Original Article Evaluation of 9-cis retinoic acid and mitotane as antitumoral agents in an adrenocortical xenograft model
Zoltán Nagy1, Kornélia Baghy2, Éva Hunyadi-Gulyás3, Tamás Micsik2, Gábor Nyírő4, Gergely Rácz2, Henriett Butz4, Pál Perge1, Ilona Kovalszky2, Katalin F Medzihradszky3, Károly Rácz1,4, Attila Patócs4,5, Peter Igaz1
1The 2nd Department of Medicine, Faculty of Medicine, Semmelweis University, H-1088 Budapest, Szentkirályi Str. 46., Hungary; 2The 1st Department of Pathology and Experimental Cancer Research, Faculty of Medicine, Semmelweis University, H-1088 Budapest, Üllői Str. 26., Hungary; 3Laboratory of Proteomics, Biological Research Centre, H-6726 Szeged, Temesvári Krt. 62., Hungary; 4Molecular Medicine Research Group, Hungarian Academy of Sciences and Semmelweis University, Szentkirályi Str. 46., H-1088 Budapest, Hungary; 5”Lendület-2013” Research Group, Hungarian Academy of Sciences and Semmelweis University, Szentkirályi Str. 46., H-1088 Budapest, Hungary
Received October 31, 2015; Accepted November 7, 2015; Epub November 15, 2015; Published December 1, 2015
Abstract: The available drug treatment options for adrenocortical carcinoma (ACC) are limited. In our previous stud- ies, the in vitro activity of 9-cis retinoic acid (9-cisRA) on adrenocortical NCI-H295R cells was shown along with its antitumoral effects in a small pilot xenograft study. Our aim was to dissect the antitumoral effects of 9-cisRA on ACC in a large-scale xenograft study involving mitotane, 9-cisRA and their combination. 43 male SCID mice inoculated with NCI-H295R cells were treated in four groups (i. control, ii. 9-cisRA, iii. mitotane, iv. 9-cisRA + mitotane) for 28 days. Tumor size follow-up, histological and immunohistochemical (Ki-67) analysis, tissue gene expression micro- array, quantitative real-time-PCR for the validation of microarray results and to detect circulating microRNAs were performed. Protein expression was studied by proteomics and Western-blot validation. Only mitotane alone and the combination of 9-cisRA and mitotane resulted in significant tumor size reduction. The Ki-67 index was significantly reduced in both 9-cisRA and 9-cisRA+mitotane groups. Only modest changes at the mRNA level were found: the 9-cisRA-induced overexpression of apolipoprotein A4 and down-regulation of phosphodiesterase 4A was validated. The expression of circulating hsa-miR-483-5p was significantly reduced in the combined treatment group. The SET protein was validated as being significantly down-regulated in the combined mitotane+9-cisRA group. 9-cisRA might be a helpful additive agent in the treatment of ACC in combination with mitotane. Circulating hsa-miR-483-5p could be utilized for monitoring the treatment efficacy in ACC patients, and the treatment-induced reduction in protein SET expression might raise its relevance in ACC biology.
Keywords: Adrenocortical cancer, mitotane, 9-cis retinoic acid, xenograft, SET protein, circulating microRNA
Introduction
Adrenocortical carcinoma (ACC) is a rare tumor (incidence is 0.5-2 cases/million people/year) with poor prognosis in its advanced stages [1]. The primary treatment is surgical resection. Even with the most widely used EDPM (etopo- side, doxorubicin, cisplatin, mitotane) chemo- therapeutic regimen, the median overall sur- vival was only 14.8 months in the recent FIRM- ACT trial [2, 3]. Mitotane (o,p-DDD) is the only adrenal specific drug that is registered for the treatment of ACC [4]. Despite its numerous side
effects and largely unknown mechanism of action this agent is used in the clinical practice for more than 50 years [5]. Intensive efforts are therefore going on for finding novel, effective drugs with fewer side effects.
In our previous in silico study of adrenocortical tumors genomics data, we have found that reti- noic acid signaling via retinoid X receptor is an important pathogenic pathway in ACC [6]. Based on these in silico data, we have per- formed in vitro studies on the NCI-H295R ACC cell line and found that 9-cis retinoic acid
9-cis retinoic acid and mitotane in adrenal cancer
(9-cisRA) was able to diminish hormone syn- thesis and cell viability in a concentration- and time-dependent manner, and it induced signifi- cant gene expression changes [7]. In a pilot in vivo xenograft study in nude mice, 9-cisRA reduced tumor growth, as well [7].
In the present study, we aimed to further dis- sect the antitumoral effect of 9-cisRA on ACC in a large xenograft study involving both mito- tane and 9-cisRA and their combination. We have applied multimodal molecular biological, genomic and proteomic approaches to deci- pher the molecular way of action of the agents tested.
Materials and methods
Cell culture
The human adrenocortical NCI-H295R cell line was obtained from the American Type Culture Collection (Manassas, VA, USA). Cells were cul- tured in Dulbecco’s modified Eagle’s medium/ Nutrient Mixture F-12 Ham (DMEM: F12) sup- plemented with 3.61*10-8 M selenium (Sigma- Aldrich, St. Louis, MO, USA), 1.92*10-5 M lin- oleic acid, 0.001 M insulin, 7.81*10-8 M trans- ferrin (Sigma-Aldrich), 1.899*10-5 M bovine serum albumin and adjusted to a final concen- tration of 1% HEPES, 1% Penicillin/Streptomy- cin (Sigma-Aldrich), 2.5% Nu-Serum (BD Bio- sciences, San Jose, CA, USA) and 2.5% L-gluta- mine (Sigma-Aldrich) at 37℃ in a humidified 5% CO2 atmosphere. The medium was changed two or three times a week and subcultured once or twice a week.
Xenograft model
44 male BALB/c SCID (severe combined immu- nodeficiency) mice aged 6-8 weeks with aver- age weight between 21-23 g were injected sub- cutaneously with NCI-H295R cell suspension (107 cells/200 ul PBS). Treatment was started when the solid tumor reached 3 mm mean diameter (37 days after the H295R inocula- tion). The animals have received the treatment by oral gavage for 28 days. Four groups were established: 1. control: 200 ul corn oil/day; 2. mitotane: 200 mg/kg/day/200 ul corn oil; 3. 9-cis retinoic acid: 5 mg/kg/day/200 ul corn oil; and 4. mitotane 200 mg/kg/day/100 ul corn oil + 9-cis retinoic acid 5 mg/kg/day/100 ul corn oil. The tumors were measured twice a
week with a caliper by the same investigator. The volumes of the tumors were calculated by the following formula: (a*a*b*11)/6 [8]. On day 29 after starting the treatments, the animals were killed by cervical dislocation in ether anes- thesia. Only one animal died before day 29 due to technical problems.
Tumors were removed and their weights were measured. One half of the tumor was fixed in formalin for histological and immunohisto- chemical examination, the other half was fro- zen in liquid nitrogen and stored at -80℃ until use. Lungs, heart, kidneys, spleen and liver were also removed for histological analysis. Whole blood was collected, then plasma was isolated and stored at -80℃ until use. All ani- mal experiments were conducted according to the ethical standards of the animal Health Care and Control Institute, Csongrád County, Hungary, permit No. XVI/02037-2/2008.
