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Reprogramming Cells for Synergistic Combination Therapy with Nanotherapeutics against Uveal Melanoma

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Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and around half of the patients develop metastasis and die shortly after because of the lack of effective therapies for metastatic UM. Consequently, new therapeutic approaches to this disease are welcome. In this regard, microRNAs have been shown to have a key role in neoplasia progression and have the potential to be used as therapeutic tools. In addition, in different cancers including UM, a particular microRNA signature appears that is different from healthy cells. Thus, restoring the regular levels of microRNAs could restore the normal behavior of cells. In this study, four microRNAs downregulated in UM have been chosen to reprogram cancer cells, to promote cell death or increase their sensitivity to the chemotherapeutic SN38. Furthermore, to improve the internalization, stability and/or solubility of the therapeutic molecules employed in this approach, gold nanoparticles (AuNPs) were used as carriers. Remarkably, this study found a synergistic effect when the four oligonucleotides were employed and when the chemotherapeutic drug was added.
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biomimetics
Article
Reprogramming Cells for Synergistic Combination
Therapy with Nanotherapeutics against
Uveal Melanoma
Paula Milán Rois, Alfonso Latorre, Ciro Rodriguez Diaz , Álvaro del Moral and Álvaro Somoza *
Instituto Madrileño de Estudios Avanzados en Nanociencia (IMDEA Nanociencia), Centro Nacional de
Biotecnología (CNB-CSIC) Associated Unit, Faraday 9, 28049 Madrid, Spain; paula.milan@imdea.org (P.M.R.);
alfonso.latorre@imdea.org (A.L.); ciro.rodriguez@imdea.org (C.R.D.); delmoilex@gmail.com (Á.d.M.)
*Correspondence: alvaro.somoza@imdea.org; Tel.: +34-912-998-856
Received: 6 July 2018; Accepted: 28 July 2018; Published: 25 September 2018


Abstract:
Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults
and around half of the patients develop metastasis and die shortly after because of the lack of effective
therapies for metastatic UM. Consequently, new therapeutic approaches to this disease are welcome.
In this regard, microRNAs have been shown to have a key role in neoplasia progression and have the
potential to be used as therapeutic tools. In addition, in different cancers including UM, a particular
microRNA signature appears that is different from healthy cells. Thus, restoring the regular levels of
microRNAs could restore the normal behavior of cells. In this study, four microRNAs downregulated
in UM have been chosen to reprogram cancer cells, to promote cell death or increase their sensitivity to
the chemotherapeutic SN38. Furthermore, to improve the internalization, stability and/or solubility
of the therapeutic molecules employed in this approach, gold nanoparticles (AuNPs) were used
as carriers. Remarkably, this study found a synergistic effect when the four oligonucleotides were
employed and when the chemotherapeutic drug was added.
Keywords: uveal melanoma; microRNAs; SN38; gold nanoparticles; combination therapy
1. Introduction
Uveal melanoma (UM) is a malignant intraocular tumor with a high metastatic risk [
1
].
Unfortunately, the treatments for the metastatic UM are not effective [
2
] due to the unique
characteristics of this tumor and because the visible clinical features only emerge at later stages
of the disease [
3
,
4
]. Drugs developed for other tumors, such as Irinotecan [
5
,
6
], which is used for
colon and lung tumors, have been used for UM. Furthermore, several chemotherapeutics agents are in
clinical trials to treat UM, such as Selumetinib or AZD 8055. While these agents are selective against
the mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) pathways,
respectively; they are not very selective and as a result, healthy cells are also affected.
Therefore, novel approaches to tackle this disease are desirable. In this sense, non-coding genetic
elements, such as microRNAs, endogenous small interference RNAs (endo-siRNAs), long non-coding
RNAs (lncRNAs), PIWI-associated small RNAs (piRNAs) and small nucleolar RNAs (snoRNAs),
are being explored as new therapeutic targets since they play a major role in cellular events such as
cell proliferation, differentiation, apoptosis or invasiveness capacity [
7
13
]. Interestingly, treatments
based on these molecules are expected to achieve excellent selectivity and reduce side effects as
compared to traditional treatments, because of the complementary sequence interactions involved in
those approaches.
Among the most studied nucleic acids are microRNAs, which besides their therapeutic potential,
can also be used to detect diseases as each tumor presents a unique microRNA profile depending on
Biomimetics 2018,3, 28; doi:10.3390/biomimetics3040028 www.mdpi.com/journal/biomimetics
Biomimetics 2018,3, 28 2 of 18
the tissue and cancer stage [
14
]. Additionally, several studies use their particular signature to classify
the different diseases and use this information to apply the most suitable treatment [8,15].
MicroRNAs are transcribed initially as primary precursors (pri-microRNAs) from intron coding
genes or intergenic regions, which are cleaved by the Drosha complex to produce the precursor hairpin
molecule (pre-microRNA). These structures are transported by exportin-5 from the nucleus to the
cytoplasm, where the Dicer complex processes pre-microRNAs into the mature microRNAs. Finally,
the mature microRNAs guide the RNA-induced silencing complex (RISC) to their corresponding target
messenger RNAs (mRNAs), promoting transcript reduction and/or inhibition [16].
MicroRNAs are dysregulated in many diseases such as Alzheimer’s, cardiac damage, and
cancer [
17
22
]. Particularly in cancers such as sarcoma, glioblastoma, pancreatic cancer, breast
and colon cancer, oncogenic microRNAs (e.g., microRNA-20a, microRNA-9, microRNA-21) are
overexpressed [
23
] and/or tumor suppressors microRNAs (e.g., microRNA-145, microRNA-204)
are downregulated [24].
In the present study, microRNA-34a, microRNA-182, microRNA-137 and microRNA-144 have
been selected since they are downregulated in UM and other cancers [
25
]. In particular, they are
used in combination as this could provide better results, when compared to the use of individual
microRNAs [
26
]. Regarding their roles, microRNA-34a is a proapoptotic transcriptional target
of the p53 tumor-suppressor gene effector network. Its primary target is the c-Met mRNA [
27
],
which is a tyrosine-kinase receptor implicated in the pathways of son of sevenless homolog (SOS),
phosphatidylinositol 3-kinase (PI3K), and the Ras protein family [
28
]. Moreover, overexpression
of microRNA-34a can downregulate the Akt protein and cell cycle-related proteins, reducing the
metastatic and proliferation potential of the cells [27].
MicroRNA-182 participates in the tumor suppression network of p53 in UM, where melanogenesis
associated transcription factor (MITF), B-cell lymphoma 2 (BCL2) and cyclin D2 are its main
targets. MITF is a master regulator of melanoma oncogenes that mediates the inhibition of Akt and
extracellular signal-regulated kinases ERK1/2 pathways, in addition to controlling c-Met. Furthermore,
microRNA-182 controls the forkhead box protein O1 (FoxO1), which is related to osteogenesis, T-cell
development and tumorigenesis [29].
MicroRNA-137 has three major targets: MITF, and the cyclin-dependent kinases CDK2 and CDK6.
It is a potent suppressor of the p160 steroid receptor co-activator (SRC) family of transcriptional
co-activators, which can inhibit SRC-mediated, steroid receptor-dependent and -independent
transcription [30]. Other studies identified C-terminal binding protein 1 (CTBP1) as a microRNA-137
target. By regulating CTBP1 through microRNA-137, it is possible to avoid E-cadherin suppression [
31
].
MicroRNA-144 acts as a tumor suppressor in UM, inhibiting cell proliferation and migration.
As with the previously mentioned microRNAs, c-Met is one of its potential targets [32].
To restore the normal levels of microRNAs in tumoral cells, vectors encoding those microRNAs
or whole microRNAs can be added to cells. However, modified nucleic acids that mimic the role of
the microRNAs (microRNAs mimics) are usually employed at the preclinical and clinical level [
26
,
33
],
such as small interference RNAs (siRNAs), which must be modified to increase their stability in serum
and achieve the required activity [
34
]. A related strategy employs the use of antisense technologies,
which are made of deoxyribonucleotides. Such DNA-based microRNA mimics are more stable and
cheaper than their RNA counterparts, and despite their lower activity, they can be used in combination
with chemotherapeutic agents with remarkable results [
35
,
36
]. Despite the enormous potential of
oligonucleotides as therapeutics, they present some disadvantages, mainly when based on RNA,
as outlined below.
1.
Low stability. They can be degraded by blood circulating enzymes [
37
], reducing their therapeutic
activity [17].
2. Poor cell internalization. Their negative charge prevents passive endocytosis [17].
3.
Poor cellular selectivity. The oligonucleotides cannot discriminate between healthy and cancer
cells, leading to a non-specific delivery [37].
Biomimetics 2018,3, 28 3 of 18
To overcome these problems, delivery systems such as micelles, liposomes, dendrimers, inorganic
particles, nanotubes and carbon nanoparticles, nanoemulsions, viral nanocarriers, polymeric or peptide
nanoparticles and solid lipid nanoparticles are being evaluated [3846].
Among the different systems, gold nanoparticles (AuNPs) are excellent nanomaterials for this
purpose, since they are easy to prepare and modify and are considered non-toxic when properly
modified. In particular, when functionalized with oligonucleotides these structures do not affect
the gene expression or viability of cells. In this case, when the AuNPs are densely modified with
oligonucleotides, they are known as spherical nucleic acids (SNAs), which, among other properties,
can translocate easily in a wide variety of cell lines [4749].
Despite the great therapeutic potential of oligonucleotides, chemotherapy-based treatments are
usually employed to treat cancers. Unfortunately, the associated lack of selectivity, drug resistance,
and high toxicity make this approach far from ideal and limits its use [
50
]. Indeed, monotherapy has
been proven ineffective for cancer treatment due to the development of resistance and metastasis. For
this reason, combination therapies are the preferred choice, since it is possible to reduce the amount
of the most toxic agent [
51
] and reduce relapse. In this sense, the combination of microRNAs and
chemotherapeutic drugs has provided excellent results in different type of cancers, such as human
glioma [26].
