ArticleJournal of Cancer2014
Potential Urinary Protein Biomarker Candidates for the Accurate Detection of Prostate Cancer among Benign Prostatic Hyperplasia Patients.
Article in Journal of Cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 37 citations in OpenAlex.
- Fluorescence Immunoassay of Prostate-Specific Antigen Using 3D Paddle Screw-Type Devices and Their Rotating System.Biosensors · 2024Article
- Recent progress in mass spectrometry-based urinary proteomics.Clinical proteomics · 2024Review
- Research of Prostate Cancer Urinary Diagnostic Biomarkers by Proteomics: The Noteworthy Influence of Inflammation.Diagnostics (Basel, Switzerland) · 2023Article
- Article
- Nurturing the marriages of urinary liquid biopsies and nano-diagnostics for precision urinalysis of prostate cancer.Smart medicine · 2023Review
- Mass Spectrometry-Based Glycoproteomics and Prostate Cancer.International journal of molecular sciences · 2021Review
- Recognition of urinary N-linked glycopeptides in kidney cancer patients by hydrophilic carbohydrate functionalized magnetic metal organic framework combined with LC-MS/MS.Mikrochimica acta · 2020Article
- Biomarkers That Differentiate Benign Prostatic Hyperplasia from Prostate Cancer: A Literature Review.Cancer management and research · 2020Review
- Approaches to urinary detection of prostate cancer.Prostate cancer and prostatic diseases · 2019Review
- Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry.Trends in analytical chemistry : TRAC · 2019Article
- Article
- Review
- Quantitative metabolomics for investigating the value of polyamines in the early diagnosis and therapy of colorectal cancer.Oncotarget · 2018Article
- MicroRNA-34a: A Key Regulator in the Hallmarks of Renal Cell Carcinoma.Oxidative medicine and cellular longevity · 2017Article
- Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides.Glycoconjugate journal · 2016Article
- Detection of aggressive prostate cancer associated glycoproteins in urine using glycoproteomics and mass spectrometry.Proteomics · 2016Article
- MicroRNA expression analysis in high fat diet-induced NAFLD-NASH-HCC progression: study on C57BL/6J mice.BMC cancer · 2016Article
- Novel non-invasive biomarkers that distinguish between benign prostate hyperplasia and prostate cancer.BMC cancer · 2015Article
- The combination of TP53INP1, TP53INP2 and AXIN2: potential biomarkers in papillary thyroid carcinoma.Endocrine · 2015Article
- Proteomics analysis of urine reveals acute phase response proteins as candidate diagnostic biomarkers for prostate cancer.Proteome science · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Globally, Prostate cancer (PCa) is the most frequently occurring non-cutaneous cancer, and is the second highest cause of cancer mortality in men. Serum prostate specific antigen (PSA) has been the standard in PCa screening since its approval by the American Food & Drug Administration (FDA) in 1994. Currently, PSA is used as an indicator for PCa - patients with a serum PSA level above 4ng/mL will often undergo prostate biopsy to confirm cancer. Unfortunately fewer than ~30% of these men will biopsy positive for cancer, meaning that the majority of men undergo invasive biopsy with little benefit. Despite PSA's notoriously poor specificity (33%), there is still a significant lack of credible alternatives. Therefore an ideal biomarker that can specifically detect PCa at an early stage is urgently required. The aim of this study was to investigate the potential of using deregulation of urinary proteins in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the protein signatures specific for PCa, protein expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using LC-MS/MS. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This approach revealed that significant the down-regulation of Fibronectin and TP53INP2 was a characteristic event among PCa patients. Fibronectin mRNA down-regulation, was identified as offering improved specificity (50%) over PSA, albeit with a slightly lower although still acceptable sensitivity (75%) for detecting PCa. As for TP53INP2 on the other hand, its down-regulation was moderately sensitive (75%), identifying many patients with PCa, but was entirely non-specific (7%), designating many of the benign samples as malignant and being unable to accurately identify more than one negative.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.