Histological and immunohistochemical analy- sis
Four um sections of formalin-fixed paraffin- embedded tissues were dewaxed with xylene and ethanol and processed either for hematox- ylin-eosin (HE) staining or Ki-67 immunostain- ing. Ki-67 immunostaining (antibody: Cat. No. M7240, DakoCytomation, Glostrup, Denmark; dilution 1:400) was conducted using a Leica BOND-MAX automated immunostaining system (Leica Biosystems, Wetzlar, Germany). Slides were scanned by Pannoramic Flash II scan- ner, and digital slides were analyzed by Pannor- amic viewer software (3DHistech, Budapest, Hungary). Different regions of the viable xeno- graft tumor were annotated and Ki-67 positive and negative cells were individually marked on these regions of interests (ROIs). Proliferation index was given in percentages of positive cells. 4-8 slides of each group with good quality were selected for analysis, and 3-5 ROIs/slides were counted with 4498-6273 cells in average. Ki-67 expression was scored by three indepen- dent pathologists in a blinded fashion.
RNA isolation from tumor tissue
Total RNA was isolated from the frozen tumors with Qiagen miRNeasy Mini Kit according to the manufacturer’s protocol (Qiagen, Hilden, Ger- many). RNA concentration was measured with NanoDrop 2000 spectrophotometer. (Thermo
9-cis retinoic acid and mitotane in adrenal cancer
Fisher Scientific, Waltham, Mam USA). RNA integrity was determined by Agilent 2100 Bio- analyzer System (Agilent Technologies, Santa Clara, CA, USA). Samples with an RNA integrity number (RIN) above 8.0 were used for further analysis. RNA was stored at -80℃ until use.
Messenger RNA (mRNA) expression profiling
Gene expression profiling was performed on 16 samples (4-4 samples from each group) using a single-color array method by 4x44K Agilent Whole Genome Microarray slides (Agilent Tech- nologies).
Total RNA (200 ng) was labeled and amplified using the low Input Quick Amp Labeling Kit according to the instructions of the manufac- turer. Labeled RNA was purified and hybridized to Agilent Human Gene Expression Microarray 4x44K array slides, according to the manufac- turer’s protocol. After washing, array scanning and feature extraction was performed with default scenario by Agilent DNA Microarray Scanner. Fluorescence intensities of spots were quantified, background subtracted, and dye normalized by Feature Extraction software, version 11.0.1 (Agilent Technologies). The raw data were analyzed with GeneSpring 12.6 soft- ware (Agilent Technologies).
Reverse transcription quantitative polymerase chain reaction (RT-qPCR)
Seven genes were selected for validation by real-time RT-qPCR with Taqman gene expres- sion assays (Thermo Fisher Scientific): MYC (Hs00153408_m1), APOA4 (Hs00166636_ m1), CXCR3 (Hs01847760_s1), BAALC (Hs00- 227249_m1), PDE4A (Hs00183479_m1), PR- DM1 (Hs00153357_m1) and TGFBI (Hs009- 32747_m1). Based on the selection criteria of Cheng et al. [9] and our previous study [10], ZNF625 (Hs00377010_m1) was chosen as ref- erence gene.
Total RNA (10 ng) was reverse transcribed using High-Capacity RNA-to-cDNA Kit (Thermo Fisher Scientific). Quantitative RT-PCR was perform- ed by TaqMan Fast Universal PCR Master Mix (2x) (Thermo Fisher Scientific) on a 7500 Fast Real-Time PCR System (Thermo Fisher Scienti- fic) according to the manufacturer’s protocol. Samples were run in triplicate. For the evalua- tion of the data we used the ddCT method [11]
using Microsoft Excel 2010 (Microsoft Corpo- ration).
RNA isolation from plasma
Total RNA was isolated from 100 ul plasma samples with Qiagen miRNeasy Serum/Plasma Kit according to the attached manufacturer’s protocol (Qiagen) amended with addition of a spike-in control miRNA cel-miR-39 (2594091) (Qiagen). RNA concentration was measured with NanoDrop 2000 spectrophotometer (Ther- mo Fisher Scientific). RNA was stored at -80℃ until use.
RT-qPCR for circulating microRNA measure- ment
Based on our previous studies and literature data, four microRNAs were selected for valida- tion by RT-qPCR with Taqman miRNA assays (Thermo Fisher Scientific): hsa-miR-181b (00- 1098), hsa-miR-184 (000485), hsa-miR-210 (000512) and hsa-miR-483-5p (002338). Cel- mir-39 (000200) was used as reference gene [12].
Total RNA (1 ul) was reverse transcribed using specific TaqMan miRNA assays and TaqMan MicroRNA Reverse Transcription Kit (Thermo Fisher Scientific) on Proflex Base PCR System (Thermo Fisher Scientific). Quantitative RT-PCR was performed by TaqMan Fast Universal PCR Master Mix (2x) and TaqMan miRNA assays on a 7500 Fast Real-Time PCR System. PCR reac- tions were run in triplicate. Negative control reactions did not include cDNA templates.
RT-qPCR for tissue microRNA measurement
Considering the results from the circulating microRNA measurements, tissue hsa-miR- 483-5p (002338) was studied by RT-qPCR with Taqman miRNA assays according to the instruc- tions of the manufacturer. Four reference genes were used: U6 (001973), RNU6B (001093), RNU44 (001094) and RNU48 (001006).
Proteomics study
Equal amount of protein lysates (20-20 µg of each sample, 3 samples from each group) were separated by SDS-PAGE on a 10% minigel and stained with colloidal Coomassie Brillant Blue. The gel lanes were cut to 10 pieces and their protein content were in-gel digested with tryp-
9-cis retinoic acid and mitotane in adrenal cancer
sin (Promega, Fitchburg, WI, USA) for 4 hours at 37°℃ after reduction with dithiotreitol and alkyl- ation with iodoacetamide. The digestion reac- tion was stopped by acidification with formic acid, and the tryptic peptides were extracted from the gel and dried.
Samples were redissolved in 30 ul of 0.1% formic acid and subjected to LC-MSMS (Li- quid Chromatography-Mass Spectrometry and Liquid Chromatography-Tandem Mass Spec- trometry b, on a Waters nanoAcquity ULC on- line coupled to an Orbitrap Elite Mass spec- trometer) analysis. 5 ul sample was loaded onto a Symmetry C18 (5 um, 180 um ×20 mm) trap column (Waters, 186003514) in 3% of sol- vent B and analyzed on a BEH300 C18 (1.7 um, 075 um ×250 mm) nanoAcquity UPLC column (Waters 186003815) using a gradient elution (3-40% of solvent B during 37 min, solvent A: 0.1% formic acid in water, solvent B: was 0.1% formic acid in acetonitrile:DMSO (95:5)). The flow rate was 300 nl/min. The LTQ-Orbitrap Elite mass spectrometer operated in data dependent mode, each survey scan (full MS measured in the Orbitrap R=60000, m/z range: 380-1600) was followed with ion-trap collision induced dissociation (CID) scans of the 10 most intense peaks. Dynamic exclusion was used for 30 seconds and single charged ions were not selected for fragmentation.
