Placental growth factor (PlGF), a VEGF-homolog implicated in tumor angiogenesis and adaptation to antiangiogenic therapy, is emerging as candidate target in malignancies. Here, we addressed the expression, function, and prognostic value of PlGF in neuroendocrine tumors (NETs). PlGF was determined in NET patients' sera collected retrospectively (n=88) and prospectively (n=87) using Roche-Elecsys and correlated with clinicopathological data. Tumoral PlGF was evaluated by immunohistochemistry, effects of PlGF on proliferation and migration in vitro were assessed using different NET cell lines and effects on tumor growth in vivo in orthotopic xenografts. Circulating and tumoral PlGF was elevated in patients with pancreatic NETs (pNETs) compared with control sera and respective healthy tissue. De novo PlGF expression occurred primarily in the tumor stroma, suggesting paracrine stimulatory circuits. Indeed, PlGF enhanced NET proliferation and migration in vitro and, conversely, neutralizing antibodies to PlGF reduced tumor growth in vivo. Elevated circulating PlGF levels in NET patients correlated with advanced tumor grading and were associated with reduced tumor-related survival in pNETs. Subsequent determinations confirmed and extended our observation of elevated PlGF levels in a prospective cohort of grade 1 and grade 2 pNETs (n=30) and intestinal NETs (n=57). In low-grade pNETs, normal circulating PlGF levels were associated with better survival. In intestinal NETs, circulating PlGF above median emerged as an independent prognostic factor for shorter time-to-progression in multivariate analyses. These data assign to PlGF a novel function in the pathobiology of NETs and propose PlGF as a prognostic parameter and therapeutic target.

Latest data suggest that placental growth factor (PLGF), growth differentiation factor-15 (GDF-15) and hepatic growth factor (HGF) are involved in hepatic fibrogenesis. Diagnostic performance of these markers for non-invasive liver fibrosis prediction was evaluated based on liver histology and stiffness. In total 834 patients were recruited. Receiver-operating-characteristics were used to define cut-offs for markers correlating to fibrosis stages. Odds-ratios were calculated for the presence/absence of fibrosis/cirrhosis and confirmed in the sub-group of patients phenotyped by elastography only. Logistic and uni- and multivariate regression analyses were used to test for association of markers with liver fibrosis stages and for independent prediction of liver histology and stiffness. Marker concentrations correlated significantly (P<0.001) with histology and stiffness. Cut-offs for liver fibrosis (≥F2) were PLGF = 20.20 pg/ml, GDF15 = 1582.76 pg/ml and HGF = 2598.00 pg/ml. Logistic regression confirmed an increase of ORs from 3.6 over 33.0 to 108.4 with incremental (1–3) markers positive for increased liver stiffness (≥12.8kPa; all P<0.05). Subgroup analysis revealed associations with advanced fibrosis for HCV (three markers positive: OR = 59.9, CI 23.4–153.4, P<0.001) and non-HCV patients (three markers positive: OR = 144, CI 59–3383, P<0.001). Overall, serum markers identified additional 50% of patients at risk for advanced fibrosis presenting with low elastography results. In conclusion, this novel combination of markers reflects the presence of significant liver fibrosis detected by elastography and histology and may also identify patients at risk presenting with low elastography values.

893 Introduction: A European collaborative harmonization study involving 61 laboratories is being conducted under the auspices of the European Treatment and Outcome Study (EUTOS) for CML that aims to facilitate reporting of molecular BCR-ABL quantification results according to the International Scale (IS). The aim of this analysis was to investigate the effectiveness of this process and specifically the stability of conversion factors (CF) over time. Methods: The currently accepted way of adopting the IS is to establish and validate a laboratory-specific CF which is then used to convert local results to the IS. For round 1, preliminary CFs were calculated by centrally distributing standard samples containing 10–20 million WBC approximating to 10%, 1%, 0.1%, and 0.01% BCR-ABL IS. Rounds 2 and 3 were employed to refine the CF calculations using 25–30 CML patient samples from each participating laboratories covering a range of BCR-ABL levels between 0.01% and 10%. Log BCR-ABL values for the same samples were compared between reference and local laboratories applying the Bland-Altman bias plot. In order to judge the stability of each laboratory`s methodology, a CF index (ratio of round 3 CF divided by round 2 CF) was calculated and evaluated according to its capability to achieve optimum concordance of results. Results: Of the 61 laboratories participating in round 1, evaluable patient samples have been provided to date by 56 and 30 laboratories in rounds 2 and 3, respectively. Of the 30 laboratories with complete data, 12 had stable CFs (defined as a CF index within 0.75–1.33) whereas 18 laboratories were outside this range. Comparison of the CFs derived from round 2 with those derived from round 3 revealed better and more consistent concordance between laboratories with stable CFs compared to those with unstable CFs. For the 12 stable laboratories, 79% (round 3 CF) vs 79% (round 2 CF) of the samples were within a 2-fold range (0.5–2.0) and 93% vs 89% were within a 3-fold range (0.33–3.0). For the 18 unstable laboratories, 74% vs 55% of the samples were within a 2-fold range (0.5–2.0), p=0.0005 and 92% vs 77% were within a 3-fold range (0.33–3.0), p=0.0005. 2 of 12 laboratories with stable CFs and 8 of 18 laboratories with unstable CFs indicated changes in either one or more components of their procedures (cDNA synthesis, PCR platform, RQ-PCR protocol) that may have impacted on their CFs. Conclusion: These data indicate that CFs may be unstable in some laboratories even in the absence of significant changes to laboratory protocols. Further, it supports the need for continuous revalidation of CFs. In laboratories with unstable CFs we suggest revalidation within 3 to 6 months whereas those with stable CFs should be assessed on a yearly basis. We also suggest that laboratories with unstable CFs need to rigorously examine their internal processes to identify potential sources of variation. Disclosures: Müller: Novartis: Honoraria, Research Funding. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

The following information is missing from the Funding Section: FL received funding from the Federal Ministry of Education and Research (BMBF LiSyM 031L0051).There is an error in the first sentence of the Patients and methods section. The correct sentence is: Overall, we prospectively recruited 834 consecutive European individuals (age 18-84 years, males n = 510) with viral (n = 559) and non-viral (n = 275) chronic liver diseases.In the Patients and methods section, there is an error in the penultimate sentence under the subheading "Statistical analysis." The correct sentence is: All variables with P < 0.1 in the univariate analyses were then included in the multivariate model.In the Results section, there is an error in the ninth sentence under the subheading "Serum markers discriminate histological fibrosis stages." The correct sentence is: The positive predictive value of presenting with at least one marker positive and having fibrosis stage ! F2 was 89%.In the Results section, there is an error in the seventh sentence under the subheading "Performance of markers with respect to liver stiffness." The correct sentence is: This association was similarly present in patients without HCV infection (one marker: OR = 3.9, CI 1.9-8.2, P<0.001; two markers: OR = 18.3, CI 7.8-42.7, P<0.001; three markers: OR = 144, CI 59-3383, P<0.001).In the Results section, there is an error in the ninth sentence under the subheading "Performance of markers with respect to liver stiffness." The correct sentence is: To address the question whether the presence of positive markers adds information in patients with low TE values (i.e. <9.2 kPa), we used contingency tables.

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