In this study, we have used SN38 (7-ethyl-10-hidroxycamptothecin), a topoisomerase I
inhibitor [
52
] in combination with oligonucleotides, which are designed to mimic the role of the
above-mentioned microRNAs. SN38 has not been tested in UM, although there are reports on
Irinotecan, its prodrug, which presents 200–2000-fold less activity [
53
]. The principal drawback of SN38
is its poor aqueous solubility (<5
µ
g/mL), which prevents systemic administration [
54
]. To overcome
this limitation, drug delivery systems based on liposomes have been reported [
53
]. In this regard,
we envision that the conjugation of therapeutic oligonucleotides and SN38 on AuNPs can overcome
the inherent limitations of these molecules and provide a more effective therapy.
2. Materials and Methods
2.1. Materials
Solvents and chemical reagents were purchased from Sigma-Aldrich (San Luis, MO, USA),
abcr GmbH (Karlsruhe, Germany), Thermo Fisher Scientific (Waltham, MA, USA), Scharlab (Sentmenat,
Barcelona, Spain), FluoroChem (Hadfield, UK) and VWR (Radnor, PA, USA).
Oligonucleotides were purchased from Integrated DNA Technologies (IDT, Coralville, IA, USA).
Roswell Park Memorial Institute (RPMI) medium, streptomycin–penicillin (100X), fetal bovine
serum (FBS), L-glutamine (100X), trypsin (10X), phosphate-buffered saline (PBS) and cell culture
plasticware were purchased from VWR. Thiazolyl blue tetrazolium bromide, propidium iodide (PI),
Hoechst 33342 and dimethyl sulfoxide (DMSO) were obtained from Sigma-Aldrich; and Lipofectamine
2000, RNase H and Opti-MEM from Thermo Fisher Scientific. c-Met and anti-rabbit IgG Alexa Fluor
488 antibodies were purchased from Cell Signaling Technology (Danvers, MA, USA).
2.2. Modified Oligonucleotides
The sequences of the oligonucleotides employed are described in Table 1. siRNA duplexes were
obtained after the annealing of complementary sequences using an annealing buffer described in
Section 2.3.1. The aptamer AS1411 was prepared as previously reported in a Mermade 4 DNA
synthesizer [47].
Biomimetics 2018,3, 28 4 of 18
Table 1. Oligonucleotides (DNA and RNA) used in this study.
Entry Oligonucleotides Sequence
1 DNA-34a 50-TGGCAGTGTCTTAGCTGGTTGTTAAAAA-30
2 DNA-182 50-TTTGGCAATGGTAGAACTCACACTAAAAA-30
3 DNA-137 50-TTATTGCTTAAGAATACGCGTAGAAAAA-30
4 DNA-144 50-GGATATCATCATATACTGTAAGAAAAA-30
5 DNA-34a 50-TGGCAGTGTCTTAGCTGGTTGTTAAAAA–Thiol-30
6 DNA-182 50-TTTGGCAATGGTAGAACTCACACTAAAAA–Thiol-30
7 DNA-137 50-TTATTGCTTAAGAATACGCGTAGAAAAA–Thiol-30
8 DNA-144 50-GGATATCATCATATACTGTAAGAAAAA–Thiol-30
9 RNA-34a pass 50-Thiol–AAAAAArCrArArCrCrArGrCrUrArArGrArCrArCrUrGrCrCrU-30
10 RNA-34a guide 50-rUrGrGrCrArGrUrGrUrCrUrUrArGrCrUrGrGrUrUrGrU-30
11 RNA-182 pass
5
0
-Thiol–AAAAAArGrUrGrUrGrArGrUrUrCrUrArCrCrArUrUrGrCrCrArArA-3
0
12 RNA-182 guide 50-rUrUrUrGrGrCrArArUrGrGrUrArGrArArCrUrCrArCrArCrU-30
13 RNA-137 pass 50-Thiol–AAAAACUACGCGUAUUCUUAAGCAAUAA-30
14 RNA-137 guide 50-rUrUrArUrUrGrCrUrUrArArGrArArUrArCrGrCrGrUrArG-30
15 RNA-144 pass 50-Thiol–AAAAArCrUrUrArCrArGrUrArUrArUrGrArUrGrArUrArUrCrC-30
16 RNA-144 guide 50-rGrGrArUrArUrCrArUrCrArUrArUrArCrUrGrUrArArG-30
17 AS1411 [47] 50-GGTGGTGGTGGTTGTGGTGGTGGTGGTTTTTT–Dithiolane-30
2.3. Oligonucleotide Solution Preparation
2.3.1. RNA Annealing (siRNAs)
siRNA duplexes were obtained by mixing the guide and the passenger oligonucleotides in
an annealing buffer. The annealing buffer was prepared following the Sigma-Aldrich protocol for
annealing oligonucleotides [55].
siRNA-34a was obtained from oligonucleotides 9 and 10; siRNA-182 was obtained from 11 and
12; siRNA-137 was obtained from 13 and 14 and siRNA-144 was obtained from 15 and 16 (Table 1).
2.3.2. siRNA Mix
A sample containing the four siRNAs previously prepared was obtained by mixing equimolar
quantities of each siRNA.
2.3.3. DNA Mix
DNA mix-1 (34.04
µ
M, final concentration) was obtained from equimolar amounts of
oligonucleotides 1, 2, 3 and 4 (Table 1) in water. This mixture contains unmodified oligonucleotides.
DNA mix-2 (20
µ
M, final concentration) was obtained from equimolar amounts of
oligonucleotides 5, 6, 7 and 8 (Table 1) in water. This mixture contained thiol-modified oligonucleotides
and was used for the functionalization of AuNPs.
2.4. Gold Nanoparticles Synthesis and Characterization
The gold nanoparticles were prepared following standard reported procedures [
56
]. The AuNPs
concentration was calculated using the Beer–Lambert law [
57
] from the absorbance recorded at 520
nm and the extinction coefficient of 2.7 ×108for 13 nm nanoparticles [58].
Particle size and shape were examined by transmission electron microscopy (TEM) in a JEOL JEM
1010 (JOEL, Akhisima, Japan), operating at 100 kV. Samples were prepared by placing one drop of a
dilute suspension onto a carbon-coated copper grid and drying the drop with paper after 2 min. The
size distributions were determined through manual analysis of ensembles of over 200 particles found
in randomly selected areas of the enlarged micrographs, with Image J software [
59
] to obtain the mean
size and standard deviation (Supplementary Figure S1).
Gold Nanoparticle Functionalization
The bare nanoparticles were modified with the different components using the conditions
summarized in Table 2. The oligonucleotides (DNA mix 2 and siRNA mix) were previously treated
for 1 h with tris(2-carboxyethyl) phosphine hydrochloride (TCEP), to remove the protecting groups
Biomimetics 2018,3, 28 5 of 18
on the thiol moieties. After the addition of each reagent, the solution was incubated for 30 min. The
procedure was done as follows: The reagents were added to 1 mL of a solution of AuNPs (10 nM) in
the order and quantities detailed in Table 2. The last step involves the addition of NaCl (70
µ
L, 5 M)
and incubation with agitation at room temperature overnight. The particles were centrifuged down
(300
×
g) at 4
C, the supernatant removed and resuspended in water. The process was repeated three
times to remove the unbound material [60].
Table 2. Modification of gold nanoparticles (AuNPs).
Nanoparticle Reagents Used in the Preparation
AuNP DNA mix 500 µL DNA mix 2
AuNP siRNA mix 500 µL siRNA mix
AuNP SN38 4.06 µL AS1411 (492 µM) + 5 µL SN38 (2 mM in DMSO)
The amount of oligonucleotide on the nanoparticle was determined as follows: after purification
of the nanoparticle the supernatants were dried in an Eppendorf Concentrator plus (V-AQ mode)
(Eppendorf, Hamburg, Germany) for 5 h; then the sample was diluted in water (1 mL) and the
concentration of oligonucleotides quantified by absorbance at 260 nm in a plate reader Synergy
H4 Hybrid reader (BioTEK, Winooski, VT, USA). This amount was subtracted from the amount
added. Concentrations of AuNP–DNA mix and AuNP siRNA mix were 3.9 and 3.28
µ
M, respectively.
The quantification of SN38 on the nanoparticle was carried out in the same way as above, but the
absorbance was recorded at 380 nm, resulting in a concentration of 10 µM.
The hydrodynamic size, by dynamic light scattering (DLS), and zeta-potential of the AuNPs was
measured on a Zeta Sizer Nano-ZS (Malvern Instruments, Worcestershire, UK). The studies were
performed in 12 runs, in a standard cuvette at 25
C. The AuNPs were diluted in 1 mL water (pH 5.8) to
a final concentration of 1 nM. The AuNP’s refraction index for a spherical particle was 1.330. The data
presented is the average distribution of these measurements as a function of the number of particles
expressed as a percentage.
2.5. Cell Culture and Viability Studies
Mel 202 cells were cultured (Mel202 were donated by Susana Ortiz-Urda at the University of
California, San Francisco, CA, USA) in RPMI medium with 10% FBS, 1% streptomycin–penicillin and
1% L-glutamine at 37
C in a Binder CB210 incubator (5% CO
2
). All the procedures were performed
inside a laminar flow hood Telstar CV-30/70 (Telstar, Terrassa, Spain). Cells were grown in 24-well
plates (30,000 cells/well).
The experiments were done when cells reached 60% confluency.
2.5.1. alamarBlue Viability Assay
A stock solution of resazurin sodium salt (Sigma-Aldrich, St. Louis, MO, USA) (1 mg/mL) in PBS
was diluted 1% (v/v) in complete RPMI medium and added to the cells. After 3 h in the incubator
(37
C), the fluorescence was measured at 25
C in a plate reader Synergy H4 Hybrid reader (BioTEK),
λex = 550 nm, λem = 590 nm.
The fluorescent intensity measurements were processed using the following Equation:
% Cell viability = ((Sample data Negative control)/(Positive control Negative control)) ×100
The positive control corresponds with untreated cells. A resazurin solution without cells was
used as negative control.
Biomimetics 2018,3, 28 6 of 18
2.5.2. Oligonucleotide Transfection
A total of 50
µ
L Opti-MEM was mixed with oligonucleotides (14, 15, 16, 17) or DNA mix 1.
