Alexander Burges

M2 Macrophages Infiltrating Epithelial Ovarian Cancer Express MDR1: A Feature That May Account for the Poor Prognosis

Multi drug resistance protein 1 (MDR1) expression on tumor cells has been widely investigated in context of drug resistance. However, the role of MDR1 on the immune cell infiltrate of solid tumors remains unknown. The aim of this study was to analyze the prognostic significance of a MDR1+ immune cell infiltrate in epithelial ovarian cancer (EOC) and to identify the MDR1+ leucocyte subpopulation. MDR1 expression was analyzed by immunohistochemistry in 156 EOC samples. In addition to MDR1+ cancer cells, we detected a MDR1+ leucocyte infiltrate (high infiltrate >4 leucocytes per field of view). Correlations and survival analyses were calculated. To identify immune cell subpopulations immunofluorescence double staining was performed. The MDR1+ leucocyte infiltrate was associated with human epidermal growth factor receptor 2 (HER2) (cc = 0.258, p = 0.005) and tumor-associated mucin 1 (TA-MUC1) (cc = 0.202, p = 0.022) expression on cancer cells. A high MDR1+ leucocyte infiltrate was associated with impaired survival, especially in patients whose carcinoma showed either serous histology (median OS 28.80 vs. 50.64 months, p = 0.027, n = 91) or TA-MUC1 expression (median OS 30.60 vs. 63.36 months, p = 0.015, n = 110). Similar findings for PFS suggest an influence of MDR1+ immune cells on the development of chemoresistance. A Cox regression analysis confirmed the independency of a high MDR1+ leucocyte infiltrate as prognostic factor. M2 macrophages were identified as main part of the MDR1+ leucocyte infiltrate expressing MDR1 as well as the M2 marker CD163 and the pan-macrophage marker CD68. Infiltration of MDR1+ leucocytes, mostly M2 macrophages, is associated with poor prognosis of EOC patients. Further understanding of the interaction of M2 macrophages, MDR1 and TA-MUC1 appears to be a key aspect to overcome chemoresistance in ovarian cancer.

Dilution of Molecular–Pathologic Gene Signatures by Medically Associated Factors Might Prevent Prediction of Resection Status After Debulking Surgery in Patients With Advanced Ovarian Cancer

Abstract Purpose: Predicting surgical outcome could improve individualizing treatment strategies for patients with advanced ovarian cancer. It has been suggested earlier that gene expression signatures (GES) might harbor the potential to predict surgical outcome. Experimental Design: Data derived from high-grade serous tumor tissue of FIGO stage IIIC/IV patients of AGO-OVAR11 trial were used to generate a transcriptome profiling. Previously identified molecular signatures were tested. A theoretical model was implemented to evaluate the impact of medically associated factors for residual disease (RD) on the performance of GES that predicts RD status. Results: A total of 266 patients met inclusion criteria, of those, 39.1% underwent complete resection. Previously reported GES did not predict RD in this cohort. Similarly, The Cancer Genome Atlas molecular subtypes, an independent de novo signature and the total gene expression dataset using all 21,000 genes were not able to predict RD status. Medical reasons for RD were identified as potential limiting factors that impact the ability to use GES to predict RD. In a center with high complete resection rates, a GES which would perfectly predict tumor biological RD would have a performance of only AUC 0.83, due to reasons other than tumor biology. Conclusions: Previously identified GES cannot be generalized. Medically associated factors for RD may be the main obstacle to predict surgical outcome in an all-comer population of patients with advanced ovarian cancer. If biomarkers derived from tumor tissue are used to predict outcome of patients with cancer, selection bias should be focused on to prevent overestimation of the power of such a biomarker. See related commentary by Handley and Sood, p. 9

Ovarian Cancer–Specific BRCA -like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial

Abstract Purpose: Previously, we developed breast cancer BRCA1-like and BRCA2-like copy-number profile shrunken centroid classifiers predictive for mutation status and response to therapy, targeting homologous recombination deficiency (HRD). Therefore, we investigated BRCA1- and BRCA2-like classification in ovarian cancer, aiming to acquire classifiers with similar properties as those in breast cancer. Experimental Design: We analyzed DNA copy-number profiles of germline BRCA1- and BRCA2-mutant ovarian cancers and control tumors and observed that existing breast cancer classifiers did not sufficiently predict mutation status. Hence, we trained new shrunken centroid classifiers on this set and validated them in the independent The Cancer Genome Atlas dataset. Subsequently, we assessed BRCA1/2-like classification and obtained germline and tumor mutation and methylation status of cancer predisposition genes, among them several involved in HR repair, of 300 ovarian cancer samples derived from the consecutive cohort trial AGO-TR1 (NCT02222883). Results: The detection rate of the BRCA1-like classifier for BRCA1 mutations and promoter hypermethylation was 95.6%. The BRCA2-like classifier performed less accurately, likely due to a smaller training set. Furthermore, three quarters of the BRCA1/2-like tumors could be explained by (epi)genetic alterations in BRCA1/2, germline RAD51C mutations and alterations in other genes involved in HR. Around half of the non–BRCA-mutated ovarian cancer cases displayed a BRCA-like phenotype. Conclusions: The newly trained classifiers detected most BRCA-mutated and methylated cancers and all tumors harboring a RAD51C germline mutations. Beyond that, we found an additional substantial proportion of ovarian cancers to be BRCA-like.

Sirtuin 1 and Sirtuin 3 in Granulosa Cell Tumors

Sirtuins (SIRTs) are NAD+-dependent deacetylases that regulate proliferation and cell death. In the human ovary, granulosa cells express sirtuin 1 (SIRT1), which has also been detected in human tumors derived from granulosa cells, i.e., granulosa cell tumors (GCTs), and in KGN cells. KGN cells are an established cellular model for the majority of GCTs and were used to explore the role of SIRT1. The SIRT1 activator SRT2104 increased cell proliferation. By contrast, the inhibitor EX527 reduced cell numbers, without inducing apoptosis. These results were supported by the outcome of siRNA-mediated silencing studies. A tissue microarray containing 92 GCTs revealed nuclear and/or cytoplasmic SIRT1 staining in the majority of the samples, and also, SIRT2-7 were detected in most samples. The expression of SIRT1–7 was not correlated with the survival of the patients; however, SIRT3 and SIRT7 expression was significantly correlated with the proliferation marker Ki-67, implying roles in tumor cell proliferation. SIRT3 was identified by a proteomic analysis as the most abundant SIRT in KGN. The results of the siRNA-silencing experiments indicate involvement of SIRT3 in proliferation. Thus, several SIRTs are expressed by GCTs, and SIRT1 and SIRT3 are involved in the growth regulation of KGN. If transferable to GCTs, these SIRTs may represent novel drug targets.

Bevacizumab May Differentially Improve Prognosis of Advanced Ovarian Cancer Patients with Low Expression of VEGF-A165b, an Antiangiogenic VEGF-A Splice Variant

Abstract Purpose: The identification of a robust IHC marker to predict the response to antiangiogenic bevacizumab in ovarian cancer is of high clinical interest. VEGF-A, the molecular target of bevacizumab, is expressed as multiple isoforms with pro- or antiangiogenic properties, of which VEGF-A165b is the most dominant antiangiogenic isoform. The balance of VEGF-A isoforms is closely related to the angiogenic capacity of a tumor and may define its vulnerability to antiangiogenic therapy. We investigated whether the expression of VEGF-A165b could be related to the effect of bevacizumab in advanced ovarian cancer patients. Experimental Design: Formalin-fixed paraffin-embedded tissues from 413 patients of the ICON7 multicenter phase III trial, treated with standard platinum-based chemotherapy with or without bevacizumab, were probed for VEGF-A165b expression by IHC. Results: In patients with low VEGF-A165b expression, the addition of bevacizumab to standard platinum-based chemotherapy significantly improved progression-free (HR: 0.727; 95% CI, 0.538–0.984; P = 0.039) and overall survival (HR: 0.662; 95% CI, 0.458–0.958; P = 0.029). Multivariate analysis showed that the addition of bevacizumab in low VEGF-A165b–expressing patients conferred significant improvements in progression-free survival (HR: 0.610; 95% CI, 0.446–0.834; P = 0.002) and overall survival (HR: 0.527; 95% CI, 0.359–0.775; P = 0.001), independently from established risk factors. Conclusions: We demonstrate for the first time that bevacizumab may differentially improve the prognosis of advanced ovarian cancer patients with low expression of VEGF-A165b, an antiangiogenic VEGF-A splice variant. We envision that this novel biomarker could be implemented into routine diagnostics and may have direct clinical implications for guiding bevacizumab-related treatment decisions in advanced ovarian cancer patients.

Prevalence of BRCA in Patients With Ovarian Cancer

The aim of this prospective registration and translational research study is to evaluate the praevalence of BRCA regarding germline and somatic mutations.