Abstract
Tumor spheroids are important model systems due to the capability of
capturing in vivo tumor complexity. In this work, the experimental
design of metabolomics workflows using three-dimensional multicellular
tumor spheroid (3D MTS) models is addressed. Non-scaffold based
cultures of the HCT116 colon carcinoma cell line delivered highly
reproducible MTSs with regard to size and other key parameters (such as
protein content and fraction of viable cells) as a prerequisite.
Carefully optimizing the multiple steps of sample preparation, the
developed procedure enabled us to probe the metabolome of single MTSs
(diameter range 790 ± 22 µm) in a highly repeatable manner at a
considerable throughput. The final protocol consisted of rapid washing
of the spheroids on the cultivation plate, followed by cold methanol
extraction. ^13C enriched internal standards, added upon extraction,
were key to obtaining the excellent analytical figures of merit.
Targeted metabolomics provided absolute concentrations with average
biological repeatabilities of <20% probing MTSs individually. In a
proof of principle study, MTSs were exposed to two metal-based
anticancer drugs, oxaliplatin and the investigational anticancer drug
KP1339 (sodium trans-[tetrachloridobis(1H-indazole)ruthenate(III)]),
which exhibit distinctly different modes of action. This difference
could be recapitulated in individual metabolic shifts observed from
replicate single MTSs. Therefore, biological variation among single
spheroids can be assessed using the presented analytical strategy,
applicable for in-depth anticancer drug metabolite profiling.
Keywords: multicellular tumor spheroids, metabolomics, metallodrugs,
oxaliplatin, KP1339, method development, LC-MS, IT-139
1. Introduction
Three-dimensional multicellular tumor spheroids (3D MTSs) emerged as
essential tools in cancer research with the aim of increasing the
efficiency of oncologic drug development. Indeed, MTSs provide a cancer
model of intermediate complexity, not replacing animal models entirely,
but constituting a substantial improvement compared to two-dimensional
(2D) monolayer cell cultures [[32]1,[33]2]. 3D MTSs grown from
established cancer cell lines resemble more closely early-stage
avascular tumors than 2D monolayer cell cultures in many aspects. For
example, nutrient and oxygen concentration gradients as present in
tumors are established in 3D MTS models, which in turn results in a
concentration of proliferating cancer cells in the outer layers of the
MTS, while in the inner zone, deprived of nutrients and oxygen,
necrotic cells accumulate (depending on the MTS size). In addition,
viable quiescent cells are found in a transition zone between the
necrotic core and outer layer of proliferating cells [[34]3]. This
inhomogeneity is an important feature of in vivo tumors, which 2D
monolayer cell cultures fail to recapitulate as they predominantly
contain normoxic, actively proliferating cells [[35]2,[36]4]. Many
anticancer drugs exert their cytotoxicity against proliferating cells,
with quiescent cells evading the treatment [[37]5]. Thus, a model
system such as 3D MTSs, which involve quiescent cells, is of utmost
importance.
Another key aspect is the fact that the three-dimensionality
intrinsically affects the cell morphology (rather round instead of
stretched-out on a plastic surface), which relates to cell-to-cell
contacts, stimuli exerted by cell surface receptors, and, ultimately,
transcription and protein expression levels [[38]6]. Furthermore,
reduced oxygen levels and hypoxia lead to the generation of reactive
oxygen species (ROS) and hypoxia-inducible factor-1 (HIF-1)
stabilization, which is a major transcription factor responsible for
metabolic transformation and tumor progression
[[39]7,[40]8,[41]9,[42]10].