Mass spectrometry raw data were converted to MSMS peak list files using PAVA script [13]. Peak list files corresponding to the same sam- ple (10 to each) were merged and searched against the human, mouse species specified UniProtKB random concat (06.11.2014) pro- tein database, containing 136244 human and 74540 mouse proteins and their randomized sequences. The search was done with the fol- lowing parameters: fully specific tryptic pep- tides with maximum 2 missed cleavages were allowed. All cysteines were considered as carb- amidomethylated and some variable modifica- tion has been allowed: oxidized methionine, acetylation of protein N-termini and pyroglu- tamic acid modification at peptide N-terminal glutamine. Parent mass tolerance was set to 10 ppm, while fragment mass tolerance was 0.6 Da. All database search were completed on our in-house ProteinProspector (ver. 5.14.1) (Baker, P.R. and Clauser, K.R. http://prospector. ucsf.edu accessed: July 22. 2015) search en- gine.
Spectral count was used for semi-quantitation. The number of spectra identified a protein were normalized by the number of all identified spec- tra in the sample. These relative spectral counts were compared in between the different samples.
Western-blot analysis
Based on our proteomic results and literature data, the SET (SET nuclear proto-oncogene) protein was chosen for Western-blot analysis on 3 samples from each group of the xenograft study and on altogether 6 human adrenocorti- cal samples (2 normal adrenal cortices, 2 ACAs (adrenocortical adenoma) and 2 ACCs (adreno- cortical cancer)). Normal human adrenal corti- ces were obtained from patients operated for hypernephroma [14]. The study on human sam- ples was approved by the Ethical Committee of the Hungarian Health Council and inform- ed consent was obtained from all patients involved.
Tumor tissues were pulverized in liquid nitrogen and lysed in 1 ml of Lysis Buffer (0.02 M Tris, 0.15 M NaCl, 0.002 M EDTA, 0.5% Triton X- 100, 0.5% Protease Inhibitor Cocktail (Sigma Aldrich), 0.01 M NaF, 0.002 M Na VOL on ice for 30 minutes. Next, samples were centrifuged at 13000 rpm for 15 min. Supernatants were kept and protein concentrations were measured as described before by Bradford [15]. 20 µg of total protein per sample was mixed with loading buffer containing ß-mercaptoethanol and was incubated at 99℃ for 5 min. Denatured sam- ples were loaded onto a 10% polyacrylamide gel and were run for 30 min at 200 V on a Mi- ni Protean vertical electrophoresis equipment (Bio-Rad, Hercules, CA). Proteins were trans- ferred onto a PVDF membrane (Milipore, Biller- ca, MA) by blotting overnight at 75 mA. Ponceau- staining was applied to see the loading and blotting efficiency. Membranes were blocked with 5 w/v% non-fat dry milk (Bio-Rad) in TBS (0.15 M NaCl, 0.02 M Tris-HCl pH=7.5) for 1 hour followed by incubation with either anti- SET antibody (ab1183, Abcam, Cambridge, MA, dilution 1:1000) or anti-ß-actin antibody (A22- 28, Sigma Aldrich) for 16 h at 4℃. Membranes were washed 5 times with TBST (TBS+0.05% Tween-20) then incubated with secondary, HRP-conjugated anti-rabbit (P0448, DakoCyto- mation) or anti-mouse (P0447, DakoCytoma- tion) antibodies for 1 hour. SuperSignal West Pico Chemiluminescent Substrate Kit (Pierce/
A
Normalized tumor volume (mm3)
B 45
45
*
= control
40
Normalized tumor volume (mm3)
*
40
mitotane
35
35
30
9-cisRA
30
25
combined
25
20
20
15
15
10
10
5
5
0
0
1
5
10
15
20
25
control
mitotane
9-cisRA
combined *p<0.05
Days
p<0.05
Mean
Mean±0,95 Conf. Interval
工
Mean±SD
C
D
**
60
**
control
mitotane
**
50
**
Ki-67 index (%)
40
*
30
9-cisRA
combined
20
10
0
control
mitotane
9-cisRA
combined * p<0.05
p<0.005
Thermo Fisher Scientific) and Kodak Image Station 4000 MM Digital Imaging System were used to visualize the signals. ß-actin served as loading control. Band density was measured by ImageJ software (National Institutes of Health, Bethesda, MD, USA).
Statistical analysis
For the statistical analysis of tumor grow- th, Mann-Whitney U test was applied (SPSS Statistics 20, IBM). The analysis of Ki-67 index was performed by One-way ANOVA followed by Tukey’s post Hoc test or Kruskal-Wallis ANOVA & Median Test (STATISTICA 7.0) depending on the results of the Shapiro-Wilks normality test. P<0.05 was considered to be significant.
The results from the microarray data were ana- lyzed by Genespring 12.6 software (Agilent
Technologies). A filter on expression at the 20th percentile of raw signal values, then a 2-fold change filter was used, and One-way ANOVA was performed, followed by Tukey’s post Hoc test without Benjamini-Hochberg false discov- ery rate calculation. RT-qPCR and proteomics data were analyzed by One-way ANOVA followed by Tukey’s post Hoc test (STATISTICA 7.0).
Western-blot was evaluated by Kruskal-Wallis ANOVA & Median Test (STATISTICA 7.0).
Results
Analysis of xenograft tumor growth
The normalized tumor volume (relative to the first measured volume) was smaller in all treat- ed groups than in controls during the whole experiment. At the end of our experiment, the
Fold change
3
APOA4 (relative to control)
Fold Change
PDE4A (relative to control)
2.5
*
2.5
2
2
1.5
1
1.5
*
0.5
1
mitotane
9-cisRA
combined
0
mitotane
9-cisRA
combined
Mean
Mean+SE
I
Mean±SD
* p<0.05
Mean
Mean±SE
I
Mean±SD
* p<0.05
average values of normalized tumor volumes were 22.48-fold, 9.3-fold, 12.3-fold and 8.22- fold higher in the control, mitotane treated, 9-cisRA-treated, and 9-cisRA+mitotane groups relative to the starting tumor volume, respec- tively. The reduction in tumor size has been sig- nificant in the mitotane only and 9-cisRA+ mitotane groups (Figure 1A and 1B).
Histology, Ki-67 scoring
Tumors in the 9-cis RA receiving groups appeared to be more differentiated compared to the control and mitotane groups by hema- toxylin and eosin (H&E) staining. The Ki-67 pro- liferation index scored blindly by three indepen- dent pathologists was significantly lower in the 9-cisRA (32.64 ± 3.07%) group in comparison to the control (54.23 ± 3.71%) and mitotane groups (46.35% ± 2.2%) (P=0.00018 vs. con- trol; P=0.00022 vs. mitotane). The lowest Ki-67 index was noted in the combined 9-cisRA+ mitotane group (25.6 ± 4.09%) that was signifi- cantly smaller compared to all other groups (P=0.00018 vs. control; P=0.00018 vs. mito- tane; P=0.01684 vs. 9-cisRA) (Figure 1C and 1D). Among the other tissues, only moderate fatty lesions were observed in the liver, proba- bly due to the corn oil vehicle. No signs of treat- ment toxicity have been found.
