The IMR-32 (MYCN-amplified) and SK-N-SH (non-MYCN-amplified) cells are human neuroblastoma/neuroepthelioma cell lines purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) where routine STR testing was conducted and the cells were confirmed to derive from human species. In addition, the cells were routinely tested for mycoplasma, aerobic and anaerobic bacteria, and human pathogenic viruses including human immunodeficiency virus (HIV), hepatitis B (HepB), human papilloma virus (HPV), Epstein-Barr virus (EBV) and cytomegalovirus (CMV), all of which our cells tested negative for and were used within 6 months of purchase from ATCC. The cells were cultured in minimal essential Eagle's medium (EMEM; cat. no. M2279) supplemented with 2 mM L-glutamine (cat. no. 7513; Sigma, St. Louis, MO, USA), 2% penicillin streptomycin (cat. no. P4333SIGMA), 1 mM sodium pyruvate (cat. no. S8636), 2% non-essential amino acids (cat. no. M7145) and 10% fetal bovine serum (cat. no. F9665) (all from Sigma). The cells were cultured to 80% confluence in T25 flasks at 5% CO₂ and 37°C. The medium was replenished every 48 h. After 8 days, the cells covering 80% of the flask were collected and transferred into a 15 ml falcon tube to be centrifuged at 200 × g for 10 min at 4°C. The old medium was discarded and the cells were re-suspended in 10 ml of fresh medium and transferred into a T75 flask. The cells harvested from T75 flasks were frozen in Corning^® Cryotubes (Corning Inc., New York, NY, USA) using 50% fetal bovine serum (FBS), 40% EMEM and 10% DMSO (D2650; Sigma) to a final volume of 1 ml. The cryotubes were frozen first at −80°C for 24 h in isopropanol to provide a gradual decrease in temperature. They were then transferred to liquid nitrogen for long term storage.

The IMR-32 and SK-N-SH neuroblastoma cells were grown in the standard culture conditions until they reached confluency after which they were washed 6 times with serum-free medium and then cultured in serum-free medium supplemented with 'heavy' isotopes where arginine and lysine were replaced with ¹³C₆-Arg and ¹³C₆, ¹⁵N2-Lys (Cambridge Isotopes, Andover, MA, USA) for 6 doublings to ensure incorporation of the isotopes into the entire cellular population. After 6 doublings, the cells were collected, lysed, quantified and mixed together into one SuperSILAC mastermix cocktail and saved at −80°C. The cells were then cultured in serum-free growth medium supplemented with 'light' isotopes where arginine and lysine were replaced with ¹²C₆ -Arg and ¹²C₆, ¹⁴N₂-Lys until they reached ~80% confluency. The cells were lysed at that point and quantified, and a 'spike-in' strategy used to spike-in the 'heavy' labeled cellular lysates into the 'light' labeled cellular lysates at a 1:1 ratio. Approximately 100 μg of total protein mixture (50:50 μg of cell lysate:SuperSILAC cocktail) was loaded onto a 4–12% polyacrylamide gel and electrophoresed until the proteins were well-separated. The gel was fixed and stained with Commassie Blue (Bio-Rad, Hercules, CA, USA) then de-stained overnight in H₂O at 4°C. The gels were then sliced into ~35–40 bands which underwent in-gel digestion with trypsin (Promega, Madison, WI, USA) using a previously documented protocol (14) and the resultant peptides derived from each band were dried by vacuum centrifugation (240 × g) at room temperature, and re-suspended in 6 μl of 0.1% TFA for analysis by mass spectrometry and proteomics analysis as previously described (15).

The methods used to conduct the mass spectrometry and protein identification and quantification were exactly as described in the study by Formolo et al (15).