In the recent past, the combination of cancer models with cutting edge
–omics type of analysis showed to be a powerful approach for generating
new hypotheses regarding the prediction of drug susceptibility, drug
resistance, and mode of action [[43]11,[44]12]. This was accompanied by
a reemerging interest in cancer metabolism [[45]13]. Metabolic
signatures are accepted as the closest proxy for a phenotype
[[46]14,[47]15]. One of the biggest hopes in cancer metabolomics is the
discovery of molecular signatures with predictive power in cancer
therapy [[48]16]. As a consequence of this renewed interest in
metabolism, dedicated workflows were introduced, addressing the needs
of preclinical and clinical studies [[49]17,[50]18,[51]19]. Cancer cell
model studies required the development and validation of multi-step
sample preparation protocols [[52]20]. While today metabolomics
experiments with 2D monolayer cell cultures are routine, sample
preparation protocols for 3D MTSs are rarely discussed in detail. Up to
date, only a few reports on metabolomics in 3D MTS models exist. The
studies involved a range of LC-MS-based metabolomics workflows
including lipidomics and fluxomics applications
[[53]21,[54]22,[55]23,[56]24,[57]25]. Despite showing the power of
combining advanced models such as 3D MTSs and metabolomics, the
validation of sample preparation was not addressed comprehensively.
Even a detailed description of the experimental design (e.g., whether
MTS samples were pooled for the analysis or how gels established in 3D
culture were removed upon metabolome extraction) was lacking.
In this work, we focus on the experimental design enabling metabolomics
in 3D MTSs, using non-scaffold based cell cultures grown on ultra-low
attachment plates from cell suspensions. This approach avoids 3D
scaffolds or gels for obtaining a three-dimensional structure, which
facilitates metabolomics measurements. More specifically, sample
preparation protocols are developed with the goal to provide a
validated procedure capable of probing single MTSs; at the same time
not compromising on analytical throughput and, thus, the number of
biological replicates. The validity of the established preclinical
tool-set was shown for the example of metal-based anticancer drug
development. Metal-based drugs are a prime example since a clear cut
mechanism remains to be elucidated despite extensive clinical use and
fundamental research [[58]26,[59]27]. In fact, how the drugs exert
their cytotoxicity differs even for the three clinically approved
platinum(II) drugs [[60]28,[61]29,[62]30]. Although massive research
efforts resulted in a plethora of promising candidate drugs, the
failure rate upon translation into clinics was/is extremely high for
metal-based anticancer drugs [[63]31]. Discovering potential metabolic
pertubations specific for drug exposure, by measuring molecular
signatures in advanced 3D MTS models, bear the potential of
accelerating discoveries with regard to the mode of action and
susceptibility towards the drug. In this work, a 3D human colon cancer
model was studied. Metabolic shifts, as exerted by the clinically
established oxaliplatin and KP1339, a promising candidate drug, were
investigated.
2. Results
2.1. Establishment and Validation of Sample Preparation Procedures Suitable
for Probing the Metabolome of Spheroids
2.1.1. Determining the Minimal Number of MTS Required for Metabolomics
Experiment
A uniform size distribution of MTSs was obtained by using the colon
cancer model HCT116; seeding of 3 × 10^3 cells and cultivation for 4
days following the suspension-based procedure described in the
experimental section. The average resulting spheroid diameter was 560 ±
30 µm (n = 56). Suspension-based 3D cultivation enabled a
straightforward establishment of metabolomics workflows otherwise
hampered by tedious washing procedures in hydrogel and other
scaffold-based techniques. The investigated size range amounted to 9.9
× 10^3 ± 3.9 × 10^3 cells with 81% ± 5% viable cells ([64]Table S1,
“cellNumbers” sheet). The estimation was based on disaggregating the
MTS with a recombinant enzyme reagent, staining with a dye, and
subsequent measurement with a flow cytometer to determine cell counts
and viability in the final suspension.
In order to exclude poor extraction efficiencies for MTSs in this work,
metabolomics experiments resorted to boiling ethanol extractions,
implementing the yeast-derived fully ^13C labeled (U^13C) internal
standard. More specifically, extractions were carried out on single
spheroids (three biological replicates, N = 3) and pooled spheroid
samples, i.e., pools of 5 (N = 3), 10 (N = 3) and 15 spheroids (N = 2),
respectively. The applied boiling ethanol protocol is the established
gold standard in yeast metabolomics, offering nearly 100% extraction
efficiency and recovery for a large panel of primary metabolites
[[65]32,[66]33]. In cancer cell monolayer cultures, less tedious cold
extraction protocols are established, which demand thorough validation
when applied to MTS investigations [[67]20,[68]34].
