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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.
Human lymph nodes play a central part of immune defense against infection agents and tumor cells. Lymphoid follicles are compartments of the lymph node which are spherical, mainly filled with B cells. B cells are cellular components of the adaptive immune systems. In the course of a specific immune response, lymphoid follicles pass different morphological differentiation stages. The morphology and the spatial distribution of lymphoid follicles can be sometimes associated to a particular causative agent and development stage of a disease. We report our new approach for the automatic detection of follicular regions in histological whole slide images of tissue sections immuno-stained with actin. The method is divided in two phases: (1) shock filter-based detection of transition points and (2) segmentation of follicular regions. Follicular regions in 10 whole slide images were manually annotated by visual inspection, and sample surveys were conducted by an expert pathologist. The results of our method were validated by comparing with the manual annotation. On average, we could achieve a Zijbendos similarity index of 0.71, with a standard deviation of 0.07.
Consciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness. While the level of consciousness can be taken to describe the actual brain state, a complete characterization should also include its potential behavior against external perturbations. We developed and analyzed whole-brain computational models to show that the stability of conscious states provides information complementary to their similarity to conscious wakefulness. Our work leads to a novel methodological framework to sort out different brain states by their stability and reversibility, and illustrates its usefulness to dissociate between physiological (sleep), pathological (brain-injured patients), and pharmacologically-induced (anesthesia) loss of consciousness.
Mental imagery provides an essential simulation tool for remembering the past and planning the future, with its strength affecting both cognition and mental health. Research suggests that neural activity spanning prefrontal, parietal, temporal, and visual areas supports the generation of mental images. Exactly how this network controls the strength of visual imagery remains unknown. Here, brain imaging and transcranial magnetic phosphene data show that lower resting activity and excitability levels in early visual cortex (V1-V3) predict stronger sensory imagery. Further, electrically decreasing visual cortex excitability using tDCS increases imagery strength, demonstrating a causative role of visual cortex excitability in controlling visual imagery. Together, these data suggest a neurophysiological mechanism of cortical excitability involved in controlling the strength of mental images.
Mental imagery provides an essential simulation tool for remembering the past and planning the future, with its strength affecting both cognition and mental health. Research suggests that neural activity spanning prefrontal, parietal, temporal, and visual areas supports the generation of mental images. Exactly how this network controls the strength of visual imagery remains unknown. Here, brain imaging and transcranial magnetic phosphene data show that lower resting activity and excitability levels in early visual cortex (V1-V3) predict stronger sensory imagery. Electrically decreasing visual cortex excitability using tDCS increases imagery strength, demonstrating a causative role of visual cortex excitability in controlling visual imagery. These data suggest a neurophysiological mechanism of cortical excitability involved in controlling the strength of mental images.
Purpose: Molecular diagnostics including next generation gene sequencing are increasingly used to determine options for individualized therapies in brain tumor patients. We aimed to evaluate the decision-making process of molecular targeted therapies and analyze data on tolerability as well as signals for efficacy.
Methods: Via retrospective analysis, we identified primary brain tumor patients who were treated off-label with a targeted therapy at the University Hospital Frankfurt, Goethe University. We analyzed which types of molecular alterations were utilized to guide molecular off-label therapies and the diagnostic procedures for their assessment during the period from 2008 to 2021. Data on tolerability and outcomes were collected.
Results: 413 off-label therapies were identified with an increasing annual number for the interval after 2016. 37 interventions (9%) were targeted therapies based on molecular markers. Glioma and meningioma were the most frequent entities treated with molecular matched targeted therapies. Rare entities comprised e.g. medulloblastoma and papillary craniopharyngeoma. Molecular targeted approaches included checkpoint inhibitors, inhibitors of mTOR, FGFR, ALK, MET, ROS1, PIK3CA, CDK4/6, BRAF/MEK and PARP. Responses in the first follow-up MRI were partial response (13.5%), stable disease (29.7%) and progressive disease (46.0%). There were no new safety signals. Adverse events with fatal outcome (CTCAE grade 5) were not observed. Only, two patients discontinued treatment due to side effects. Median progression-free and overall survival were 9.1/18 months in patients with at least stable disease, and 1.8/3.6 months in those with progressive disease at the first follow-up MRI.
Conclusion: A broad range of actionable alterations was targeted with available molecular therapeutics.
However, efficacy was largely observed in entities with paradigmatic oncogenic drivers, in particular with BRAF mutations. Further research on biomarker-informed molecular matched therapies is urgently necessary.