Ingenuity Systems, Inc. 2000–2014 (content version, 18030641; release date, December 6, 2013) was used to derive the target molecules within the data set, upstream regulators, molecule type, predicted activation status with activation z-score and P-values of the proteins differentially expressed between the IMR-32 and SK-N-SH cells based on expression of and number of peptides detected per protein, where anything >2-fold is considered upregulated and anything below 0.5-fold is considered downregulated. The Enrichr (16,17) tool was used to annotate the differentially expressed proteins between the IMR-32 and SK-N-SH cells. Proteins in the network that were differentially expressed in the IMR-32 cells were mapped to the top diseases and bio-functions. Differential expression was determined as either upregulated (>2-fold) or downregulated (<0.5-fold) in the IMR-32 compared to the SK-N-SH cells. The STRING protein network tool was used to determine any interactions (experimentally determined, from curated databases and text-mining) between our proteins of interest.

The IMR32 and SK-N-SH cells were collected into 15-ml falcon tubes and centrifuged at 200 × g for 10 min at 4°C. The medium was discarded and the pellet was washed twice with Dulbecco's phosphate-buffered saline (PBS; D8537; Sigma). PBS was then discarded and the cells were incubated on ice for 40 min with 120 μl of lysis buffer (for a confluent T75 flaks) composed of 50 Mm tris-HCl (pH 7.5), 1 mM EDTA, 250 mM NaCl, 50 mM NaF, 0.1 mM Na₃VO₄, 0.5% Titron X-100 and 1X protease inhibitor cocktail (cat no. 11697498001; Roche, Indianapolis, IN, USA). The lysates were transferred to Eppendorf tubes where they were centrifuged at 4°C for 20 min at 8,000 × g to eliminate cellular debris. The supernatants were then transferred to new Eppendorf tubes where they were mixed with 60 μl of the 3X sample buffer (0.5 M tris-HCl, glycerol, 10% SDS, β-mercaptoethanol and 0.05% bromophenol blue) in preparation for western blot analysis.

Protein expression was confirmed by western blot analysis as previously described (18). Briefly, For L1-CAM, glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and HMGA1 detection, a 10% polyacrylamide (cat. no. 161-0156; Bio-Rad) gel was used; however, for FABP5 and MYCN detection a 12% polyacrylamide gel was used. A 5% stacking gel was used to form the wells. The extracted proteins were separated on gels using a current of 150 mV. Proteins were then transferred to a PVDF membrane (cat. no. 1620177; Bio-Rad) for 90 min at 100 mV which was then blocked using 5% BSA (cat. no. A2153-100G; Sigma) diluted in 1X TBS with 1% Tween-20 (cat. no. 9005-64-5).

The blots were incubated with rabbit monoclonal L1-CAM (cat. no. ab20148), HMGA1 (cat. no. ab129153), FABP5 (cat. no. ab84028), survivin (cat. no. ab469) (all from Abcam, Cambridge MA, USA) and MYCN antibodies (cat. no. 9405; Cell Signaling Technology, Danvers, MA, USA) and with mouse monoclonal GAPDH antibody (cat. no. ab9484) (Abcam) overnight (all diluted 1:1,000 in TBS-T +5% BSA blocking solution). The blots were washed 5 times for 5 min with TBST and then incubated with secondary antibodies [goat anti-rabbit (cat. no. 170-5046) or goat anti-mouse (cat. no. 170-5047) HRP-conjugated secondary antibodies from Bio-Rad] for 1 h. After washing, the blots were incubated with Clarity Western ECL substrate (cat. no. 1705060; Bio-Rad) for 3 min and imaged using the Bio-Rad^© ChemiDoc system and analyzed using ImageLab^® software. The bands obtained were normalized to GAPDH.