Targeted metabolomics measurements were performed implementing
reversed-phase chromatography coupled to tandem mass spectrometry using
a 100%-wettable column providing enhanced separation for branched amino
acids and organic acids [[69]35]. Metabolite abundances relative to the
isotopically enriched internal standard, i.e., relative response
ratios, were addressed in single MTS extractions versus pooled
extractions. The validation considered 29 metabolites (amino acids,
organic acids, nucleotides, nucleosides). Single spheroid extractions
resulted on average in repeatabilities of 28%, while pooled samples
showed repeatabilites of 17% and 32% for 5 and 10 MTSs pooled,
respectively ([70]Table S1, “metabolitesExtract” sheet). In order to
evaluate whether the number of pooled MTSs correlated with cell number
and protein content, the cell pellets remaining upon boiling ethanol
were submitted to acidic hydrolysis. Absolute amounts of 8 amino acids
(alanine, arginine, glycine, histidine, lysine, phenylalanine, proline,
tyrosine) were determined. The selected amino acids were quantitatively
recovered [[71]36] by the applied sample preparation protocol and were
used for traceable protein quantification. The obtained absolute amino
acid amounts displayed a strong linear correlation with the number of
MTSs ([72]Table S1, “aminoAcids_pellet”, and [73]Figure A3). This
linear correlation (coefficient of determination above 0.99) was a
prerequisite for further evaluation of metabolome abundances in single
versus pooled MTS samples, depending on the assumption of linear
correlation between cell number, protein concentration, and the number
of spheroids (for a uniformly sized MTS sample set). Upon transforming
the linear regressions of metabolite abundances from intracellular cell
extracts versus number of spheroids by normalizing the metabolite
abundances to average abundance found in single MTS samples, the
parameters of the linear regression became comparable: assuming an
ideal scenario (as represented by 100% extraction efficiency and
recovery regardless of whether pooled or single samples are
investigated) for these plots, a slope of 1 is expected and can be
observed for the investigated metabolites, the ideal case of slope of 1
is nearly met ([74]Table S1, “regressionNormalized”, [75]Figure A2 and
[76]Figure A3). On average, the slope of the normalized regression is
1.11 and the average coefficient of determination is 0.94. Overall, the
strong linear correlation of the relative responses with the number of
uniform-size spheroids indicates that metabolomics experiments, even
from single spheroids, are highly repeatable.
These findings are captured in a correlation matrix ([77]Figure 1),
which reveals that most of the investigated metabolites have a strong
positive correlation with the amino acids measured from the
corresponding pellet as well as from the number of MTSs they were
extracted from.
Figure 1.
[78]Figure 1
[79]Open in a new tab
Correlation matrix of number of multicellular tumor spheroids (MTS),
relative responses (^12C/^13C) of 29 metabolites from boiling ethanolic
extracts with ^13C internal standardization, absolute amounts of 8
amino acids [nmol] measured from hydrolyzed pellet (indicated with the
“pellet” suffix) from samples containing 1 (N = 3), 5 (N = 3), 10 (N =
3), and 15 MTS (N = 2) from the same population. Most metabolites show
a strong correlation with all the amino acids hydrolyzed from the
pellet and the number of MTSs.
2.1.2. Speeding Up the Sample Preparation
In the next step, alternative extraction protocols were addressed with
the aim of increasing analytical throughput without compromising
overall accuracy. The workflow based on boiling ethanol, involved the
transfer of MTSs into tubes, three washing steps, and quenching by
flash freezing with liquid nitrogen, which was followed by hot
extraction. As a drawback, the procedure is rather time-consuming and
on top of that, only a very limited number of MTS samples can be
prepared in parallel. In fact, during collection and washing, only a
limited number of spheroids can be handled at a given time. Only after
the handled samples are quenched can be the next MTS collected. This
often implies different durations of incubation at uncontrolled
temperatures and CO[2] partial pressure, which might lead to systematic
metabolic biases. Thus, it is key to decrease the time until quenching,
as only a high degree of synchronization enables reasonable study sizes
(number of replicates) and investigations of cells upon multiple
metabolic perturbations [[80]20].
