TTF-1 status in early-stage lung adenocarcinoma is an independent predictor of relapse and survival superior to tumor grading.

OBJECTIVES: Thyroid transcription factor 1 (TTF-1) is a well-established independent prognostic factor in lung adenocarcinoma (LUAD), irrespective of stage. This study aims to determine if TTF-1's prognostic impact is solely based on histomorphological differentiation (tumor grading) or if it independently relates to a biologically more aggressive phenotype. We analyzed a large bi-centric LUAD cohort to accurately assess TTF-1's prognostic value in relation to tumor grade. PATIENTS AND METHODS: We studied 447 patients with resected LUAD from major German lung cancer centers (Berlin and Cologne), correlating TTF-1 status and grading with clinical, pathologic, and molecular data, alongside patient outcomes. TTF-1's impact was evaluated through univariate and multivariate Cox regression. Causal graph analysis was used to identify and account for potential confounders, improving the statistical estimation of TTF-1's predictive power for clinical outcomes. RESULTS: Univariate analysis revealed TTF-1 positivity associated with significantly longer disease-free survival (DFS) (median log HR -0.83; p = 0.018). Higher tumor grade showed a non-significant association with shorter DFS (median log HR 0.30; p = 0,62 for G1 to G2 and 0.68; p = 0,34 for G2 to G3). In multivariate analysis, TTF-1 positivity resulted in a significantly longer DFS (median log HR -0.65; p = 0.05) independent of all other parameters, including grading. Adjusting for potential confounders as indicated by the causal graph confirmed the superiority of TTF-1 over tumor grading in prognostics power. CONCLUSIONS: TTF-1 status predicts relapse and survival in LUAD independently of tumor grading. The prognostic power of tumor grading is limited to TTF-1-positive patients, and the effect size of TTF-1 surpasses that of tumor grading. We recommend including TTF1 status as a prognostic factor in the diagnostic guidelines of LUAD.

Initial Proportion and Dynamic of B.1.1.7 SARS-CoV-2 in a Large City in the West of Germany.

Rationale: Several mutational variants of SARS-CoV-2 have been identified in the past months with increasing prevalence worldwide. Some variants, such as B.1.1.7, are of high relevance due to increased transmissibility, facilitating virus spread and calling for stricter containment measures. Objectives: The aim of this study was to examine proportion and dynamic of B.1.1.7 in SARS-CoV-2-positive samples in a large city in the west of Germany. Methods: Consecutive SARS-CoV-2-positive samples from a local outpatient clinic, obtained over a period of 4 weeks (mid-January to mid-February 2021), were examined for the presence of the variant B.1.1.7. The size of B.1.1.7 infection clusters was compared with non-B.1.1.7 clusters. The transmissibility of SARS-CoV-2 variant B.1.1.7 was described based on corresponding cases of an infection cluster in a local child daycare centre. Results: Among 226 SARS-CoV-2-positive cases, B.1.1.7 was detected in 74 subjects (33%). The 7-day moving mean of the B.1.1.7 proportion started at 20% and reached 50% only 3 weeks later. B.1.1.7 clusters comprised 10.7 ± 12.1 persons per cluster, while non-B.1.1.7 clusters were considerably smaller (5.1 ± 5.8). One specific B.1.1.7 infection cluster in a 40-children daycare centre started with one teacher leading to 11 infected children and 8 infections among teachers. The infection spread to 6 families and one other daycare centre, with a total 43 SARS-CoV-2-positive subjects. Conclusions: We found a rapid increase in the SARS-CoV-2 variant B.1.1.7 with larger infection clusters than non-B.1.1.7. These results suggested a rapid increase in the B.1.1.7 proportion and a renewed increase in the total number of SARS-CoV-2 infections for the time following the analysed period. Considering the rapid emergence and spread of viral variants, close monitoring of mutation events is essential. Therefore, routine whole-genome sequencing appears to be useful in addition to searching for known mutations.