The 4 siRNA oligonucleotides for L1-CAM (Hs L1-CAM_4 SI00009296, Hs L1-CAM_3 SI00009289, Hs L1-CAM_2 SI00009282 and Hs L1-CAM_1 SI00009275; Qiagen, Valencia, CA, USA), HMGA1 (D-004597-01 HMGA1, D-004597-02 HMGA1, D-004597-03 HMGA1 and D-004597-18 HMGA1; Dharmacon, Lafayette, CO, USA), MYCN (Hs_MYCN_7 SI03113670, Hs_MYCN_6 SI03087518, Hs_MYCN_5 SI03078222 and Hs_MYCN_3 SI00076300; Qiagen) and FABP5 (Hs_FABP5_10 SI04277553, Hs_FABP5_9 SI04210948, Hs_FABP5_8 SI04210941 and Hs_FABP5_5 SI03145835; Qiagen) were reconstituted in RNAase-free water to a final concentration of 10 μM. A total of 5×10⁵ cells were seeded in each well of a 6-well plate in a final volume of 2 ml of antibiotics-free medium. The cells were transfected with the siRNA using the fast-forward Hiperfect transfection protocol following the manufacturer's instructions (cat. no. 301705; Qiagen). A final concentration of 100 nM of each siRNA was achieved by mixing 10 μl of the 10 μM siRNA with 10 μl of Hiperfect (cat. no. 301705; Qiagen) and 370 μl of OptiMEM (cat. no. 31985-062; Life Technologies, Carlsbad, CA, USA). The mixture was incubated at room temperature for 20 min, and added in a drop-wise manner to the corresponding wells. The negative control was prepared by treating the cells with 90 μl of OptiMEM and 10 μl of Hiperfect. The cells were then incubated with the siRNAs for 48 h, lysed and processed for western blot analysis.

In order to examine the effects of KD on cellular proliferation, a WST-1 cell proliferation assay was conducted. A total of 5×10⁴ cells were cultured in each well of a 96-well plate in a final volume of 100 μl. Duplicates of each condition were prepared. The cells were transfected with L1-CAM, HMGA1, MYCN, FABP5 or scrambled siRNAs in a final concentration of 100 nM. The cells were incubated in 100 μl growth medium for 24, 48 and 72 h and treated with 10 μl of WST-1 reagent (cat. no. ab155902; Abcam) per well prior to reading. The absorbance was detected after 3 h using an Epoch™ Microplate Spectrophotometer at 450 nm (BioTek, Winooski, VT, USA).

The IMR32 cells were cultured in a 6-well plate (5×10⁵ cells/well), and transfected with the various siRNA constructs as described above. Negative control cells were either unlabeled/untreated or Annexin V-FITC- and PI-labeled and untreated. Positive control cells were transfected with 100 nM siRNA of our target constructs and labeled with Annexin V-FITC and PI or Annexin V-FITC alone. The cells were then collected at 48 h using accutase (cat. no. A11105-01; Thermo Fisher Scientific, Waltham, MA, USA) and centrifuged at 200 × g for 5 min at 4°C. They were then re-suspended in 500 μl of 1X binding buffer, treated with 5 μl of Annexin V-FITC or PI from Abcam (cat. no. ab14085) and incubated in the dark for 5 min prior to flow cytometric analysis using FACSCalibur flow cytometer (BD Biosciences, San Jose, CA, USA). Data were analyzed using IQuest Pro software (version 5.1) (BD Biosciences). IMR32 cells were identified by their forward-scatter (FSC) and side-scatter (SSC) characteristics. Viable, early apoptotic, late apoptotic and dead cell populations were identified as Annexin V⁻/PI⁻, Annexin V⁺/PI⁻, Annexin V⁺/PI⁺ and Annexin V⁻/PI⁺, respectively. Cells stained with Annexin V-FITC or PI alone were used to adjust color compensation settings on flow cytometer. A minimum of 20,000 cell events were recorded for each sample.

The IMR-32 cells were grown to ~70% confluency in triplicates of 12-well plates in standard culture medium and conditions. FABP5 or HMGA1 siRNA transfection was conducted as described above and after 24 h, the cells were scraped down the midline of the plate to resemble a 'wound'. The cells which were scraped off were washed 2X with serum-free medium and fresh medium replenished and the cells were then imaged (0 h time-point) and cultured under standard growth culture conditions for 24 h. The cells were then imaged at several random fields down the scratched 'wound' area and the area (μM²) of 'wound-closure' after 24 h in siRNA KD-compared to control siRNA-transfected cells was measured using AxioVision Systems software (Zeiss, Oberkochen, Germany). The average of the areas of multiple random fields was represented as a fold change compared to untransfected controls and graphed using Microsoft Excel software.