In this work, the reduction of cell manipulations was addressed as
follows: First, comparative metabolomics experiments compared different
strategies regarding the first washing steps. Instead of transferring
MTSs to tubes for repeated washing, single-step washing was performed
on the cultivation plate directly. (For the sake of clarity the first
approach was denoted as “OFF”, while the single washing step on the
well-plate was denoted as “ON”.) Second, the extraction procedure was
optimized. More specifically, the hot extraction (boiling ethanol,
“BE”) was compared to a cold methanol-based extraction (“CM”). In the
past, it was shown that the harsh conditions of hot ethanol were not a
stringent requirement for monolayer mammalian cell cultures [[81]34],
where mild cold extractions proved to be valid strategies.
The already-mentioned studies [[82]18,[83]19,[84]20,[85]21,[86]22] with
3D cultures involving LC-MS-based metabolomics workflows, including
lipidomics and fluxomics applications utilized washing of the samples
and organic solvents (methanol, acetonitrile) with an aqueous
proportion for extraction, mostly in cold state. To the best of our
knowledge, a thorough evaluation of 3D cancer cell models is still
lacking.
[87]Figure 2 depicts the two sample preparation strategies involving
washing, quenching, internal standardization using ^13C internal
standards and extraction. The validation experiments were carried out
using replicates of single spheroids. The cultivation was designed to
produce large spheroids (diameter = 744 ± 15 µm, 4-day long
cultivation, and 10^4 cells seeded) representing a “worst-case
scenario” for efficient extraction. Four different sample preparation
strategies were compared, namely OFF and ON plate washing, both
followed by either BE or CM, respectively, all involving U^13C internal
standardization upon extraction. The extracts were measured as
described in [[88]37]. In brief, a hydrophilic interaction liquid
chromatography (HILIC) separation at pH 4 was used combined with
high-resolution MS. Targeted absolute quantification of 26 metabolites
based on external calibration with internal standardization served as
validation of the sample preparation.
Figure 2.
[89]Figure 2
[90]Open in a new tab
The study design for speeding up the sample preparation. Two different
washing procedures (“ON”: washing the multicellular tumor spheroid once
with PBS on the 96-well plate vs. “OFF” washing three-times in an
Eppendorf-tube after transfer from cultivation well) and two
alternative extractions (boiling ethanol vs. cold methanol extraction)
were tested on large multicellular tumor spheroids (744 ± 15 µm), which
in combination resulted in four sample groups.
In addition to the biological repeatability, the technical
repeatability was assessed by injections of a pooled sample over the
measurement series (denoted as QC). [91]Figure 3 summarizes the
quantitative metabolome data. Overall, it was found that the
accelerated workflow with the reduced washing steps was key to improve
repeatability, as this resulted in the lowest average relative standard
deviations (18% and 19% for ON/BE and ON/CM, respectively. See
[92]Table 1.). Moreover, it could be shown that the cold methanol (CM)
extraction was comparable to boiling ethanol (BE) in terms of
extraction efficiency, as the quantitative values were in good
agreement (within their uncertainty).
Figure 3.
[93]Figure 3
[94]Open in a new tab
Barplots of the absolute amounts (pmol) of 26 selected metabolites
extracted from single multicellular tumor spheroids with four different
sample preparation method as well as two washing procedures (“ON”:
washing the multicellular tumor spheroid once with PBS on the 96-well
plate vs. “OFF” washing three times in an Eppendorf-tube after transfer
from the culture plate) and two alternative extractions (boiling
ethanol, “BE” vs. cold methanol extraction “CM”). OFF/BE (N = 6), ON/BE
(N = 4), OFF/CM (N = 5), ON/CM (N = 7) Measurement with liquid
chromatography (HILIC separation) high-resolution Orbitrap mass
spectrometry. All extractions utilized U^13C internal standardization.
For the abbreviations of compounds, see [95]Appendix A.
Table 1.
Average relative standard deviations based on absolute concentrations
of 26 analytes in four investigated sample preparation strategies for
single multicellular tumor spheroids. The four different sample
preparation methods involved two washing procedures (“ON”: washing the
multicellular tumor spheroid once with PBS on the 96-well plate vs.
