Browse
Submit Data
Databases
API
Help

Dataset Information

26 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis.

ABSTRACT:

Objectives

To identify and validate a biomarker panel by serum metabolic profiling for improvement of PCa diagnosis.

Materials and methods

Totally, 134 individuals were included in this study. Among them, 39 PCa patients and 45 control patients (negative prostate biopsy) were involved in the discovery phase and 50 healthy controls were enrolled for validation phase of metabolomics study. LC-MS Analysis was used for the identification of the serum metabolites of patients.

Results

Logistics regression analysis shows that 5 metabolites [dMePE(18:0/18:2), PC(16:0/20:2), PS(15:0/18:2), SM(d16:0/24:1], Carnitine C14:0) were significantly changed in PCa patients compared with control patients. A metabolic panel (MET) was calculated, showing a significantly higher diagnostic performance than PSA in differentiating PCa from control patients [AUC (MET vs. PSA): 0.823 ± 0.046 vs. 0.712 ± 0.057, p<0.001]. Moreover, this panel was superior to PSA in distinguishing PCa from negative prostate biopsies when PSA levels were less than 20 ng/ml [AUC (MET vs. PSA]: 0.836 ± 0.050 vs. 0.656 ± 0.067, p<0.001]. In the validation set, the MET panel yielded an AUC of 0.823 in distinguishing PCa patients from healthy controls, showing a significant improvement of PCa detection.

Conclusions

The metabolite biomarker panel discovered in this study presents a good diagnostic performance for the detection of PCa.

SUBMITTER: Xu H

PROVIDER: S-EPMC8138432 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine.

Project description:BackgroundThe lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management.MethodsA metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection.ResultsResults showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%.ConclusionsIt is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.

| S-EPMC6889512 | biostudies-literature

Clinical utility of a serum biomarker panel in distinguishing prostate cancer from benign prostate hyperplasia.

Project description:Prostate-specific antigen (PSA) screening for prostate cancer (PCa) is limited by the lack of specificity but is further complicated in the benign prostatic hyperplasia (BPH) population which also exhibit elevated PSA, representing a clear unmet need to distinguish BPH from PCa. Herein, we evaluated the utility of FLNA IP-MRM, age, and prostate volume to stratify men with BPH from those with PCa. Diagnostic performance of the biomarker panel was better than PSA alone in discriminating patients with negative biopsy from those with PCa, as well as those who have had multiple prior biopsies (AUC 0.75 and 0.87 compared to AUC of PSA alone 0.55 and 0.57 for patients who have had single compared to multiple negative biopsies, respectively). Of interest, in patients with PCa, the panel demonstrated improved performance than PSA alone in those with Gleason scores of 5-7 (AUC 0.76 vs. 0.56) and Gleason scores of 8-10 (AUC 0.74 vs. 0.47). With Gleason scores (8-10), the negative predictive value of the panel is 0.97, indicating potential to limit false negatives in aggressive cancers. Together, these data demonstrate the ability of the biomarker panel to perform better than PSA alone in men with BPH, thus preventing unnecessary biopsies.

| S-EPMC8302659 | biostudies-literature

A Plasma Biomarker Panel of Four MicroRNAs for the Diagnosis of Prostate Cancer.

Project description:Prostate cancer is diagnosed in over 1 million men every year globally, yet current diagnostic modalities are inadequate for identification of significant cancer and more reliable early diagnostic biomarkers are necessary for improved clinical management of prostate cancer patients. MicroRNAs (miRNAs) modulate important cellular processes/pathways contributing to cancer and are stably present in body fluids. In this study we profiled 372 cancer-associated miRNAs in plasma collected before (~60% patients) and after/during commencement of treatment (~40% patients), from age-matched prostate cancer patients and healthy controls, and observed elevated levels of 4 miRNAs - miR-4289, miR-326, miR-152-3p and miR-98-5p, which were validated in an independent cohort. The miRNA panel was able to differentiate between prostate cancer patients and controls (AUC = 0.88). Analysis of published miRNA transcriptomic data from clinical samples demonstrated low expression of miR-152-3p in tumour compared to adjacent non-malignant tissues. Overexpression of miR-152-3p increased proliferation and migration of prostate cancer cells, suggesting a role for this miRNA in prostate cancer pathogenesis, a concept that was supported by pathway analysis of predicted miR-152-3p target genes. In summary, a four miRNA panel, including miR-152-3p which likely targets genes with key roles in prostate cancer pathogenesis, has the potential to improve early prostate cancer diagnosis.

| S-EPMC5923293 | biostudies-literature

Serum Biomarker Panel for Diagnosis and Prognosis of Pancreatic Ductal Adenocarcinomas.

