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IntroductionHead and neck squamous cell carcinomas (HNSCC) are characterized by strong cellular and molecular heterogeneity and treatment resistance entailing poor survival. Besides cell-intrinsic properties, carcinoma cells receive important cues from non-malignant cells within the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are a major component of the TME that impact on the molecular make-up of malignant cells and have a decisive function in tumor progression. However, the potential functionality of fibroblasts within tumor-adjacent, macroscopically normal tissue remains poorly explored.MethodsHere, we isolated primary peritumoral fibroblasts (PtFs) from macroscopically normal tissue in vicinity of primary human papillomavirus-negative and -positive oropharyngeal HNSCC and compared their phenotype and functionality with matched CAFs (n = 5 pairs) and with human oral fibroblasts (hOFs).ResultsExpression patterns of CD90, CD73, CD105, smooth muscle actin, Vimentin, and S100A4 were comparable in PtFs, CAFs, and hOFs. Cell proliferation and doubling times of CAFs and PtFs were heterogeneous across patients (n =2 PtF>CAF; n = 1 CAF>PtF; n = 2 CAF=PtF) and reflected inferior growth than hOFs. Furthermore, PtFs displayed an reduced heterogeneity in cell size compared to matched CAFs, which were characterized by the presence of single large cells. Overall, conditioned supernatants from CAFs had more frequently growth-promoting effects on a panel of carcinoma cell lines of the upper aerodigestive tract carcinoma cell lines (Cal27, Cal33, FaDu, and Kyse30), whereas significant differences in migration-inducing effects demonstrated a higher potential of PtFs. Except for Kyse30, CAFs were significantly superior to hOFs in promoting proliferation, while PtFs induced stronger migration than hOFs in all carcinoma lines tested. Analysis of soluble factors demonstrated significantly increased VEGF-A production in CAFs (except in pat.8), and significantly increased PDGF-BB production in PtFs of two patients. Tube formation assays confirmed a significantly enhanced angiogenic potential of conditioned supernatants from CAFs compared to hOFs on human umbilical vascular endothelial cells (HUVECs) in vitro.DiscussionHence, matched CAFs and PtFs present in HNSCC patients are heterogeneous in their proliferation-, migration-, and angiogenesis-promoting capacity. Despite this heterogeneity, CAFs induced stronger carcinoma cell proliferation and HUVEC tube formation overall, whereas PtFs promoted migration of tumor cells more strongly.

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.

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting., info:eu-repo/semantics/published

Objective: Immunological treatment strategies, including checkpoint inhibition, are currently under investigation for high-grade gliomas, but their success is limited. Hence, it is crucial to determine immunological pathways that can be targeted and to identify subgroups of patients likely to benefit[for full text, please go to the a.m. URL], 70. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Skandinavischen Gesellschaft für Neurochirurgie

Introduction/ Background The measurement of cell proliferation via Ki67 immunohistochemistry is an important part of tumor diagnostics leading to treatment decisions. The assessment according to the current guidelines is very time consuming which likely leads to counting only few cells or making the analysis completely estimated in many cases. Here, automated image analysis promises a standardized, time-saving and reproducible assessment. Aims We prior developed a computerized method that allows for an automated scoring of Ki67. This approach was validated with a study cohort of more than 1000 patients and showed a very high significance in both overall and disease free survival. The aim of this study was to test the capability of this method for the application in the daily routine diagnostics with the concomitant time pressure and huge variability in the patient material and staining results. Methods The developed computer algorithm and software was applied in daily routine breast cancer diagnostics under real conditions over more than one year. More than 100 cases have been analyzed. Results The retrospective analysis showed that the method was capable of accurately processing most of the images. Problems occurred when the counter staining was too weak which made it even difficult to conventionally assess those images. A user interaction was required in some cases to exclude falsely counted non-tumor cells., Diagnostic Pathology, Vol 1 No 8 (2016): 13. European Congress on Digital Pathology

Introduction/ Background Comfortable navigation through diagnostic images is a prospective challenge for the acceptance of virtual microscopy applications in routine pathology [1],[2]. Tracing different regions of interest through multiple sections on one or several slides is a typical task in diagnostic slide examination. This laborious and time-consuming co-localization is currently executed by pathologists. Retaining the relative positions of tissue structures while alternating between multiple slides is still not feasible in a satisfactory manner in conventional nor virtual microscopy. Aims To address this issue we present a more comfortable and intuitive method to read slides using computer-assisted navigation. Furthermore, we demonstrate the strengths of our method by applying it to large series of serial colorectal tissue sections, creating new kinds of visualizations of different adenomatous mucosal architectures in human tissue, while looking for human correlates of lesions recently described in mice [3]. Methods Histological images contain multiple distortions from different sources in the laboratory and digitalization process. An interconnection model was created to describe distortions by several layers, providing a normalized tissue representation. Layers were associated with specific distortions with each layer serving as a new level of abstraction. The first layers enabled a coarse alignment of tissue sections. Further alignment is achieved by piecewise, multi-resolution, SIFT-based [4] correspondence extraction and refinement. Inside the convex hull of all fiducial points local affine transformations were applied whereas a global affine transformation was used on the outside. Animated stacks were generated for regions of interest using local rigid transformations to preserve exact morphological coherences. For subsequent creation of 3D models, the relevant histological objects within these images were annotated by pathologists, partly using computer assisted segmentation based on active contours [5]. These annotations were used subsequently to create simplified 3D models by applying VTK [6]. Results The presented methods provide an efficient means to retrieve correspondences and additional spatial information from serial sections of histological slides. They also show good applicability for specimen from different origin. Alignment methods can be applied to generate block-centric visualizations such as parallel and transparent viewing of multiple stains. Moreover, the generated stack videos and 3D models demonstrate the very good accuracy of section alignment even in large series. The visualizations enable pathologists and researchers to grasp the 3D structural relationships in the tissue at a glance, providing an excellent tool to communicate more complex histomorphological findings. Interestingly, we see two kinds of tubular adenomas, which could imply multiple ways to tubular adenoma formation in FAP-patients, possibly akin to the recent observations in mice [3]., Diagnostic Pathology, Vol 1 No 8 (2016): 13. European Congress on Digital Pathology

Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.