for 6 d. Changes in exposure to nicotine and 11 other HPHCs from Baseline to Day 6 were compared among study groups.

Results: Changes in nicotine exposure did not significantly differ between JUUL2 and UB Cigarette groups (ps > 0.37). Among participants who switched completely to JUUL2 products, median percent reductions (Day 6-Baseline) in non-nicotine BOEs ranged from 65% to 94%, significantly greater than changes in the UB Cigarette group (ps < 0.001). None of the non-nicotine BOEs significantly differed between the JUUL2 groups and the Abstinence group (ps > 0.025).

Conclusions: This randomized study demonstrates that adults who switch completely from smoking cigarettes to use of JUUL2 ENDS products substantially reduce their exposure to HPHCs associated with smoking-related diseases.

International standard registered clinical trial number: ISRCTN27662176.

Objective: To examine the role and diagnostic potential of miR-421 in prostate cancer (PCa).

Methods: Expression data and clinical information for miR-421 were obtained from the TCGA and Genotype-Tissue Expression (GTEx) databases. Experimental validation was performed at the cellular, blood, and tissue levels to confirm miR-421 expression and its association with clinicopathological features. ROC curves were drawn on the bioinformatic study using TCGA data. The target genes of miR-421 were predicted via four online databases, and protein interaction associations were analyzed for intersecting targets. Gene Ontology (GO) analysis was subsequently conducted to assess functional relevance.

Results: MiR-421 was significantly overexpressed in prostate cancer (PCa) patients, a finding validated in cell, blood, and tissue samples. ROC analysis on the bioinformatic study using TCGA data revealed that miR-421 reliably differentiated PCa tissues from normal tissues. Higher miR-421 expression was associated with an elevated Gleason score, advanced TNM stage, and metastasis. GO enrichment analysis indicated that the target genes of miR-421 were significantly related to diverse molecular functions.

Conclusions: MiR-421 is a promising biomarker for diagnosing and predicting PCa.

Introduction: Colorectal cancer (CRC) incidence and mortality before 50 have been rising alarmingly in the recent decades.

Methods: Using a cohort of 10,000 patients, this study investigates the clinical, mutational, and co-mutational features of CRC in early-onset (EOCRC, < 50 years) compared to late-onset (LOCRC, ≥ 50 years).

Results: EOCRC was associated with a higher prevalence of Asian and Hispanic patients, rectal or left-sided tumors (72% vs. 59%), and advanced-stage disease. Molecular analyses revealed differences in mutation patterns, with EOCRC having higher frequencies of TP53 (74% vs. 68%, p < 0.01) and SMAD4 (17% vs. 14%, p = 0.015), while BRAF (5% vs. 11%, p < 0.001) and NOTCH1 (2.7% vs. 4.1%, p = 0.01) mutations were more prevalent in LOCRC. Stratification by tumor site and MSI status highlighted significant location- and age-specific molecular differences, such as increased KRAS and CTNNB1 mutations in right-sided EOCRC and higher BRAF prevalence in MSI-H LOCRC (47% vs. 6.7%, p < 0.001). Additionally, co-occurrence analysis revealed unique mutational networks in EOCRC MSS, including significant co-occurrences of FBXW7 with NOTCH3, RB1, and PIK3R1.

Conclusion: This study highlights the significance of age-specific molecular profiling, offering insights into the unique biology of EOCRC and potential clinical applications.

Background: The Thrombolysis in Myocardial Infarction (TIMI) risk score estimates mortality for patients with ST-elevation myocardial infarction (STEMI). This study aimed to investigate whether biomarkers reflecting the neurohormonal response (pro-atrial natriuretic peptide (proANP), mid-regional pro-adrenomedullin (MR-proADM), and copeptin), inflammation (suppression of tumorigenicity 2 (ST2), C-reactive protein (CRP), and leukocytes), and troponin add prognostic value to the TIMI risk score.

