Next-generation tissue microarray (ngTMA) increases the quality of biomarker studies: an example using CD3, CD8, and CD45RO in the tumor microenvironment of six different solid tumor types

Background Tissue microarray (TMA) technology revolutionized the investigation of potential biomarkers from paraffin-embedded tissues. However, conventional TMA construction is laborious, time-consuming and imprecise. Next-generation tissue microarrays (ngTMA) combine histological expertise with digital pathology and automated tissue microarraying. The aim of this study was to test the feasibility of ngTMA for the investigation of biomarkers within the tumor microenvironment (tumor center and invasion front) of six tumor types, using CD3, CD8 and CD45RO as an example. Methods Ten cases each of malignant melanoma, lung, breast, gastric, prostate and colorectal cancers were reviewed. The most representative H&E slide was scanned and uploaded onto a digital slide management platform. Slides were viewed and seven TMA annotations of 1 mm in diameter were placed directly onto the digital slide. Different colors were used to identify the exact regions in normal tissue (n = 1), tumor center (n = 2), tumor front (n = 2), and tumor microenvironment at invasion front (n = 2) for subsequent punching. Donor blocks were loaded into an automated tissue microarrayer. Images of the donor block were superimposed with annotated digital slides. Exact annotated regions were punched out of each donor block and transferred into a TMA block. 420 tissue cores created two ngTMA blocks. H&E staining and immunohistochemistry for CD3, CD8 and CD45RO were performed. Results All 60 slides were scanned automatically (total time < 10 hours), uploaded and viewed. Annotation time was 1 hour. The 60 donor blocks were loaded into the tissue microarrayer, simultaneously. Alignment of donor block images and digital slides was possible in less than 2 minutes/case. Automated punching of tissue cores and transfer took 12 seconds/core. Total ngTMA construction time was 1.4 hours. Stains for H&E and CD3, CD8 and CD45RO highlighted the precision with which ngTMA could capture regions of tumor-stroma interaction of each cancer and the T-lymphocytic immune reaction within the tumor microenvironment. Conclusion Based on a manual selection criteria, ngTMA is able to precisely capture histological zones or cell types of interest in a precise and accurate way, aiding the pathological study of the tumor microenvironment. This approach would be advantageous for visualizing proteins, DNA, mRNA and microRNAs in specific cell types using in situ hybridization techniques.

The equine DNAH3 gene: SNP discovery and exclusion of an involvement in recurrent airway obstruction (RAO) in European Warmblood horses

Recurrent airway obstruction is one of the most common airway diseases affecting mature horses. Increased bronchoalveolar mucus, neutrophil accumulation in airways, and airway obstruction are the main features of this disease. Mucociliary clearance is a key component of pulmonary defense mechanisms. Cilia are the motile part of this system and a complex linear array of dynein motors is responsible for their motility by moving along the microtubules in the axonemes of cilia and flagella. We previously detected a QTL for RAO on ECA 13 in a half-sib family of European Warmblood horses. The gene encoding DNAH3 is located in the peak of the detected QTL and encodes a dynein subunit. Therefore, we analysed this gene as a positional and functional candidate gene for RAO. In a mutation analysis of all 62 exons we detected 53 new polymorphisms including 7 non-synonymous variants. We performed an association study using 38 polymorphisms in a cohort of 422 animals. However, after correction for multiple testing we did not detect a significant association of any of these polymorphisms with RAO (P>0.05). Therefore, it seems unlikely that variants at the DNAH3 gene are responsible for the RAO QTL in European Warmblood horses.

Identification of 2-Piperidone as a Biomarker of CYP2E1 Activity Through Metabolomic Phenotyping

