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Architecture of The Human Ape1 Interactome Defines Novel Cancers Signatures

APE1 is essential in cancer cells due to its central role in the Base Excision Repair pathway of DNA lesions and in the transcriptional regulation of genes involved in tumor progression/chemoresistance. Indeed, APE1 overexpression correlates with chemoresistance in more aggressive cancers, and APE1 protein-protein interactions (PPIs) specifically modulate different protein functions in cancer cells. Although important, a detailed investigation on the nature and function of protein interactors regulating APE1 role in tumor progression and chemoresistance is still lacking. The present work was aimed at analyzing the APE1-PPI network with the goal of defining bad prognosis signatures through systematic bioinformatics analysis. By using a well-characterized HeLa cell model stably expressing a flagged APE1 form, which was subjected to extensive proteomics analyses for immunocaptured complexes from different subcellular compartments, we here demonstrate that APE1 is a central hub connecting different subnetworks largely composed of proteins belonging to cancer-associated communities and/or involved in RNA- and DNA-metabolism. When we performed survival analysis in real cancer datasets, we observed that more than 80% of these APE1-PPI network elements is associated with bad prognosis. Our findings, which are hypothesis generating, strongly support the possibility to infer APE1-interactomic signatures associated with bad prognosis of different cancers; they will be of general interest for the future definition of novel predictive disease biomarkers. Future studies will be needed to assess the function of APE1 in the protein complexes we discovered. Data are available via ProteomeXchange with identifier PXD013368.

S3 buffered saline (TBS), immunoprecipitates were eluted through incubation with FLAG peptide (0.15 mg/ml) in TBS, and further characterized (see below). In parallel, immunoprecipitation of cell extracts from HeLa cells expressing APE1 FLAG-tagged was also performed with a resin lacking the FLAG antibody.

Immunofluorescence confocal and Proximity Ligation analyses
Immunofluorescence procedures and Proximity Ligation Assay (PLA) were carried out as described earlier 3 . To study the interaction between APE1 and three identified protein interactors in vivo, we used the in situ Proximity Ligation Assay technology (Duolink, Sigma-Aldrich). After incubation with

Proteomic analysis
Protein digests of gel slices from immunoprecipitated material of whole, nuclear and cytoplasmic cell extracts of HeLa cell clones expressing ectopic APE1 FLAG-tagged protein or stably transfected with the empty vector (SCR) were analyzed through Mass-Spectrometry. As a negative control, identical cell extracts from HeLa cells expressing APE1 FLAG-tagged were co-immunoprecipitated, in parallel, with a resin lacking the FLAG antibody (res). Mass-Spectrometry analyses were performed with a nanoLC-ESI-Q-Orbitrap-MS/MS platform consisting of an UltiMate 3000 HPLC RSLC nano system (Thermo Fisher Scientific, USA) coupled to a Q-ExactivePlus mass spectrometer through a Nanoflex ion source (Thermo Fisher Scientific). Peptides were loaded on an Acclaim PepMap TM RSLC C18 column (150 mm × 75 μm ID, 2 μm particles, 100 Å pore size) (Thermo Fisher Scientific) and eluted with a gradient of solvent B (19.92/80/0.08 v/v/v water/acetonitrile/formic acid) in solvent A (99.9/0.1 v/v water/formic acid), at a flow rate of 300 nl/min. The gradient of solvent B started at 3%, increased to 40% over 40 min, raised to 80% over 5 min, remained at 80% for 4 min, and finally returned to 3% in 1 min, with a column equilibrating step of 30 min before the subsequent chromatographic run. The mass spectrometer operated in data-dependent mode using a full scan (m/z range 375-1,500, a nominal resolution of 70,000, an automatic gain control target of 3,000,000, and a maximum ion target of 50 ms), followed by MS/MS scans of the 10 most abundant ions. MS/MS spectra were acquired in a scan m/z range 200-2000, using a normalized collision energy of 32%, an automatic gain control target of 100,000, a maximum ion target of 100 ms, and a resolution of 17,500. A dynamic exclusion value of 30s was also used. Duplicate analysis of each sample was performed to increase the number of identified peptides/protein coverage. variable modifications. Peptide mass tolerance and fragment mass tolerance were set to ± 10 ppm and ± 0.05 Da, respectively. Proteolytic enzyme and maximum number of missed cleavages were set to trypsin and 2, respectively. Protein candidates assigned on the basis of at least two sequenced peptides and Mascot score ≥30 were considered confidently identified. Definitive peptide assignment was always associated with manual spectra visualization and verification. Results were filtered to 1% false discovery rate. A comparison with results from the corresponding samples from control experiments (SCR and res) allowed to identify contaminant proteins in each experiment that, despite their abundance, were removed from the list of APE1-interacting partners (Supplementary Table S1 and S2).

S10
Asterisks represent a significant difference with respect to untreated cells. Data were evaluated statistically by two-tails Student t-test.

Supplementary Tables
Supplementary Table S1.

Supplementary Table S6.
Abbreviations used for TCGA datasets.

APE1-PPI bad prognostic signatures top regulators analysis. GeneXplain identification of the Top 3
putative master regulators of bad prognostic genes in the 11 selected TCGA cancer datasets (ranked by ascending Ranks sum). Bibliographic references are given for the association with the proliferation, apoptosis and resistance functional terms, indicating the involvement of top upstream regulators in these pathways (x indicates that no reference was found).

Supplementary Table S8.
GeneXplain identification of the Top10 putative master regulators of the APE1-PPI global network (ranked by ascending Ranks sum).