Das akut-auf-chronische Leberversagen (ACLF) entsteht durch eine akute Dekompensation einer vorbestehenden Leberzirrhose mit begleitendem Multiorganversagen und ist durch eine sehr hohe Kurzzeitmortalität gekennzeichnet. Die Kriterien der European Association for the Study of Chronic Liver Failure (EASL-CLIF) definieren in diesem Zusammenhang ein Lungenversagen als Abfall des Horovitz-Quotienten unter 200mmHg oder als Abfall des Quotienten aus SpO2/FiO2 unter 214. Während Lungenfunktionsstörungen als unabhängiger Risikofaktor für Mortalität bei Patienten mit Leberzirrhose belegt sind, wurde die Bedeutung von mechanischer Beatmung und Lungenversagen bisher nicht isoliert untersucht. Ziel der Studie ist die Rolle von mechanischer Beatmung und Lungenversagen im ACLF zu analysieren und eine mögliche Unterinterpretation in den etablierten prädiktiven Modellen zu evaluieren.
Es wurden Daten aus 775 Hospitalisationen mit intensivmedizinischer Behandlung am Universitätsklinikum Frankfurt von insgesamt 498 Patienten mit Leberzirrhose im Zeitraum März 2015 bis Juli 2019 retrospektiv erfasst und ausgewertet. ACLF und Organversagen wurden gemäß EASL-CLIF Kriterien definiert. Es erfolgte die statistische Analyse verschiedener Kohorten, wobei ACLF-Patienten mittels Propensity Score hinsichtlich CLIF-C ACLF Score und Geschlecht gematcht und anhand der pulmonalen Beeinträchtigung in eine dreiarmige Testkohorte bestehend aus 49 Patienten mit Lungenversagen, 49 Patienten mit Schutzintubation und 49 Patienten ohne pulmonale Beeinträchtigung aufgeteilt wurden.
216 Patienten zeigten ein ACLF bei Aufnahme, 121 wurden mechanisch beatmet und 68 hatten ein Lungenversagen. In der gematchten Kohorte (n=147) konnten Lungenversagen (HR 3,0) und mechanische Beatmung (HR 1,7) als unabhängige Risikofaktoren für eine hohe 28-Tage-Mortalität identifiziert werden. Der CLIF-C ACLF Score konnte als bestes Modell für die Vorhersage der Kurzzeitmortalität bestätigt werden (AUROC 0,81), zeigte allerdingt deutliche Schwächen in der Subkohorte der Patienten mit Lungenversagen (AUROC 0,49) und mechanischer Beatmung (AUROC 0,68). Eine Kalibrierung des CLIF-C ACLF Scores für diese beiden Risikofaktoren liefert auch in der Gesamtkohorte aller zirrhotischer Patienten eine signifikant verbesserte prädiktive Performance (AUROC 0,87; p=0,001).
Mechanische Beatmung und Lungenversagen sind im Rahmen eines ACLF mit einer erhöhten Kurzzeitmortalität assoziiert und nur ungenügend in den etablierten Prädiktionsmodellen abgebildet. Die Kalibrierung des CLIF-C ACLF Scores für diese Risikofaktoren führt zu einer verbesserten Vorhersagegenauigkeit.
The new variant of concern (VOC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Omicron (B.1.1.529), is genetically very different from other VOCs. We compared Omicron with the preceding VOC Delta (B.1.617.2) and the wildtype strain (B.1) with respect to their interactions with the antiviral type I interferon (IFN-alpha/beta) response in infected cells. Our data indicate that Omicron has gained an elevated capability to suppress IFN-beta induction upon infection and to better withstand the antiviral state imposed by exogenously added IFN-alpha.
The SARS-CoV-2 Omicron variant is currently causing a large number of infections in many countries. A number of antiviral agents are approved or in clinical testing for the treatment of COVID-19. Despite the high number of mutations in the Omicron variant, we here show that Omicron isolates display similar sensitivity to eight of the most important anti-SARS-CoV-2 drugs and drug candidates (including remdesivir, molnupiravir, and PF-07321332, the active compound in paxlovid), which is of timely relevance for the treatment of the increasing number of Omicron patients. Most importantly, we also found that the Omicron variant displays a reduced capability of antagonising the host cell interferon response. This provides a potential mechanistic explanation for the clinically observed reduced pathogenicity of Omicron variant viruses compared to Delta variant viruses.
Recently, we have shown that SARS-CoV-2 Omicron virus isolates are less effective at inhibiting the host cell interferon response than Delta viruses. Here, we present further evidence that reduced interferon-antagonising activity explains at least in part why Omicron variant infections are inherently less severe than infections with other SARS-CoV-2 variants. Most importantly, we here also show that Omicron variant viruses display enhanced sensitivity to interferon treatment, which makes interferons promising therapy candidates for Omicron patients, in particular in combination with other antiviral agents.