Two Novel Ceramide-Like Molecules and miR-5100 Levels as Biomarkers Improve Prediction of Prostate Cancer in Gray-Zone PSA.
Ontology highlight
ABSTRACT:
SUBMITTER: Mello-Grand M
PROVIDER: S-EPMC8640468 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background and objectivesProstate specific antigen (PSA) is currently the most commonly used biomarker for prostate cancer diagnosis. However, when PSA is in the gray area of 4-10 ng/ml, the diagnostic specificity of prostate cancer is extremely low, leading to overdiagnosis in many clinically false-positive patients. This study was trying to discover and evaluate a novel urine biomarker long non-coding RNA (lncRNA546) to improve the diagnostic accuracy of prostate cancer in PSA gray-zone.MethodsA cohort study including consecutive 440 participants with suspected prostate cancer was retrospectively conducted in multi-urology centers. LncRNA546 scores were calculated with quantitative real-time polymerase chain reaction. The area under the receiver operating characteristic curve (AUROC), decision curve analysis (DCA) and a biopsy-specific nomogram were utilized to evaluate the potential for clinical application. Logistic regression model was constructed to confirm the predictive power of lncRNA546.ResultsLncRNA546 scores were sufficient to discriminate positive and negative biopsies. ROC analysis showed a higher AUC for lncRNA546 scores than prostate cancer antigen 3 (PCA3) scores (0.78 vs. 0.66, p<0.01) in the overall cohort. More importantly, the AUC of lncRNA546 (0.80) was significantly higher than the AUCs of total PSA (0.57, p=0.02), percentage of free PSA (%fPSA) (0.64, p=0.04) and PCA3 (0.63, p<0.01) in the PSA 4-10 ng/ml cohort. A base model constructed by multiple logistic regression analysis plus lncRNA546 scores improved the predictive accuracy (PA) from 79.8% to 86.3% and improved AUC results from 0.862 to 0.915. DCA showed that the base model plus lncRNA546 displayed greater net benefit at threshold probabilities beyond 15% in the PSA 4-10 ng/ml cohort.ConclusionLncRNA546 is a promising novel biomarker for the early detection of prostate cancer, especially in the PSA 4-10 ng/ml cohort.
| S-EPMC9411806 | biostudies-literature
Project description:To improve the diagnostic efficiency of prostate cancer (PCa) and reduce unnecessary biopsies, we defined and analyzed the diagnostic efficiency of peripheral zone prostate-specific antigen (PSA) density (PZ-PSAD). Patients who underwent systematic 12-core prostate biopsies in Shanghai General Hospital (Shanghai, China) between January 2012 and January 2018 were retrospectively identified (n = 529). Another group of patients with benign prostatic hyperplasia (n = 100) were randomly preselected to obtain the PSA density of the non-PCa cohort (N-PSAD). Prostate volumes and transition zone volumes were measured using multiparameter magnetic resonance imaging (mpMRI) and were combined with PSA and N-PSAD to obtain the PZ-PSAD from a specific algorithm. Receiver operating characteristic (ROC) curve analysis was used to assess the PCa detection efficiency in patients stratified by PSA level, and the area under the ROC curve (AUC) of PZ-PSAD was higher than that of PSA, PSA density (PSAD), and transition zone PSA density (TZ-PSAD). PZ-PSAD could amend the diagnosis for more than half of the patients with inaccurate transrectal ultrasonography (TRUS) and mpMRI results. When TRUS and mpMRI findings were ambiguous to predict PCa (PIRADS score ≤3), PZ-PSAD could increase the positive rate of biopsy from 21.7% to 54.7%, and help 63.8% (150/235) of patients avoid unnecessary prostate biopsy. In patients whose PSA was 4.0-10.0 ng ml-1, 10.1-20.0 ng ml-1, and >20.0 ng ml-1, the ideal PZ-PSAD cut-off value for predicting clinically significant PCa was 0.019 ng ml-2, 0.297 ng ml-2, and 1.180 ng ml-2, respectively (sensitivity >90%). Compared with PSA, PSAD, and TZ-PSAD, the efficiency of PZ-PSAD for predicting PCa is the highest, leading to fewer missed diagnoses and unnecessary biopsies.
