Anne-Laure Trepant

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.

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.

Identification of OLIG2 as the most specific glioblastoma stem cell marker starting from comparative analysis of data from similar DNA chip microarray platforms

Despite advances in surgical and adjuvant treatments, overall survival of glioblastoma (GBM) patients remains poor. The cancer stem cell concept suggests that a rare stem cell population, called glioma stem cells (GSCs), has high ability to self-renewal leading to recurrence in GBM. The identification of specific markers of GSCs would provide a powerful tool to detect and to characterise them in order to develop targeted therapies. We carried out a comparative analysis based on the identification of inter-study concordances to identify the genes that exhibit at best differential levels of expression between GSC-enriched cell cultures and differentiated tumour cell cultures from independent studies using DNA chip microarray technologies. We finally studied the protein expression of the marker we considered the most specific by immunohistochemistry and semi-quantitative analysis on a retrospective series of 18 GBMs. Of the selected studies, 32 genes were retained. Among them, eight genes were identified to be overexpressed in GSC-enriched cultures compared to differentiated tumour cell cultures. Finally, among the eight genes, oligodendrocyte lineage transcription factor 2 (OLIG2) was characterised by the most different expression level in the “GSC model” compared to the “differentiated tumour cells model”. Our approach suggests that OLIG2 is the most specific GSC marker; additional investigations with careful considerations about methodology and strategies of validation are, however, mandatory.

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.

IGF-IR: a new prognostic biomarker for human glioblastoma

Background:Glioblastomas (GBMs) are the most common malignant primary brain tumours in adults and are refractory to conventional therapy, including surgical resection, radiotherapy and chemotherapy. The insulin-like growth factor (IGF) system is a complex network that includes ligands (IGFI and IGFII), receptors (IGF-IR and IGF-IIR) and high-affinity binding proteins (IGFBP-1 to IGFBP-6). Many studies have reported a role for the IGF system in the regulation of tumour cell biology. However, the role of this system remains unclear in GBMs.Methods:We investigate the prognostic value of both the IGF ligands’ and receptors’ expression in a cohort of human GBMs. Tissue microarray and image analysis were conducted to quantitatively analyse the immunohistochemical expression of these proteins in 218 human GBMs.Results:Both IGF-IR and IGF-IIR were overexpressed in GBMs compared with normal brain (P<10−4 and P=0.002, respectively). Moreover, with regard to standard clinical factors, IGF-IR positivity was identified as an independent prognostic factor associated with shorter survival (P=0.016) and was associated with a less favourable response to temozolomide.Conclusions:This study suggests that IGF-IR could be an interesting target for GBM therapy.

Abstract B10: Clinical validation of targeted next-generation sequencing for glioblastoma patients

Objective: Glioblastomas (GBMs) are the most common malignant primary brain tumours in adults. These tumours are resistant to conventional treatment approaches including surgical resection, radiotherapy and chemotherapy. International efforts to catalogue mutations for multiple forms of cancer coupled with the successes of targeted agents in patients with molecularly defined tumors and improvements in genomic technology have generated enthusiasm for incorporating genomic profiling into clinical cancer practice. The development of tyrosine kinase inhibitor treatments has made it important to test cancer patients for clinically significant gene mutations that influence the benefit of treatment. Therefore, the number of biomarkers that will need to be assessed is expected to increase rapidly. Recently, next generation sequencing (NGS) has begun to supplant other technologies for gene panel sequencing. However, few studies have validated the use of targeted NGS for GBM patients. In the present study we evaluate the clinical applicability of targeted NGS for patients with GBM. Methods: DNA from 50 GBM samples (formalin-fixed paraffin-embedded tissue) was retrospectively subjected to targeted NGS with the Ampliseq Cancer Hotspot Panel, using the Ion Torrent Personal Genome Machine, which allowed us to analyze 2850 known cancer-related mutations in 50 genes. In addition, MGMT methylation status, EGFR amplification and 1p19q deletion were evaluated by Methylation Specific PCR (MSP), chromogenic in situ hybridisation (ISH) and fluorescence ISH, respectively. Results: Preliminary results on 28 patients, all successfully sequenced, showed that the most frequent mutations were found in TP53 (25%) and EGFR (18%). Potentially actionable mutations were identified in 9 patients (32%), including 5 EGFR mutations, 2 PIK3CA mutations, 1 PTEN mutation, 1 PDGFRA mutation and 1 IDH1 mutation. The frequencies of these variants detected by NGS were consistent with frequencies reported in public databases. Moreover, PDGFRA and EGFR amplifications were detected by coverage analysis for 10 (36%) and 2 (7%) patients respectively. Conclusions: Overall, the AmpliSeq Cancer Hotspot Panel can be applied in daily practice for GBM samples. Moreover, it can provide clinically relevant information for GBM patients. Citation Format: Anne-Laure Trepant, Marie Le Mercier, Calliope Maris, Nancy De Neve, Oriane Blanchard, Nicky D9Haene, Isabelle Salmon. Clinical validation of targeted next-generation sequencing for glioblastoma patients. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr B10.