Microarray analysis
4 samples from each group (altogether 16 sam- ples) have been subjected to microarray. By analyzing the raw data, we have found 483 significant gene expression changes after the statistical analysis, but only by omitting the
Benjamini-Hochberg false discovery rate (FDR). By using FDR, only two significantly differential- ly expressed transcripts emerged whose bio- logical relevance is unknown. Microarray data are accessible at Gene Expression Omnibus (GEO; www.ncbi.nlm.nih.gov/geo, accession nu- mber: GSE73417).
RT-qPCR validation
Seven genes have been selected for validation based on the microarray data chosen from genes with the highest positive and negative fold changes, taking into account literature data, as well. However, only two genes could be validated to be significantly differentially ex- pressed (Figure 2). The well-known 9-cis reti- noic acid target gene APOA4 (apolipoprotein A4) turned out to be significantly overexpress- ed in the combined treated group relative to the control group (P=0.0045), whereas PDE4A (phosphodiesterase 4A) appeared to be signifi- cantly underexpressed in the combined treat- ment group (P=0.0024).
Proteomics analysis and Western-blot
47 significant protein changes have been found between the groups (Table 1). By considering literature data regarding the tumor biological relevance of these proteins, the SET protein [16-20] was chosen for validation by Western- blotting.
SET protein expression was smaller in all treat- ed groups relative to control, but only reached the level of significance in the combined treat- ed group (Figure 3A and 3C). To look at the
9-cis retinoic acid and mitotane in adrenal cancer
| UniProt ID | Gene Name | Protein Name |
|---|---|---|
| P30050 | RPL12 | 60S ribosomal protein L12 |
| Q13765 | NACA | Nascent polypeptide-associated complex subunit alpha |
| B1AK87 | CAPZB | Capping protein (Actin filament) muscle Z-line, beta |
| Q01105 | SET | Phosphatase 2A inhibitor I2PP2A |
| Q86SZ7 | PSME2 | PSME2 protein |
| P14314 | PRKCSH | Protein kinase C substrate 60.1 kDa protein heavy chain |
| Q5U8W9 | HRMT1L2 | Protein arginine methyltransferase 1 isoform 4 |
| Q6DC98 | LMNB1 | LMNB1 protein |
| M0QZL1 | BLVRB | Flavin reductase (NADPH) |
| P61158 | ACTR3 | Actin-related protein 3 |
| Q9UBQ7 | GRHPR | Glyoxylate reductase/hydroxypyruvate reductase |
| O75347 | TBCA | Tubulin-specific chaperone A |
| Q6NVY0 | CACYBP | Calcyclin binding protein |
| K7ES63 | TUBB6 | Tubulin beta-6 chain |
| P42126 | ECI1 | Enoyl-CoA delta isomerase 1 |
| Q5T1M5 | FKBP15 | FK506-binding protein 15 |
| O75477 | ERLIN1 | Erlin-1 |
| H7BZ09 | ANP32A | Acidic leucine-rich nuclear phosphoprotein 32 family member A |
| E9PK45 | FTH1 | Ferritin heavy chain |
| P62714 | PPP2CB | Serine/threonine-protein phosphatase 2A catalytic subunit beta |
| P31040 | SDHA | Succinate dehydrogenase |
| H7C333 | GBAS | Protein NipSnap homolog 2 |
| Q15404 | RSU1 | Ras suppressor protein 1 |
| Q92882 | OSTF1 | Osteoclast-stimulating factor 1 |
| D6RC06 | HINT1 | Histidine triad nucleotide-binding protein 1 |
| P62888 | RPL30 | 60S ribosomal protein L30 |
| Q969G3 | SMARCE1 | SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily E member 1 |
| P61326 | MAGOH | Protein mago nashi homolog |
| Q16539 | MAPK14 | Mitogen-activated protein kinase 14 |
| P10599 | TXN | Thioredoxin |
| Q9Y333 | LSM2 | U6 snRNA-associated Sm-like protein LSm2 |
| P26885 | FKBP2 | Peptidyl-prolyl cis-trans isomerase FKBP2 |
| Q9UJV8 | PURG | Purine-rich element-binding protein gamma |
| P04080 | CSTB | Cystatin-B |
| E5RJH5 | ENO3 | Beta-enolase |
| P28062 | PSMB8 | Proteasome subunit beta type-8 |
| P67775 | PPP2CA | Serine/threonine-protein phosphatase 2A catalytic subunit alpha isoform |
| Q53G26 | DNAJA3 | DnaJ (Hsp40) homolog, subfamily A, member 3 variant |
| Q9UBI6 | GNG12 | Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-12 |
| Q8NHP8 | PLBD2 | Putative phospholipase B-like 2 |
| D6R9R5 | SAR1B | GTP-binding protein SAR1b |
| Q00169 | PITPNA | Phosphatidylinositol transfer protein alpha isoform |
| P63173 | RPL38 | 60S ribosomal protein L38 |
| Q5T6V5 | C9orf64 | UPF0553 protein C9orf64 |
| A4D2P2 | RAC1 | Ras-related C3 botulinum toxin substrate 1 |
potential relevance of SET in human adrenocor- tical tumors, we have analyzed some human tissues in a preliminary study, and found that
SET protein is undetectable in normal and ACA tissues, whereas it is expressed in ACC (Figure 3B).
A
ß-actin 40kDa
40kDa
SET
I
II
III
IV
C
SET/ß-actin
normalized to control
2.5
2.0
1.5
1.0
0.5
*
0.0
mitotane
9-cisRA
combined
Mean
Mean±0,95*SE
エ
Min-Max
* p<0.05
B
40kDa
40kDa
a
b
microRNA expression
From the four selected circulating miRNAs, hsa- miR-483-5p has been significantly underex- pressed in the combined group relative to control (P=0.028) (Figure 4). The expression of the other three tested circulating microRNAs was unchanged. However, we have not found significant changes in the expression of tis- sue hsa-miR-483-5p. From the four reference genes tested for tissue microRNAs, RNU44 and RNU6B turned out to be the best for normaliz- ing the results.
Discussion
Mitotane is the only available adrenal cortex specific agent in the therapy of adrenocortical cancer. Despite being used for more than 50 years, its precise mechanism of action is large- ly unknown [5]. The degeneration of mitochon- dria, free radicals, inhibition of steroid biosyn- thetic enzymes, lipid-mediated endoplasmic reticulum stress have all been suggested to take part in the action of mitotane [5, 21]. The narrow therapeutic range and frequent side
effects of mitotane constitute serious prob- lems in clinical practice. Based on our previous in vitro and pilot xenograft study [7], 9-cisRA appeared to be a promising agent in ACC treat- ment. To further dissect its actions and to com- pare it to mitotane, we have performed a large- scale xenograft study involving 9-cisRA, mito- tane and their combination. We have observed that these agents act together in a synergistic manner on tumor growth.