Next, it was mixed with 1
µ
L lipofectamine 2000 in 50
µ
L Opti-MEM. The final mixture was incubated
for 20 min and then 100
µ
L of the final mixture was added to cells. The final concentration of 14, 15,
16, 17 or DNA mix 1 was 140 nM. After 24 h, the cells were washed three times with PBS and RPMI
medium was added.
2.5.3. Chemotherapy
SN38 stock solution was prepared at 100
µ
M in DMSO. Then different concentrations of SN38 (100,
50, and 25 nM) were prepared in RPMI medium. It was incubated for 24 h with the cells, then washed
three times with PBS and RPMI medium was added. After an additional 24 h, the viability assay was
carried out as described in Section 2.5.1.
2.5.4. Combination Treatment
In this case, the oligonucleotides were transfected, as indicated in Section 2.5.2. After 24 h the
cells were washed three times with PBS. Then SN38 (25 nM/well) was added and incubated for an
additional 24 h. Then, the cells were washed with PBS and RPMI medium was added. The cell viability
was evaluated after their incubation for an additional 24 h.
2.5.5. Nanoparticles Treatment
A volume of 100
µ
L functionalized AuNPs were added in Opti-MEM (500
µ
L, total volume).
The cells were incubated for 24 h, washed with PBS and RPMI medium was added. Twenty-four hours
later, the viability was assessed, as described in Section 2.5.1.
2.6. c-Met Immunofluorescence
Cells were treated with the oligonucleotides as described in Section 2.5.2 and an
immunofluorescence staining was performed as reported elsewhere [
59
] using an anti-c-Met antibody
(Ab 1003, Cellular Signaling Technology, Danvers, MA, USA) (1:200) as a primary antibody and a
goat anti-rabbit IgG Alexa 488 (1:200) as a secondary antibody. The nucleus was stained with Hoechst
33342 and fluorescence was examined using a Leica DMI3000 M inverted microscope (Leica, Wetzlar,
Germany) at 274.29 exposure units. Images were collected and analyzed using a customized script for
Fiji [61].
2.7. Flow Cytometry
Cells were harvested in 6-well plates at a 60% confluency and the treatment was carried out
as described above. Then, the samples were trypsinized, fixed with paraformaldehyde 1% (v/v),
washed with PBS and centrifuged at 177
×
gfor 5 min in an Eppendorf centrifuge 5804 R (Eppendorf,
Hamburg, Germany). Each sample was treated with 10
µ
g RNAsa A and 20
µ
g PI. Cell cycle analysis
was performed in a Beckman Coulter Cytomics 500 Flow Cytometer (Beckman Coulter, Indianapolis,
IN, USA) using 20,000 cells. The acquired data was analyzed with Multicycle software (Perttu Terho,
Turku Centre for Biotechnology, Turku, Finland).
These experiments were performed in the Flow Cytometry Service at the CNB-CSIC.
2.8. Synthesis of Modified SN38
All reactions (Scheme 1) were monitored by thin-layer chromatography (TLC), which was
performed on sheets of silica gel 60 F254 (Sigma-Aldrich). The products were purified by flash
column chromatography using silica gel (60 Å, 230
×
400 mesh). Nuclear magnetic resonance (NMR)
spectra were recorded on a Bruker Instrument (Bruker, Mannheim, Germany) and reported in MHz
Biomimetics 2018,3, 28 7 of 18
as solutions in CDCl
3
, the chemical shifts are reported in parts per million (ppm), and the coupling
constants are reported in Hz.
Biomimetics 2018, 3, x FOR PEER REVIEW 7 of 18
All reactions (Scheme 1) were monitored by thin-layer chromatography (TLC), which was
performed on sheets of silica gel 60 F254 (Sigma-Aldrich). The products were purified by flash
column chromatography using silica gel (60 Å, 230 × 400 mesh). Nuclear magnetic resonance (NMR)
spectra were recorded on a Bruker Instrument (Bruker, Mannheim, Germany) and reported in MHz
as solutions in CDCl3, the chemical shifts are reported in parts per million (ppm), and the coupling
constants are reported in Hz.
Scheme 1. Synthesis of the modified SN38 (2) with the linker for the conjugation with AuNPs. Lipoic
acid was activated (1) and incubated with SN38 to yield the desired product (2). DCC: N,N’-
dicyclohexylcarbodimide; DIPEA: N,N-diisopropylethylamine; DMAP: 4-Dimethylaminopyridine;
DMF: Dimethylformamide; NHS: N-hydroxysuccinimide; RT: Room temperature; THF:
Tetrahydrofuran.
2.8.1. α-Lipoic Acid–NHS (1)
Lipoic acid (1 g, 1 equiv) and N-hydroxysuccinimide (NHS) (667 mg, 1.2 equiv) were dissolved
in tetrahydrofuran (THF) (20.8 mL), and the solution was stirred at 0 °C for 10 min. A solution of
N,N’-dicyclohexylcarbodimide (DCC) (1.2 g, 1.2 equiv) in THF (1.7 mL) was added slowly to the
lipoic acid and NHS solution. The reaction was stirred at room temperature for 5 h. The mixture was
filtered, and the solution was kept in the freezer overnight, it was filtered again and the solvent was
eliminated in vacuum. The compound 1 (Scheme 1) was obtained as yellow oil (1.43 g, 99% yield)
[62]. 1H NMR (400 MHz, CDCl3): δ = 3.60–3.50 (m, 4H), 3.20–3.06 (m, 1H), 2.81 (s, 4H), 2.61 (t, J = 7.4
Hz, 2H), 2.50–2.36 (m, 1H), 1.94–1.88 (m, 1H), 1.82–1.72 (m, 2H), 1.72–1.66 (m, 2H), 1.62–1.46 (m, 2H)
(Supplementary Figure S2). 13C NMR (101 MHz, CDCl3): δ = 169.13, 168.42, 67.42, 40.15, 38.52, 34.42,
33.21, 30.79, 25.59, 22.59, 24.36, 23.39.
2.8.2. α-Lipoic Acid–SN38 (2)
Compound 1 (56 mg, 2 equiv), SN38 (36 mg, 1 equiv) and 4-dimethylaminopyridine (DMAP) (3
mg) were dissolved in dimethylformamide (DMF) (3.7 mL), then N,N-diisopropylethylamine
(DIPEA) was added to the solution. The reaction was stirred at 50 °C for 18 h. The solvent was
eliminated in vacuum and the crude was purified by flash chromatography (CH2Cl2
CH2Cl2/MeOH 40:1) to obtain the compound 2 (Scheme 1) as white-yellow solid (21 mg, 40% yield).
1H-NMR (400 MHz, CDCl3): δ = 8.24 (d, J = 9.2 Hz, 1H), 7.83 (d, J = 2.5 Hz, 1H), 7.65 (s, 1H), 7.55 (dd,
J = 9.2, 2.5 Hz, 1H), 5.76 (d, J = 16.3 Hz, 1H), 5.35–5.29 (m, 1H), 5.26 (s, 2H), 3.68–3.59 (m, 1H), 3.25–
3.10 (m, 4H), 2.69 (t, J = 7.4 Hz, 2H), 2.55–2.46 (m, 1H), 2.00–1.93 (m, 1H), 1.90–1.83 (m, 3H), 1.83–1.76
(m, 2H), 1.70–1.59 (m, 3H), 1.40 (t, J = 7.7 Hz, 3H), 1.04 (t, J = 7.4 Hz, 3H) (Supplementary Figure S3).
13C-NMR (101 MHz, CDCl3): δ = 173.95, 171.85, 157.67, 151.94, 150.18, 149.64, 147.49, 146.95, 145.27,
132.13, 127.48, 127.27, 125.41, 118.55, 114.59, 97.98, 72.76, 66.38, 56.34, 49.40, 40.29, 38.55, 34.61, 34.21,
31.62, 28.75, 24.58, 23.19, 14.01, 7.83 (Supplementary Figure S4).
Scheme 1.
Synthesis of the modified SN38 (
2
) with the linker for the conjugation with
AuNPs. Lipoic acid was activated (
1
) and incubated with SN38 to yield the desired product (
2
). DCC:
N,N’-dicyclohexylcarbodimide; DIPEA: N,N-diisopropylethylamine; DMAP: 4-Dimethylaminopyridine;
DMF: Dimethylformamide; NHS: N-hydroxysuccinimide; RT: Room temperature; THF: Tetrahydrofuran.
2.8.1. α-Lipoic Acid–NHS (1)
Lipoic acid (1 g, 1 equiv) and N-hydroxysuccinimide (NHS) (667 mg, 1.2 equiv) were dissolved
in tetrahydrofuran (THF) (20.8 mL), and the solution was stirred at 0
C for 10 min. A solution of
N,N’-dicyclohexylcarbodimide (DCC) (1.2 g, 1.2 equiv) in THF (1.7 mL) was added slowly to the
lipoic acid and NHS solution. The reaction was stirred at room temperature for 5 h. The mixture was
filtered, and the solution was kept in the freezer overnight, it was filtered again and the solvent was
eliminated in vacuum. The compound
1
(Scheme 1) was obtained as yellow oil (1.43 g, 99% yield) [
62
].
1
H NMR (400 MHz, CDCl3):
δ
= 3.60–3.50 (m, 4H), 3.20–3.06 (m, 1H), 2.81 (s, 4H), 2.61 (t, J= 7.4 Hz,
2H), 2.50–2.36 (m, 1H), 1.94–1.88 (m, 1H), 1.82–1.72 (m, 2H), 1.72–1.66 (m, 2H), 1.62–1.46 (m, 2H)
(Supplementary Figure S2).
13
C NMR (101 MHz, CDCl3):
δ
= 169.13, 168.42, 67.42, 40.15, 38.52, 34.42,
33.21, 30.79, 25.59, 22.59, 24.36, 23.39.
2.8.2. α-Lipoic Acid–SN38 (2)
Compound
1
(56 mg, 2 equiv), SN38 (36 mg, 1 equiv) and 4-dimethylaminopyridine (DMAP)
(3 mg) were dissolved in dimethylformamide (DMF) (3.7 mL), then N,N-diisopropylethylamine
(DIPEA) was added to the solution. The reaction was stirred at 50
C for 18 h. The solvent was
eliminated in vacuum and the crude was purified by flash chromatography (CH
2
Cl
2
CH
2
Cl
2
/MeOH
40:1) to obtain the compound
2
(Scheme 1) as white-yellow solid (21 mg, 40% yield).
