Xavier Moles Lopez

Expression of endoplasmic reticulum stress markers in the islets of patients with type 1 diabetes.

Aims/hypothesisEndoplasmic reticulum (ER) stress may play a role in cytokine-mediated beta cell death in type 1 diabetes, but it remains controversial whether ER stress markers are present in islets from type 1 diabetic individuals. Therefore, we evaluated by immunostaining the expression of markers of the three main branches of the ER stress response in islets from 13 individuals with and 15 controls without type 1 diabetes (eight adults and seven children).MethodsAntibodies against the ER stress markers C/EBP homologous protein (CHOP), immunoglobulin heavy chain (BIP) and X-box binding protein 1 (XBP-1) were validated using HeLa cells treated with the ER stressor thapsigargin. These antibodies were then used to stain serial sections of paraffin-embedded pancreas from type 1 diabetic and non-diabetic individuals; samples were also immunostained for CD45, insulin and glucagon. Immunostaining intensities of the ER stress markers were quantified using a software-based, unbiased quantitative approach.ResultsIslets from individuals with type 1 diabetes showed increased levels of CHOP and, at least for insulitis-positive and beta cell-containing islets, BIP. XBP-1 expression was not, however, increased.Conclusions/interpretationIslet cells from individuals with type 1 diabetes display a partial ER stress response, with evidence of the induction of some, but not all, components of the unfolded protein response.

A simplified approach for the molecular classification of glioblastomas.

Glioblastoma (GBM) is the most common malignant primary brain tumors in adults and exhibit striking aggressiveness. Although GBM constitute a single histological entity, they exhibit considerable variability in biological behavior, resulting in significant differences in terms of prognosis and response to treatment. In an attempt to better understand the biology of GBM, many groups have performed high-scale profiling studies based on gene or protein expression. These studies have revealed the existence of several GBM subtypes. Although there remains to be a clear consensus, two to four major subtypes have been identified. Interestingly, these different subtypes are associated with both differential prognoses and responses to therapy. In the present study, we investigated an alternative immunohistochemistry (IHC)-based approach to achieve a molecular classification for GBM. For this purpose, a cohort of 100 surgical GBM samples was retrospectively evaluated by immunohistochemical analysis of EGFR, PDGFRA and p53. The quantitative analysis of these immunostainings allowed us to identify the following two GBM subtypes: the “Classical-like” (CL) subtype, characterized by EGFR-positive and p53- and PDGFRA-negative staining and the “Proneural-like” (PNL) subtype, characterized by p53- and/or PDGFRA-positive staining. This classification represents an independent prognostic factor in terms of overall survival compared to age, extent of resection and adjuvant treatment, with a significantly longer survival associated with the PNL subtype. Moreover, these two GBM subtypes exhibited different responses to chemotherapy. The addition of temozolomide to conventional radiotherapy significantly improved the survival of patients belonging to the CL subtype, but it did not affect the survival of patients belonging to the PNL subtype. We have thus shown that it is possible to differentiate between different clinically relevant subtypes of GBM by using IHC-based profiling, a method that is advantageous in its ease of daily implementation and in large-scale clinical application.

Central role and mechanisms of β-cell dysfunction and death in friedreich ataxia-associated diabetes.

Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disease caused in almost all cases by homozygosity for a GAA trinucleotide repeat expansion in the frataxin gene. Frataxin is a mitochondrial protein involved in iron homeostasis. FRDA patients have a high prevalence of diabetes, the pathogenesis of which is not known. We aimed to evaluate the relative contribution of insulin resistance and β‐cell failure and the pathogenic mechanisms involved in FRDA diabetes.

Requirements for the valid quantification of immunostains on tissue microarray materials using image analysis

Antibody‐based proteomics applied to tissue microarray (TMA) technology provides a very efficient means of visualizing and locating antigen expression in large collections of normal and pathological tissue samples. To characterize antigen expression on TMAs, the use of image analysis methods avoids the effects of human subjectivity evidenced in manual microscopical analysis. Thus, these methods have the potential to significantly enhance both precision and reproducibility. Although some commercial systems include tools for the quantitative evaluation of immunohistochemistry‐stained images, there exists no clear agreement on best practices to allow for correct and reproducible quantification results. Our study focuses on practical aspects regarding (i) image acquisition (ii) segmentation of staining and counterstaining areas and (iii) extraction of quantitative features. We illustrate our findings using a commercial system to quantify different immunohistochemistry markers targeting proteins with different expression patterns (cytoplasmic, nuclear or membranous) in colon cancer or brain tumor TMAs. Our investigations led us to identify several steps that we consider essential for standardizing computer‐assisted immunostaining quantification experiments. In addition, we propose a data normalization process based on reference materials to be able to compare measurements between studies involving different TMAs. In conclusion, we recommend certain critical prerequisites that commercial or in‐house systems should satisfy in order to permit valid immunostaining quantification.

Clustering methods applied in the detection of Ki67 hot-spots in whole tumor slide images: An efficient way to characterize heterogeneous tissue-based biomarkers

Whole‐slide scanners allow the digitization of an entire histological slide at very high resolution. This new acquisition technique opens a wide range of possibilities for addressing challenging image analysis problems, including the identification of tissue‐based biomarkers. In this study, we use whole‐slide scanner technology for imaging the proliferating activity patterns in tumor slides based on Ki67 immunohistochemistry. Faced with large images, pathologists require tools that can help them identify tumor regions that exhibit high proliferating activity, called “hot‐spots” (HSs). Pathologists need tools that can quantitatively characterize these HS patterns. To respond to this clinical need, the present study investigates various clustering methods with the aim of identifying Ki67 HSs in whole tumor slide images. This task requires a method capable of identifying an unknown number of clusters, which may be highly variable in terms of shape, size, and density. We developed a hybrid clustering method, referred to as Seedlink. Compared to manual HS selections by three pathologists, we show that Seedlink provides an efficient way of detecting Ki67 HSs and improves the agreement among pathologists when identifying HSs.

