Prognostic significance of urokinase plasminogen activator and plasminogen activator inhibitor-1 mRNA expression in lymph node- and hormone receptor-positive breast cancer

BACKGROUND: One of the most thoroughly studied systems in relation to its prognostic relevance in patients with breast cancer, is the plasminogen activation system that comprises of, among others, the urokinase Plasminogen Activator (uPA) and its main inhibitor, the Plasminogen Activator Inhibitor-1 (PAI-1). In this study, we investigated the prognostic value of uPA and PAI-1 at the mRNA level in lymph node- and hormone receptor-positive breast cancer. METHODS: The study included a retrospective series of 87 patients with hormone-receptor positive and axillary lymph node-positive breast cancer. All patients received radiotherapy, adjuvant anthracycline-based chemotherapy and five years of tamoxifen treatment. The median patient age was 54 and the median follow-up time was 79 months. Distant relapse occurred in 30 patients and 22 patients died from breast cancer during follow-up. We investigated the prognostic value of uPA and PAI-1 at the mRNA level as measured by real-time quantitative RT-PCR. RESULTS: uPA and PAI-1 gene expression was not found to be correlated with any of the established clinical and pathological factors. Metastasis-free Survival (MFS) and Breast Cancer specific Survival (BCS) were significantly shorter in patients expressing high levels of PAI-1 mRNA (p < 0.0001; p < 0.0001; respectively). In Cox multivariate analysis, the level of PAI-1 mRNA appeared to be the strongest prognostic factor for MFS (Hazard Ratio (HR) = 10.12; p = 0.0002) and for BCS (HR = 13.17; p = 0.0003). Furthermore, uPA gene expression was not significantly associated neither with MFS (p = 0.41) nor with BCS (p = 0.19). In a Cox-multivariate regression analysis, uPA expression did not demonstrate significant independent prognostic value. CONCLUSION: These findings indicate that high PAI-1 mRNA expression represents a strong and independent unfavorable prognostic factor for the development of metastases and for breast cancer specific survival in a population of hormone receptor- and lymph node-positive breast cancer patients

Exploring the gut microbiota in patients with pre-diabetes and treatment naïve diabetes type 2 - a pilot study

Abstract Background Compared to their healthy counterparts, patients with type 2 diabetes (T2D) can exhibit an altered gut microbiota composition, correlated with detrimental outcomes, including reduced insulin sensitivity, dyslipidemia, and increased markers of inflammation. However, a typical T2D microbiota profile is not established. The aim of this pilot study was to explore the gut microbiota and bacteria associated with prediabetes (pre-T2D) patients, and treatment naïve T2D patients, compared to healthy subjects. Methods Fecal samples were collected from patients and healthy subjects (from Norway). The bacterial genomic DNA was extracted, and the microbiota analyzed utilizing the bacterial 16S rRNA gene. To secure a broad coverage of potential T2D associated bacteria, two technologies were used: The GA-map® 131-plex, utilizing 131 DNA probes complementary to pre-selected bacterial targets (covering the 16S regions V3-V9), and the LUMI-Seq™ platform, a full-length 16S sequencing technology (V1-V9). Variations in the gut microbiota between groups were explored using multivariate methods, differential bacterial abundance was estimated, and microbiota signatures discriminating the groups were assessed using classification models. Results In total, 24 pre-T2D patients, 18 T2D patients, and 52 healthy subjects were recruited. From the LUMI-Seq™ analysis, 10 and 9 bacterial taxa were differentially abundant between pre-T2D and healthy, and T2D and healthy, respectively. From the GA-map® 131-plex analysis, 10 bacterial markers were differentially abundant when comparing pre-T2D and healthy. Several of the bacteria were short-chain fatty acid (SCFA) producers or typical opportunistic bacteria. Bacteria with similar function or associated properties also contributed to the separation of pre-T2D and T2D from healthy as found by classification models. However, limited overlap was found for specific bacterial genera and species. Conclusions This pilot study revealed that differences in the abundance of SCFA producing bacteria, and an increase in typical opportunistic bacteria, may contribute to the variations in the microbiota separating the pre-T2D and T2D patients from healthy subjects. However, further efforts in investigating the relationship between gut microbiota, diabetes, and associated factors such as BMI, are needed for developing specific diabetes microbiota signatures

Data from: Diagnostic performance of alpha-fetoprotein, protein induced by vitamin K absence, osteopontin, Dickkopf-1 and its combinations for hepatocellular carcinoma