| S-EPMC8269833 | biostudies-literature
Project description:BackgroundThis study aimed to explore the diagnostic value of alpha-l-fucosidase (AFU) in prostate cancer (PCa) patients with "gray-zone PSA" and to investigate the correlation between AFU expression and clinicopathological characteristics of PCa patients.MethodsThe level of AFU and other necessary clinicopathological variables of patients were retrieved from electronic medical records. The transcriptome profiling and clinical information of PCa patients were obtained from The Cancer Genome Atlas (TCGA) database. The protein level of AFU in tissue was assessed by immunohistochemistry (IHC). All the data were processed by appropriate analysis methods. The p-value of <0.05 was considered statistically significant.ResultsAFU showed ideal diagnostic value for PCa with prostate-specific antigen (PSA) levels ranging from 4 to 10 ng/ml, and its optimal cutoffs were 19.5 U/L. Beyond this, low AFU expression was associated with high pathological grade, T stage and N stage, more postoperative residual tumors, and poor primary therapy outcome, as well as shorter progression-free interval. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis illustrated that FUCA1/FUCA2 exerted tumor-suppressive function by regulating the glycosylation.ConclusionsAFU (<19.5 U/L) could effectively distinguish the PCa from the patients with "gray-zone PSA", and low expression of AFU was an independent unfavorable predictor for the clinicopathological characteristics of PCa patients.
| S-EPMC8645591 | biostudies-literature
Project description:BackgroundThe prostate-specific antigen (PSA) has been widely used in screening and early diagnosis of prostate cancer (PCa). However, in the PSA grey zone of 4-10 ng/ml, the sensitivity and specificity for diagnosing PCa are limited, resulting in considerable number of unnecessary and invasive prostate biopsies, which may lead to potential overdiagnosis and overtreatment. We aimed to predict clinically significant PCa (CSPCa) by combining the maximal standardized uptake value (SUVmax) based on 68Ga‑PSMA PET/CT and clinical indicators in men with gray zone PSA levels.Methods81 patients with suspected PCa based on increased serum total PSA (TPSA) levels of 4 - 10 ng/mL who underwent transrectal ultrasound/magnetic resonance imaging (MRI)/PET fusion-guided biopsy were enrolled. Among them, patients confirmed by histopathology were divided into the CSPCa group and the non-CSPCa group, and data on PSA concentration, prostate volume (PV), PSA density (PSAD), free PSA (FPSA)/TPSA, Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS v2.1) score, 68Ga-PSMA PET/CT imaging evaluation results and SUVmax were compared. Multivariate logistic regression analysis was performed to identify the independent predictors for CSPCa, thereby establishing a predictive model based on SUVmax that was evaluated by analyzing the receiver operating characteristic (ROC) curve and decision curve analysis.ResultsCompared to non-CSPCa, CSPCa patients had smaller PVs (median, 31.40 mL), lower FPSA/TPSA (median, 0.12), larger PSADs (median, 0.21 ng/mL2) and higher PI-RADS scores (P < 0.05). The prediction model comprising 68Ga-PSMA PET/CT maximal standardized uptake value, PV and FPSA/TPSA had the highest AUC of 0.927 compared with that of other predictors alone (AUCs of 0.585 for PSA, 0.652 for mpMRI and 0.850 for 68Ga-PSMA PET/CT). The diagnostic sensitivity and specificity of the prediction model were 86.21% and 86.54%, respectively.ConclusionGiven the low diagnostic accuracy of regular PSA tests, a new prediction model based on the 68Ga-PSMA PET/CT SUVmax, PV and FPSA/TPSA was developed and validated, and this model could provide a more satisfactory predictive accuracy for CSPCa. This study provides a noninvasive prediction model with high accuracy for the diagnosis of CSPCa in the PSA gray zone, thus may be better avoiding unnecessary biopsy procedures.