TIMP-4 and CD63: new prognostic biomarkers in human astrocytomas.

Based on the molecular profiling of astrocytomas, we previously identified a series of genes involved in astrocytoma invasion. Of these, tissue inhibitor of metalloproteinase-4 (TIMP-4) was found to be overexpressed in pilocytic astrocytomas relative to diffuse astrocytomas of any histological grade. Although some data suggest that TIMP-4 may be an anti-tumoral actor in astrocytomas, recent findings challenge this concept. The present study aims to investigate the diagnostic and prognostic values of TIMP-4 and its putative partner CD63 in human astrocytomas. Tissue microarray and image analysis were first carried out to quantitatively analyze the immunohistochemical expression of these proteins in 471 gliomas including 354 astrocytomas. Pathological semi-quantitative scores of both markers’ expression were then established and correlated to astrocytoma diagnosis and patient prognosis. TIMP-4 and CD63 expressions were both overexpressed in astrocytomas compared with oligodendrogliomas (P<0.001) and in pilocytic astrocytomas compared with grade II diffuse astrocytomas (P<0.001). In glioblastomas, high TIMP-4/CD63 co-expression scores were identified as independent prognostic factors associated with progression and shorter survival. In conclusion, this work provides the first evidence of a TIMP-4/CD63 association in astrocytoma tumor cells. It identifies TIMP-4 and CD63 as markers of the astrocytic phenotype in patients with gliomas. In addition, this work highlights the contribution of high TIMP-4/CD63 co-expression to the adverse outcomes of patients with glioblastomas.

A rich internet application for remote visualization and collaborative annotation of digital slides in histology and cytology

Digital slide scanning is advancing the field of pathology and biomedical research, resulting in very large amounts of imaging data. From the computer science point of view, it is challenging to efficiently share, annotate and analyze such data due to their distinct geographical localizations, their high dimensionality, and their numerous sources of variability (scanning equipments, file formats, acquisition protocols, application domains, ...).

An Automated Blur Detection Method for Histological Whole Slide Imaging

Whole slide scanners are novel devices that enable high-resolution imaging of an entire histological slide. Furthermore, the imaging is achieved in only a few minutes, which enables image rendering of large-scale studies involving multiple immunohistochemistry biomarkers. Although whole slide imaging has improved considerably, locally poor focusing causes blurred regions of the image. These artifacts may strongly affect the quality of subsequent analyses, making a slide review process mandatory. This tedious and time-consuming task requires the scanner operator to carefully assess the virtual slide and to manually select new focus points. We propose a statistical learning method that provides early image quality feedback and automatically identifies regions of the image that require additional focus points.

Impact of neoadjuvant therapy on cancer-associated fibroblasts in rectal cancer

BACKGROUND AND PURPOSE Cancer-associated fibroblasts (CAFs) are increasingly recognised as promoters of tumour progression. It is poorly investigated whether cancer management protocols, such as neoadjuvant radio(chemo)therapy, have an impact on CAFs and, by consequence, on tumour progression. This prompted us to study the impact of neoadjuvant radio(chemo)therapy on the α-SMA/epithelial area ratio in rectal cancer, and the impact of this ratio on recurrence-free survival. MATERIAL AND METHODS Immunohistochemistry for the CAF marker α-SMA and the proliferation marker Ki67 was performed on sections from 98 rectal cancers of which 62 had undergone neoadjuvant radio(chemo)therapy. RESULTS Computer-assisted quantitative analysis showed that the α-SMA/neoplastic epithelial area ratio was higher after neoadjuvant therapy, and that rectal cancers with high α-SMA/epithelial area ratio had low proliferation rates. Interestingly, the α-SMA/epithelial area ratio was an adverse prognostic factor with regard to recurrence-free survival in univariate analysis. In addition, multivariate analysis showed that an α-SMA/epithelial area ratio above 1 provides an independent prognostic value associated with a poor recurrence-free survival. CONCLUSION These results suggest that neoadjuvant treatment has an impact on CAFs in rectal cancer. The correlation of CAFs with decreased recurrence-free survival and abundant experimental data in the literature suggest that under certain circumstances, not yet very well understood, CAFs may favour tumour progression.

Registration of whole immunohistochemical slide images: an efficient way to characterize biomarker colocalization

BACKGROUND AND OBJECTIVE Extracting accurate information from complex biological processes involved in diseases, such as cancers, requires the simultaneous targeting of multiple proteins and locating their respective expression in tissue samples. This information can be collected by imaging and registering adjacent sections from the same tissue sample and stained by immunohistochemistry (IHC). Registration accuracy should be on the scale of a few cells to enable protein colocalization to be assessed. METHODS We propose a simple and efficient method based on the open-source elastix framework to register virtual slides of adjacent sections from the same tissue sample. We characterize registration accuracies for different types of tissue and IHC staining. RESULTS Our results indicate that this technique is suitable for the evaluation of the colocalization of biomarkers on the scale of a few cells. We also show that using this technique in conjunction with a sequential IHC labeling and erasing technique offers improved registration accuracies. DISCUSSION Brightfield IHC enables to address the problem of large series of tissue samples, which are usually required in clinical research. However, this approach, which is simple at the tissue processing level, requires challenging image analysis processes, such as accurate registration, to view and extract the protein colocalization information. CONCLUSIONS The method proposed in this work enables accurate registration (on the scale of a few cells) of virtual slides of adjacent tissue sections on which the expression of different proteins is evidenced by standard IHC. Furthermore, combining our method with a sequential labeling and erasing technique enables cell-scale colocalization.