Contrary to the several human in vivo studies applying mitotane, there are only few studies on mitotane-treated xenograft models to date [22-27]. Since there was no uniformly defined dose of mitotane given to mice, we have cho- sen the average amount used in published studies. The results of these studies on the effectiveness of mitotane in animal models are also contradictory. Lindhe et al. described that mitotane has antitumoral effect given simulta- neously with the tumor cells inoculation [24], whereas Doghman et al. did not find any long- lasting effect in a similar study [25]. Here, we have observed the antitumoral activity of mito- tane.
Fold change
hsa-miR-483-5p
**
2
*
1.5
*
1
0.5
0
control
mitotane
9-cisRA Meant 0.95 Conf. Interval ** p<0.005
p<0.001
combined p<0.05
Mean
MeantSE
genes [7] whereas the effect of mitotane on gene expres- sion was more limited [10]. In contrast to these in vitro data and the observed changes in tumor size and Ki-67 levels, we could ob- serve only modest changes in gene expression in the present study. By omitt- ing the Benjamini-Hochberg False Discovery Rate, 483 genes were found to be sig- nificantly genes, and from the 7 selected genes only 2 (APOA4, PDEA4) was vali- dated to be significantly dif- ferentially expressed.
Retinoids, the natural and synthetic derivates of vitamin A play crucial roles in cell differentia- tion, growth, and death. The anti-proliferative and antitumoral effects [28] of 9-cisRA acting via the retinoid X receptor are well documented in many different types of tumors in vitro and in vivo e.g. gastric cell line [29], head and neck squamous cell line [30], neuroblastoma [31] and breast cancer [32].
The dose of 9-cis retinoic acid (5 mg/kg) was much less than the documented toxic dose [30] and it was comparable to other in vivo doses used in the literature [31, 33-35].
We have observed antitumoral effects of both 9-cisRA and mitotane when used alone, but sig- nificant reduction in tumor volume could only be achieved by groups receiving mitotane alone and the combination of mitotane and 9-cisRA. The Ki-67 index was the lowest in the group receiving the combined treatment. Despite mitotane was more effective than 9-cisRA as a single agent for reducing tumor size, the Ki-67 index was lower in the 9-cisRA-treated group than in the mitotane only group (Figure 1). The background for this phenomenon is unclear.
To decipher the molecular mechanisms behind the observed effects on tumor growth and pro- liferation, we have performed molecular analy- sis at mRNA and protein levels. In our previous in vitro studies on the adrenocortical cell line NCI-H295R, we have observed that 9-cisRA affected the expression of more than 2000
APOA4, a member of apolipoprotein family is a known 9-cisRA target gene that has important roles in fat and glucose metabolism [36], in antioxidant [37], and anti-atherogenic process- es [38], but it has been suggested also as a predictive factor in inflammatory bowel disease [39, 40], and as a novel serum biomarker in ovarian, cervical cancer, and acute lymphocytic leukemia [41-44]. There are no data, however, on the potential relevance of APOA4 in adreno- cortical tumors.
PDE4A, as a member of PDE (phosphodiester- ase) family, act as crucial cAMP level regulator [45], and it is involved in the basic cell path- ways and also takes part in cancer progression. Its inhibition has been associated with many antitumoral actions e.g. regression of brain tumors [46], reduced proliferation and angio- genesis in lung cancer [47], reduced motility and invasion in colon [48] and breast cancer cell line [49], decreased growth of malignant melanoma [50]. In line with these observa- tions, we have also observed reduced expres- sion of PDE4A in the combined treatment group, thus PDE4A might also be involved in ACC pathogenesis or progression.
We hypothesize that after the long treatment period of 28 days, mRNA expression does not really reflects the altered tumor behavior. We have therefore turned to the protein level, where we have found 47 significantly differen- tially expressed proteins by proteomics analy- sis. We have chosen the SET protein from the
9-cis retinoic acid and mitotane in adrenal cancer
significantly differentially expressed proteins for validation by Western-blot. As expected, SET expression was down-regulated by the treatments, showing the lowest expression in the combined treatment group.
Protein SET is an inhibitor of tumor suppressor PP2A (protein phosphatase 2A) that has wide- spread actions in the cellular functions imply- ing cell cycle [18], apoptosis [51] and cell migra- tion [19]. Due its target PP2A, it also influences ß-catenin [20], c-Myc [17] and Akt [16] path- ways, and via inhibition of nm23-H1 (NME/ NM23 nucleoside diphosphate kinase 1) it also promotes metastatic potential [52], and thus it is associated with tumor progression. SET over- expression is described in many tu- mors e.g. Wilm’s tumor [53], acute lymphoblas- tic leukaemia [54], chronic lymphocytic leuke- mia and non-Hodgkin lymphoma [55], lung [56], colon [57], pancreatic [58], prostate [59] and ovarian cancer [60], as well. To the best of our knowledge, our study is the first to raise the potential relevance of SET in ACC biology.
We have performed a preliminary evaluation of SET protein expression in human adrenocorti- cal tumor samples, as well. SET was weakly expressed in ACC, but absent from benign ade- nomas and normal adrenocortical samples. This finding that certainly awaits validation on a larger cohort appears to support our xenograft findings where SET expression was the highest in the untreated xenograft, and suppressed in the treated samples parallel to tumor shrink- age.
In addition to our mechanistic efforts aimed at deciphering the molecular way of action of 9-cisRA and mitotane in our xenograft model, we have also studied some circulating microR- NAs as potential markers for treatment efficacy monitoring based on our previous studies in humans. Circulating hsa-miR-483-5p appears to be the best circulating microRNA marker of adrenocortical malignancy [61-63]. From the four analyzed circulating microRNAs, only hsa- miR-483-5p expression was modulated by the treatments, and its expression was significantly suppressed by the combined 9-cisRA + mito- tane treatment. Circulating hsa-miR-483-5p thus appears to be a marker of treatment effi- cacy, and this could be relevant in the clinical setting, as well. Regarding the tissue expres- sion of hsa-miR-483-5p, however, no signifi-
cant differences have been observed. We can conclude that the circulating and tissue hsa- miR-483-5p alter independently. There are data that microRNAs can be changed parallel, contrary, or independently between the circula- tion and tissues [64, 65], but the molecular mechanisms underlying these discrepancies and the regulation of adrenocortical hsa-miR- 483-5p expression are largely unknown, yet.
In conclusion, 9-cisRA might represent an alter- native additive treatment option in ACC that seems to be most efficient when combined with mitotane. The tumor size, Ki-67, SET pro- tein, and circulating hsa-miR-483-5p were all lowest in the group receiving the combined treatment that suggest synergistic action of 9-cisRA and mitotane in our xenograft model. The molecular background of the observed syn- ergistic mitotane-9-cisRA action is, however, unclear. We have found only modest gene expression changes, and although the number of affected proteins is higher, their list is not extensive, either. The decrease of SET protein expression by the treatments might be note- worthy, as paralleled by its expression in human adrenocortical tumors. The potential applicabil- ity of circulating hsa-miR-483-5p for monitor- ing ACC treatment efficacy might be relevant in the clinical setting, as there is no reliable blood- based tumor marker of ACC at present. Cir- culating microRNA might be exploited for treat- ment monitoring in other diseases, as well.