“OFF” washing three times in an Eppendorf tube after transfer from
cultivation well) and two alternative extractions are combined (boiling
ethanol “BE” vs. cold methanol extraction “CM”). OFF/BE (N = 6), ON/BE
(N = 4), OFF/CM (N = 5), ON/CM (N = 7) One pooled sample from
independent OFF/CM and ON/CM samples, QC was a mixture of one OFF/CM
and ON/CM sample and was measured as quality control throughout the
measurement (N = 4). Measurement was performed with liquid
chromatography (HILIC separation) high-resolution Orbitrap mass
spectrometry. All extractions utilized U^13C internal standardization.
Sample Preparation Average RSD [%]
OFF/BE 34%
ON/BE 19%
OFF/CM 24%
ON/CM 18%
QC 7%
[96]Open in a new tab
Thus it can be concluded that the protocol ON/CM offers a fast and
convenient fit-for-purpose method to generate 60 biological replicates
in parallel. The 60 replicates were treated and washed within a few
minutes (depending on the operator) and then were quenched at the same
time by flash freezing them with liquid nitrogen. Overall, a 96-well
plate accommodates up to 60 spheroid cultivations since wells at the
edges are not used to avoid the “edge effect” (artifacts due to
inhomogeneity in evaporation rates).
2.2. Assessing Metabolic Shifts in Single MTS Exposed to Metal-Based
Anticancer Drugs
Finally, the optimized ON/CM workflow was applied in a proof of
principle study addressing metabolic perturbations in single MTSs due
to exposure of metal-based anticancer drugs. Again human colon cancer
cells (HCT116) were selected. The spheroids were grown from 10^4 cells
for 8 days (790 ± 22 µm). Two drugs of distinctly different proposed
modes of action were investigated, namely the clinically established
oxaliplatin and the investigational anticancer drug sodium
trans-[tetrachloridobis(1H-indazole)ruthenate(III)] (denoted as
KP1339). While oxaliplatin exerts its cytotoxic effects through DNA
damage and ribosome biogenesis stress [[97]38], there is growing
evidence that KP1339 is not a DNA-damaging agent but its primary mode
of action is through endoplasmic reticulum stress [[98]39].
Furthermore, KP1339 shows a prodrug nature, as it is thought to be
preferentially reduced in the more reductive milieu of solid tumors to
the active Ru(II) form. Finally, while oxaliplatin is considered a bona
fide immunogenic cell death inducer [[99]40], KP1339 also exhibits the
hallmarks of immunogenic cell death [[100]41,[101]42].
The choice of incubation time and drug concentration was based on
previous studies using monolayer cultures, which showed prominent
metabolomic shifts only after 24 h exposure to sub-cytotoxic drug
concentrations [[102]37]. Specifically, the applied concentrations were
20 and 200 µM for oxaliplatin and KP1339, respectively. As the
dissolution and thus the application of KP1339 involved dimethyl
sulfoxide (DMSO), an additional control group resembling the DMSO
background in the medium was included. [103]Figure A4 and [104]Table S3
(protein_µg sheet) show the protein concentrations obtained in
replicate single MTSs for the different conditions under investigation.
The plotted protein content was assessed by measuring the concentration
in the remaining cell pellets of the individual MTS samples. As can be
readily observed, oxaliplatin treatment resulted in a minor reduction
of the overall protein content; otherwise the average mean protein
concentration was comparable (within its uncertainty) for all
conditions, pointing towards comparable growth rates. On top of that,
the data clearly showed that using the average protein content of
parallel MTS cultivations would compromise the quality of comparative
metabolomics experiments. When aiming at the investigation at single
MTS level, it is a requirement to normalize metabolic abundances to the
corresponding protein content obtained from the same sample. Finally,
the ON/CM sample preparation procedure optimized for single MTS
analysis comprised the addition of yeast ^13C standards. The
measurements relied on hydrophilic interaction chromatography—Orbitrap
MS and included external calibrants with internal standards for a large
panel of metabolites [[105]37]. Implementing the internal
standardization approach together with the use of high-resolution
Orbitrap MS enabled us to perform targeted and non-targeted
metabolomics in a single analytical run.