1
H-NMR (400
MHz, CDCl
3
):
δ
= 8.24 (d, J= 9.2 Hz, 1H), 7.83 (d, J= 2.5 Hz, 1H), 7.65 (s, 1H), 7.55 (dd, J= 9.2, 2.5 Hz,
1H), 5.76 (d, J= 16.3 Hz, 1H), 5.35–5.29 (m, 1H), 5.26 (s, 2H), 3.68–3.59 (m, 1H), 3.25–3.10 (m, 4H), 2.69
(t, J= 7.4 Hz, 2H), 2.55–2.46 (m, 1H), 2.00–1.93 (m, 1H), 1.90–1.83 (m, 3H), 1.83–1.76 (m, 2H), 1.70–1.59
(m, 3H), 1.40 (t, J= 7.7 Hz, 3H), 1.04 (t, J= 7.4 Hz, 3H) (Supplementary Figure S3).
13
C-NMR (101 MHz,
CDCl3):
δ
= 173.95, 171.85, 157.67, 151.94, 150.18, 149.64, 147.49, 146.95, 145.27, 132.13, 127.48, 127.27,
125.41, 118.55, 114.59, 97.98, 72.76, 66.38, 56.34, 49.40, 40.29, 38.55, 34.61, 34.21, 31.62, 28.75, 24.58, 23.19,
14.01, 7.83 (Supplementary Figure S4).
2.9. Statistical Analysis
The statistical analysis was performed in R Project for Statistical Computing (R-3.2.5) software [
63
].
One-way analysis of variance (ANOVA) was used to compare the mean value of each condition vs.
Biomimetics 2018,3, 28 8 of 18
control. Significant differences between the means were accepted when the p-value was lower than
0.001 (***).
3. Results
3.1. DNA-Based microRNA Mimics
DNA-based microRNA mimics 1, 2, 3, and 4 (Table 1) were transfected individually into Mel
202 cells and cell viability was assessed using the alamarBlue assay after 48 h. The reduction in cell
viability was negligible in all cases (Figure 1a), and the effect of the microRNA mimics when combined
was evaluated, both in pairs (Figure 1b) and all together in DNA mix 1 (Figure 1c). Interestingly, a 30%
reduction in cell viability was observed in the latter conditions.
In addition, the effect of the mixture on the expression of c-Met was analyzed by
immunofluorescence (Figure 1d,e). Remarkably, the images revealed significant changes in fluorescence
when the cells were treated with the DNA mix, precisely a 67% reduction in the expression of c-Met.
Biomimetics 2018, 3, x FOR PEER REVIEW 8 of 18
2.9. Statistical Analysis
The statistical analysis was performed in R Project for Statistical Computing (R-3.2.5) software
[63]. One-way analysis of variance (ANOVA) was used to compare the mean value of each condition
vs. control. Significant differences between the means were accepted when the p-value was lower
than 0.001 (***).
3. Results
3.1. DNA-Based microRNA Mimics
DNA-based microRNA mimics 1, 2, 3, and 4 (Table 1) were transfected individually into Mel 202
cells and cell viability was assessed using the alamarBlue assay after 48 h. The reduction in cell
viability was negligible in all cases (Figure 1a), and the effect of the microRNA mimics when
combined was evaluated, both in pairs (Figure 1b) and all together in DNA mix 1 (Figure 1c).
Interestingly, a 30% reduction in cell viability was observed in the latter conditions.
In addition, the effect of the mixture on the expression of c-Met was analyzed by
immunofluorescence (Figure 1d,e). Remarkably, the images revealed significant changes in
fluorescence when the cells were treated with the DNA mix, precisely a 67% reduction in the
expression of c-Met.
Figure 1. Activity of microRNA mimics. (ac) Cell viability assay in Mel 202 cells using different
combination of oligonucleotides 1, 2, 3 and 4: (a) Mel 202 cells were transfected with individuals
oligonucleotides (1, 2, 3 and 4) treatment at 140 nM/well; (b) Mel 202 cells were transfected with
oligonucleotides in pairs (final oligonucleotide concentration of 140 nM); (c) Mel 202 cells were
transfected with DNA mix 1 at 140 nM (*** p < 0.001). (d,e) Immunofluorescence analysis in Mel 202
cells: (d) Fluorescence intensity (arbitrary units, AU) of c-Met in untreated cells and treated with the
DNA mix 1 (*** p < 0.001); (e) Representative immunofluorescence images of cells untreated (I) and
treated with the DNA mix 1 (II). c-Met is shown in green and nucleus are labeled in blue by Hoechst
staining. Statistical analysis was performed using one-way ANOVA (each group vs. control).
3.2. Combination Therapy
Since the DNA mix 1 provided a cytotoxic effect and reduced c-Met expression, we decided to
study the effect in combination with the chemotherapeutic drug SN38. The siRNA mix was also
evaluated in combination with SN38, since a higher reduction in cell viability could be expected.
Figure 1.
Activity of microRNA mimics. (
a
c
) Cell viability assay in Mel 202 cells using different
combination of oligonucleotides 1, 2, 3 and 4: (
a
) Mel 202 cells were transfected with individuals
oligonucleotides (1, 2, 3 and 4) treatment at 140 nM/well; (
b
) Mel 202 cells were transfected with
oligonucleotides in pairs (final oligonucleotide concentration of 140 nM); (
c
) Mel 202 cells were
transfected with DNA mix 1 at 140 nM (*** p< 0.001). (
d
,
e
) Immunofluorescence analysis in Mel
202 cells: (
d
) Fluorescence intensity (arbitrary units, AU) of c-Met in untreated cells and treated with
the DNA mix 1 (*** p< 0.001); (
e
) Representative immunofluorescence images of cells untreated (I) and
treated with the DNA mix 1 (II). c-Met is shown in green and nucleus are labeled in blue by Hoechst
staining. Statistical analysis was performed using one-way ANOVA (each group vs. control).
3.2. Combination Therapy
Since the DNA mix 1 provided a cytotoxic effect and reduced c-Met expression, we decided
to study the effect in combination with the chemotherapeutic drug SN38. The siRNA mix was also
evaluated in combination with SN38, since a higher reduction in cell viability could be expected.
First, the half maximal inhibitory concentration (IC50) of SN38 (100 nM) was assessed in Mel
202 cells (Figure 2a), and then the combined effect of the SN38 with DNA mix 1 and siRNA mix
were examined (Figure 2b). A significant reduction in cell viability (50%) was observed using low
concentrations of the drug (25 nM) and the DNA mix 1 or siRNA mix.
With the aim to study the potential effect of this combination on the cell cycle (Figure 3), cells were
harvested after the treatment and analyzed by flow cytometry. The effect of DNA mix 1 was negligible
Biomimetics 2018,3, 28 9 of 18
(Figure 3b) as compared with the effect obtained with SN38, which significantly increases G2/M phase
cells (Figure 3c).
Biomimetics 2018,3, 28 9 of 18
(Figure 3b) as compared with the effect obtained with SN38, which significantly increases G2/M phase
cells (Figure 3c).
Biomimetics 2018, 3, x FOR PEER REVIEW 9 of 18
First, the half maximal inhibitory concentration (IC50) of SN38 (100 nM) was assessed in Mel 202
cells (Figure 2a), and then the combined effect of the SN38 with DNA mix 1 and siRNA mix were
examined (Figure 2b). A significant reduction in cell viability (50%) was observed using low
concentrations of the drug (25 nM) and the DNA mix 1 or siRNA mix.
With the aim to study the potential effect of this combination on the cell cycle (Figure 3), cells
were harvested after the treatment and analyzed by flow cytometry. The effect of DNA mix 1 was
negligible (Figure 3b) as compared with the effect obtained with SN38, which significantly increases
G2/M phase cells (Figure 3c).
Figure 2. Half maximal inhibitory concentration (IC50) of SN38 and combination therapy effect. (a)
Cell viability assay in Mel 202 cells treated with SN38 at different concentrations. The IC50 in which
the cell viability is reduced 50% is 100 nM for Mel 202 cells (*** p < 0.001). (b) Cell viability assay in
Mel 202 cells treated with SN38, DNA mix 1 and siRNA mix. The cell viability is reduced by 50% at a
very low concentration of SN38 in the combination conditions (*** p < 0.001). Statistical analysis was
performed using one-way ANOVA (each group vs. control).
Figure 2.
Half maximal inhibitory concentration (IC50) of SN38 and combination therapy efect. (
a
) Cell
viability assay in Mel 202 cells treated with SN38 at different concentrations. The IC50 in which the cell
viability is reduced 50% is 100 nM for Mel 202 cells (*** p< 0.001). (
b
) Cell viability assay in Mel 202
cells treated with SN38, DNA mix 1 and siRNA mix. The cell viability is reduced by 50% at a very low
concentration of SN38 in the combination conditions (*** p< 0.001). Statistical analysis was performed
using one-way ANOVA (each group vs. control).
Biomimetics 2018, 3, x FOR PEER REVIEW 9 of 18
First, the half maximal inhibitory concentration (IC50) of SN38 (100 nM) was assessed in Mel 202
cells (Figure 2a), and then the combined effect of the SN38 with DNA mix 1 and siRNA mix were
examined (Figure 2b). A significant reduction in cell viability (50%) was observed using low
concentrations of the drug (25 nM) and the DNA mix 1 or siRNA mix.
With the aim to study the potential effect of this combination on the cell cycle (Figure 3), cells
were harvested after the treatment and analyzed by flow cytometry. The effect of DNA mix 1 was
negligible (Figure 3b) as compared with the effect obtained with SN38, which significantly increases
G2/M phase cells (Figure 3c).
Figure 2. Half maximal inhibitory concentration (IC50) of SN38 and combination therapy effect. (a)
Cell viability assay in Mel 202 cells treated with SN38 at different concentrations. The IC50 in which
the cell viability is reduced 50% is 100 nM for Mel 202 cells (*** p < 0.001). (b) Cell viability assay in
Mel 202 cells treated with SN38, DNA mix 1 and siRNA mix. The cell viability is reduced by 50% at a
very low concentration of SN38 in the combination conditions (*** p < 0.001). Statistical analysis was
performed using one-way ANOVA (each group vs. control).