Project description:BackgroundPatients with pancreatic ductal adenocarcinoma (PDAC) have late diagnosis which results in poor prognosis. Currently, surgical resection is the only option for curative intent. Identifying high-risk features for patients with aggressive PDAC is essential for accurate diagnosis, prognostication, and personalised care due to the disease burden and risk of recurrence despite surgical resection. A panel of three biomarkers identified in tumour tissue (S100A4, Ca125 and Mesothelin) have shown an association with poor prognosis and overall survival. The diagnostic and prognostic value of the serum concentration of this particular biomarker panel for patients with PDAC has not been previously studied.MethodsRetrospectively collected blood samples of PDAC patients (n =120) and healthy controls (n =80) were evaluated for the serum concentration of select biomarkers - S100A4, S100A2, Ca-125, Ca 19-9 and mesothelin. Statistical analyses were performed for diagnostic and prognostic correlation.ResultsA panel of four biomarkers (S100A2, S100A4, Ca-125 and Ca 19-9) achieved high diagnostic potential (AUROC 0.913). Three biomarkers (S100A4, Ca-125 and Ca 19-9) correlated with poor overall survival in a univariable model (p < 0.05). PDAC patients with abnormal levels of 2 or more biomarkers in their serum demonstrated significantly lower survival compared to patients with abnormal levels of one or less biomarker (p < 0.05).Conclusion and impactThe identified biomarker panels have shown the potential to diagnose PDAC patients and stratify patients based on their prognostic outcomes. If independently validated, this may lead to the development of a diagnostic and prognosticating blood test for PDAC.

| S-EPMC8287202 | biostudies-literature

Platelet protein biomarker panel for ovarian cancer diagnosis.

Project description:Background:Platelets support cancer growth and spread making platelet proteins candidates in the search for biomarkers. Methods:Two-dimensional (2D) gel electrophoresis, Partial Least Squares Discriminant Analysis (PLS-DA), Western blot, DigiWest. Results:PLS-DA of platelet protein expression in 2D gels suggested differences between the International Federation of Gynaecology and Obstetrics (FIGO) stages III-IV of ovarian cancer, compared to benign adnexal lesions with a sensitivity of 96% and a specificity of 88%. A PLS-DA-based model correctly predicted 7 out of 8 cases of FIGO stages I-II of ovarian cancer after verification by western blot. Receiver-operator curve (ROC) analysis indicated a sensitivity of 83% and specificity of 76% at cut-off >0.5 (area under the curve (AUC)?=?0.831, p?<?0.0001) for detecting these cases. Validation on an independent set of samples by DigiWest with PLS-DA differentiated benign adnexal lesions and ovarian cancer, FIGO stages III-IV, with a sensitivity of 70% and a specificity of 83%. Conclusion:We identified a group of platelet protein biomarker candidates that can quantify the differential expression between ovarian cancer cases as compared to benign adnexal lesions.

| S-EPMC5767003 | biostudies-literature

Serum N-glycan profiling is a potential biomarker for castration-resistant prostate cancer.

Project description:We investigated the diagnostic and prognostic potential of serum N-glycan profiling for castration-resistant prostate cancer (CRPC). We retrospectively investigated serum N-glycan structural analysis by glycoblotting for 287 patients with benign prostatic hyperplasia (BPH), 289 patients with newly diagnosed prostate cancer (PC), 57 patients with PC treated with androgen-deprivation therapy without disease progression (PC-ADT), and 60 patients with CRPC. N-Glycan profiling was compared between the non-CRPC (BPH, newly diagnosed PC and PC-ADT) and CRPC patients. We obtained the quantitative score for CRPC (CRPC N-glycan score) by discriminant analysis based on the combination of 9 N-glycans that were significantly associated with CRPC. The median CRPC N-glycan score was found to be significantly greater in CRPC patients than in non-CRPC patients. The CRPC N-glycan score could classify CRPC patients with sensitivity, specificity, and area under the curve of 87%, 69%, and 0.88, respectively. The CRPC N-glycan score >1.7 points was significantly associated with poor prognosis in patients with CRPC. The glycoprotein analysis showed that not immunoglobulins but ?-1-acid glycoprotein (AGP) were a potential candidate for the carrier protein of N-glycans. The overexpression of specific N-glycans may be associated with their castration-resistant status and be a potential biomarker for CRPC.

| S-EPMC6856113 | biostudies-literature

Evaluation of serum exosomal LncRNA-based biomarker panel for diagnosis and recurrence prediction of bladder cancer.