Cytochrome P450 2E1 (CYP2E1) is a key enzyme in the metabolic activation of many low molecular weight toxicants and also an important contributor to oxidative stress. A noninvasive method to monitor CYP2E1 activity in vivo would be of great value for studying the role of CYP2E1 in chemical-induced toxicities and stress-related diseases. In this study, a mass spectrometry-based metabolomic approach was used to identify a metabolite biomarker of CYP2E1 through comparing the urine metabolomes of wild-type (WT), Cyp2e1-null, and CYP2E1-humanized mice. Metabolomic analysis with multivariate models of urine metabolites revealed a clear separation of Cyp2e1-null mice from WT and CYP2E1-humanized mice in the multivariate models of urine metabolomes. Subsequently, 2-piperidone was identified as a urinary metabolite that inversely correlated to the CYP2E1 activity in the three mouse lines. Backcrossing of WT and Cyp2e1-null mice, together with targeted analysis of 2-piperidone in mouse serum, confirmed the genotype dependency of 2-piperidone. The accumulation of 2-piperidone in the Cyp2e1-null mice was mainly caused by the changes in the biosynthesis and degradation of 2-piperidone because compared with the WT mice, the conversion of cadaverine to 2-piperidone was higher, whereas the metabolism of 2-piperidone to 6-hydroxy-2-piperidone was lower in the Cyp2e1-null mice. Overall, untargeted metabolomic analysis identified a correlation between 2-piperidone concentrations in urine and the expression and activity of CYP2E1, thus providing a noninvasive metabolite biomarker that can be potentially used in to monitor CYP2E1 activity.

A next-generation tissue microarray (ngTMA) protocol for biomarker studies

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a 'donor' block into a 'recipient' block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 'recipient' blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research.

Leukemic stem cell frequency: a strong biomarker for clinical outcome in acute myeloid leukemia.

INTRODUCTION Treatment failure in acute myeloid leukemia is probably caused by the presence of leukemia initiating cells, also referred to as leukemic stem cells, at diagnosis and their persistence after therapy. Specific identification of leukemia stem cells and their discrimination from normal hematopoietic stem cells would greatly contribute to risk stratification and could predict possible relapses. RESULTS For identification of leukemic stem cells, we developed flow cytometric methods using leukemic stem cell associated markers and newly-defined (light scatter) aberrancies. The nature of the putative leukemic stem cells and normal hematopoietic stem cells, present in the same patient's bone marrow, was demonstrated in eight patients by the presence or absence of molecular aberrancies and/or leukemic engraftment in NOD-SCID IL-2Rγ-/- mice. At diagnosis (n=88), the frequency of the thus defined neoplastic part of CD34+CD38- putative stem cell compartment had a strong prognostic impact, while the neoplastic parts of the CD34+CD38+ and CD34- putative stem cell compartments had no prognostic impact at all. After different courses of therapy, higher percentages of neoplastic CD34+CD38- cells in complete remission strongly correlated with shorter patient survival (n=91). Moreover, combining neoplastic CD34+CD38- frequencies with frequencies of minimal residual disease cells (n=91), which reflect the total neoplastic burden, revealed four patient groups with different survival. CONCLUSION AND PERSPECTIVE Discrimination between putative leukemia stem cells and normal hematopoietic stem cells in this large-scale study allowed to demonstrate the clinical importance of putative CD34+CD38- leukemia stem cells in AML. Moreover, it offers new opportunities for the development of therapies directed against leukemia stem cells, that would spare normal hematopoietic stem cells, and, moreover, enables in vivo and ex vivo screening for potential efficacy and toxicity of new therapies.

Comprehensive validation of published immunohistochemical prognostic biomarkers of prostate cancer-what has gone wrong? A blueprint for the way forward in biomarker studies

BACKGROUND Treatment planning of localised prostate cancer remains challenging. Besides conventional parameters, a wealth of prognostic biomarkers has been proposed so far. None of which, however, have successfully been implemented in a routine setting so far. The aim of our study was to systematically verify a set of published prognostic markers for prostate cancer. METHODS Following an in-depth PubMed search, 28 markers were selected that have been proposed as multivariate prognostic markers for primary prostate cancer. Their prognostic validity was examined in a radical prostatectomy cohort of 238 patients with a median follow-up of 60 months and biochemical progression as endpoint of the analysis. Immunohistochemical evaluation was performed using previously published cut-off values, but allowing for optimisation if necessary. Univariate and multivariate Cox regression were used to determine the prognostic value of biomarkers included in this study. RESULTS Despite the application of various cut-offs in the analysis, only four (14%) markers were verified as independently prognostic (AKT1, stromal AR, EZH2, and PSMA) for PSA relapse following radical prostatectomy. CONCLUSIONS Apparently, many immunohistochemistry-based studies on prognostic markers seem to be over-optimistic. Codes of best practice, such as the REMARK guidelines, may facilitate the performance of conclusive and transparent future studies.