Frederick Klauschen

The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014

BACKGROUND The morphological evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is gaining momentum as evidence strengthens for the clinical relevance of this immunological biomarker. Accumulating evidence suggests that the extent of lymphocytic infiltration in tumor tissue can be assessed as a major parameter by evaluation of hematoxylin and eosin (H&E)-stained tumor sections. TILs have been shown to provide prognostic and potentially predictive value, particularly in triple-negative and human epidermal growth factor receptor 2-overexpressing BC. DESIGN A standardized methodology for evaluating TILs is now needed as a prerequisite for integrating this parameter in standard histopathological practice, in a research setting as well as in clinical trials. This article reviews current data on the clinical validity and utility of TILs in BC in an effort to foster better knowledge and insight in this rapidly evolving field, and to develop a standardized methodology for visual assessment on H&E sections, acknowledging the future potential of molecular/multiplexed approaches. CONCLUSIONS The methodology provided is sufficiently detailed to offer a uniformly applied, pragmatic starting point and improve consistency and reproducibility in the measurement of TILs for future studies.

SAP-controlled T-B cell interactions underlie germinal centre formation

Generation of long-term antibody-mediated immunity depends on the germinal centre reaction, which requires cooperation between antigen-specific T and B lymphocytes. In human X-linked lymphoproliferative disease and its gene-targeted mouse model, loss-of-function mutations in signalling lymphocyte activation molecule-associated protein (SAP, encoded by SH2D1a) cause a profound defect in germinal centre formation by an as yet unknown mechanism. Here, using two-photon intravital imaging, we show that SAP deficiency selectively impairs the ability of CD4+ T cells to stably interact with cognate B cells but not antigen-presenting dendritic cells. This selective defect results in a failure of antigen-specific B cells to receive adequate levels of contact-dependent T-cell help to expand normally, despite Sap-/- T cells exhibiting the known characteristics of otherwise competent helper T cells. Furthermore, the lack of stable interactions with B cells renders Sap-/- T cells unable to be efficiently recruited to and retained in a nascent germinal centre to sustain the germinal centre reaction. These results offer an explanation for the germinal centre defect due to SAP deficiency and provide new insights into the bi-directional communication between cognate T and B cells in vivo.

Sphingosine-1-phosphate mobilizes osteoclast precursors and regulates bone homeostasis

Osteoclasts are the only somatic cells with bone-resorbing capacity and, as such, they have a critical role not only in normal bone homeostasis (called ‘bone remodelling’) but also in the pathogenesis of bone destructive disorders such as rheumatoid arthritis and osteoporosis. A major focus of research in the field has been on gene regulation by osteoclastogenic cytokines such as receptor activator of NF-κB-ligand (RANKL, also known as TNFSF11) and TNF-α, both of which have been well documented to contribute to osteoclast terminal differentiation. A crucial process that has been less well studied is the trafficking of osteoclast precursors to and from the bone surface, where they undergo cell fusion to form the fully differentiated multinucleated cells that mediate bone resorption. Here we report that sphingosine-1-phosphate (S1P), a lipid mediator enriched in blood, induces chemotaxis and regulates the migration of osteoclast precursors not only in culture but also in vivo, contributing to the dynamic control of bone mineral homeostasis. Cells with the properties of osteoclast precursors express functional S1P1 receptors and exhibit positive chemotaxis along an S1P gradient in vitro. Intravital two-photon imaging of bone tissues showed that a potent S1P1 agonist, SEW2871, stimulated motility of osteoclast precursor-containing monocytoid populations in vivo. Osteoclast/monocyte (CD11b, also known as ITGAM) lineage-specific conditional S1P1 knockout mice showed osteoporotic changes due to increased osteoclast attachment to the bone surface. Furthermore, treatment with the S1P1 agonist FTY720 relieved ovariectomy-induced osteoporosis in mice by reducing the number of mature osteoclasts attached to the bone surface. Together, these data provide evidence that S1P controls the migratory behaviour of osteoclast precursors, dynamically regulating bone mineral homeostasis, and identifies a critical control point in osteoclastogenesis that may have potential as a therapeutic target.

Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization

Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.

Tumor-Infiltrating Lymphocytes and Response to Neoadjuvant Chemotherapy With or Without Carboplatin in Human Epidermal Growth Factor Receptor 2–Positive and Triple-Negative Primary Breast Cancers

PURPOSE Modulation of immunologic interactions in cancer tissue is a promising therapeutic strategy. To investigate the immunogenicity of human epidermal growth factor receptor 2 (HER2) -positive and triple-negative (TN) breast cancers (BCs), we evaluated tumor-infiltrating lymphocytes (TILs) and immunologically relevant genes in the neoadjuvant GeparSixto trial. PATIENTS AND METHODS GeparSixto investigated the effect of adding carboplatin (Cb) to an anthracycline-plus-taxane combination (PM) on pathologic complete response (pCR). A total of 580 tumors were evaluated before random assignment for stromal TILs and lymphocyte-predominant BC (LPBC). mRNA expression of immune-activating (CXCL9, CCL5, CD8A, CD80, CXCL13, IGKC, CD21) as well as immunosuppressive factors (IDO1, PD-1, PD-L1, CTLA4, FOXP3) was measured in 481 tumors. RESULTS Increased levels of stromal TILs predicted pCR in univariable (P < .001) and multivariable analyses (P < .001). pCR rate was 59.9% in LPBC and 33.8% for non-LPBC (P < .001). pCR rates ≥ 75% were observed in patients with LPBC tumors treated with PMCb, with a significant test for interaction with therapy in the complete (P = .002) and HER2-positive (P = .006), but not the TNBC, cohorts. Hierarchic clustering of mRNA markers revealed three immune subtypes with different pCR rates (P < .001). All 12 immune mRNA markers were predictive for increased pCR. The highest odds ratios (ORs) were observed for PD-L1 (OR, 1.57; 95% CI, 1.34 to 1.86; P < .001) and CCL5 (OR, 1.41; 95% CI, 1.23 to 1.62; P < .001). CONCLUSION Immunologic factors were highly significant predictors of therapy response in the GeparSixto trial, particularly in patients treated with Cb. After further standardization, they could be included in histopathologic assessment of BC.