Experiments were conducted in triplicate, repeated 3 independent times and the means ± the standard error of the means (SEM) of all 3 experiments was calculated and plotted. A two-sided Student's t-test was used to determine statistically significant differences between groups. A one-way analysis of variance (ANOVA) test was used followed by a post hoc Fisher's least significant difference (LSD) test to determine the significance among the means of multiple groups obtained from ≥3 independent experiments. The means ± SEM of 3 or more experiments was derived and graphed using Microsoft Excel software. Statistical significance was set at a P-value <0.05.

We conducted preliminary proteomics analysis of the MYCN-amplified IMR-32 compared to the non-MYCN-amplified SK-N-SH human neuroblastoma cell lines using a highly quantitative SILAC methodology. The significant, differentially expressed proteins were then annotated using IPA in order to predict the upstream regulators of highly tumorigenic proteins in the IMR-32 compared to the SK-N-SH cells. The total numbers of differentially expressed proteins were found to be 875 out of 4,960 proteins (either >2-fold upregulated or <0.5-fold down-regulated) in the IMR-32 compared to the SK-N-SH cells. These proteins were affiliated with upstream regulators that IPA predicted to be activated in the IMR-32 compared to the SK-N-SH cells based on the molecules identified in our dataset (data not shown).

Table I lists the top diseases and disorders, molecular and cellular bio-functions, as well as physiological system development and function categories that proteins significantly overexpressed in the IMR-32 cells are mapped to; the fold change cut-off was set at ≥2-fold. Renal and urological, neurological, hereditary and infectious diseases, as well as organismal injury and abnormalities, were among the top disease categories that the proteins were mapped to Table IA. RNA post-transcriptional modification, molecular transport, RNA trafficking, cellular compromise and gene expression were among the top molecular and cellular functions that the overexpressed proteins in the IMR-32 cells were mapped to Table IB. The physiological system development and function categories that proteins belonged to included tissue development, nervous system development and function, connective tissue development and function and embryonic development (Table IC).

IPA was used to predict the activation status of the upstream regulators of the differentially expressed proteins between the IMR-32 and SK-N-SH cells. Table II lists the top molecules and the fold change of upregulated proteins which included, CaM kinase like vesicle associated (CAMKV), tumor protein D52 (TPD52), argininosuccinate synthetase 1 (ASS1), FABP6, L1-CAM, FABP5, DNA polymerase γ, catalytic subunit (POLG), collapsin response mediator protein 1 (CRMP1), ribonuclease H2 subunit B (RNASEH2B) and G protein subunit αO1 (GNAO1). MYCN, hepatocyte nuclear factor 4α (HNF4A), microtubule associated protein Tau (MAPT), APP and E2F were predicted to be activated upstream regulators of the proteins in this dataset, as determined by IPA (based on the target molecules that were found to be >2-fold upregulated in the IMR-32 compared to the SK-N-SH cells). In addition to the top upstream regulators, Table III lists additional upstream regulators predicted to be activated or inhibited in the IMR-32 compared to the SK-N-SH cells. Of note, is the activation of cancer-promoting, angiogenic and cancer stemness players, such as MYC, HIF-1α, eukaryotic translation initiation factor 4γ1 (EIF4G1), IL3, angiopoietin 2 (ANGPT2) and SREBF in the IMR-32 cells. Molecules predicted to be inhibited in the IMR-32 compared to the SK-N-SH cells included Aly/REF export factor (ALYREF), Ankyrin (ANK)2, autophagy related 7 (ATG7), coiled-coil domain containing 88A (CCDC88A), chromatin target of PRMT1 (CHTOP), cleavage and polyadenylation specific factor 1 (CPSF1), CPSF2 and CPSF3 among others, primarily involved in RNA post-transcriptional modification, molecular transport and RNA trafficking.