| S-EPMC10476329 | biostudies-literature
Project description:ObjectiveProstate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic gray zone of 4-10 ng/ml of PSA. In the current study, the performance of serum metabolomics profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4-10 ng/ml was explored.MethodsA total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4-10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles.ResultsSeveral differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, variable importance in projection (VIP) > 1, and Student's t-test threshold p < 0.05. Eighteen lipid or lipid-related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, d-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, hexadecyl acetyl glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4-10 ng/ml (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG).ConclusionThe findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the gray zone of 4-10 ng/ml.
| S-EPMC8554118 | biostudies-literature
Project description:PurposeTo create a nomogram that can predict the probability of prostate cancer using prostate health index (PHI) and clinical parameters of patients. And the optimal cut-off value of PHI for prostate cancer was also assessed.Materials and methodsA prospective, multi-center study was conducted. PHI was evaluated prior to biopsy in patients requiring prostate biopsy due to high prostate-specific antigen (PSA). Among screened 1,010 patients, 626 patients with clinically suspected prostate cancer with aged 40 to 85 years, and with PSA levels ranging from 2.5 to 10 ng/mL were analyzed.ResultsAmong 626 patients, 38.82% (243/626) and 22.52% (141/626) were diagnosed with prostate cancer and clinically significant prostate cancer, respectively. In the PSA 2.5 to 4 ng/mL group, the areas under the curve (AUCs) of the nomograms for overall prostate cancer and clinically significant prostate cancer were 0.796 (0.727-0.866; p<0.001), and 0.697 (0.598-0.795; p=0.001), respectively. In the PSA 4 to 10 ng/mL group, the AUCs of nomograms for overall prostate cancer and clinically significant prostate cancer were 0.812 (0.783-0.842; p<0.001), and 0.839 (0.810-0.869; p<0.001), respectively.ConclusionsEven though external validations are necessary, a nomogram using PHI might improve the prediction of prostate cancer, reducing the need for prostate biopsies.
| S-EPMC10782127 | biostudies-literature
Project description:Prostate cancer (PCa) is the most commonly diagnosed neoplasm among men. Since it often resembles benign prostate hyperplasia (BPH), biomarkers with a higher differential value than PSA are required. Epigenetic biomarkers in liquid biopsies, especially miRNA, could address this challenge. The absolute expression of miR-375-3p, miR-182-5p, miR-21-5p, and miR-148a-3p were quantified in blood plasma and seminal plasma of 65 PCa and 58 BPH patients by digital droplet PCR. The sensitivity and specificity of these microRNAs were determined using ROC curve analysis. The higher expression of miR-182-5p and miR-375-3p in the blood plasma of PCa patients was statistically significant as compared to BPH (p = 0.0363 and 0.0226, respectively). Their combination achieved a specificity of 90.2% for predicting positive or negative biopsy results, while PSA cut-off of 4 µg/L performed with only 1.7% specificity. In seminal plasma, miR-375-3p, miR-182-5p, and miR-21-5p showed a statistically significantly higher expression in PCa patients with PSA >10 µg/L compared to ones with PSA ≤10 µg/L. MiR-182-5p and miR-375-3p in blood plasma show higher performance than PSA in discriminating PCa from BPH. Seminal plasma requires further investigation as it represents an obvious source for PCa biomarker identification.