Biomimetics 2018, 3, x FOR PEER REVIEW 10 of 18
Figure 3. Pie charts describing flow cytometry data in Mel 202 cells. (a) Untreated cells; (b) Cells
treated with 140 nM DNA mix 1; (c) Cells treated with 25 nM SN38; (d) Cells treated with 140 nM
microRNA mimics and 25 nM SN38. Green: cells in G1 phase; blue: cells in S phase; yellow: cells in
G2/M phase.
3.3. Gold Nanoparticles as Carriers
Gold nanoparticles were prepared based on the Turkevich method [64] and modified with the
oligonucleotides (DNA mix 2 and siRNA mix) and SN38 as described in Section 2.4. Specifically, the
bare nanoparticles were incubated with oligonucleotides (DNA mix 2 or siRNA mix) modified with
a thiol moiety in the presence of NaCl for 16 h. In the case of the nanoparticle modified with SN38,
the particles were previously incubated with the aptamer AS1411 for 30 min, and the modified SN38
(2) was then added to the solution (Figure 4).
Figure 4. Functionalization of AuNPs with (a) DNA mix 2, and (b) aptamer AS1411 and modified
SN38 (2).
Once the unbound material was removed, the sizes of the three formulations (AuNPs DNA mix,
AuNPs siRNA mix, and AuNP SN38) were characterized by DLS. The average size of the
hydrodynamic diameter was 13–15 nm (Figure 5a–c).
Figure 3.
Pie charts describing flow cytometry data in Mel 202 cells. (
a
) Untreated cells; (
b
) Cells
treated with 140 nM DNA mix 1; (
c
) Cells treated with 25 nM SN38; (
d
) Cells treated with 140 nM
microRNA mimics and 25 nM SN38. Green: cells in G1 phase; blue: cells in S phase; yellow: cells in
G2/M phase.
Figure 2.
Half maximal inhibitory concentration (IC50) of SN38 and combination therapy efect. (
a
) Cell
viability assay in Mel 202 cells treated with SN38 at different concentrations. The IC50 in which the cell
viability is reduced 50% is 100 nM for Mel 202 cells (*** p< 0.001). (
b
) Cell viability assay in Mel 202
cells treated with SN38, DNA mix 1 and siRNA mix. The cell viability is reduced by 50% at a very low
concentration of SN38 in the combination conditions (*** p< 0.001). Statistical analysis was performed
using one-way ANOVA (each group vs. control).
Biomimetics 2018, 3, x FOR PEER REVIEW 9 of 18
First, the half maximal inhibitory concentration (IC50) of SN38 (100 nM) was assessed in Mel 202
cells (Figure 2a), and then the combined effect of the SN38 with DNA mix 1 and siRNA mix were
examined (Figure 2b). A significant reduction in cell viability (50%) was observed using low
concentrations of the drug (25 nM) and the DNA mix 1 or siRNA mix.
With the aim to study the potential effect of this combination on the cell cycle (Figure 3), cells
were harvested after the treatment and analyzed by flow cytometry. The effect of DNA mix 1 was
negligible (Figure 3b) as compared with the effect obtained with SN38, which significantly increases
G2/M phase cells (Figure 3c).
Figure 2. Half maximal inhibitory concentration (IC50) of SN38 and combination therapy effect. (a)
Cell viability assay in Mel 202 cells treated with SN38 at different concentrations. The IC50 in which
the cell viability is reduced 50% is 100 nM for Mel 202 cells (*** p < 0.001). (b) Cell viability assay in
Mel 202 cells treated with SN38, DNA mix 1 and siRNA mix. The cell viability is reduced by 50% at a
very low concentration of SN38 in the combination conditions (*** p < 0.001). Statistical analysis was
performed using one-way ANOVA (each group vs. control).
Biomimetics 2018, 3, x FOR PEER REVIEW 10 of 18
Figure 3. Pie charts describing flow cytometry data in Mel 202 cells. (a) Untreated cells; (b) Cells
treated with 140 nM DNA mix 1; (c) Cells treated with 25 nM SN38; (d) Cells treated with 140 nM
microRNA mimics and 25 nM SN38. Green: cells in G1 phase; blue: cells in S phase; yellow: cells in
G2/M phase.
3.3. Gold Nanoparticles as Carriers
Gold nanoparticles were prepared based on the Turkevich method [64] and modified with the
oligonucleotides (DNA mix 2 and siRNA mix) and SN38 as described in Section 2.4. Specifically, the
bare nanoparticles were incubated with oligonucleotides (DNA mix 2 or siRNA mix) modified with
a thiol moiety in the presence of NaCl for 16 h. In the case of the nanoparticle modified with SN38,
the particles were previously incubated with the aptamer AS1411 for 30 min, and the modified SN38
(2) was then added to the solution (Figure 4).
Figure 4. Functionalization of AuNPs with (a) DNA mix 2, and (b) aptamer AS1411 and modified
SN38 (2).
Once the unbound material was removed, the sizes of the three formulations (AuNPs DNA mix,
AuNPs siRNA mix, and AuNP SN38) were characterized by DLS. The average size of the
hydrodynamic diameter was 13–15 nm (Figure 5a–c).
Figure 3.
Pie charts describing flow cytometry data in Mel 202 cells. (
a
) Untreated cells; (
b
) Cells
treated with 140 nM DNA mix 1; (
c
) Cells treated with 25 nM SN38; (
d
) Cells treated with 140 nM
microRNA mimics and 25 nM SN38. Green: cells in G1 phase; blue: cells in S phase; yellow: cells in
G2/M phase.
Biomimetics 2018,3, 28 10 of 18
3.3. Gold Nanoparticles as Carriers
Gold nanoparticles were prepared based on the Turkevich method [
64
] and modified with the
oligonucleotides (DNA mix 2 and siRNA mix) and SN38 as described in Section 2.4. Specifically,
the bare nanoparticles were incubated with oligonucleotides (DNA mix 2 or siRNA mix) modified
with a thiol moiety in the presence of NaCl for 16 h. In the case of the nanoparticle modified with
SN38, the particles were previously incubated with the aptamer AS1411 for 30 min, and the modified
SN38 (2) was then added to the solution (Figure 4).
Biomimetics 2018, 3, x FOR PEER REVIEW 10 of 18
Figure 3. Pie charts describing flow cytometry data in Mel 202 cells. (a) Untreated cells; (b) Cells
treated with 140 nM DNA mix 1; (c) Cells treated with 25 nM SN38; (d) Cells treated with 140 nM
microRNA mimics and 25 nM SN38. Green: cells in G1 phase; blue: cells in S phase; yellow: cells in
G2/M phase.
3.3. Gold Nanoparticles as Carriers
Gold nanoparticles were prepared based on the Turkevich method [64] and modified with the
oligonucleotides (DNA mix 2 and siRNA mix) and SN38 as described in Section 2.4. Specifically, the
bare nanoparticles were incubated with oligonucleotides (DNA mix 2 or siRNA mix) modified with
a thiol moiety in the presence of NaCl for 16 h. In the case of the nanoparticle modified with SN38,
the particles were previously incubated with the aptamer AS1411 for 30 min, and the modified SN38
(2) was then added to the solution (Figure 4).
Figure 4. Functionalization of AuNPs with (a) DNA mix 2, and (b) aptamer AS1411 and modified
SN38 (2).
Once the unbound material was removed, the sizes of the three formulations (AuNPs DNA mix,
AuNPs siRNA mix, and AuNP SN38) were characterized by DLS. The average size of the
hydrodynamic diameter was 13–15 nm (Figure 5a–c).
Figure 4.
Functionalization of AuNPs with (
a
) DNA mix 2, and (
b
) aptamer AS1411 and modified
SN38 (2).
Once the unbound material was removed, the sizes of the three formulations (AuNPs DNA
mix, AuNPs siRNA mix, and AuNP SN38) were characterized by DLS. The average size of the
hydrodynamic diameter was 13–15 nm (Figure 5a–c).
The zeta-potential was carried out to assess the charges in the AuNPs before and after the
functionalization using solutions of the samples in water at 8.3 nM. Bare AuNPs had a zeta-potential
of
37.9
±
0.603 mV; AuNP SN38 of
22.1
±
1.84 mV; AuNP DNA mix of
35
±
2.72 mV; and AuNP
siRNA mix of 35.8 ±2.35 mV.
The ultraviolet–visible (UV–vis) spectrum, performed in a plate reader synergy H4 Hybrid reader
(BioTEK) at 25 C, revealed the characteristic plasmon band at 520 nm of AuNPs (Figure 4d).
The activity of functionalized AuNPs was evaluated in Mel 202 cells, where the AuNP DNA mix
did not reduce the viability of the cells. When the AuNP SN38 was added the viability was reduced,
and this reduction was even higher when used in combination with the AuNP siRNA mix (Figure 6a).
Cell viability on Mel 202 was reduced after AuNP siRNAs mix treatment, and it was further
reduced when AuNP siRNAs were combined with AuNP SN38. (Figure 6b). Interestingly, the cell cycle
was affected when SN38 was present, but not when siRNAs were used in the formulation (Figure 7,
and Supplementary Figures S5 and S6).
Biomimetics 2018,3, 28 11 of 18
Biomimetics 2018, 3, x FOR PEER REVIEW 11 of 18
The zeta-potential was carried out to assess the charges in the AuNPs before and after the
functionalization using solutions of the samples in water at 8.3 nM. Bare AuNPs had a zeta-potential
of 37.9 ± 0.603 mV; AuNP SN38 of 22.1 ± 1.84 mV; AuNP DNA mix of 35 ± 2.72 mV and AuNP
siRNA mix of 35.8 ± 2.35 mV.
The ultraviolet–visible (UV–vis) spectrum, performed in a plate reader synergy H4 Hybrid
reader (BioTEK) at 25 °C, revealed the characteristic plasmon band at 520 nm of AuNPs (Figure 4d).
Figure 5. Characterization of AuNPs. (ac) Hydrodynamic diameter size (nm) of modified AuNPs
and polydispersity index (Pdi). (d) Ultraviolet–visible (UV–vis) spectrum where the corresponding
plasmon band at 520 nm was noticeable.