As suggested by the standardization initiative of the Metabolomics
Society, pooled MTS extracts were used as quality control samples
[[106]43,[107]44]. Combining positive and negative data, absolute
concentration values were obtained. Only analytes with technical
repeatability obtained from repeated injections of the QC sample below
30% were considered, which resulted in a total number of 58 remaining
analytes. The average relative standard deviation (RSD) for the 58
metabolites was 6.5% for the technical replicates and 13% for
biological replicates considering each four group ([108]Table S3,
pmolMetabolite sheet). The average RSD after the protein content
normalization was 15.2% ([109]Table S3, pmolMetabolitePerµgProtein
sheet).
Unsupervised statistical analysis of the targeted, protein content
normalized data revealed that there is group clustering according to
the type of drug treatment in the case of KP1339 treatment (PCA plot in
[110]Figure A5 and heat map in [111]Figure 4). The KP1339-treated
samples showed significant regulation of 19 metabolites (proline,
propionyl-L-carnitine, ribulose-5-phosphate/ribose-5-phosphate,
adenosine monophosphate, lactate, aspartate, reduced glutathione,
guanosine monophosphate, glutamine, inosine, glutamate, N-acetylserine,
adenosine, dihydroxyacetone phosphate, asparagine, mevalonic acid,
alanine, and sarcosine; [112]Table S3, (“significant_cmpds_KP1339”)
compared to six metabolites (adenosine, guanosine monophosphate,
cytidine monophosphate, nicotinamide adenine dinucleotide phosphate
(oxidized), uridine monophosphate, and uracil; from [113]Table S3
“significant_cmpds_oxaliPt”) in oxaliplatin-treated samples. The
stronger metabolic change caused by the ruthenium drug (KP1339)
treatment compared to oxaliplatin treatment was further confirmed by
hierarchical cluster analysis, where KP1339-treated samples were
separated from both controls, which was not the case for
oxaliplatin-treated samples ([114]Figure 4). Overall, the fact that we
see a stronger effect in the metabolome with KP1339 treatment than with
oxaliplatin treatment is not surprising, since in a study with
monolayer cell cultures of the same cell line, we observed considerably
milder effects with oxaliplatin, as well [[115]37].
Figure 4.
[116]Figure 4
[117]Open in a new tab
Heatmap displaying absolute amounts of metabolites normalized to total
protein content (pmol/µg) of samples from single 3D MTS. Spheroids were
treated for 24 h with either 200 µM KP1339, 20 µM oxaliplatin (OxPt),
medium (CntrlOxPt) or medium with 0.5% DMSO (CntrlKP1339). Numbers in
sample names refer to independent biological replicates. Extraction
with cold methanol and internal standardization, measurement by HILIC
high-resolution Orbitrap MS.
Pathway enrichment analysis using targeted data revealed that
oxaliplatin exposure affected purine metabolism (GMP and adenosine
being most significantly down-regulated; glutamine, IMP, inosine,
guanosine, guanine, adenine, and AMP were also affected) and pyrimidine
synthesis (UMP and CMP being most significantly down-regulated; but
cytidine, uracil, glutamine and thymine were also affected), which is
in agreement with the accepted mechanism of action of DNA targeting
[[118]45] ([119]Figure 5a, [120]Table S3,
“pathways_pathways_oxaliplatin”). These findings were also supported by
other significant metabolic shifts involving DNA building blocks. Other
retrieved pathways could be related to redox stress such as the pentose
phosphate pathway, glutathione metabolism, and nicotinamide metabolism,
but also purine metabolism, which is in accordance with the ribosome
biogenesis stress only recently proposed as the primary reason for the
cytotoxic effect [[121]38]—a hypothesis generated based on
transcriptomic analysis. In our work, the measurement of the metabolome
provided additional evidence supporting this hypothesis, as the levels
of many RNA monomers were significantly altered upon drug exposure
([122]Table S3, “pathways_pathways_oxaliplatin”), and RNA being one of
the major component of ribosomes. This was further supported by the
fact that the “aminoacyl-tRNA biosynthesis” pathway was also among the
affected pathways (see [123]Table S3 for the complete list). Finally,
the MetaboAnalyst 4.0 Pathway Analysis module [[124]46] revealed
another interesting pathway to be further investigated, namely, the
“pantothenate and CoA biosynthesis” pathway (through uracil
downregulation). A recent study [[125]29] addressed signature genes for
patients responding to oxaliplatin therapy by machine learning. Among
the most accurate signature genes for oxaliplatin treatment was PANK3
which encodes for pantothenate kinase, a key regulatory enzyme in the
biosynthesis of coenzyme A (CoA). A seminal study correlating
transcriptomics and metabolomics for the NCI60 cell line panel showed
the involvement of the TCA cycle, pyruvate metabolism, lipoprotein
uptake and nucleotide synthesis in platinum sensitivity
[[126]47,[127]48]. Again, the metabolomics data of this study support
the generated hypothesis as the TCA cycle, purine and pyrimidine
metabolism, and pyruvate metabolism were indicated by pathway
enrichment analysis.
