Abstract 758: Studies in cancer models with AGX51, a Direct Transcriptional RegulatorTM

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.