The activity of functionalized AuNPs was evaluated in Mel 202 cells, where the AuNP DNA mix
did not reduce the viability of the cells. When the AuNP SN38 was added the viability was reduced,
and this reduction was even higher when used in combination with the AuNP siRNA mix (Figure
6a).
Cell viability on Mel 202 was reduced after AuNP siRNAs mix treatment, and it was further
reduced when AuNP siRNAs were combined with AuNP SN38. (Figure 6b). Interestingly, the cell
cycle was affected when SN38 was present, but not when siRNAs were used in the formulation
(Figure 7 and Supplementary Figures S5 and S6).
Figure 5.
Characterization of AuNPs. (
a
c
) Hydrodynamic diameter size (nm) of modified AuNPs
and polydispersity index (Pdi). (
d
) Ultraviolet–visible (UV–vis) spectrum where the corresponding
plasmon band at 520 nm was noticeable.
Biomimetics 2018,3, 28 11 of 18
Biomimetics 2018, 3, x FOR PEER REVIEW 11 of 18
The zeta-potential was carried out to assess the charges in the AuNPs before and after the
functionalization using solutions of the samples in water at 8.3 nM. Bare AuNPs had a zeta-potential
of 37.9 ± 0.603 mV; AuNP SN38 of 22.1 ± 1.84 mV; AuNP DNA mix of 35 ± 2.72 mV and AuNP
siRNA mix of 35.8 ± 2.35 mV.
The ultraviolet–visible (UV–vis) spectrum, performed in a plate reader synergy H4 Hybrid
reader (BioTEK) at 25 °C, revealed the characteristic plasmon band at 520 nm of AuNPs (Figure 4d).
Figure 5. Characterization of AuNPs. (ac) Hydrodynamic diameter size (nm) of modified AuNPs
and polydispersity index (Pdi). (d) Ultraviolet–visible (UV–vis) spectrum where the corresponding
plasmon band at 520 nm was noticeable.
The activity of functionalized AuNPs was evaluated in Mel 202 cells, where the AuNP DNA mix
did not reduce the viability of the cells. When the AuNP SN38 was added the viability was reduced,
and this reduction was even higher when used in combination with the AuNP siRNA mix (Figure
6a).
Cell viability on Mel 202 was reduced after AuNP siRNAs mix treatment, and it was further
reduced when AuNP siRNAs were combined with AuNP SN38. (Figure 6b). Interestingly, the cell
cycle was affected when SN38 was present, but not when siRNAs were used in the formulation
(Figure 7 and Supplementary Figures S5 and S6).
Figure 5.
Characterization of AuNPs. (
a
c
) Hydrodynamic diameter size (nm) of modified AuNPs
and polydispersity index (Pdi). (
d
) Ultraviolet–visible (UV–vis) spectrum where the corresponding
plasmon band at 520 nm was noticeable.
Biomimetics 2018, 3, x FOR PEER REVIEW 12 of 18
Figure 6. Cell viability assay in Mel 202 cells treated with (a) AuNP DNA mix, AuNP SN38, and their
combination (AuNP DNA mix + AuNP SN38) (*** p < 0.001). (b) AuNP siRNA mix, AuNP SN38 and
their combination (AuNP siRNA mix + AuNP SN38) (*** p < 0.001). Statistical analysis was performed
using one-way ANOVA test (each group vs. control).
Figure 7. Pie charts describing flow cytometry data in Mel 202 cells. (a) Untreated cells; (b) Cells
treated with 100 μL AuNP DNA mix 2; (c) Cells treated with 100 μL AuNPs siRNA mix; (d) Cells
treated with 25 nM AuNPs SN38; (e) Cells treated with 100 μL AuNPs DNA mix 2 and 25 nM AuNP
SN38; (f) Cells treated with 100 μL AuNPs siRNA mix and 25 nM AuNP SN38. Green: cells in G1
phase; blue: cells in S phase; yellow: cells in G2/M phase.
4. Discussion
4.1. DNA-Based microRNA Mimics
Antisense technology has been used to reduce the expression of mRNAs [64]. It requires the
formation of duplexes between the oligonucleotides and the target mRNAs, which usually leads to
the degradation of the RNA by ribonuclease H (RNase H). Herein, this reactivity has been exploited
Figure 6.
Cell viability assay in Mel 202 cells treated with (
a
) AuNP DNA mix, AuNP SN38, and their
combination (AuNP DNA mix + AuNP SN38) (*** p< 0.001). (
b
) AuNP siRNA mix, AuNP SN38 and
their combination (AuNP siRNA mix + AuNP SN38) (*** p< 0.001). Statistical analysis was performed
using one-way ANOVA test (each group vs. control).
Figure 6.
Cell viability assay in Mel 202 cells treated with (
a
) AuNP DNA mix, AuNP SN38, and their
combination (AuNP DNA mix + AuNP SN38) (*** p< 0.001). (
b
) AuNP siRNA mix, AuNP SN38 and
their combination (AuNP siRNA mix + AuNP SN38) (*** p< 0.001). Statistical analysis was performed
using one-way ANOVA test (each group vs. control).
Biomimetics 2018,3, 28 12 of 18
Biomimetics 2018, 3, x FOR PEER REVIEW 12 of 18
Figure 6. Cell viability assay in Mel 202 cells treated with (a) AuNP DNA mix, AuNP SN38, and their
combination (AuNP DNA mix + AuNP SN38) (*** p < 0.001). (b) AuNP siRNA mix, AuNP SN38 and
their combination (AuNP siRNA mix + AuNP SN38) (*** p < 0.001). Statistical analysis was performed
using one-way ANOVA test (each group vs. control).
Figure 7. Pie charts describing flow cytometry data in Mel 202 cells. (a) Untreated cells; (b) Cells
treated with 100 μL AuNP DNA mix 2; (c) Cells treated with 100 μL AuNPs siRNA mix; (d) Cells
treated with 25 nM AuNPs SN38; (e) Cells treated with 100 μL AuNPs DNA mix 2 and 25 nM AuNP
SN38; (f) Cells treated with 100 μL AuNPs siRNA mix and 25 nM AuNP SN38. Green: cells in G1
phase; blue: cells in S phase; yellow: cells in G2/M phase.
4. Discussion
4.1. DNA-Based microRNA Mimics
Antisense technology has been used to reduce the expression of mRNAs [64]. It requires the
formation of duplexes between the oligonucleotides and the target mRNAs, which usually leads to
the degradation of the RNA by ribonuclease H (RNase H). Herein, this reactivity has been exploited
Figure 7.
Pie charts describing flow cytometry data in Mel 202 cells. (
a
) Untreated cells; (
b
) Cells
treated with 100
µ
L AuNP DNA mix 2; (
c
) Cells treated with 100
µ
L AuNPs siRNA mix; (
d
) Cells
treated with 25 nM AuNPs SN38; (
e
) Cells treated with 100
µ
L AuNPs DNA mix 2 and 25 nM AuNP
SN38; (
f
) Cells treated with 100
µ
L AuNPs siRNA mix and 25 nM AuNP SN38. Green: cells in G1
phase; blue: cells in S phase; yellow: cells in G2/M phase.
4. Discussion
4.1. DNA-Based microRNA Mimics
Antisense technology has been used to reduce the expression of mRNAs [
64
]. It requires the
formation of duplexes between the oligonucleotides and the target mRNAs, which usually leads
to the degradation of the RNA by ribonuclease H (RNase H). Herein, this reactivity has been
exploited using oligonucleotides with the same sequence as four microRNAs downregulated in
UM: microRNA-34a, microRNA-182, microRNA-137, and microRNA-144 [
24
]. These DNA-based
microRNA mimics are expected to reduce the tumor behavior of cancer cells [
65
] or increase their
sensitivity to chemotherapeutics [66].
To test the effectiveness of the selected DNA-based microRNA mimics, 1, 2, 3 and 4 (Table 1) were
transfected individually, in pairs and all together into Mel 202 cells (Figure 1a–c). The effect achieved
by single oligonucleotides was negligible, including when combined in pairs. Interestingly, a 30%
reduction in viability resulted when all the oligonucleotides were used as a 1:1:1:1 mixture, despite their
lower individual concentration compared with the previous two experiments. This reduction might be
due to a synergistic activity when combining the inhibitions of the different pathways associated with
the microRNAs.
After this experiment, the effect of the microRNA mimics in the cells was assessed using other
techniques. Since the microRNAs selected can reduce the expression of c-Met [
27
,
32
,
67
], the effect of
the DNA mix 1 was studied by immunofluorescence. c-Met is a tyrosine kinase receptor implicated in
the metastasis and malignancy of UM [
28
] and is usually overexpressed in UM [
68
,
69
]. Remarkably,
the images revealed significant changes in fluorescence when the cells were treated with DNA mix 1,
which resulted in a 67% reduction in expression (Figure 1e).
4.2. Combination Therapy
Since the DNA-based microRNA mimics affect cell viability and c-Met expression, their effect was
studied in combination with a chemotherapeutic drug. This approach might prevent the generation of
Biomimetics 2018,3, 28 13 of 18
resistance since c-Met is significantly reduced [
70
]. Here, SN38 was selected as an analog of Irinotecan,
which has been recently used in metastatic UM [71].
After assessing the IC50 of the drug in Mel 202 cells (Figure 2a), the effect of the SN38 in
combination with DNA mix 1 and the siRNA mix was studied (Figure 2b). A significant reduction in
the cell viability (50%) was observed using low concentrations of the drug (25 nM) and DNA mix 1 or
the siRNA mix. Remarkably, the effect observed was synergistic according to the method described by
Valeriote [
72
]. In this method, the efficacy of the individual drugs (
ε
A,
ε
B) is compared to the combined
treatment (
ε
A + B). It is synergistic if
ε
A+B<(
ε
A
×ε
B)/100; additive, if
ε
A+B=(
ε
A
×ε
B)/100;
sub-additive if (
ε
A
×ε
B)/100 <
ε
A + B <
ε
A, provided
ε
A <
ε
B; interfering if
ε
A <
ε
A + B <
ε
B,
when
ε
A <
ε
B; or antagonistic, if
ε
B <
ε
A + B, when
ε
A <
ε
B. According to this method, the proposed
treatment had a synergistic effect.