Project description:Exosomes are small membrane vesicles released by many cells. These vesicles can mediate cellular communications by transmitting active molecules including long non-coding RNAs (lncRNAs). In this study, our aim was to identify a panel of lncRNAs in serum exosomes for the diagnosis and recurrence prediction of bladder cancer (BC). The expressions of 11 candidate lncRNAs in exosome were investigated in training set (n = 200) and an independent validation set (n = 320) via quantitative real-time PCR. A three-lncRNA panel (PCAT-1, UBC1 and SNHG16) was finally identified by multivariate logistic regression model to provide high diagnostic accuracy for BC with an area under the receiver-operating characteristic curve (AUC) of 0.857 and 0.826 in training set and validation set, respectively, which was significantly higher than that of urine cytology. The corresponding AUCs of this panel for patients with Ta, T1 and T2-T4 were 0.760, 0.827 and 0.878, respectively. In addition, Kaplan-Meier analysis showed that non-muscle-invasive BC (NMIBC) patients with high UBC1 expression had significantly lower recurrence-free survival (P = 0.01). Multivariate Cox analysis demonstrated that UBC1 was independently associated with tumour recurrence of NMIBC (P = 0.018). Our study suggested that lncRNAs in serum exosomes may serve as considerable diagnostic and prognostic biomarkers of BC.

| S-EPMC6349164 | biostudies-literature

Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer.

Project description:A key barrier to the realization of personalized medicine for cancer is the identification of biomarkers. Here we describe a two-stage strategy for the discovery of serum biomarker signatures corresponding to specific cancer-causing mutations and its application to prostate cancer (PCa) in the context of the commonly occurring phosphatase and tensin homolog (PTEN) tumor-suppressor gene inactivation. In the first stage of our approach, we identified 775 N-linked glycoproteins from sera and prostate tissue of wild-type and Pten-null mice. Using label-free quantitative proteomics, we showed that Pten inactivation leads to measurable perturbations in the murine prostate and serum glycoproteome. Following bioinformatic prioritization, in a second stage we applied targeted proteomics to detect and quantify 39 human ortholog candidate biomarkers in the sera of PCa patients and control individuals. The resulting proteomic profiles were analyzed by machine learning to build predictive regression models for tissue PTEN status and diagnosis and grading of PCa. Our approach suggests a general path to rational cancer biomarker discovery and initial validation guided by cancer genetics and based on the integration of experimental mouse models, proteomics-based technologies, and computational modeling.

| S-EPMC3044355 | biostudies-literature

A study of circulating microRNAs identifies a new potential biomarker panel to distinguish aggressive prostate cancer.

Project description:Prostate cancer is one of the most common cancers in men worldwide. Currently available diagnostic and prognostic tools for this disease, such as prostate specific antigen, suffer from lack of specificity and sensitivity, resulting in over- and misdiagnosis. Hence, there is an urgent need for clinically relevant biomarkers capable of distinguishing between aggressive and nonaggressive forms of prostate cancer to aid in stratification, management and therapeutic decisions. To address this unmet need, we investigated the patterns of expression of a panel of 68 plasma-derived microRNAs (miRNAs) in a cohort of African American (AA) and European American (EA) prostate cancer patients (n = 114). miRNA qPCR results were analyzed using in-depth statistical methods, and a bioinformatics analysis was conducted to identify potential targets of the differentially expressed miRNAs. Our data demonstrate that a new previously unreported circulating miRNA signature consisting of a combination of interacting miRNAs (miR-17/miR-192) and an independent miRNA (miR-181a) are capable of segregating aggressive and nonaggressive prostate cancer in both AA and EA patients. The interacting miRNAs outperformed independent miRNAs in identifying aggressiveness. Our results suggest that these circulating miRNAs may constitute novel biomarkers of prostate cancer aggressiveness in both races and warrant further investigation.

| S-EPMC6853653 | biostudies-literature

Corrigendum: Serum Biomarker Panel for Diagnosis and Prognosis of Pancreatic Ductal Adenocarcinomas.

Project description:[This corrects the article DOI: 10.3389/fonc.2021.708963.].

| S-EPMC8527849 | biostudies-literature