Entwicklung eines digitalen Therapieempfehlungs-Algorithmus zur Therapie metastasierter Mammakarzinome und Validierung der Empfehlungssicherheit durch Vergleich mit den Empfehlungen eines interdisziplinären Tumorboards eines universitären Brustzentrums

Der Stellenwert von Tumorboards, die sowohl vom Nationalen Krebsplan als auch von onkologischen Fachgesellschaften als Standard in der Behandlung onkologischer Patienten gefordert werden, konnte in den vergangenen Jahren wissenschaftlich vielfach untermauert werden. Dabei stellt in der Praxis die zunehmende Komplexität onkologischer Therapien die behandelnden Ärzte der einzelnen Fachrichtungen in den Tumorkonferenzen vor eine enorme Herausforderung. Insbesondere die zur Zertifizierung als Krebszentrum erforderliche Vorstellung aller Patienten in einem Tumorboard führt in der Realität häufig zu einem sehr ungünstigen Verhältnis von Fallzahl zu vorhandener Zeit. Ein sinnvoller Ansatz könnte hier eine digitale Entscheidungsunterstützung („Digital Decision Support“) bieten. Eine automatisierte Therapieempfehlung für definierte Standardfälle könnte Tumorboards quantitativ entlasten und hierdurch mehr Raum zur Diskussion komplexer Fälle ermöglichen. In einer retrospektiven Analyse wurden die Empfehlungen des M1 Tumorboard Mammakarzinom des CIO der Uniklinik Köln mit den Therapieempfehlungen eines zuvor entwickelten Experten-kuratierten Digital Support Systems verglichen. Hierfür wurde für alle eingeschlossenen Fälle anhand der in der Tumorboard-Anmeldung angegebenen Informationen zunächst eine digitale Therapieempfehlung ermittelt. Diese wurde mit der originalen Tumorboardempfehlung auf Übereinstimmung verglichen. Analysiert wurden Übereinstimmungsraten sowie Gründe für Diskonkordanzen und Studienausschluss. Im Anschluss wurden mögliche Fehler im Therapiealgorithmus identifiziert, dieser entsprechend modifiziert und mit einem aktuellen Datensatz erneut validiert. Die Übereinstimmungsraten beider Algorithmen wurden mittels Fisher-Test auf Unabhängigkeit überprüft. Zudem wurden Zusammenhänge zwischen Patienten- und Tumormerkmalen und Übereinstimmung mittels binärer logistischer Regression identifiziert. Im ersten Analyseschritt zeigte sich bei Verwendung des Abfragealgorithmus eine vollständige oder teilweise Übereinstimmungsrate von 71 % im Vergleich zu den Empfehlungen des Tumorboards. Wichtige Erkenntnisse für die Anwendung des Therapiealgorithmus lieferte insbesondere die Betrachtung der Gründe für fehlende Übereinstimmungen, die sich zumeist in einer durch einen Rezeptorswitch bedingten Änderung der Histologie oder in klinisch nicht relevanten Abfragen fanden. Um hierdurch entstehenden Fehlern in der Therapiefindung vorzubeugen, wurde der Algorithmus angepasst. Nach Anpassung der Abfragelogik konnte die Gesamtübereinstimmung auf 87 %, in einzelnen Subgruppen sogar bis auf 100 %, verbessert werden. In Analogie zu anderen Studien lassen die Ergebnisse den Rückschluss zu, dass digitale Medien eine gute Möglichkeit bieten, die Therapieentscheidungen wenig komplexer Standardfälle zu unterstützen und sich die dahinterstehende Abfragelogik als Grundlage für ein „Digital Support System“ eignen. Komplexe Erkrankungen, insbesondere solche, die sich im metastasierten Stadium jenseits der Erstlinientherapie befinden, werden von dem Therapiealgorithmus nicht erfasst und bedürfen weiterhin einer interdisziplinären Diskussion im Tumorboard. Die Studie untermauert zudem die Notwendigkeit der regelmäßigen Validierung digitaler Systeme, die zu einer Identifikation von Fehlern führt und inhaltlich nicht korrekte Therapieempfehlungen verhindern kann

Dibenzazecine compounds with a novel dopamine/5HT(2A )receptor profile and 3D-QSAR analysis

BACKGROUND: Antipsychotics are divided into typical and atypical compounds based on clinical efficacy and side effects. The purpose of this study was to characterize in vitro a series of novel azecine-type compounds at human dopamine D(1)-D(5 )and 5HT(2A )receptors and to assign them to different classes according to their dopamine/5HT(2A )receptor profile. RESULTS: Regardless of using affinity data (pK(i )values at D(1)-D(5 )and 5HT(2A)) or selectivity data (15 log (K(i )ratios)), principal component analysis with azecine-type compounds, haloperidol, and clozapine revealed three groups of dopamine/5HT(2A )ligands: 1) haloperidol; 2) clozapine plus four azecine-type compounds; 3) two hydroxylated dibenzazecines. Reducing the number of K(i )ratios used for principal component analysis from 15 to two (the D(1)/D(2 )and D(2)/5HT(2A )K(i )ratios) obtained the same three groups of compounds. The most potent dibenzazecine clustering in the same group as clozapine was the non-hydroxylated LE410 which shows a slightly different D(2)-like receptor profile (D(2L )> D(3 )> D(4.4)) than clozapine (D(4.4 )> D(2L )> D(3)). The monohydroxylated dibenzacezine LE404 clusters in a separate group from clozapine/LE410 and from haloperidol and shows increased D(1 )selectivity. CONCLUSION: In conclusion, two compounds with a novel dopamine/5HT(2A )receptor profile, LE404 and LE410, with some differences in their respective D(1)/D(2 )receptor affinities including a validated pharmacophore-based 3D-QSAR model for D(1 )antagonists are presented

