METHODS: We used multiplex array technology to simultaneously detect and quantify 32 plasma analyte (22 reported analytes and 10 novel analytes) levels in 38 patients.
RESULTS: In our study, 16 analytes are found to be significantly deregulated (13 higher, 3 lower, Mann-Whitney U-test, P-value <0.005), where 5 of them have never been reported before in AML. We predicted a seven-analyte-containing multiplex panel for diagnosis of AML and, among them, MIF could be a possible therapeutic target. In addition, we observed that circulating analytes show five co-expression signatures.
CONCLUSIONS: Circulating analyte expression in AML significantly differs from normal, and follow distinct expression patterns.
METHODS: Study subjects included men with initial PSA between 4.0 and 10.0 ng/ml that have undergone 12-core TRUS-guided prostate biopsy between 2009 and 2016. The prostate cancer detection rate was calculated, while potential factors associated with detection were investigated via univariable and multivariable analysis.
RESULTS: A total of 617 men from a multi-ethnic background encompassing Chinese (63.5%), Malay (23.1%) and Indian (13.3%) were studied. The overall cancer detection rate was 14.3% (88/617), which included cancers detected at biopsy 1 (first biopsy), biopsy 2 (second biopsy with previous negative biopsy) and biopsy ≥ 3 (third or more biopsies with prior negative biopsies). Indian men displayed higher detection rate (23.2%) and increased risk of prostate cancer development (OR 1.85, 95% CI 1.03-3.32, p
MATERIALS AND METHODS: From March 2015 to August 2016, all men consecutively undergoing transrectal ultrasound (TRUS)-guided prostate biopsy with total PSA values ≤ 20ng/ ml were recruited. Blood samples were taken immediately before undergoing prostate biopsy. The performance of total PSA, %fPSA, %p2PSA and PHI in determining the presence of PCa on prostate biopsy were compared.
RESULTS: PCa was diagnosed in 25 of 84 patients (29.7%). %p2PSA and PHI values were significantly higher (p<0.05) in patients with PCa than those without PCa. The areas under the receiver operating characteristic curves for total PSA, %fPSA, %p2PSA and PHI were 0.558, 0.560, 0.734 and 0.746, respectively. At 90% sensitivity, the specificity of PHI (42.4%) was five times better than total PSA (8.5%) and two times better than %fPSA (20.3%). By utilising PHI cut-off >22.52, 27 of 84 (32.1%) patients could have avoided undergoing biopsy.
CONCLUSION: Findings of our study support the potential clinical effectiveness of PHI in predicting PCa in a wider concentration range of total PSA up to 20ng/ml.
METHODS: In this study, plasma miRNA profiles from eight early-stage breast cancer patients and nine age-matched (± 2 years) healthy controls were characterized by miRNA array-based approach, followed by differential gene expression analysis, Independent T-test and construction of Receiver Operating Characteristic (ROC) curve to determine the capability of the assays to discriminate between breast cancer and the healthy control.
RESULTS: Based on the 372-miRNAs microarray profiling, a set of 40 differential miRNAs was extracted regarding to the fold change value at 2 and above. We further sub grouped 40 miRNAs of breast cancer patients that were significantly expressed at 2-fold change and higher. In this set, we discovered that 24 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in breast cancer patients, as compared to the miRNA expression of healthy subjects. ROC curve analysis revealed that seven miRNAs (miR-125b-5p, miR-142-3p, miR-145-5p, miR-193a-5p, miR-27b-3p, miR-22-5p and miR-423-5p) had area under curve (AUC) value > 0.7 (AUC p-value < 0.05). Overlapping findings from differential gene expression analysis, ROC analysis, and Independent T-Test resulted in three miRNAs (miR-27b-3p, miR-22-5p, miR-145-5p). Cohen's effect size for these three miRNAs was large with d value are more than 0.95.
CONCLUSION: miR-27b-3p, miR-22-5p, miR-145-5p could be potential biomarkers to distinguish breast cancer patients from healthy controls. A validation study for these three miRNAs in an external set of samples is ongoing.
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OBJECTIVE: To investigate the effect of the neutrophil-lymphocyte ratio on prognosis in non-metastatic primary nasopharyngeal carcinoma patients and to further refine the cut off between high and low neutrophil-lymphocyte ratio values.
METHODS: The medical charts of patients with histologically confirmed nasopharyngeal carcinoma from 1st January 2005 until 31st December 2009 were reviewed retrospectively and theneutrophil-lymphocyte ratio was calculated to see if there was any association between their higher values with higher failure rates.
RESULTS: Records of 98 patients (n=98) were retrieved and reviewed. Only neutrophil-lymphocyte ratio (p=0.004) and tumor node metastasis staging (p=0.002) were significantly different between recurrent and non-recurrent groups, with the neutrophil-lymphocyte ratio being independent of tumor node metastasis staging (p=0.007). Treatment failure was significantly higher in the high neutrophil-lymphocyte ratio group (p=0.001). Disease free survival was also significantly higher in this group (p=0.000077).
CONCLUSION: High neutrophil-lymphocyte ratio values are associated with higher rates of recurrence and worse disease free survival in non-metastatic nasopharyngeal carcinoma patients undergoing primary curative treatment.
METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.
CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.
IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.