Acknowledgements
This study has been supported by grants from the Hungarian National Research, Development and Innovation Office-NKFIH (grants K100295 and K115398) to Dr. Peter Igaz.
Disclosure of conflict of interest
None.
Address correspondence to: Dr. Peter Igaz, The 2nd Department of Medicine, Faculty of Medicine, Sem- melweis University, H-1088 Budapest, Szentkirályi Str. 46., Hungary. Tel: +36-1-4591500; Fax: +36- 1-2660816; E-mail: igaz.peter@med.semmelweis- univ.hu
References
[1] Fassnacht M, Kroiss M, Allolio B. Update in adrenocortical carcinoma. J Clin Endocrinol Metab 2013; 98: 4551-64.
9-cis retinoic acid and mitotane in adrenal cancer
[2] Else T, Kim AC, Sabolch A, Raymond VM, Kandathil A, Caoili EM, Jolly S, Miller BS, Giordano TJ, Hammer GD. Adrenocortical Car- cinoma. Endocr Rev 2014; 35: 282-326.
[3] Fassnacht M, Terzolo M, Allolio B, Baudin E, Haak H, Berruti A, Welin S, Schade-Brittinger C, Lacroix A, Jarzab B, Sorbye H, Torpy DJ, Stepan V, Schteingart DE, Arlt W, Kroiss M, Leboulleux S, Sperone P, Sundin A, Hermsen I, Hahner S, Willenberg HS, Tabarin A, Quinkler M, de la Fouchardière C, Schlumberger M, Mantero F, Weismann D, Beuschlein F, Gelderblom H, Wilmink H, Sender M, Edgerly M, Kenn W, Fojo T, Müller HH, Skogseid B. Combination chemo- therapy in advanced adrenocortical carcino- ma. N Engl J Med 2012; 366: 2189-97.
[4] Terzolo M, Angeli A, Fassnacht M, Daffara F, Tauchmanova L, Conton PA, Rossetto R, Buci L, Sperone P, Grossrubatscher E, Reimondo G, Bollito E, Papotti M, Saeger W, Hahner S, Koschker AC, Arvat E, Ambrosi B, Loli P, Lombardi G, Mannelli M, Bruzzi P, Mantero F, Allolio B, Dogliotti L, Berruti A. Adjuvant mito- tane treatment for adrenocortical carcinoma. N Engl J Med 2007; 356: 2372-80.
[5] Igaz P, Tombol Z, Szabo P, Liko I, Racz K. Steroid Biosynthesis Inhibitors in the Therapy of Hypercortisolism: Theory and Practice. Curr Med Chem 2008; 15: 2734-47.
[6] Szabó PM, Tamási V, Molnár V, Andrásfalvy M, Tömböl Z, Farkas R, Kövesdi K, Patócs A, Tóth M, Szalai C, Falus A, Rácz K, Igaz P. Meta- analysis of adrenocortical tumour genomics data: novel pathogenic pathways revealed. Oncogene 2010; 29: 3163-72.
[7] Szabó DR, Baghy K, Szabó PM, Zsippai A, Marczell I, Nagy Z, Varga V, Éder K, Tóth S, Buzás EI, Falus A, Kovalszky I, Patócs A, Rácz K, Igaz P. Antitumoral effects of 9-cis retinoic acid in adrenocortical cancer. Cell Mol Life Sci 2014; 71: 917-32.
[8] Doghman M, El Wakil A, Cardinaud B, Thomas E, Wang J, Zhao W, Peralta-Del Valle MH, Figueiredo BC, Zambetti GP, Lalli E. Regula- tion of insulin-like growth factor-mammalian target of rapamycin signaling by microRNA in childhood adrenocortical tumors. Cancer Res 2010; 70: 4666-75.
[9] Cheng WC, Chang CW, Chen CR, Tsai ML, Shu WY, Li CY, Hsu IC. Identification of reference genes across physiological states for qRT-PCR through microarray meta-analysis. PLoS One 2011; 6: e17347.
[10] Zsippai A, Szabó DR, Tömböl Z, Szabó PM, Éder K, Pállinger É, Gaillard RC, Patócs A, Tóth S, Falus A, Rácz K, Igaz P. Effects of mitotane on gene expression in the adrenocortical cell line NCI-H295R: a microarray study. Pharmaco- genomics 2012; 13: 1351-61.
[11] Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantita- tive PCR and the 2(-Delta Delta C(T)) Method. Methods 2001; 25: 402-8.
[12] Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O’Briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stire- walt DL, Gentleman R, Vessella RL, Nelson PS, Martin DB, Tewari M. Circulating microRNAs as stable blood-based markers for cancer detec- tion. Proc Natl Acad Sci U S A 2008; 105: 10513-8.
[13] Guan S, Price JC, Prusiner SB, Ghaemmaghami S, Burlingame AL. A Data Processing Pipeline for Mammalian Proteome Dynamics Studies Using Stable Isotope Metabolic Labeling. Mol Cell Proteomics 2011; 10: M111.010728- M111.010728.
[14] Tömböl Z, Szabó PM, Molnár V, Wiener Z, Tölgyesi G, Horányi J, Riesz P, Reismann P, Patócs A, Likó I, Gaillard RC, Falus A, Rácz K, Igaz P. Integrative molecular bioinformatics study of human adrenocortical tumors: mi- croRNA, tissue-specific target prediction, and pathway analysis. Endocr Relat Cancer 2009; 16: 895-906.
[15] Bradford MM. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 1976; 72: 248-54.
[16] Leopoldino AM, Squarize CH, Garcia CB, Almeida LO, Pestana CR, Polizello AC, Uyemura SA, Tajara EH, Gutkind JS, Curti C. Accumulation of the SET protein in HEK293T cells and mild oxidative stress: Cell survival or death signal- ing. Mol Cell Biochem 2012; 363: 65-74.
[17] Arnold HK, Sears RC. A tumor suppressor role for PP2A-B56alpha through negative regula- tion of c-Myc and other key oncoproteins. Cancer Metastasis Rev 2008; 27: 147-58.
[18] Canela N, Rodriguez-Vilarrupla A, Estanyol JM, Diaz C, Pujol MJ, Agell N, Bachs O. The SET pro- tein regulates G2/M transition by modulating cyclin B-cyclin-dependent kinase 1 activity. J Biol Chem 2003; 278: 1158-64.
[19] Ten Klooster JP, Leeuwen Iv, Scheres N, Anthony EC, Hordijk PL. Rac1-induced cell mi- gration requires membrane recruitment of the nuclear oncogene SET. EMBO J 2007; 26: 336- 45.
[20] Götz J, Probst A, Mistl C, Nitsch RM, Ehler E. Distinct role of protein phosphatase 2A sub- unit Ca in the regulation of E-cadherin and B-catenin during development. Mech Dev 2000; 93: 83-93.