Methods: This sub-study of the prospective PREDICT cohort included 1700 non-comatose and non-cardiogenic shock STEMI patients upon admission. Blood samples were collected before coronary angiography. Biomarker quartiles (Q4vsQ1-3) association with 30-day mortality were examined using Cox proportional hazard models.

Results: High levels of all biomarkers were associated with 30-day mortality independently of TIMI risk score, hazard ratio (HR)_Q4vsQ1-3 (95%CI), MR-proADM: 8.8 (3.9-20), proANP: 3.5 (1.8-6.7), copeptin: 1.9 (1.1-3.5), ST2: 4.5 (2.3-8.6), CRP: 2.6 (1.3-4.9), and leukocyte: 2.18 (1.2;4.0). TIMI risk score had a high prognostic value, AUC(95%CI): 0.76 (0.69-0.83). Only MR-proADM, proANP, CRP, ST2, and TnT added prognostic value to the risk score, 0.84 (0.77-0.91), 0.80 (0.74-0.87), 0.78 (0.71-0.86), 0.81 (0.73-0.88), and 0.79 (0.71-0.87), respectively. However, MR-proADM demonstrated a higher prognostic value on its own (0.86 (0.80-0.91)).

Conclusion: TIMI risk score and all the biomarkers added prognostic values of 30-day mortality. The strongest predictor of 30-day mortality was observed for MR-proADM alone.

Background: Mortality in patients after carotid artery stenting (CAS), a treatment approach for atherosclerotic carotid artery stenosis, is influenced by numerous factors. This study aimed to investigate the prognostic value of the Naples prognostic score (NPS), which reflects nutritional and inflammatory status, in CAS patients.

Methods: We retrospectively included 697 patients who underwent CAS from January 2016 to December 2020 at our institute. The primary endpoint of the study was long-term all-cause mortality. The study population was divided into two groups based on the NPS value: Low NPS (NPS 0-2) and high NPS (NPS 3-4). Univariable and multivariable Cox regression analysis was used to identify independent predictors of death.

Results: The median follow-up time was 60.8 (46.36-75.36) months. During the follow-up period, all-cause mortality was higher in the high-NPS group compared to the low-NPS group [54% (n = 88) vs. 24% (n = 128) p < 0.001]. Advanced age (p = 0.003), diabetes (p = 0.023), and NPS (hazard ratio: 1.83, confidence interval: 1.58-2.12, p < 0.001) were found to be independent predictors of all-cause mortality at long-term follow-up.

Conclusion: Consequently, NPS as a marker of malnutrition and inflammation, was found to be associated with long-term mortality and serves as an independent predictor of long-term mortality in patients undergoing CAS.

Background: At present, there is a lack of efficient biomarkers for the diagnosis of thyroid cancer, and the influence of natural factors such as high iodine exposure on the expression of biomarkers remains unclear.

Methods: Serum samples from papillary thyroid cancer (PTC) and non-cancer controls matched 1:1 in different iodine nutritional regions were analyzed metabolomically using an ultra-high performance liquid chromatography-Orbitrap Exploris mass spectrometry (UHPLC-OE-MS) platform. Then the data were randomly divided into training and test sets in a 1:1 ratio according to the different iodine nutritional regions and different PTC status. In the training set, differential metabolites were selected by multivariate statistical analysis methods, and the prediction models were then built using Random forest (RF), Gradient boosting machine (GBM), and Support vector machine (SVM) models. At last, their diagnostic effects were examined in the test set.

Results: PTCs were significantly separated from non-cancer samples, and a total of 37 differentially expressed metabolites were selected. The results of pathway analysis showed that the PTC-related differential metabolites were mainly involved in the sphingolipid metabolism and glycerophosphate metabolism. The prediction models constructed by the 6 screened potential biomarkers could all better identify PTCs in the test set. The metabolomic fingerprinting between PTC and non-cancer groups in different water iodine regions did not show significant disturbance. However, high iodine exposure would effect on the expression of six metabolites, reflecting in a significantly different diagnostic efficacy in different water iodine regions.

