TY  - JOUR
A1  - Eckardt, Jan-Niklas
A1  - Stasik, Sebastian
A1  - Kramer, Michael
A1  - Röllig, Christoph
A1  - Krämer, Alwin
A1  - Scholl, Sebastian
A1  - Hochhaus, Andreas
A1  - Crysandt, Martina
A1  - Brümmendorf, Tim H.
A1  - Naumann, Ralph
A1  - Steffen, Björn
A1  - Kunzmann, Volker
A1  - Einsele, Hermann
A1  - Schaich, Markus
A1  - Burchert, Andreas
A1  - Neubauer, Andreas
A1  - Schäfer-Eckart, Kerstin
A1  - Schliemann, Christoph
A1  - Krause, Stefan W.
A1  - Herbst, Regina
A1  - Hänel, Mathias
A1  - Frickhofen, Norbert
A1  - Noppeney, Richard
A1  - Kaiser, Ulrich
A1  - Baldus, Claudia D.
A1  - Kaufmann, Martin
A1  - Rácil, Zdenek
A1  - Platzbecker, Uwe
A1  - Berdel, Wolfgang E.
A1  - Mayer, Jiří
A1  - Serve, Hubert
A1  - Müller-Tidow, Carsten
A1  - Ehninger, Gerhard
A1  - Stölzel, Friedrich
A1  - Kroschinsky, Frank
A1  - Schetelig, Johannes
A1  - Bornhäuser, Martin
A1  - Thiede, Christian
A1  - Middeke, Jan Moritz
T1  - Loss-of-function mutations of BCOR are an independent marker of adverse outcomes in intensively treated patients with acute myeloid leukemia
JF  - Cancers
N2  - Acute myeloid leukemia (AML) is characterized by recurrent genetic events. The BCL6 corepressor (BCOR) and its homolog, the BCL6 corepressor-like 1 (BCORL1), have been reported to be rare but recurrent mutations in AML. Previously, smaller studies have reported conflicting results regarding impacts on outcomes. Here, we retrospectively analyzed a large cohort of 1529 patients with newly diagnosed and intensively treated AML. BCOR and BCORL1 mutations were found in 71 (4.6%) and 53 patients (3.5%), respectively. Frequently co-mutated genes were DNTM3A, TET2 and RUNX1. Mutated BCORL1 and loss-of-function mutations of BCOR were significantly more common in the ELN2017 intermediate-risk group. Patients harboring loss-of-function mutations of BCOR had a significantly reduced median event-free survival (HR = 1.464 (95%-Confidence Interval (CI): 1.005–2.134), p = 0.047), relapse-free survival (HR = 1.904 (95%-CI: 1.163–3.117), p = 0.01), and trend for reduced overall survival (HR = 1.495 (95%-CI: 0.990–2.258), p = 0.056) in multivariable analysis. Our study establishes a novel role for loss-of-function mutations of BCOR regarding risk stratification in AML, which may influence treatment allocation.
KW  - acute myeloid leukemia
KW  - BCOR
KW  - BCORL1
KW  - loss-of-function
KW  - risk stratification
KW  - survival
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-236735
SN  - 2072-6694
VL  - 13
IS  - 9
ER  - 
TY  - JOUR
A1  - Lüke, Florian
A1  - Haller, Florian
A1  - Utpatel, Kirsten
A1  - Krebs, Markus
A1  - Meidenbauer, Norbert
A1  - Scheiter, Alexander
A1  - Spoerl, Silvia
A1  - Heudobler, Daniel
A1  - Sparrer, Daniela
A1  - Kaiser, Ulrich
A1  - Keil, Felix
A1  - Schubart, Christoph
A1  - Tögel, Lars
A1  - Einhell, Sabine
A1  - Dietmaier, Wolfgang
A1  - Huss, Ralf
A1  - Dintner, Sebastian
A1  - Sommer, Sebastian
A1  - Jordan, Frank
A1  - Goebeler, Maria-Elisabeth
A1  - Metz, Michaela
A1  - Haake, Diana
A1  - Scheytt, Mithun
A1  - Gerhard-Hartmann, Elena
A1  - Maurus, Katja
A1  - Brändlein, Stephanie
A1  - Rosenwald, Andreas
A1  - Hartmann, Arndt
A1  - Märkl, Bruno
A1  - Einsele, Hermann
A1  - Mackensen, Andreas
A1  - Herr, Wolfgang
A1  - Kunzmann, Volker
A1  - Bargou, Ralf
A1  - Beckmann, Matthias W.
A1  - Pukrop, Tobias
A1  - Trepel, Martin
A1  - Evert, Matthias
A1  - Claus, Rainer
A1  - Kerscher, Alexander
T1  - Identification of disparities in personalized cancer care — a joint approach of the German WERA consortium
JF  - Cancers
N2  - (1) Background: molecular tumor boards (MTBs) are crucial instruments for discussing and allocating targeted therapies to suitable cancer patients based on genetic findings. Currently, limited evidence is available regarding the regional impact and the outreach component of MTBs; (2) Methods: we analyzed MTB patient data from four neighboring Bavarian tertiary care oncology centers in Würzburg, Erlangen, Regensburg, and Augsburg, together constituting the WERA Alliance. Absolute patient numbers and regional distribution across the WERA-wide catchment area were weighted with local population densities; (3) Results: the highest MTB patient numbers were found close to the four cancer centers. However, peaks in absolute patient numbers were also detected in more distant and rural areas. Moreover, weighting absolute numbers with local population density allowed for identifying so-called white spots—regions within our catchment that were relatively underrepresented in WERA MTBs; (4) Conclusions: investigating patient data from four neighboring cancer centers, we comprehensively assessed the regional impact of our MTBs. The results confirmed the success of existing collaborative structures with our regional partners. Additionally, our results help identifying potential white spots in providing precision oncology and help establishing a joint WERA-wide outreach strategy.
KW  - precision oncology
KW  - MTB
KW  - patient access
KW  - cancer care
KW  - outreach
KW  - real world data
KW  - outcomes research
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-290311
SN  - 2072-6694
VL  - 14
IS  - 20
ER  -