[21] Sbiera S, Leich E, Liebisch G, Sbiera I, Schirbel A, Wiemer L, Matysik S, Eckhardt C, Gardill F, Gehl A, Kendi S, Weigand I, Bala M, Ronchi CL,
9-cis retinoic acid and mitotane in adrenal cancer
Deutschbein T, Schmitz G, Rosenwald A, Allolio B, Fassnacht M, Kroiss M. Mitotane inhibits Sterol-O-Acyl Transferase 1 triggering lipid- mediated endoplasmic reticulum stress and apoptosis in adrenocortical carcinoma cells. Endocrinology 2015; 156: 3895-908.
[22] Stacpoole PW, Varnado CE, Island DP. Stimu- lation of rat liver 3-hydroxy-3-methylglutaryl- coenzyme A reductase activity by o,p’-DDD. Biochem Pharmacol 1982; 31: 857-60.
[23] Barker EN, Campbell S, Tebb AJ, Neiger R, Herrtage ME, Reid SWJ, Ramsey IK. A compari- son of the survival times of dogs treated with mitotane or trilostane for pituitary-dependent hyperadrenocorticism. J Vet Intern Med 2005; 19: 810-5.
[24] Lindhe Ö, Skogseid B. Mitotane Effects in a H295R Xenograft Model of Adjuvant Treatment of Adrenocortical Cancer. Horm Metab Res 2010; 42: 725-30.
[25] Doghman M, Lalli E. Lack of long-lasting ef- fects of mitotane adjuvant therapy in a mouse xenograft model of adrenocortical carcinoma. Mol Cell Endocrinol 2013; 381: 66-9.
[26] Arenas C, Melián C, Pérez-Alenza MD. Long- term survival of dogs with adrenal-dependent hyperadrenocorticism: A comparison between mitotane and twice daily trilostane treatment. J Vet Intern Med 2014; 28: 473-80.
[27] Hantel C, Jung S, Mussack T, Reincke M, Beus- chlein F. Liposomal polychemotherapy im- proves adrenocortical carcinoma treatment in a preclinical rodent model. Endocr Relat Cancer 2014; 21: 383-94.
[28] Sun SY, Lotan R. Retinoids and their receptors in cancer development and chemoprevention. Crit Rev Oncol Hematol 2002; 41: 41-55.
[29] Liu Y, Zhu Z, Zhang SN, Mou J, Liu L, Cui T, Pei DS. Combinational effect of PPARy agonist and RXR agonist on the growth of SGC7901 gastric carcinoma cells in vitro. Tumour Biol 2013; 34: 2409-18.
[30] Shalinsky DR, Bischoff ED, Gregory ML, Gottardis MM, Hayes JS, Lamph WW, Heyman RA, Shirley MA, Cooke TA, Davies PJ. Retinoid- induced suppression of squamous cell differ- entiation in human oral squamous cell carci- noma xenografts (line 1483) in athymic nude mice. Cancer Res 1995; 55: 3183-91.
[31] Ponthan F, Kogner P, Bjellerup P, Klevenvall L, Hassan M. Bioavailability and dose-dependent anti-tumour effects of 9-cis retinoic acid on human neuroblastoma xenografts in rat. Br J Cancer 2001; 85: 2004-9.
[32] Maeng S, Kim GJ, Choi EJ, Yang HO, Lee DS, Sohn YC. 9-Cis-retinoic acid induces growth in- hibition in retinoid-sensitive breast cancer and sea urchin embryonic cells via retinoid X recep-
tor a and replication factor C3. Mol Endocrinol 2012; 26: 1821-35.
[33] McCormick DL, Rao KV, Steele VE, Lubet RA, Kelloff GJ, Bosland MC. Chemoprevention of rat prostate carcinogenesis by 9-cis-retinoic acid. Cancer Res 1999; 59: 521-4.
[34] Shalinsky DR, Bischoff ED, Gregory ML, Lamph WW, Heyman RA, Hayes JS, Thomazy V, Davies PJ. Enhanced antitumor efficacy of cisplatin in combination with ALRT1057 (9-cis retinoic acid) in human oral squamous carcinoma xe- nografts in nude mice. Clin Cancer Res 1996; 2: 511-20.
[35] Wu K, Kim H, Rodriquez JL, Munoz-medellin D, Mohsin SK, Hilsenbeck SG, Lamph WW, Gottardis MM, Shirley MA, Kuhn JG, Green JE, Brown PH. 9-cis-Retinoic Acid Suppress- es Mammary Tumorigenesis in C3(1)-Simian Virus 40 T Antigen-transgenic Mice 9-cis-Reti- noic Acid Suppresses Mammary Tumorigenesis in. Clin Cancer Res 2000; 3: 3696-704.
[36] Wang F, Kohan AB, Kindel TL, Corbin KL, Nunemaker CS, Obici S, Woods SC, Davidson WS, Tso P. Apolipoprotein A-IV improves glu- cose homeostasis by enhancing insulin secre- tion. Proc Natl Acad Sci U S A 2012; 109: 9641-6.
[37] Spaulding HL. Apolipoprotein A-IV attenuates oxidant-induced apoptosis in mitotic compe- tent, undifferentiated cells by modulating in- tracellular glutathione redox balance. AJP Cell Physiol 2005; 290: C95-103.
[38] Culnan DM, Cooney RN, Stanley B, Lynch CJ. Apolipoprotein A-IV, a putative satiety/antiath- erogenic factor, rises after gastric bypass. Obesity (Silver Spring) 2009; 17: 46-52.
[39] Broedl UC, Schachinger V, Lingenhel A, Lehrke M, Stark R, Seibold F, Goke B, Kronenberg F, Parhofer KG, Konrad-Zerna A. Apolipoprotein A-IV is an independent predictor of disease ac- tivity in patients with inflammatory bowel dis- ease. Inflamm Bowel Dis 2007; 13: 391-7.
[40] Orsó E, Moehle C, Boettcher A, Szakszon K, Werner T, Langmann T, Liebisch G, Buechler C, Ritter M, Kronenberg F, Dieplinger H, Bornstein SR, Stremmel W, Schmitz G. The satiety factor apolipoprotein A-IV modulates intestinal epi- thelial permeability through its interaction with a-catenin: Implications for inflammatory bowel diseases. Horm Metab Res 2007; 39: 601-11.
[41] Timms JF, Arslan-Low E, Kabir M, Worthington J, Camuzeaux S, Sinclair J, Szaub J, Afrough B, Podust VN, Fourkala EO, Cubizolles M, Kronen- berg F, Fung ET, Gentry-Maharaj A, Menon U, Jacobs I. Discovery of serum biomarkers of ovarian cancer using complementary pro- teomic profiling strategies. Proteomics Clin Appl 2014; 8: 982-93.
9-cis retinoic acid and mitotane in adrenal cancer
[42] Guo X, Hao Y, Kamilijiang M, Hasimu A, Yuan J, Wu G, Reyimu H, Kadeer N, Abudula A. Potential predictive plasma biomarkers for cervical cancer by 2D-DIGE proteomics and Ingenuity Pathway Analysis. Tumor Biol 2014; 36: 1711-20.
