Blankenstein, M.A.

Proximal fluid proteome profiling of mouse colon tumors reveals biomarkers for early diagnosis of human colorectal cancer (Article)

2012-05-01T00:00:00Z

Purpose: Early detection of colorectal cancer (CRC) and its precursor lesions is an effective approach to reduce CRC mortality rates. This study aimed to identify novel protein biomarkers for the early diagnosis of CRC. Experimental Design: Proximal fluids are a rich source of candidate biomarkers as they contain high concentrations of tissue-derived proteins. The FabplCre;Apc15lox/+mouse model represents early-stage development of human sporadic CRC. Proximal fluids were collected from normal colon and colon tumors and subjected to in-depth proteome profiling by tandem mass spectrometry. Carcinoembryonic antigen (CEA) and CHI3L1 human serum protein levels were determined by ELISA. Results: Of the 2,172 proteins identified, quantitative comparison revealed 192 proteins that were significantly (P < 0.05) and abundantly (>5-fold) more excreted by tumors than by controls. Further selection for biomarkers with highest specificity and sensitivity yielded 52 candidates, including S100A9, MCM4, and four other proteins that have been proposed as candidate biomarkers for human CRC screening or surveillance, supporting the validity of our approach. For CHI3L1, we verified that protein levels were significantly increased in sera from patients with adenomas and advanced adenomas compared with control individuals, in contrast to the CRC biomarker CEA. Conclusion: These data show that proximal fluid proteome profiling with a mouse tumor model is a powerful approach to identify candidate biomarkers for early diagnosis of human cancer, exemplified by increased CHI3L1 protein levels in sera from patients with CRC precursor lesions.

Neurofilament ELISA validation (Article)

2010-01-31T00:00:00Z

Background: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. Methods: The UmanDiagnostics NF-light ®enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68 kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories' accuracy and preparation of standards were documented and used for the statistical analyses. Results: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R = 0.60, p < 0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R = 0.98, p < 0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss' multi-rater kappa and Gwet's AC1 statistics. Conclusion: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online.

A worldwide multicentre comparison of assays for cerebrospinal fluid biomarkers in Alzheimer's disease (Article)

2009-05-01T00:00:00Z

Background: Different cerebrospinal fluid (CSF) amyloid-beta 1-42 (Aβ1-42), total Tau (Tau) and Tau phosphorylated at threonine 181 (P-Tau) levels are reported, but currently there is a lack of quality control programmes. The aim of this study was to compare the measurements of these CSF biomarkers, between and within centres. Methods: Three CSF-pool sampleswere distributed to 13 laboratories in 2004 and thesame sampleswere again distributed to 18 laboratories in 2008. In 2004 six laboratories measured Aβ1-42, Tau and P-Tau and seven laboratories measured one or two of these marker(s) by enzyme-linked immunosorbent assays (ELISAs). In 2008, 12 laboratories measured all three markers, three laboratories measured one or two marker(s) by ELISAs and three laboratories measured the markers by Luminex. Results: In 2004, the ELISA intercentre coefficients of variance (interCV) were 31%, 21% and 13% for Aβ1-42, Tau and P-Tau, respectively. These were 37%, 16% and 15%, respectively, in 2008. When we restricted the analysis to the Innotestw (N = 13) for Aβ1-42, lower interCV were calculated (22%). The centres that participated in both years (N = 9) showed interCVs of 21%, 15% and 9% and intra-centre coefficients (intraCV) of variance of 25%,18% and 7% in 2008. Conclusions: The highest variability was found for Aβ1-42. The variabilities for Tau and P-Tau were lower in both years. The centres that participated in both years showed a high intraCV comparable to their interCV, indicating that there is not only a high variation between but also within centres. Besides a uniform standardization of (pre)analytical procedures, the same assay should be used to decrease the inter/intracentre variation.

Pooled analysis of prognostic impact of urokinase-type plasminogen activator and its inhibitor PAI-1 in 8377 breast cancer patients (Article)

2002-01-16T00:00:00Z

BACKGROUND: Urokinase-type plasminogen activator (uPA) and its inhibitor (PAI-1) play essential roles in tumor invasion and metastasis. High levels of both uPA and PAI-1 are associated with poor prognosis in breast cancer patients. To confirm the prognostic value of uPA and PAI-1 in primary breast cancer, we reanalyzed individual patient data provided by members of the European Organization for Research and Treatment of Cancer-Receptor and Biomarker Group (EORTC-RBG). METHODS: The study included 18 datasets involving 8377 breast cancer patients. During follow-up (median 79 months), 35% of the patients relapsed and 27% died. Levels of uPA and PAI-1 in tumor tissue extracts were determined by different immunoassays; values were ranked within each dataset and divided by the number of patients in that dataset to produce fractional ranks that could be compared directly across datasets. Associations of ranks of uPA and PAI-1 levels with relapse-free survival (RFS) and overall survival (OS) were analyzed by Cox multivariable regression analysis stratified by dataset, including the following traditional prognostic variables: age, menopausal status, lymph node status, tumor size, histologic grade, and steroid hormone-receptor status. All P values were two-sided. RESULTS: Apart from lymph node status, high levels of uPA and PAI-1 were the strongest predictors of both poor RFS and poor OS in the analyses of all patients. Moreover, in both lymph node-positive and lymph node-negative patients, higher uPA and PAI-1 values were independently associated with poor RFS and poor OS. For (untreated) lymph node-negative patients in particular, uPA and PAI-1 included together showed strong prognostic ability (all P<.001). CONCLUSIONS: This pooled analysis of the EORTC-RBG datasets confirmed the strong and independent prognostic value of uPA and PAI-1 in primary breast cancer. For patients with lymph node-negative breast cancer, uPA and PAI-1 measurements in primary tumors may be especially useful for designing individualized treatment strategies.

Oestrogen receptors and prolactin in rat mammary tumour development (Doctoral Thesis)

1980-05-21T00:00:00Z

Mammary cancer has been a challenge to researchers for many years, because of the continuous menace of this disease to (wo)mankind. Since it is difficult to study the mechanism of mammary gland carcinogenesis experimentally in the human, model systems had to be devised. "Spontaneous" mammary tumours in rats are quite rare, or occur only after a very long period (Burek & Hollander, 1977; Burek, 1978). Therefore, induction of tumours has been used to obtain large amounts of tumour tissue. Two tumour model systems which are relevant to the work presented in this thesis will be described in some detail.