AID/APOBEC-network reconstruction identifies pathways associated with survival in ovarian cancer

Background Building up of pathway-/disease-relevant signatures provides a persuasive tool for understanding the functional relevance of gene alterations and gene network associations in multifactorial human diseases. Ovarian cancer is a highly complex heterogeneous malignancy in respect of tumor anatomy, tumor microenvironment including pro-/antitumor immunity and inflammation; still, it is generally treated as single disease. Thus, further approaches to investigate novel aspects of ovarian cancer pathogenesis aiming to provide a personalized strategy to clinical decision making are of high priority. Herein we assessed the contribution of the AID/APOBEC family and their associated genes given the remarkable ability of AID and APOBECs to edit DNA/RNA, and as such, providing tools for genetic and epigenetic alterations potentially leading to reprogramming of tumor cells, stroma and immune cells. Results We structured the study by three consecutive analytical modules, which include the multigene-based expression profiling in a cohort of patients with primary serous ovarian cancer using a self-created AID/APOBEC-associated gene signature, building up of multivariable survival models with high predictive accuracy and nomination of top-ranked candidate/target genes according to their prognostic impact, and systems biology-based reconstruction of the AID /APOBEC-driven disease-relevant mechanisms using transcriptomics data from ovarian cancer samples. We demonstrated that inclusion of the AID/APOBEC signature-based variables significantly improves the clinicopathological variables-based survival prognostication allowing significant patient stratification. Furthermore, several of the profiling-derived variables such as ID3, PTPRC/CD45, AID, APOBEC3G, and ID2 exceed the prognostic impact of some clinicopathological variables. We next extended the signature-/modeling- based knowledge by extracting top genes co-regulated with target molecules in ovarian cancer tissues and dissected potential networks/pathways/regulators contributing to pathomechanisms. We thereby revealed that the AID/APOBEC- related network in ovarian cancer is particularly associated with remodeling/fibrotic pathways, altered immune response, and autoimmune disorders with inflammatory background. Conclusions The herein study is, to our knowledge, the first one linking expression of entire AID/APOBECs and interacting genes with clinical outcome with respect to survival of cancer patients. Overall, data propose a novel AID/APOBEC-derived survival model for patient risk assessment and reconstitute mapping to molecular pathways. The established study algorithm can be applied further for any biologically relevant signature and any type of diseased tissue

Tumor Growth Rate Estimates Are Independently Predictive of Therapy Response and Survival in Recurrent High-Grade Serous Ovarian Cancer Patients

This study aimed to assess the predictive value of tumor growth rate estimates based on serial cancer antigen-125 (CA-125) levels on therapy response and survival of patients with recurrent high-grade serous ovarian cancer (HGSOC). In total, 301 consecutive patients with advanced HGSOC (exploratory cohort: n = 155, treated at the Medical University of Vienna; external validation cohort: n = 146, from the Ovarian Cancer Therapy–Innovative Models Prolong Survival (OCTIPS) consortium) were enrolled. Tumor growth estimates were obtained using a validated two-phase equation model involving serial CA-125 levels, and their predictive value with respect to treatment response to the next chemotherapy and the prognostic value with respect to disease-specific survival and overall survival were assessed. Tumor growth estimates were an independent predictor for response to second-line chemotherapy and an independent prognostic factor for second-line chemotherapy use in both univariate and multivariable analyses, outperforming both the predictive (second line: p = 0.003, HR 5.19 [1.73–15.58] vs. p = 0.453, HR 1.95 [0.34–11.17]) and prognostic values (second line: p = 0.042, HR 1.53 [1.02–2.31] vs. p = 0.331, HR 1.39 [0.71–2.27]) of a therapy-free interval (TFI) < 6 months. Tumor growth estimates were a predictive factor for response to third- and fourth-line chemotherapy and a prognostic factor for third- and fourth-line chemotherapy use in the univariate analysis. The CA-125-derived tumor growth rate estimate may be a quantifiable and easily assessable surrogate to TFI in treatment decision making for patients with recurrent HGSOC

Exploring the clonal evolution of CD133/aldehyde-dehydrogenase-1 (ALDH1)-positive cancer stem-like cells from primary to recurrent high-grade serous ovarian cancer (HGSOC). A study of the Ovarian Cancer Therapy–Innovative Models Prolong Survival (OCTIPS) Consortium