[43] ] Li L, Xu Y, Yu CX. Proteomic analysis of serum of women with elevated Ca-125 to differenti- ate malignant from benign ovarian tumors. Asian Pacific J Cancer Prev 2012; 13: 3265- 70.
[44] Braoudaki M, Lambrou GI, Vougas K, Kara- molegou K, Tsangaris GT, Tzortzatou-Statho- poulou F. Protein biomarkers distinguish be- tween high- and low-risk pediatric acute lym- phoblastic leukemia in a tissue specific man- ner. J Hematol Oncol 2013; 6: 52.
[45] Conti M, Richter W, Mehats C, Livera G, Park JY, Jin C. Cyclic AMP-specific PDE4 phosphodi- esterases as critical components of cyclic AMP signaling. J Biol Chem 2003; 278: 5493-6.
[46] Goldhoff P, Warrington NM, Limbrick DD, Hope A, Woerner BM, Jackson E, Perry A, Piwnica- Worms D, Rubin JB. Targeted inhibition of cy- clic AMP phosphodiesterase-4 promotes brain tumor regression. Clin Cancer Res 2008; 14: 7717-25.
[47] Pullamsetti SS, Banat GA, Schmall A, Szibor M, Pomagruk D, Hänze J, Kolosionek E, Wilhelm J, Braun T, Grimminger F, Seeger W, Schermuly RT, Savai R. Phosphodiesterase-4 promotes proliferation and angiogenesis of lung cancer by crosstalk with HIF. Oncogene 2013; 32: 1121-34.
[48] Murata K, Sudo T, Kameyama M, Fukuoka H, Mukai M, Doki Y, Sasaki Y, Ishikawa O, Kimura Y, Imaoka S. No Title. Clin Exp Metastasis 2000; 18: 599-604.
[49] Dong H, Claffey KP, Brocke S, Epstein PM. Inhibition of breast cancer cell migration by ac- tivation of cAMP signaling. Breast Cancer Res Treat 2015; 152: 17-28.
[50] Narita M, Murata T, Shimizu K, Nakagawa T, Sugiyama T, Inui M, Hiramoto K, Tagawa T. A role for cyclic nucleotide phosphodiesterase 4 in regulation of the growth of human malignant melanoma cells. Oncol Rep 2007; 17: 1133-9.
[51] Madeira A, Pommet JM, Prochiantz A, Allin- quant B. SET protein (TAF1beta, I2PP2A) is in- volved in neuronal apoptosis induced by an amyloid precursor protein cytoplasmic subdo- main. FASEB J 2005; 19: 1905-7.
[52] Fan Z, Beresford PJ, Oh DY, Zhang D, Lieberman J. Tumor suppressor NM23-H1 is a granzyme A-activated DNase during CTL-mediated apop- tosis, and the nucleosome assembly protein set is its inhibitor. Cell 2003; 112: 659-72.
[53] Carlson SG, Eng E, Kim EG, Perlman EJ, Copeland TD, Ballermann BJ. Expression of
SET, an inhibitor of protein phosphatase 2A, in renal development and Wilms’ tumor. J Am Soc Nephrol 1998; 9: 1873-80.
[54] Sirma Ekmekci S, G Ekmekci C, Kandilci A, Gulec C, Akbiyik M, Emrence Z, Abaci N, Kara- kas Z, Agaoglu L, Unuvar A, Anak S, Devecioglu O, Ustek D, Grosveld G, Ozbek U. SET onco- gene is upregulated in pediatric acute lympho- blastic leukemia. Tumori 2012; 98: 252-6.
[55] Christensen DJ, Chen Y, Oddo J, Matta KM, Neil J, Davis ED, Volkheimer AD, Lanasa MC, Fried- man DR, Goodman BK, Gockerman JP, Diehl LF, de Castro CM, Moore JO, Vitek MP, Weinberg JB. SET oncoprotein overexpression in B-cell chronic lymphocytic leukemia and non-Hodg- kin lymphoma: a predictor of aggressive dis- ease and a new treatment target. Blood 2011; 118: 4150-8.
[56] Liu H, Gu Y, Yin J, Zheng G, Wang C, Zhang Z, Deng M, Liu J, Jia X, He Z. SET-mediated NDRG1 inhibition is involved in acquisition of epithelial-to-mesenchymal transition pheno- type and cisplatin resistance in human lung cancer cell. Cell Signal 2014; 26: 2710-20.
[57] Jiang Q, Zhang C, Zhu J, Chen Q, Chen Y. The set gene is a potential oncogene in human colorectal adenocarcinoma and oral squa- mous cell carcinoma. Mol Med Rep 2011; 4: 993-9.
[58] Bhutia YD, Hung SW, Krentz M, Patel D, Lovin D, Manoharan R, Thomson JM, Govindarajan R. Differential processing of let-7a precursors influences RRM2 expression and chemosensi- tivity in pancreatic cancer: role of LIN-28 and SET oncoprotein. PLoS One 2013; 8: e53436.
[59] Anazawa Y, Nakagawa H, Furihara M, Ashida S, Tamura K, Yoshioka H, Shuin T, Fujioka T, Katagiri T, Nakamura Y. PCOTH, a Novel Gene Overexpressed in Prostate Cancers, Promotes Prostate Cancer Cell Growth through Phospho- rylation of Oncoprotein TAF-IB/SET. Cancer Res 2005; 65: 4578-86.
[60] Ouellet V, Page CL, Guyot MC, Lussier C, Tonin PN, Provencher DM, Mes-Masson AM. SET complex in serous epithelial ovarian cancer. Int J Cancer 2006; 119: 2119-26.
[61] Patel D, Boufragech M, Jain M, Zhang L, He M, Gesuwan K, Gulati N, Nilubol N, Fojo T, Kebebew E. MiR-34a and miR-483-5p are can- didate serum biomarkers for adrenocortical tumors. Surgery 2013; 154: 1224-8.
[62] Chabre O, Libe R, Assie G, Barreau O, Bertherat J, Bertagna X, Feige JJ, Cherradi N. Serum miR- 483-5p and miR-195 are predictive of recur- rence risk in adrenocortical cancer patients. Endocr Relat Cancer 2013; 20: 579-94.
[63] Szabó DR, Luconi M, Szabó PM, Tóth M, Szücs N, Horányi J, Nagy Z, Mannelli M, Patócs A, Rácz K, Igaz P. Analysis of circulating microR-
9-cis retinoic acid and mitotane in adrenal cancer
NAS in adrenocortical tumors. Lab Investig 2014; 94: 331-9.
[64]
Waters PS, McDermott AM, Wall D, Heneghan HM, Miller N, Newell J, Kerin MJ, Dwyer RM. Relationship between Circulating and Tissue microRNAs in a Murine Model of Breast Cancer. PLoS One 2012; 7: 1-8.
[65] Wang J, Zhang KY, Liu SM, Sen S. Tumor- Associated circulating micrornas as biomark- ers of cancer. Molecules 2014; 19: 1912-38.