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Objectives: An increasing number of treatment-determining biomarkers has been identified in non-small cell lung cancer (NSCLC) and molecular testing is recommended to enable optimal individualized treatment. However, data on implementation of these recommendations in the “real-world” setting are scarce. This study presents comprehensive details on the frequency, methodology and results of biomarker testing of advanced NSCLC in Germany.
Patients and methods: This analysis included 3,717 patients with advanced NSCLC (2,921 non-squamous; 796 squamous), recruited into the CRISP registry at start of systemic therapy by 150 German sites between December 2015 and June 2019. Evaluated were the molecular biomarkers EGFR, ALK, ROS1, BRAF, KRAS, MET, TP53, RET, HER2, as well as expression of PD-L1.
Results: In total, 90.5 % of the patients were tested for biomarkers. Testing rates were 92.2 % (non-squamous), 70.7 % (squamous) and increased from 83.2 % in 2015/16 to 94.2% in 2019. Overall testing rates for EGFR, ALK, ROS1, and BRAF were 72.5 %, 74.5 %, 66.1 %, and 53.0 %, respectively (non-squamous). Testing rates for PD-L1 expression were 64.5 % (non-squamous), and 58.5 % (squamous). The most common testing methods were immunohistochemistry (68.5 % non-squamous, 58.3 % squamous), and next-generation sequencing (38.7 % non-squamous, 14.4 % squamous). Reasons for not testing were insufficient tumor material or lack of guideline recommendations (squamous). No alteration was found in 37.8 % (non-squamous), and 57.9 % (squamous), respectively. Most common alterations in non-squamous tumors (all patients/all patients tested for the respective biomarker): KRAS (17.3 %/39.2 %), TP53 (14.1 %/51.4 %), and EGFR (11.0 %/15.1 %); in squamous tumors: TP53 (7.0 %/69.1 %), MET (1.5 %/11.1 %), and EGFR (1.1 %/4.4 %). Median PFS (non-squamous) was 8.7 months (95 % CI 7.4–10.4) with druggable EGFR mutation, and 8.0 months (95 % CI 3.9–9.2) with druggable ALK alterations.
Conclusion: Testing rates in Germany are high nationwide and acceptable in international comparison, but still leave out a significant portion of patients, who could potentially benefit. Thus, specific measures are needed to increase implementation.
Background: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a novel AI software version for automated BA assessment in comparison to the Greulich-Pyle method.
Methods: Radiographs of 514 patients were analysed in this retrospective study. Total BA was assessed independently by three blinded radiologists applying the GP method and by the AI software. Overall and gender-specific BA assessment results, as well as reading times of both approaches, were compared, while the reference BA was defined by two blinded experienced paediatric radiologists in consensus by application of the Greulich-Pyle method.
Results: Mean absolute deviation (MAD) and root mean square deviation (RSMD) were significantly lower between AI-derived BA and reference BA (MAD 0.34 years, RSMD 0.38 years) than between reader-calculated BA and reference BA (MAD 0.79 years, RSMD 0.89 years; p < 0.001). The correlation between AI-derived BA and reference BA (r = 0.99) was significantly higher than between reader-calculated BA and reference BA (r = 0.90; p < 0.001). No statistical difference was found in reader agreement and correlation analyses regarding gender (p = 0.241). Mean reading times were reduced by 87% using the AI system.
Conclusions: A novel AI software enabled highly accurate automated BA assessment. It may improve efficiency in clinical routine by reducing reading times without compromising the accuracy compared with the Greulich-Pyle method.
We report here the nuclear magnetic resonance 19F screening of 14 RNA targets with different secondary and tertiary structure to systematically assess the druggability of RNAs. Our RNA targets include representative bacterial riboswitches that naturally bind with nanomolar affinity and high specificity to cellular metabolites of low molecular weight. Based on counter-screens against five DNAs and five proteins, we can show that RNA can be specifically targeted. To demonstrate the quality of the initial fragment library that has been designed for easy follow-up chemistry, we further show how to increase binding affinity from an initial fragment hit by chemistry that links the identified fragment to the intercalator acridine. Thus, we achieve low-micromolar binding affinity without losing binding specificity between two different terminator structures.
The nuclear factor kappa beta (NFκB) signaling pathway plays an important role in liver homeostasis and cancer development. Tax1-binding protein 1 (Tax1BP1) is a regulator of the NFκB signaling pathway, but its role in the liver and hepatocellular carcinoma (HCC) is presently unknown. Here we investigated the role of Tax1BP1 in liver cells and murine models of HCC and liver fibrosis. We applied the diethylnitrosamine (DEN) model of experimental hepatocarcinogenesis in Tax1BP1+/+ and Tax1BP1−/− mice. The amount and subsets of non-parenchymal liver cells in in Tax1BP1+/+ and Tax1BP1−/− mice were determined and activation of NFκB and stress induced signaling pathways were assessed. Differential expression of mRNA and miRNA was determined. Tax1BP1−/− mice showed increased numbers of inflammatory cells in the liver. Furthermore, a sustained activation of the NFκB signaling pathway was found in hepatocytes as well as increased transcription of proinflammatory cytokines in isolated Kupffer cells from Tax1BP1−/− mice. Several differentially expressed mRNAs and miRNAs in livers of Tax1BP1−/− mice were found, which are regulators of inflammation or are involved in cancer development or progression. Furthermore, Tax1BP1−/− mice developed more HCCs than their Tax1BP1+/+ littermates. We conclude that Tax1BP1 protects from liver cancer development by limiting proinflammatory signaling.