Evaluation of automated brain MR image segmentation and volumetry methods.

We compare three widely used brain volumetry methods available in the software packages FSL, SPM5, and FreeSurfer and evaluate their performance using simulated and real MR brain data sets. We analyze the accuracy of gray and white matter volume measurements and their robustness against changes of image quality using the BrainWeb MRI database. These images are based on “gold‐standard” reference brain templates. This allows us to assess between‐ (same data set, different method) and also within‐segmenter (same method, variation of image quality) comparability, for both of which we find pronounced variations in segmentation results for gray and white matter volumes. The calculated volumes deviate up to >10% from the reference values for gray and white matter depending on method and image quality. Sensitivity is best for SPM5, volumetric accuracy for gray and white matter was similar in SPM5 and FSL and better than in FreeSurfer. FSL showed the highest stability for white (<5%), FreeSurfer (6.2%) for gray matter for constant image quality BrainWeb data. Between‐segmenter comparisons show discrepancies of up to >20% for the simulated data and 24% on average for the real data sets, whereas within‐method performance analysis uncovered volume differences of up to >15%. Since the discrepancies between results reach the same order of magnitude as volume changes observed in disease, these effects limit the usability of the segmentation methods for following volume changes in individual patients over time and should be taken into account during the planning and analysis of brain volume studies. Hum Brain Mapp, 2009.

A Systems Analysis Identifies a Feedforward Inflammatory Circuit Leading to Lethal Influenza Infection

For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium versus dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis, together with these gene expression and flow data, identified a chemokine-driven feedforward circuit involving proinflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation, but not ablation, of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology.

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

Understanding and interpreting classification decisions of automated image classification systems is of high value in many applications, as it allows to verify the reasoning of the system and provides additional information to the human expert. Although machine learning methods are solving very successfully a plethora of tasks, they have in most cases the disadvantage of acting as a black box, not providing any information about what made them arrive at a particular decision. This work proposes a general solution to the problem of understanding classification decisions by pixel-wise decomposition of nonlinear classifiers. We introduce a methodology that allows to visualize the contributions of single pixels to predictions for kernel-based classifiers over Bag of Words features and for multilayered neural networks. These pixel contributions can be visualized as heatmaps and are provided to a human expert who can intuitively not only verify the validity of the classification decision, but also focus further analysis on regions of potential interest. We evaluate our method for classifiers trained on PASCAL VOC 2009 images, synthetic image data containing geometric shapes, the MNIST handwritten digits data set and for the pre-trained ImageNet model available as part of the Caffe open source package.

Detection and Segmentation of Cell Nuclei in Virtual Microscopy Images: A Minimum-Model Approach

Automated image analysis of cells and tissues has been an active research field in medical informatics for decades but has recently attracted increased attention due to developments in computer and microscopy hardware and the awareness that scientific and diagnostic pathology require novel approaches to perform objective quantitative analyses of cellular and tissue specimens. Model-based approaches use a priori information on cell shape features to obtain the segmentation, which may introduce a bias favouring the detection of cell nuclei only with certain properties. In this study we present a novel contour-based “minimum-model” cell detection and segmentation approach that uses minimal a priori information and detects contours independent of their shape. This approach avoids a segmentation bias with respect to shape features and allows for an accurate segmentation (precision = 0.908; recall = 0.859; validation based on ∼8000 manually-labeled cells) of a broad spectrum of normal and disease-related morphological features without the requirement of prior training.

Robust Anti-viral Immunity Requires Multiple Distinct T Cell-Dendritic Cell Interactions

Host defense against viruses and intracellular parasites depends on effector CD8(+) T cells, whose optimal clonal expansion, differentiation, and memory properties require signals from CD4(+) T cells. Here, we addressed the role of dendritic cell (DC) subsets in initial activation of the two T cell types and their co-operation. Surprisingly, initial priming of CD4(+) and CD8(+) T cells was spatially segregated within the lymph node and occurred on different DCs with temporally distinct patterns of antigen presentation via MHCI versus MHCII molecules. DCs that co-present antigen via both MHC molecules were detected at a later stage; these XCR1(+) DCs are the critical platform involved in CD4(+) T cell augmentation of CD8(+) T cell responses. These findings delineate the complex choreography of cellular interactions underlying effective cell-mediated anti-viral responses, with implications for basic DC subset biology, as well as for translational application to the development of vaccines that evoke optimal T cell immunity.