This result highlights the potential of this approach, where reprograming the behavior of UM
through oligonucleotides allows for a significant reduction of the dose of SN38 to 25 nM; potentially
decreasing side effects [73].
Furthermore, the reduction of c-Met expression observed in the combination approach could also
lead to a reduction of drug resistance, as mentioned previously.
The effect of this approach was also studied on the cell cycle, which is related to tumor progression
and cell death. DNA mix 1 did not modify the cell cycle significantly. In contrast, SN38 promoted
a reduction in the G1 phase and an increase in G2 phase (Figure 3c), as previously reported [
74
,
75
].
When DNA mix 1 and SN38 were used in combination, the G2 arrest was also increased but less than in
the case of SN38 alone (Figure 3c,d), despite the higher decrease in cell viability observed (Figure 2b).
4.3. Gold Nanoparticles as Vehicles
As mentioned in the Introduction, the delivery of oligonucleotides and drugs can be problematic
for several reasons. The charges of phosphate groups on the oligonucleotides prevent their
internalization inside the cells [
49
,
76
], and the drug has low solubility in water [
17
]. Thus, gold
nanoparticles were used to overcome these limitations. The conjugation of oligonucleotides was
achieved through a thiol modification. Thus, the oligonucleotides were deprotected using TCEP and
incubated with the gold nanoparticles, affording stable nanostructures. In the case of SN38, a linker
was prepared that allows its easy conjugation to the nanoparticles. However, the first attempts led to
the aggregation of the nanostructure. To increase its stability, the aptamer AS1411 was used, which has
previously been employed to stabilize nanoparticles [
47
]. This aptamer can recognize the nucleolin
protein present in the membrane of tumoral cells [
77
] and therefore can be used to increase their
internalization. Using this approach, stable AuNPs modified with SN38 were obtained.
The changes in the zeta-potential confirms that the nanoparticles have been modified. In this
regard, the addition of SN38 reduced the negative charge, as expected. In the case of AuNP DNA mix
or AuNP siRNA mix we did not observe significant changes in the charge. This is due to the presence
of the phosphate groups.
The particles prepared were tested in cell culture, individually and in combination, revealing
that when the two types of nanoparticles where used (AuNP DNA mix and AuNP SN38), a higher
inhibition was obtained, as observed previously with the oligonucleotides and the free drug.
Furthermore, AuNPs modified with siRNAs instead of DNAs were assessed, since siRNAs inhibit
gene expression or mimic microRNAs better than DNA oligonucleotides. In this case, the inhibition
by the AuNP siRNA mix was higher than that by the AuNP DNA mix, and it was even higher when
combined with SN38. Interestingly, in both cases, the effect was synergistic [
72
], probably due to their
different mechanism of action and the different process and pathways involved in both therapeutics.
The cell cycle analysis showed a significant effect when AuNP SN38 was used. However, this
effect was reduced when combined with AuNP DNA mix, and particularly with AuNP siRNA mix.
This result suggests that the DNA or RNA therapy reprogrammed the cells to a state where the G2
arrest of SN38 cannot be detected. In other words, the selected oligonucleotides could lead the cell
Biomimetics 2018,3, 28 14 of 18
cycle progression as was previously reported with other microRNAs, such as the microRNA-181
family [78].
5. Conclusions
The use of microRNA mimics as therapeutics against uveal melanoma has been evaluated.
These DNA-based mimics are not active when used individually or in pairs, but they present significant
activity when used in combination. This might be due to the synergy of the sequences selected that
interact with different pathways involved in cell survival. Remarkably, this system can be used to
increase the sensitivity of Mel 202 cells to SN38, requiring only 25 nM to achieve the same activity
of the drug alone at 100 nM. Again, the synergy observed with this combination might be due to
the complementary targets of the bioactive molecules (microRNA mimics and SN38). Furthermore,
microRNA mimics and SN38 have been conjugated to gold nanoparticles to overcome their inherent
limitations for biomedical applications, such as stability, translocation, and solubility. Interestingly,
the nanoformulations obtained present an activity comparable to the free bioactive molecules, and the
same synergistic effect when combined. Finally, RNA-based mimics have been used in the same way,
providing even higher cytotoxic activity. The unique combination of oligonucleotides employed here
might be reprogramming the cancer cells, making them more susceptible to SN38.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2313-7673/3/4/28/s1.
Figure S1: TEM analysis of AuNPs, Figure S2:
1
H NMR of compound
1
, Figure S3:
1
H NMR of compound
2
,
Figure S4:
13
C NMR of compound
2
, Figure S5: Cell cycle analysis, Figure S6: Distribution of Mel 202 cells treated
with AuNPs by flow cytometry.
Author Contributions:
Conceptualization, Á.S.; Methodology, P.M.R. and A.L.; Software, Á.d.M.; Formal analysis,
P.M.R., C.R.D. and A.L.; Writing—review and editing, Á.S., P.M.R. and C.R.D.
Funding:
This work was supported by the Spanish Ministry of Economy and Competitiveness (SAF2017-87305-R),
Fundación Científica Asociación Española Contra el Cáncer, and IMDEA Nanociencia. IMDEA Nanociencia
acknowledges support from the ‘Severo Ochoa’ Programme for Centres of Excellence in R&D (MINECO, Grant
SEV-2016-0686).
Conflicts of Interest: The authors declare no conflict of interest.
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(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
... For example, selumetinib selectively targets the MAPK pathway, and AZD 8055 interferes with the mammalian target of rapamycin (mTOR) signaling pathway in UM cells; however, they both target these same signaling pathways in healthy cells as well. Emerging studies suggest a key role of a number of miRNAs in UM progression and that some specific miRNAs are involved in chemotherapeutic resistance [116]. Despite having potential to be developed as therapeutic tools, some disadvantages of miRNAs reduce their therapeutic activity. ...
... Furthermore, the four miRNAs (miR-34a, miR-137 miR-144, and miR-182) were chosen based on their downregulation in UM, and their combined application exhibited a synergistic effect [125]. Moreover, SN38 (7-ethyl-10-hidroxycamptothecin) is a topoisomerase I inhibitor with poor aqueous solubility [126], and the combination of these four miRNAs increases UM cell sensitivity to chemotherapeutic SN38 [116]. Remarkably, these studies demonstrate that the conjugated effect of the four miRNAs and SN38 with AuNP delivery overcomes the innate constraints of these individual molecules and proves to be a highly effective therapeutic approach against UM [116]. ...
... Moreover, SN38 (7-ethyl-10-hidroxycamptothecin) is a topoisomerase I inhibitor with poor aqueous solubility [126], and the combination of these four miRNAs increases UM cell sensitivity to chemotherapeutic SN38 [116]. Remarkably, these studies demonstrate that the conjugated effect of the four miRNAs and SN38 with AuNP delivery overcomes the innate constraints of these individual molecules and proves to be a highly effective therapeutic approach against UM [116]. ...
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Uveal melanoma (UM) is the most common intraocular malignant tumor in adults with an extremely high mortality rate. Genetic and epigenetic dysregulation contribute to the development of UM. Recent discoveries have revealed dysregulation of the expression levels of microRNAs (miRNAs) as one of the epigenetic mechanisms underlying UM tumorigenesis. Based on their roles, miRNAs are characterized as either oncogenic or tumor suppressive. This review focuses on the roles of miRNAs in UM tumorigenesis, diagnosis, and prognosis, as well as their therapeutic potentials. Particularly, the actions of collective miRNAs are summarized with respect to their involvement in major, aberrant signaling pathways that are implicated in the development and progression of UM. Elucidation of the underlying functional mechanisms and biological aspects of miRNA dysregulation in UM is invaluable in the development of miRNA-based therapeutics, which may be used in combination with conventional treatments to improve therapeutic outcomes. In addition, the expression levels of some miRNAs are correlated with UM initiation and progression and, therefore, may be used as biomarkers for diagnosis and prognosis.
... AuNPs were employed as a nanocarrier for the delivery of microRNA mimics to restore a physiological miRNAs signature in uveal melanoma [206]. In particular, this strategy was used to increase the levels of two tumor suppressor miRNAs, miRNA-34a and miRNA-144, which play a crucial role in EMT inhibition [207,208]. ...
... In particular, this strategy was used to increase the levels of two tumor suppressor miRNAs, miRNA-34a and miRNA-144, which play a crucial role in EMT inhibition [207,208]. Hence, restoring a standard miRNAs profile using AuNPs led to chemosensitivity and cell death [206]. ...
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Epithelial-mesenchymal transition (EMT) has emerged as a key regulator of cell invasion and metastasis in cancers. Besides the acquisition of migratory/invasive abilities, the EMT process is tightly connected with the generation of cancer stem cells (CSCs), thus contributing to chemoresistance. However, although EMT represents a relevant therapeutic target for cancer treatment, its application in the clinic is still limited due to various reasons, including tumor-stage heterogeneity, molecular-cellular target specificity, and appropriate drug delivery. Concerning this last point, different nanomaterials may be used to counteract EMT induction, providing novel therapeutic tools against many different cancers. In this review, (1) we discuss the application of various nanomaterials for EMT-based therapies in cancer, (2) we summarize the therapeutic relevance of some of the proposed EMT targets, and (3) we review the potential benefits and weaknesses of each approach.
... Oligonucleotides and drugs face some challenges for their optimal delivery in cells and animal models. Particularly, oligonucleotides (e.g., antisense, gapmers, and siRNAs) usually present low stability and suffer from reduced cell internalization and selectivity [1,2] and, for these reasons, transfection reagents such as lipofectamine are usually employed to improve delivery. On the other hand, drugs can be too hydrophobic and require solubilizing molecules (e.g., dimethylsulfoxide [DMSO], ethanol). ...