Background & Aims: Alpha-fetoprotein (AFP) is the most widely used serum biomarker for hepatocellular carcinoma (HCC), despite its limitations. As complementary biomarkers, protein induced by vitamin K absence (PIVKA-II), osteopontin (OPN), and Dickkopf-1 (DKK-1) have been proposed. This study aimed to perform a head-to-head comparison of the diagnostic performance of AFP, PIVKA-II, OPN and DKK-1 as single or in combination to seek the best biomarker or panel, and to investigate the clinical factors affecting their performance. Methods: Using 401 stored plasma samples obtained from 208 HCC patients and 193 liver cirrhosis control patients, plasma AFP, PIVKA-II, OPN and DKK-1 levels were measured by ELISA, and receiver operating characteristic curve analyses were performed for each biomarker and for every combination of two to four markers. Results: Of the four biomarkers, AFP showed the highest area under the curve (0.786). The sensitivity and specificity for each single biomarker was 62% and 90.2% (AFP>20 ng/mL), 51.0% and 91.2% (PIVKA-II>10 ng/mL), 46.2% and 80.3% (OPN>100 ng/mL), and 50.0% and 80.8% (DKK-1>500 pg/mL), respectively. Among the combinations of two biomarkers, AFP>20 ng/mL or DKK-1>500 pg/mL showed the best diagnostic performance (sensitivity 78.4%, specificity 72.5%). Triple or quadruple combination did not improve the diagnostic performance further. The patient’s age, etiology and tumor invasiveness of HCC affected the performance of each marker. Conclusions: AFP was the most useful single biomarker for HCC diagnosis, and the combined measurement of AFP and DKK-1 could maximize the diagnostic yield. Clinical decision should be based on the consideration of various factors affecting the diagnostic performance of each biomarker. Efforts to seek novel HCC biomarkers should be continued

Diagnostic Performance of Alpha-Fetoprotein, Protein Induced by Vitamin K Absence, Osteopontin, Dickkopf-1 and Its Combinations for Hepatocellular Carcinoma.

Alpha-fetoprotein (AFP) is the most widely used serum biomarker for hepatocellular carcinoma (HCC), despite its limitations. As complementary biomarkers, protein induced by vitamin K absence (PIVKA-II), osteopontin (OPN), and Dickkopf-1 (DKK-1) have been proposed. This study aimed to perform a head-to-head comparison of the diagnostic performance of AFP, PIVKA-II, OPN and DKK-1 as single or in combination to seek the best biomarker or panel, and to investigate the clinical factors affecting their performance.Using 401 stored plasma samples obtained from 208 HCC patients and 193 liver cirrhosis control patients, plasma AFP, PIVKA-II, OPN and DKK-1 levels were measured by ELISA, and receiver operating characteristic curve analyses were performed for each biomarker and for every combination of two to four markers.Of the four biomarkers, AFP showed the highest area under the curve (0.786). The sensitivity and specificity for each single biomarker was 62% and 90.2% (AFP>20 ng/mL), 51.0% and 91.2% (PIVKA-II>10 ng/mL), 46.2% and 80.3% (OPN>100 ng/mL), and 50.0% and 80.8% (DKK-1>500 pg/mL), respectively. Among the combinations of two biomarkers, AFP>20 ng/mL or DKK-1>500 pg/mL showed the best diagnostic performance (sensitivity 78.4%, specificity 72.5%). Triple or quadruple combination did not improve the diagnostic performance further. The patient's age, etiology and tumor invasiveness of HCC affected the performance of each marker.AFP was the most useful single biomarker for HCC diagnosis, and the combined measurement of AFP and DKK-1 could maximize the diagnostic yield. Clinical decision should be based on the consideration of various factors affecting the diagnostic performance of each biomarker. Efforts to seek novel HCC biomarkers should be continued

ROC curves of AFP, PIVKA-II, OPN, and DKK-1 for the diagnosis of HCC with LC control.

<p>(A) In entire population (B) In the subgroup with AFP levels < 20 ng/mL.</p

AUCs (with 95% confidence interval) for HCC diagnosis using AFP, PIVKA-II, OPN, and DKK-1 in subgroups categorized by clinical and tumor characteristics.

<p>AUCs for HCC diagnosis using AFP (A), PIVKA-II (B), OPN (C), and DKK-1 (D) were schematized to compare the effect of clinical and tumor factors on each biomarker’s diagnostic performance. The diamonds and solid bars represent the AUC and 95% CI of each marker in the total population. The squares and solid bars are the AUC and 95% CI of the first subgroup in each category (Age ≤ 60-years-old, male, HBV, CTP class A, non-diffuse HCC, PVI (-), and BCLC stage 0/A, respectively). The squares and short lined bars denote the AUC and 95% CI of the second subgroup in each category (Age > 60-years-old, female, HCV, CTP class B/C, diffuse HCC, PVI (+), and BCLC stage B/C/D, respectively). The squares and dotted bars are the AUC and 95% CI of the third subgroup in the each category (NBNC). AUC values were not obtained from multivariable analysis. Detailed AUC values with 95% CI and a direct comparison between the AUC of the four markers are presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151069#pone.0151069.s002" target="_blank">S2 Table</a>.</p