Background High-grade serous ovarian cancer (HGSOC) causes 80% of all ovarian cancer (OC) deaths. In this setting, the role of cancer stem-like cells (CSCs) is still unclear. In particular, the evolution of CSC biomarkers from primary (pOC) to recurrent (rOC) HGSOCs is unknown. Aim of this study was to investigate changes in CD133 and aldehyde dehydrogenase-1 (ALDH1) CSC biomarker expression in pOC and rOC HGSOCs. Methods Two-hundred and twenty-four pOC and rOC intrapatient paired tissue samples derived from 112 HGSOC patients were evaluated for CD133 and ALDH1 expression using immunohistochemistry (IHC); pOCs and rOCs were compared for CD133 and/or ALDH1 levels. Expression profiles were also correlated with patients' clinicopathological and survival data. Results Some 49.1% of the patient population (55/112) and 37.5% (42/112) pOCs were CD133+ and ALDH1+ respectively. CD133+ and ALDH1+ samples were detected in 33.9% (38/112) and 36.6% (41/112) rOCs. CD133/ALDH1 coexpression was observed in 23.2% (26/112) and 15.2% (17/112) of pOCs and rOCs respectively. Pairwise analysis showed a significant shift of CD133 staining from higher (pOCs) to lower expression levels (rOCs) (p < 0.0001). Furthermore, all CD133 + pOC patients were International Federation of Gynaecology and Obstetrics (FIGO)-stage III/IV (p < 0.0001) and had significantly worse progression-free interval (PFI) (p = 0.04) and overall survival (OS) (p = 0.02). On multivariate analysis, CD133/ALDH1 coexpression in pOCs was identified as independent prognostic factor for PFI (HR: 1.64; 95% CI: 1.03–2.60; p = 0.036) and OS (HR: 1.71; 95% CI: 1.01–2.88; p = 0.045). Analysis on 52 pts patients with known somatic BRCA status revealed that BRCA mutations did not influence CSC biomarker expression. Conclusions The study showed that CD133/ALDH1 expression impacts HGSOC patients' survival and first suggests that CSCs might undergo phenotypic change during the disease course similarly to non stem-like cancer cells, providing also a first evidence that there is no correlation between CSCs and BRCA status

Impact of BRCA Mutation Status on Tumor Dissemination Pattern, Surgical Outcome and Patient Survival in Primary and Recurrent High-Grade Serous Ovarian Cancer:A Multicenter Retrospective Study by the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) Consortium

Background: This study seeks to evaluate the impact of breast cancer (BRCA) gene status on tumor dissemination pattern, surgical outcome and survival in a multicenter cohort of paired primary ovarian cancer (pOC) and recurrent ovarian cancer (rOC). Patients and Methods: Medical records and follow-up data from 190 patients were gathered retrospectively. All patients had surgery at pOC and at least one further rOC surgery at four European high-volume centers. Patients were divided into one cohort with confirmed mutation for BRCA1 and/or BRCA2 (BRCAmut) and a second cohort with BRCA wild type or unknown (BRCAwt). Patterns of tumor presentation, surgical outcome and survival data were analyzed between the two groups. Results: Patients with BRCAmut disease were on average 4 years younger and had significantly more tumor involvement upon diagnosis. Patients with BRCAmut disease showed higher debulking rates at all stages. Multivariate analysis showed that only patient age had significant predictive value for complete tumor resection in pOC. At rOC, however, only BRCAmut status significantly correlated with optimal debulking. Patients with BRCAmut disease showed significantly prolonged overall survival (OS) by 24.3 months. Progression-free survival (PFS) was prolonged in the BRCAmut group at all stages as well, reaching statistical significance during recurrence. Conclusions: Patients with BRCAmut disease showed a more aggressive course of disease with earlier onset and more extensive tumor dissemination at pOC. However, surgical outcome and OS were significantly better in patients with BRCAmut disease compared with patients with BRCAwt disease. We therefore propose to consider BRCAmut status in regard to patient selection for cytoreductive surgery, especially in rOC

Platinum-based chemotherapy induces methylation changes in blood DNA associated with overall survival in ovarian cancer patients

