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Diaphragmatic impairments exhibit high morbidity as well as mortality while current treatment options remain unsatisfactory. Tissue engineering (TE) approaches have explored the generation of an optimal biocompatible scaffold for diaphragmatic repair through tissue decellularization or de novo construction, with or without the addition of cells. We conducted a systematic review on the current state of the art in diaphragmatic tissue engineering (DTE) and found 24 articles eligible for final synthesis. The included approaches studied decellularization-based graft generation (9) and de novo bioscaffold construction (9). Three studies focused on in vitro host-scaffold interaction with synthesized, recellularized grafts (2) and decellularized extracellular matrix scaffolds (1). Another three studies investigated evaluation tools for decellularization efficacy. Among all studies, recellularization was performed in both decellularization-based (4) and de novo generated scaffolds (4). De novo constructed biocomposites as well as decellularized and recellularized scaffolds induced pro-regenerative remodeling and recovery of diaphragmatic function in all examined animal models. Potential therapeutic applications comprise substance defects requiring patch repair, such as congenital diaphragmatic hernia, and functional diseases demanding an entire organ transplant, like muscular dystrophies or dysfunction after prolonged artificial respiration.

Recent developments in immuno-oncology demonstrate that not only cancer cells, but also features of the tumor microenvironment guide precision medicine. Still, the relationship between tumor and microenvironment remains poorly understood. To overcome this limitation and identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to lung adenocarcinomas. While the highly heterogeneous carcinoma cell transcriptomes reflected histological grade and activity of relevant oncogenic pathways, our analysis revealed two distinct microenvironmental patterns. We identified a prognostically unfavorable group of tumors with a microenvironment composed of cancer-associated myofibroblasts, exhausted CD8+ T cells, proinflammatory monocyte-derived macrophages and plasmacytoid dendritic cells (CEP2 pattern) and a prognostically favorable group characterized by myeloid dendritic cells, anti-inflammatory monocyte-derived macrophages, normal-like myofibroblasts, NK cells and conventional T cells (MAN2C pattern). Our results show that single-cell gene expression profiling allows to identify patient subgroups based on the tumor microenvironment beyond cancer cell-centric profiling.

Formalin-fixed paraffin-embedded (FFPE) tissues are a valuable resource for retrospective clinical studies. Here, we evaluate the feasibility of (phospho-)proteomics on FFPE lung tissue regarding protein extraction, quantification, pre-analytics, and sample size. After comparing protein extraction protocols, we use the best-performing protocol for the acquisition of deep (phospho-)proteomes from lung squamous cell and adenocarcinoma with >8,000 quantified proteins and >14,000 phosphosites with a tandem mass tag (TMT) approach. With a microscaled approach, we quantify 7,000 phosphosites, enabling the analysis of FFPE biopsies with limited tissue amounts. We also investigate the influence of pre-analytical variables including fixation time and heat-assisted de-crosslinking on protein extraction efficiency and proteome coverage. Our improved workflows provide quantitative information on protein abundance and phosphosite regulation for the most relevant oncogenes, tumor suppressors, and signaling pathways in lung cancer. Finally, we present general guidelines to which methods are best suited for different applications, highlighting TMT methods for comprehensive (phospho-)proteome profiling for focused clinical studies and label-free methods for large cohorts., Formalin-fixed, paraffin-embedded (FFPE) specimens are an attractive resource for retrospective clinical proteomics studies. Here, the authors benchmark and optimize proteomics workflows for FFPE sample analysis and provide guidelines on which methods to use for different samples and applications.