| S-EPMC8123314 | biostudies-literature
Project description:Although serum microRNAs (miRNAs) are currently being considered as promising noninvasive biomarkers for cancers, their role in the prognosis of oral squamous cell carcinoma (OSCC) has not been elucidated. Here we aimed to identify serum miRNA biomarkers that could be used as prognosis predictors of OSCC. Methods: A cohort of 260 serum miRNA samples was assessed in a three-step approach that included a screening stage, a training stage, and a testing stage. The correlation between prognosis of OSCC and the miRNAs expression was comprehensively analyzed. Results: A two-miRNA signature involving miR-626 and miR-5100 has been developed. Patients defined to be high-risk group by the two-miRNA signature had significantly shortened median survival time compared with the low-risk group. In multivariate analysis, this two-miRNA signature was independently predictive of survival, and achieved a superior predictive value compared with that of traditional clinicopathologic factors such as pathology grade as well as tumor and node metastasis (TNM) stage. An integrated prognostic model combining the TNM stage and miRNA signature displayed the highest prognostic performance (AUC value: 0.787, specificity: 0.884, sensitivity: 0.573) compared to the TNM stage-alone (AUC value: 0.630, specificity: 0.526, sensitivity: 0.733) or miRNA signature-alone model (AUC value: 0.771, specificity: 0.768, sensitivity: 0.773). In addition, we found that OSCC tumor cells not only expressed a high level of these two miRNAs, but also secreted certain miRNAs into the extracellular environment, suggesting these miRNAs may originate from tumor cells. Conclusion: In our study, we established a two-miRNA signature that was strongly and independently associated with prognosis in OSCC, and may serve as a promising prognosis predictor.
| S-EPMC6401397 | biostudies-literature
Project description:PurposeTo determine the clinical performance of a blood-based test for clinically significant (CS) prostate cancer (PCa) (grade group ≥ 2) intended for use in men with prostate serum antigen levels in the 'grey zone' (PSA < 10 ng/ml). The test quantifies a previously described 3.4 kb mitochondrial DNA (mtDNA) deletion.MethodsIn a first prospective study of an MRI-guided re-biopsy population (n = 126), the 3.4 kb deletion and 18S rRNA gene were amplified from plasma. A diagnostic threshold was selected from the coordinates of the receiver operating characteristic curve and tested in a second population of men who were (n = 92) biopsy naïve when the mtDNA deletion was assayed and for whom those diagnosed with cancer on initial biopsy were treated with radical prostatectomy.ResultsThe 3.4 kb deletion was a good predictor of CS PCa in the image-guided re-biopsy population [AUC 0.84, (95% CI 0.73-0.95)] and the selected threshold corresponded to a sensitivity of 87% [95% CI, 70-96%], specificity of 68% [95% CI, 47-85%] and negative predictive value (NPV) of 97%. Applying this threshold to the second population showed this deletion to be a strong predictor of CS cancer [AUC 0.98, (95% CI 0.94-1.02)], independent of PSA or age [sensitivity 100% (95% CI, 93-100%), specificity 90% (95%CI 73-98%) and NPV 100%].ConclusionThe 3.4 kb deletion in plasma is an accurate predictor of CS cancer for men in the PSA 'grey zone'. Used in advance of biopsy for improved patient selection, this deletion may reduce the number of biopsies needed to diagnose CS prostate cancers.
| S-EPMC5846823 | biostudies-literature
Project description:Melanoma is the most lethal skin cancer characterized by its high metastatic potential. It is urgent to find novel therapy strategies to overcome this feature. Metformin has been confirmed to suppress invasion and migration of various types of cancer. However, additional mechanisms underlying the antimetastatic effect of metformin on melanoma require further investigation. Here, we performed microarray analysis and uncovered an altered mRNA and miRNA expression profile between melanoma and nevus. Luciferase reporter assay confirmed that miR-5100 targets SPINK5 to activate STAT3 phosphorylation. Migration and wound healing assays showed that the miR-5100/SPINK5/STAT3 axis promotes melanoma cell metastasis; the mechanism was proven by initiation of epithelial-mesenchymal transition. Co-immunoprecipitation (Co-IP) further confirmed an indirect interaction between SPINK5 and STAT3. Furthermore, metformin dramatically inhibited miR-5100/SPINK5/STAT3 pathway, and decreased B16-F10 cell metastasis to lung in C57 mouse module. Intriguingly, pretreatment of metformin before melanoma cell injection improved this effect further. These findings exposed the underlying mechanisms of action of metformin and update the use of this drug to prevent metastasis in melanoma.
| S-EPMC9199130 | biostudies-literature