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Gold nanoparticles (AuNPs) can be used as carriers for biomolecules or drugs in cell culture and animal models. Particularly, AuNPs ease their internalization into the cell and prevent their degradation. In addition, engineered AuNPs can be employed as sensors of a variety of biomarkers, where the electronic and optical properties of the AuNPs are exploited for a convenient, easy, and fast read out. However, in all these applications, a key step requires the conjugation of the different molecules to the nanoparticles. The most common approach exploits the great affinity of sulfur for gold. Herein, we summarize the methods used by our group for the conjugation of different molecules with AuNPs. The procedure is easy and takes around 2 days, where the reagents are slowly added, following an incubation at room temperature to ensure the complete conjugation. Finally, the unbound material is removed by centrifugation.
... Additionally, checkpoint inhibitor immunotherapy fails to stop the progression of metastatic UM [79]. Therefore, radiotherapy with other adjuvant therapies, e.g., target miRNAs (with agomirs or antagomirs), would be of value for the management of UM, whenever the tumor is not extended and enucleation cannot be avoided [80]. Additionally, a modulation of miRNAs through administration of drugs can be hypothesized [41]. ...
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Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults, showing a high mortality due to metastasis. Although it is considered a rare disease, a growing number of papers have reported altered levels of RNAs (i.e., coding and non-coding RNAs) in cancerous tissues and biological fluids from UM patients. The presence of circulating RNAs, whose dysregulation is associated with UM, paved the way to the possibility of exploiting it for diagnostic and prognostic purposes. However, the biological meaning and the origin of such RNAs in blood and ocular fluids of UM patients remain unexplored. In this review, we report the state of the art of circulating RNAs in UM and debate whether the amount and types of RNAs measured in bodily fluids mirror the RNA alterations from source cancer cells. Based on literature data, extracellular RNAs in UM patients do not represent, with rare exceptions, a snapshot of RNA dysregulations occurring in cancerous tissues, but rather the complex and heterogeneous outcome of a systemic dysfunction, including immune system activity, that modifies the mechanisms of RNA delivery from several cell types.
... Notably, Rois et al. [126] published the first study using a GNP loaded mix of four tumor suppressor miRNAs mimics for UM treatment-miR-34a, miR-137, miR-144 and miR-182-which are downregulated in UM cells and have synergistic effects on UM cell viability. Remarkably, conjugation of the unique combination of miRNAs on GNPs has been found to overcome the limitations of these molecules and make UM cells more susceptible to chemotherapeutic SN38 (7-ethyl-10-hidroxycamptothecin, a topoisomerase I inhibitor). ...
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Uveal melanoma (UM) is the most common adult intraocular cancer, and metastatic UM remains deadly and incurable. UM is a complex disease associated with the deregulation of numerous genes and redundant intracellular signaling pathways. As understanding of epigenetic dysregulation in the oncogenesis of UM has increased, the abnormal expression of microRNAs (miRNAs) has been found to be an epigenetic mechanism underlying UM tumorigenesis. A growing number of miRNAs are being found to be associated with aberrant signaling pathways in UM, and some have been investigated and functionally characterized in preclinical settings. This review summarizes the miRNAs with promising therapeutic potential for UM treatment, paying special attention to the therapeutic miRNAs (miRNA mimics or inhibitors) used to restore dysregulated miRNAs to their normal levels. However, several physical and physiological limitations associated with therapeutic miRNAs have prevented their translation to cancer therapeutics. With the advent of nanotechnology delivery systems, the development of effective targeted therapies for patients with UM has received great attention. Therefore, this review provides an overview of the use of nanotechnology drug delivery systems, particularly nanocarriers that can be loaded with therapeutic miRNAs for effective delivery into target cells. The development of miRNA-based therapeutics with nanotechnology-based delivery systems may overcome the barriers of therapeutic miRNAs, thereby enabling their translation to therapeutics, enabling more effective targeting of UM cells and consequently improving therapeutic outcomes.
... Cellular assays [41] were studied using two different cancer cell lines: PANC-1 (ATCC Ò CRL-1469 TM ) and MCF-7 (ATCC Ò HTB-22 TM ). Cells were cultured in DMEM medium with 10% FBS, 1% streptomycin-penicillin and 1% L-glutamine at 37°C in a Binder CB210 incubator (5% CO 2 ). ...
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Hypothesis Superparamagnetic MnxFe3-xO4 nanoparticles are promising materials for applications in biomedicine and other fields. Small variations in the Mn/Fe ratio have a strong impact on the properties of the nanoparticles. Those variations may be caused by the synthesis itself and by common post-synthesis manipulations like surface modification. Experiments Mn-ferrite nanoparticles have been prepared changing systematically the Mn/Fe ratio of the metal precursors and repeating each reaction three times. Nanoparticles were subjected to surface modification with two different and typical molecules to stabilize them in aqueous media. The discrepancy in the Mn/Fe ratios of the precursors with the ones measured after the synthesis and the surface modification have been studied, as well as its impact on the saturation magnetization, blocking temperature, contrast enhancement for magnetic resonance imaging, magnetic heating, and on the cytotoxicity. Findings Mn is incorporated in the nanoparticles in a relatively lower amount than Fe and, as this report shows for the first time, both Mn and Fe ions leach out from the nanoparticles during the surface modification step. The blocking temperature decreases exponentially as the Mn/Fe ratio increases. The transverse and longitudinal relaxation times and the magnetic heating ability change appreciably even with small variations in the composition.
... Cellular assays [41] were studied using two different cancer cell lines: PANC-1 (ATCC Ò CRL-1469 TM ) and MCF-7 (ATCC Ò HTB-22 TM ). Cells were cultured in DMEM medium with 10% FBS, 1% streptomycin-penicillin and 1% L-glutamine at 37°C in a Binder CB210 incubator (5% CO 2 ). ...
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Autophagy is an evolutionary conserved physiological process with a fundamental role during development, differentiation, and survival of eukaryotic cells. On the other hand, autophagy dysregulation is observed in many pathological conditions, including cancer. In particular, tumor growth and progression are accompanied and promoted by increased autophagy that allows cancer cells to escape apoptosis and to proliferate also in harsh microenvironments. It is, therefore, clear that the impairment of the autophagic process may represent a valid strategy to inhibit or reduce cancer growth and progression. Among the plethora of molecular players controlling cancer growth, a group of small endogenous noncoding RNAs called microRNAs (miRNAs) has recently emerged. In fact, miRNAs can act as either oncogenes or oncosuppressors depending on their target genes. Moreover, among miRNAs, miRNA-34a has been connected with both tumor repression and autophagy regulation, and its expression is frequently lost in many cancers. Therefore, enforced expression of miRNA-34a in cancer cells may represent a valid strategy to reduce cancer growth. However, such strategy is limited by the fast biodegradation and short half-life of miRNA-34a and by the lack of an efficient intracellular delivery system. The following review describes the autophagic process and its role in cancer as well as the role of miRNAs in general and miRNA-34a in particular in regulating tumor growth by modulating autophagy. Finally, we describe the use of nanoparticles as a promising strategy to selectively deliver miRNA-34a to tumor cells for therapeutic and diagnostic purposes.
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Over the past decade, more interests have been aroused in engineering protein-based nanoformulations for cancer treatment. This excitement originates from the success of FDA approved Abraxane (Albumin-based paclitaxel nanoparticles) in 2005. The new generation of biocompatible endogenous protein-based nanoformulations is currently constructed through delivering cancer therapeutic and diagnostic agents simultaneously, as named potential theranostics. Protein nanoformulations are commonly incorporated with dyes, contrast agents, drug payloads or inorganic nanoclusters, serving as imaging-guided combinatorial cancer therapeutics. Employing the nature identity of proteins, the theranostics, escape the clearance by reticuloendothelial cells and have a long blood circulation time. The nanoscale sizet allows them to be penetrated deeply into tumor tissues. In addition, stimuli release and targeted molecules are incorporated to improve the delivery efficiency. The ongoing advancement of protein-based nanoformulations for cancer theranostics in recent 5 years is reviewed in this paper. Fine-designed nanoformulations based on albumin, ferritin, gelatin, and transferrin are highlighted from the literature. Finally, the current challenges are identified in translating protein-based nanoformulations from laboratory to clinical trials.
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Background: MicroRNAs (miRNAs) have been shown to function in many different cellular processes, including proliferation, apoptosis, differentiation and development. miR-181a, -181b, -181c and -181d are miR-181 members of the family, which has been rarely studied, especially uveal melanoma. Methods: The expression level of miR-181 family in human uveal melanoma cell lines was measured via real-time PCR (RT-PCR). The function of miR-181 on cell cycle was detected through Flow Cytometry assay. Microarray assay and Bioinformatics analysis were used to find the potential target of miR-181b, and dual-luciferase reporter assays further identified the target gene. Results: MiR-181 family members were found to be highly homologous across different species and their upregulation significantly induces UM cell cycle progression. Of the family members, miR-181b was significantly overexpressed in UM tissues and most UM cells. Bioinformatics and dual luciferase reporter assay confirmed CTDSPL as a target of miR-181b. miR-181b over-expression inhibited CTDSPL expression, which in turn led to the phosphorylation of RB and an accumulation of the downstream cell cycle effector E2F1, promoting cell cycle progression in UM cells. Knockdown CTDSPL using siRNAs showing the same effect, including increase of E2F1 and the progression of cell cycle. Conclusions: MiR-181 family members are key negative regulators of CTDSPL-mediated cell cycle progression. These results highlight that miR-181 family members, especially miR-181b, may be useful in the development of miRNA-based therapies and may serve as novel diagnostic and therapeutic candidate for UM.
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Introduction Treatment of unresectable liver metastases (LM) from uveal melanoma (UM) remains a major clinical challenge. Systemic chemotherapy and chemoimmunotherapy regimens extrapolated from cutaneous melanoma are considered to be ineffective in therapy of metastases from uveal melanoma. Studies suggest that the progression of hepatic metastases rather than the primary tumor or metastases in other organs determines survival. Case report We report a case of transarterial chemoembolization of 57-year-old man diagnosed with unresectable liver metastases from uveal melanoma with irinotecan eluting beads. Therapy resulted in long progression free survival and overall survival, 41 months and 45 months after diagnosis of metastatic disease respectively. Patient did not experience any major side effects of the therapy. Follow-up CTs indicate stable disease in mRECIST criteria and partial response in CHOI criteria. Conclusions Transarterial chemoembolization with drug eluting beads loaded with irinotecan may be an effective treatment of unresectable liver metastases from uveal melanoma.
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