Conclusion: Serum metabolites have potential value as biomarkers of PTC, and iodine status affects the expression and even diagnostic levels of certain serum metabolites.

Background: Endoglin/CD105-microvessel density (CD105-MVD) is identified as one of the most potential methods for semi-quantification of angiogenesis in human cancer tissues. Present study aimed to examine the diagnosticand prognostic value of CD105-MVD in two clinically distinct subtypes of urothelial carcinoma of bladder (UCB) namely non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC) patients.

Methods: Message expression of endoglin was analysed by real-time quantitative polymerase chain reaction (RT-qPCR) and MVD measurement was done by immunohistochemical staining in 90 UCB [NMIBC: 60; MIBC: 30] patients. SEM studies were carried out to examine tumor vasculature and extent of neoangiogenesis in NMIBC and MIBC patients.

Results: Elevated message expression of CD105 showed statistical significance with tumor stage, grade, smoking/tobacco chewing history in NMIBC andage in MIBC cohort. Higher values of CD105-MVD showed statistical relevance with tumor stage, grade, size, smoking/tobacco chewing history in NMIBC cohort. Kaplan Meier test identified high CD105-MVD as strong predictor of poor RFS in NMIBC patients.

Conclusions: Association of CD105 expression and MVD with the clinicohistopathological features as well as poor survival outcomes potentially identify it as a preferred marker of clinical significance in a given cohort of UCB patients.Clinical significanceStrong association of CD105 at message level with the demographics of UCB patients identifies it as a marker of diagnosis in a given cohort of patients.Survival analysis examined CD105-MVD as an independent strong predictor of poor recurrence free survival in NMIBC patients.Present study provides clear evidence of increased vascular density, vascular sprouts proliferation and new blood vessel formation with disease aggressiveness indicating CD105 as a preferred marker of neoangiogenesis in the given cohort of patients.The study describes CD105-MVD as a biomarker of diagnosis and prognosis with the sensitivity of 91.67% and 93.33% in a given cohort of NMIBC and MIBC patients.

Introduction: Urine metabolomics offers a non-invasive approach to diagnose and manage inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), by identifying distinct metabolic signatures.

Objectives: This narrative review summarizes current findings on urinary metabolites in IBD, evaluating their roles in disease differentiation, assessment of activity, and monitoring therapeutic response.

Methods: A comprehensive literature search of PubMed and MEDLINE up to October 2023 was conducted using keywords, such as 'urine metabolomics', 'inflammatory bowel disease', 'Crohn's disease', 'ulcerative colitis', and 'urinary biomarkers'. Studies were included that described alterations to metabolic pathways, including those related to the urea cycle, central energy metabolism (Krebs cycle), amino acid metabolism, and neurotransmitters.

Results: Specific urinary metabolites differentiate IBD patients from healthy controls and between CD and UC. Decreased urinary levels of hippurate, acetate, methanol, formate, and methylamine are observed in IBD, indicating altered gut microbiota. In CD patients, urea cycle alterations include reduced urinary urea and ornithine with increased arginine. Changes in Krebs cycle intermediates show decreased citrate and succinate in adults, but increased fumarate and isocitrate in pediatric patients, reflecting energy metabolism differences. Amino acid metabolism differs by age: Adults exhibit decreased urinary asparagine, lysine, and histidine, while pediatric patients show increased methionine, proline, aspartic acid, and isoleucine. Elevated urinary neurotransmitters like dopamine are noted in pediatric IBD patients. Urine metabolomics also can monitor treatment efficacy by distinguishing responders from non-responders to therapies and differentiating active disease from remission.

Conclusion: Urine metabolomics provides promising, non-invasive biomarkers to enhance IBD diagnostics by distinguishing CD from UC and offering insights into underlying metabolic disturbances, paving the way for more precise, accessible patient care.