Purpose: DNA damage repair can lead to epigenetic changes. DNA mismatch repair proteins bind to platinum DNA adducts and at sites of DNA damage can recruit the DNA methylating enzyme DNMT1, resulting in aberrant methylation. We hypothesised that DNA damage repair during platinum-based chemotherapy may cause aberrant DNA methylation in normal tissues of patients such as blood. Experimental Design: We used Illumina 450k methylation arrays and bisulphite pyrosequencing to investigate methylation at presentation and relapse in blood DNA from ovarian cancer patients enrolled in the SCOTROC1 trial (n=247) and in a cohort of ovarian tumour DNA samples collected at first relapse (n=46). We used an ovarian cancer cell line model to investigate the role of the DNA mismatch repair gene MLH1 in platinum induced methylation changes. Results: Specific CpG methylation changes in blood at relapse are observed following platinumbased chemotherapy and are associated with patient survival, independent of other clinical factors (HR=3.7; 95%CI 1.8-7.6, p=2.8x10-4). Similar changes occur in ovarian tumours at relapse, also associate with patient survival (HR=2.6; 95%CI 1.0-6.8, p=0.048). Using an ovarian cancer cell line model, we demonstrate that functional mismatch repair (MMR) increases the frequency of platinum-induced methylation. Conclusion: DNA methylation in blood at relapse following chemotherapy, and not at presentation, is informative about ovarian cancer patient survival. Functional DNA mismatch repair increases the frequency of DNA methylation changes induced by platinum. DNA methylation in blood following chemotherapy could provide a non-invasive means of monitoring patients’ epigenetic responses to treatment without requiring a tumour biopsy

Characterisation of tumor microvessel density during progression of high-grade serous ovarian cancer: clinico-pathological impact. An OCTIPS Consortium study.

Background: High-grade serous ovarian cancer (HGSOC) intratumoural vasculature evolution remains unknown. The study investigated changes in tumour microvessel density (MVD) in a large cohort of paired primary and recurrent HGSOC tissue samples and its impact on patients’ clinico-pathological outcome. Methods: A total of 222 primary (pOC) and recurrent (rOC) intra-patient paired HGSOC were assessed for immunohistochemical expression of angiogenesis-associated biomarkers (CD31, to evaluate MVD, and VEGF-A). Expression profiles were compared between pOCs and rOCs and correlated with patients' data. Results: High intratumoural MVD and VEGF-A expression were observed in 75.7% (84/111) and 20.7% (23/111) pOCs, respectively. MVDhighand VEGF(+)samples were detected in 51.4% (57/111) and 20.7% (23/111) rOCs, respectively. MVDhigh/VEGF(+)co-expression was found in 19.8% (22/111) and 8.1% (9/111) of pOCs and rOCs, respectively (p = 0.02). Pairwise analysis showed no significant change in MVD (p = 0.935) and VEGF-A (p = 0.121) levels from pOCs to rOCs. MVDhighpOCs were associated with higher CD3(+)(p = 0.029) and CD8(+)(p = 0.013) intratumoural effector TILs, while VEGF(+)samples were most frequently encountered among BRCA-mutated tumours (p = 0.019). Multivariate analysis showed VEGF and MVD were not independent prognostic factors for OS. Conclusions: HGSOC intratumoural vasculature did not undergo significant changes during disease progression. High concentration of CD31(+)vessels seems to promote recruitment of effector TILs. The study also provides preliminary evidence of the correlation between VEGF-positivity and BRCA status

Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers

Precision medicine for breast cancer relies on biomarkers to select therapies. However, the reliability of biomarkers drawn from gene expression arrays has been questioned and calls for reassessment, in particular for large datasets. We revisit widely used data-normalization procedures and evaluate differences in outcome in order to pinpoint the most reliable reprocessing methods biomarkers can be based upon. We generated a database of 3753 breast cancer patients out of 38 studies by downloading and curating patient samples from NCBI-GEO. As gene-expression biomarkers, we select the assessment of receptor status and breast cancer subtype classification. Each normalization procedure is applied separately, and biomarkers are then evaluated for each patient. Differences between normalization pipelines are quantified as percentages of patients having outcomes different for each pipeline. Some normalization procedures lead to quite consistent biomarkers, differing only in 1-2% of patients. Other normalization procedures—some of them have been used in many clinical studies—end up with distrusting discrepancies (10% and more). A good deal of doubt regarding the reliability of microarrays may root in the haphazard application of inadequate preprocessing pipelines. Several modes of batch corrections are evaluated regarding a possible improvement of receptor prediction from gene expression versus the golden standard of immunohistochemistry. Finally, we nominate those normalization methods yielding consistent and trustable results. Adequate bioinformatics data preprocessing is key and crucial for any subsequent statistics to arrive at trustable results. We conclude with a suggestion for future bioinformatics development to further increase the reliability of cancer biomarkers