The proteins overexpressed in the IMR-32 compared to the SK-N-SH cells that belonged to the upstream regulators predicted to be activated by IPA (SREBF1, SP1, SCAP, SREBF2, IL3, KITLG, FLI1, INSR, HIF-1α, MYC, EIF4E and ANGPT2 among others), mapped to signaling pathways that drive cancer stem cell maintenance and propagation (Notch) (19), invasion and metastasis [Rac1/Pak1/p38/MMP-2 (20) and the leptin signaling pathway (21)], cancer malignancy [SREBP signaling (22) and the AGE/RAGE pathway (23)] and proliferation [AMPK pathways (24)]. Table IV lists the upstream regulators predicted to be activated by IPA, with adjusted P-values for the overexpression level in the IMR-32 cells and the pathways in which these regulators have been demonstrated to play pivotal roles.

Of the highly tumorigenic proteins identified to be upregulated in the IMR-32 compared to the SK-N-SH cells, we decided to focus our investigation on L1-CAM, HMGA1, FABP5, BIRC5 and MYCN as they mapped to several of the activated upstream regulators, as predicted by IPA and due to their tumorigenic roles played in various types of cancer as elaborated below in the 'Discussion'. Western blot analysis was used to determine the levels of HMGA1, FABP5, BIRC5 and L1-CAM, as well as MYCN protein expression between the IMR-32 and SK-N-SH cells. As expected, we found all these targets to be significantly overexpressed in the IMR-32 compared to the SK-N-SH neuroblastoma cells. Fig. 1A is a representative demonstration of multiple western blotting experiments verifying the upregulation of these targets, as indicated by the SILAC proteomics data. Densitometric analysis revealed a significant upregulation of the protein expression of L1-CAM (~1-fold overexpressed), MYCN (~7-fold overexpressed), HMGA1 (~0.5-fold overexpressed), BIRC5 (~1-fold overexpressed) and FABP5 (~4-fold overexpressed) in the IMR-32 compared to the SK-N-SH cells (Fig. 1B).

The STRING protein network database was used to analyze the interactions (experimentally determined and from curated databases) between the activated upstream regulators of the overexpressed proteins in the IMR-32 cells (HMGA1, L1-CAM, BIRC5, FABP5, MYC, INSR, SP1, HIF1A and SREBF1/2 among others) and MYCN (Fig. 2A). In addition, we used STRING protein network analysis to focus on the interactions between the activated upstream regulators, which our validated proteins (by western blot analysis; HMGA1, L1-CAM, FABP5 and BIRC5) mapped to Fig. 2B). Of particular interest, are the various hubs (proteins with multiple edges) identified, including INSR, SP1, HIF-1α, MYC, MYCN, HMGA1 and SREBF that show strong interactions (experimentally-determined, from curated databases and text-mining) with many other tumorigenic proteins (Fig. 2A). We further highlight the important interactions (experimentally determined, from curated databases and text-mining) between our validated targets (by western blot analysis; HMGA1, BIRC5 and MYCN) and the activated upstream regulators, SP1, SREBF1, MYC, KITLG, IL3, INSR and HIF-1α (Fig. 2B). KEGG pathway analysis mapped the number of molecules to various pathways, most of which are known tumorigenic drivers, including PI3K/Akt, Ras, Rap1, Wnt, HIF-1α, transforming growth factor-β (TGF-β) and mammalian target of rapamycin (mTOR) and insulin signaling pathways (Table V). This intricate network of interplay between these highly tumorigenic proteins warrants further investigation, particularly in pre-clinical, animal models, whereby multiple targeting of more than one of these players may yield beneficial, antitumor effects and improve therapeutic outcomes.

In addition to the above-mentioned pathways, when we combined only MYC, MYCN and our validated targets in the STRING protein network analysis (Fig. 3A), we found very strong interactions between MYC, MYCN, BIRC5 and HMGA1 with Aurora kinase (AURK)A/B, cyclin-dependent kinase 1 (CDK1), cell division cycle associated 8 (CDCA8) and INCENP. These players were mapped to cellular functions highly affiliated with mitosis and cellular division and proliferation (Table VI). Lastly, L1-CAM focused network analysis revealed its strong interaction with neural cell adhesion molecule 1 (NCAM1), neurocan (NCAN), ezrin (EZR), RDX, ANK1, ANK2, contactin 2 (CNTN2), neuropilin 1 (NRP1), epidermal growth factor receptor (EGFR) and RAN binding protein 9 (RANBP9) (Fig. 3B), most of which drive angiogenic and migratory processes to fuel cellular invasion, migration and metastatic spread.