Figure 5.
[128]Figure 5
[129]Open in a new tab
KEGG pathways with MetaboAnalyst affected by oxaliplatin treatment (a)
and KP1339 treatment (b) using pathway enrichment and topology analysis
with the MetaboAnalyst pathway analysis module.
The hypothesized difference in the mode of action of the two
investigated drugs was reflected by the distinct metabolic shifts,
which were observed upon exposing MTSs to the candidate ruthenium drug
KP1339. There are indications that this drug is a GRP78 inhibitor, an
ER stress sensing chaperone [[130]39,[131]49]. It not only induces ER
stress and unfolded protein response, but it has also been shown that
it exhibits the hallmarks of immunogenic cell death, calreticulin
exposure, and ATP secretion among others [[132]42]. Less is known about
the metabolic effects of this compound. In this work, we could
individuate the impact on biochemical pathways related to redox stress:
glutathione metabolism (glutathione, oxidized glutathione and NADP+ are
up-, glutamate down-regulated), purine metabolism, pentose phosphate
pathway (ribulose 5-phosphate/ribose 5-phosphate down-regulated), which
could be explained by the hypothesized reduction of the drug. Redox
stress and elevation of ROS protective proteins [[133]42,[134]50] were
confirmed by previous proteomics studies. Finally, pathways such as
glycerophospholipid metabolism (strong choline down-regulation) and
various amino acid metabolism-related pathways were pinpointed
(glutamine and glutamate metabolism, alanine, aspartate and glutamate
metabolism, arginine biosynthesis). Altered amino acid synthesis is
related to the fact that the unfolded protein response induces changes
in the expression of genes of amino acid transport and synthesis
[[135]51].
3. Discussion
In this work, we present a carefully optimized sample preparation
workflow for metabolomics experiments in 3D MTS samples. To the best of
our knowledge, this is the first study performing extraction
optimization (n
[MATH: ≥ :MATH]
4) for single tumor spheroids. The comparison of different extraction
strategies, namely ON/BE, OFF/BE, OFF/CM, ON/CM, revealed that cold 80%
methanol extraction with a single washing step on the plate was most
promising for single tumor spheroid analysis. Using the presented
workflow increased throughput and convenience as well as resulted in
superior analytical figures of merit including the highest analyte
concentration and lowest RSDs observed for 26 metabolites in the pmol
to nmol range. The sample preparation strategy is limited to spheroids
with diameters >400–500 µm and with maximum diameters of 900–1000 µm
due to potential error-prone handling and growth limitation,
respectively. Other studies in tumor spheroid analysis were performed
using various culturing and extraction protocols such as (1) gelatinous
cultivation of spheroids and methanol-water extraction [[136]21], (2)
magnetized cells to form 3D cultures and cold acetonitrile, 70%
methanol or 80% acetone extraction [[137]22], (3) gel-based ultra-low
attachment plates of 20–25 spheroids per sample followed by
derivatization and chloroform/methanol extraction [[138]23]. Overall,
most –omics mass spectrometry-based studies on tumor spheroid analysis
rely on extraction strategies with cold organic solvents such as
methanol, ethanol or isopropanol [[139]21,[140]22,[141]23,[142]24].
