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