Absolute configuration and anti-tumor activity of torrubiellin B

K

Early Detection of Erlotinib Treatment Response in NSCLC by 3′-Deoxy-3′-[18F]-Fluoro-L-Thymidine ([18F]FLT) Positron Emission Tomography (PET)

Background: Inhibition of the epidermal growth factor receptor (EGFR) has shown clinical success in patients with advanced non-small cell lung cancer (NSCLC). Somatic mutations of EGFR were found in lung adenocarcinoma that lead to exquisite dependency on EGFR signaling; thus patients with EGFR-mutant tumors are at high chance of response to EGFR inhibitors. However, imaging approaches affording early identification of tumor response in EGFR-dependent carcinomas have so far been lacking. Methodology/Principal Findings: We performed a systematic comparison of 3′-Deoxy-3′-[$^{18}F$]-fluoro-L-thymidine ([$^{18}F$]FLT) and 2-[$^{18}F$]-fluoro-2-deoxy-D-glucose ([$^{18}F$]FDG) positron emission tomography (PET) for their potential to identify response to EGFR inhibitors in a model of EGFR-dependent lung cancer early after treatment initiation. While erlotinib-sensitive tumors exhibited a striking and reproducible decrease in [$^{18}F$]FLT uptake after only two days of treatment, [$^{18}F$]FDG PET based imaging revealed no consistent reduction in tumor glucose uptake. In sensitive tumors, a decrease in [$^{18}F$]FLT PET but not [$^{18}F$]FDG PET uptake correlated with cell cycle arrest and induction of apoptosis. The reduction in [$^{18}F$]FLT PET signal at day 2 translated into dramatic tumor shrinkage four days later. Furthermore, the specificity of our results is confirmed by the complete lack of [$^{18}F$]FLT PET response of tumors expressing the T790M erlotinib resistance mutation of EGFR. Conclusions: [$^{18}F$]FLT PET enables robust identification of erlotinib response in EGFR-dependent tumors at a very early stage. [$^{18}F$]FLT PET imaging may represent an appropriate method for early prediction of response to EGFR TKI treatment in patients with NSCLC

Navigating the garden of forking paths for data exclusions in fear conditioning research

In this report, we illustrate the considerable impact of researcher degrees of freedom with respect to exclusion of participants in paradimgs with a learning element. We illustrate this empirically through case examples from human fear conditioning research where the exclusion of ‘non-learners’ and ‘non-responders’ is common-despite a lack of consensus on how to define these groups. We illustrate the substantial heterogeneity in exclusion criteria based on a systematic literature search and highlight potential problems and pitfalls of different definitions through case examples based on re-analyses of existing data sets. Based on this, we propose a consensus on evidence-based rather than idiosyncratic criteria including clear guidelines on reporting details. Taken together, we illustrate how flexibility in data collection and analysis can be avoided, which will benefit the robustness and replicability of research findings and can be expected to be applicable to other fields of research that involve a learning element

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Common variants in P2RY11 are associated with narcolepsy.

l e t t e r s Growing evidence supports the hypothesis that narcolepsy with cataplexy is an autoimmune disease. We here report genomewide association analyses for narcolepsy with replication and fine mapping across three ethnic groups (3,406 individuals of European ancestry, 2,414 Asians and 302 African Americans). We identify a SNP in the 3′ untranslated region of P2RY11, the purinergic receptor subtype P2Y 11 gene, which is associated with narcolepsy (rs2305795, combined P = 6.1 × 10 −10 , odds ratio = 1.28, 95% CI 1.19-1.39, n = 5689). The diseaseassociated allele is correlated with reduced expression of P2RY11 in CD8 + T lymphocytes (339% reduced, P = 0.003) and natural killer (NK) cells (P = 0.031), but not in other peripheral blood mononuclear cell types. The low expression variant is also associated with reduced P2RY11-mediated resistance to ATP-induced cell death in T lymphocytes (P = 0.0007) and natural killer cells (P = 0.001). These results identify P2RY11 as an important regulator of immune-cell survival, with possible implications in narcolepsy and other autoimmune diseases

Common variants in P2RY11 are associated with narcolepsy.

Growing evidence supports the hypothesis that narcolepsy with cataplexy is an autoimmune disease. We here report genome-wide association analyses for narcolepsy with replication and fine mapping across three ethnic groups (3,406 individuals of European ancestry, 2,414 Asians and 302 African Americans). We identify a SNP in the 3' untranslated region of P2RY11, the purinergic receptor subtype P2Y₁₁ gene, which is associated with narcolepsy (rs2305795, combined P = 6.1 × 10⁻¹⁰, odds ratio = 1.28, 95% CI 1.19-1.39, n = 5689). The disease-associated allele is correlated with reduced expression of P2RY11 in CD8(+) T lymphocytes (339% reduced, P = 0.003) and natural killer (NK) cells (P = 0.031), but not in other peripheral blood mononuclear cell types. The low expression variant is also associated with reduced P2RY11-mediated resistance to ATP-induced cell death in T lymphocytes (P = 0.0007) and natural killer cells (P = 0.001). These results identify P2RY11 as an important regulator of immune-cell survival, with possible implications in narcolepsy and other autoimmune diseases.journal articleresearch support, n.i.h., extramuralresearch support, non-u.s. gov'tresearch support, u.s. gov't, p.h.s.2011 Jan2010 12 19importedErratum in : Nat Genet. 2011 Oct;43(10):1040