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Non-typeable Haemophilus influenzae (NTHi) is the most common respiratory pathogen in patients with chronic obstructive disease. Limited data is available investigating the impact of NTHi infections on cellular re-differentiation processes in the bronchial mucosa. The aim of this study was to assess the effects of stimulation with NTHi on the bronchial epithelium regarding cellular re-differentiation processes using primary bronchial epithelial cells harvested from infection-free patients undergoing bronchoscopy. The cells were then cultivated using an air-liquid interface and stimulated with NTHi and TGF-β. Markers of epithelial and mesenchymal cells were analyzed using immunofluorescence, Western blot and qRT-PCR. Stimulation with both NTHi and TGF-ß led to a marked increase in the expression of the mesenchymal marker vimentin, while E-cadherin as an epithelial marker maintained a stable expression throughout the experiments. Furthermore, expression of collagen 4 and the matrix-metallopeptidases 2 and 9 were increased after stimulation, while the expression of tissue inhibitors of metallopeptidases was not affected by pathogen stimulation. In this study we show a direct pathogen-induced trans-differentiation of primary bronchial epithelial cells resulting in a co-localization of epithelial and mesenchymal markers and an up-regulation of extracellular matrix components.

BackgroundThe World Health Organization recommends standardised treatment durations for patients with tuberculosis (TB). We identified and validated a host-RNA signature as a biomarker for individualised therapy durations for patients with drug-susceptible (DS)- and multidrug-resistant (MDR)-TB.MethodsAdult patients with pulmonary TB were prospectively enrolled into five independent cohorts in Germany and Romania. Clinical and microbiological data and whole blood for RNA transcriptomic analysis were collected at pre-defined time points throughout therapy. Treatment outcomes were ascertained by TBnet criteria (6-month culture status/1-year follow-up). A whole-blood RNA therapy-end model was developed in a multistep process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment time points.Results50 patients with DS-TB and 30 patients with MDR-TB were recruited in the German identification cohorts (DS-GIC and MDR-GIC, respectively); 28 patients with DS-TB and 32 patients with MDR-TB in the German validation cohorts (DS-GVC and MDR-GVC, respectively); and 52 patients with MDR-TB in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model (TB22) that defined cure-associated end-of-therapy time points was derived from the DS- and MDR-GIC data. The TB22 model was superior to other published signatures to accurately predict clinical outcomes for patients in the DS-GVC (area under the curve 0.94, 95% CI 0.9–0.98) and suggests that cure may be achieved with shorter treatment durations for TB patients in the MDR-GIC (mean reduction 218.0 days, 34.2%; pConclusionBiomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-TB.

Background Lung cancer is the leading cause of cancer-related death in most western countries in both, males and females, accounting for roughly 20–25% of all cancer deaths. For choosing the most appropriate therapy regimen a definite diagnosis is a prerequisite. However, histological characterization of bronchoscopic biopsies particularly with low tumor cell content is often challenging. Therefore, this study aims at (a) determining the value of DNA methylation analysis applied to specimens obtained by bronchoscopic biopsy for the diagnosis of lung cancer and (b) at comparing aberrantly CpG loci identified in bronchoscopic biopsy with those identified by analyzing surgical specimens. Results We report the HumanMethylation450-based DNA methylation analysis of paired samples of bronchoscopic biopsy specimens either from the tumor side or from the contralateral tumor-free bronchus in 37 patients with definite lung cancer diagnosis and 18 patients with suspicious diagnosis. A differential DNA methylation analysis between both biopsy sites of patients with definite diagnosis identified 1303 loci. Even those samples were separated by the set of 1303 loci in which histopathological analysis could not unambiguously define the dignity. Further differential DNA methylation analyses distinguished between SCLC and NSCLC. We validated our results in an independent cohort of 40 primary lung cancers obtained by open surgical resection and their corresponding controls from the same patient as well as in publically available DNA methylation data from a TCGA cohort which could also be classified with high accuracy. Conclusions Considering that the prognosis correlates with tumor stage at time of diagnosis, early detection of lung cancer is vital and DNA methylation analysis might add valuable information to reliably characterize lung cancer even in histologically ambiguous sample material. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01024-6.

Emerging multidrug-resistant tuberculosis is a major global health challenge. The World Health Organization currently recommends treatment durations of 9–18 months or more for patients with multidrug-resistant tuberculosis. We identified and validated a host-RNA signature to serve as a biomarker for individualized therapy durations for patients with multidrug-resistant tuberculosis. Adult patients with pulmonary tuberculosis were prospectively enrolled into 5 independent cohorts in Germany and Romania. Clinical and microbiological data, and whole-blood for RNA transcriptomic analysis were collected at pre-defined timepoints throughout therapy. Treatment outcomes were ascertained one year after end-of-therapy. A whole-blood RNA therapy end model was developed in a multi-step process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment timepoints. Fifty patients with drug-susceptible tuberculosis and 30 patients with multidrug-resistant tuberculosis were recruited in the German identification cohorts (DS- and MDR-GIC), 28 patients with drug-susceptible tuberculosis and 32 patients with multidrug-resistant tuberculosis in the German validation cohorts (DS- and MDR-GVC), and 52 patients with multidrug-resistant tuberculosis in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model that defined cure-associated end-of-therapy timepoints was derived from the DS- and MDR-GIC data. The model accurately predicted clinical outcomes for patients in the DS-GVC (AUC=0.937 [95%CI:0.899–0.976]) and suggested that cure may be achieved with shorter treatment durations for tuberculosis patients in the MDR-GIC (mean reduction 218.0 days, 34.2%, pOne Sentence SummaryWe identified and validated a transcriptome model based on a 22-gene signature to predict individual treatment durations for patients with multidrug-resistant tuberculosis.

Gene amplification is considered to be one responsible cause for upregulation of Programmed Death Ligand-1 (PD-L1) in non-small cell lung cancer (NSCLC) and to represent a specific molecular subgroup possibly associated with immunotherapy response. Our aim was to analyze the frequency of PD-L1 amplification, its relation to PD-L1 mRNA and protein expression, and to characterize the immune microenvironment of amplified cases. The study was based on two independent NSCLC cohorts, including 354 and 349 cases, respectively. Tissue microarrays were used to evaluate PD-L1 amplification by FISH and PD-L1 protein by immunohistochemistry. Immune infiltrates were characterized immunohistochemically by a panel of immune markers (CD3, CD4, CD8, PD-1, Foxp3, CD20, CD138, CD168, CD45RO, NKp46). Mutational status was determined by targeted sequencing. RNAseq data was available for 197 patients. PD-L1 amplification was detected in 4.5% of all evaluable cases. PD-L1 amplification correlated only weakly with mRNA and protein expression. About 37% of amplified cases were negative for PD-L1 protein. PD-L1 amplification did not show any association with the mutational status. In squamous cell cancer, PD-L1 amplified cases were enriched among patients with high tumoral immune cell infiltration and showed gene expression profiles related to immune exhaustion. In conclusion, PD-L1 amplification correlates with PD-L1 expression in squamous cell cancer and was associated with an immune cell rich tumor phenotype. The correlative findings help to understand the role of PD-L1 amplification as an important immune escape mechanism in NSCLC and suggest the need to further evaluate PD-L1 amplification as predictive biomarker for checkpoint inhibitor therapy. Supplementary Information The online version contains supplementary material available at 10.1007/s00262-020-02825-z.