We then aimed to transcriptionally KD the protein expression of these molecules and determine the effects of this KD on cellular bio-function. Additionally, we wished to determine whether the downregulation of one protein would affect the expression level of the other targets, thereby implicating a potential interplay between the proteins. Using transient siRNA transfection, we successfully downregulated the protein expression (Fig. 4A) of MYCN (~85%), HMGA1 (~60%), FABP5 (~60%) and L1-CAM (~80%) as determined by western blot analysis at 48 h after siRNA transfection (Fig. 4B). Of note, L1-CAM, HMGA1 and FABP5 transcriptional KD led to the significant concomitant downregulation of MYCN protein expression by ~80, 90 and 75%, respectively (Fig. 5A). In addition, MYCN transcriptional KD led to the significant concomitant downregulation of L1-CAM, HMGA1 and FABP5 protein expression by ~77, 75 and 70, respectively (Fig. 5B). Moreover, the combined transcriptional KD of L1-CAM and FABP5 led to the significant concomitant downregulation of HMGA1 protein expression by ~70% (Fig. 5C), while survivin protein expression was abrogated following the transcriptional KD of MYCN, HMGA1 and FABP5 (Fig. 5D). This interplay between these tumorigenic proteins is extremely interesting and warrants further investigation into the mechanisms utilized by this network to drive cancerous progression and malignant, treatment-evasive recurrence in high-risk, MYCN-amplified pediatric neuroblastomas.

To determine the cellular bio-functional effects of the transcriptional downregulation of our protein targets, we examined the rate of proliferation of the IMR-32 cells over 5 days following the transcriptional KD of these tumorigenic proteins. We observed no significant differences in the rate of the proliferation of IMR-32 cells at 0 and 24 h following the transcriptional KD of all the above-mentioned siRNA-targeted, tumorigenic proteins compared to the controls. However, there was a statistically significant reduction in the rate of cellular proliferation between the MYCN, L1-CAM, HMGA1 and FABP5 siRNA-transfected cells and the controls at 48, 72 and 96 h post-siRNA transfection (Fig. 6A), implicating the role of these proteins in highly proliferative signaling pathways. The rate of the proliferation of cells targeted with double-target siRNA transfection (MYCN + L1-CAM, MYCN + HMGA1, MYCN + FABP5, HMGA1 + L1-CAM, HMGA1 + FABP5 and FAB5 + L1-CAM) was also significantly decreased from 48 to 96 h post-transfection compared to the controls (Fig. 6B). Double-target siRNA transfection did not exert an additive effect on the rate of cell proliferation compared to the single-target siRNA-transfected cells (data not shown); thus, we speculate on the possible redundancy of the proliferative signaling pathways of these proteins. We then sought to examine the effects of FABP5 and HMGA1 transcriptional KD on the migration of IMR-32 cells, since L1-CAM (25) and MYCN (26,27) have been previously reported to affect neuroblastoma cell migration. Using the 'wound healing' scratch assay (Fig. 6C) we observed a significant decrease in the migratory capacity of the IMR-32 cells subjected to FABP5 or HMGA1 transcriptional KD at 24 h after 'wound induction' (Fig. 6D).

Lastly we wished to determine whether the transcriptional KD of the tumorigenic proteins would affect the rate of apoptosis of IMR-32 cells. The late apoptotic rate was not observed to differ significantly between the controls and siRNA-transfected cells of any target at 48 h following transcriptional KD (Fig. 7A). However, early apoptosis was significantly higher in the cells subjected to FABP5 and MYCN transcriptional siRNA KD at 48 h, as determined by Annexin V/PI staining and FACS analysis (Fig. 7B). This was confirmed by immunofluorescence staining of the cells with Annexin V and PI (Fig. 7C). Perhaps a difference in the rate of late apoptosis would be observed had we conducted the apoptosis assay at 72 or 96 h post-transcriptional KD.