This is consistent with our tumor spheroid workflow based on
non-scaffold based cultivation on ultra-low attachment plates and the
optimized cold 80% methanol extraction with a single washing step. The
obtained strong linear correlation with the number of (uniform-size)
spheroids and relative responses indicates highly repeatable
metabolomics readout from single spheroids. The use of ^13C labeled
standards for quantification represents a significant advance compared
to label-free quantification approaches as the internal standardization
allowed to account for sample losses during sample preparation, storage
and measurement. Additionally, ^13C metabolites represent an
interesting normalization strategy for comprehensive non-targeted
metabolomics experiments on tumor spheroids. The novel procedure
enabled us to probe individual spheroids with excellent biological
repeatability (average RSD of 18%) in a considerable throughput. An
experiment with a single 96-well plate allows the investigation of up
to 60 single spheroids (since wells at the edges are not used).
However, high throughput analysis is feasible as there is no
theoretical limit in the number of biological replicates or
investigated conditions when multiple plates are combined.
The proposed methodology enabled us to investigate different conditions
of 3D human cancer models in a parallelized manner comparable to the
degree obtained in 2D monolayer cell cultures. The applicability of the
method was shown on the example of the metal-based anticancer drugs
KP1339 and oxaliplatin. Comparison of the two drugs (n
[MATH: ≥ :MATH]
4) revealed stronger metabolic changes caused by the ruthenium drug
(KP1339) treatment compared to oxaliplatin treatment, which is
consistent with the literature on monolayer cell cultures [[143]37]. We
observed significant metabolic changes with purine and pyrimidine
pathways after oxaliplatin treatment, which is in agreement with the
accepted mechanism of action of DNA targeting of oxaliplatin [[144]45]
and consistent with the proposed induction of ribosome biogenesis
stress [[145]38]. Further biological interpretation of the data is
beyond the scope of this work.
The presented optimized sample preparation workflow is the ideal
starting point for single spheroid metabolomics experiments. A
relatively large proportion of clinically tested drugs fail in phase 3
of the trials due to insufficient efficacy or unacceptable toxicity,
which means a substantial financial loss [[146]6,[147]52]. Since tumor
spheroids are three-dimensional models derived from established human
cell lines, it is possible to capture more of the complexity of a tumor
compared to standard 2D monolayer cultures [[148]1]. Ultimately,
metabolomics studies on tumor spheroids could be integrated into
anticancer drug screening, helping to prevent late clinical failure of
drug candidates. Future studies will focus on in-depth metabolomics
analysis of different anticancer drugs effects using tumor spheroids.
Overall, we strongly believe that drug development will benefit
significantly from the new discovery tools provided by the unique
combination of 3D MTSs and metabolomics.
4. Materials and Methods
4.1. Cell Culture
4.1.1. Cultivation of Spheroids
The human colon carcinoma cell line HCT116 was kindly provided by
Brigitte Marian, Institute of Cancer Research, Department of Medicine
I, Medical University of Vienna. HCT116 cells were cultured as adherent
monolayers in 75 cm^2 flasks (StarLab Germany) in McCoy’s 5a medium
(Sigma-Aldrich) supplemented with 10% fetal calf serum (FCS) (BioWest)
and 4 mM L-glutamine without antibiotics at 37 °C (StarLab) under a
humidified atmosphere containing 5% CO[2]. All cell culture media and
reagents were obtained from Sigma-Aldrich (Vienna, Austria), and all
plastic dishes, plates and flasks were from StarLab (Germany) unless
stated otherwise. For spheroid generation, HCT116 cells were harvested
from culture flasks by trypsinization, resuspended in their respective
supplemented medium, and seeded in 200 µL on ultra-low attachment
round-bottom 96-well plates (Nunclon Sphera^TM, Thermo Fisher
Scientific). To avoid effects caused by evaporation, the outermost
wells were not used for spheroid production and filled with 200 mL of
PBS instead. In the experiment where 1, 5, 10, 15 spheroids were
investigated, the spheroids were seeded at a density of 3 × 10^3 viable
cells per well in 200 µL. Plates were incubated at 37 °C with 5% CO[2]
for 96 h to allow spheroid formation. In the experiment where washing
procedures and extraction methods were compared, 10 × 10^3 viable cells
were seeded in 200 µL medium and cultivated at 37 °C with 5% CO[2] for
96 h to allow spheroid formation. In the proof of concept experiment
with metallodrugs, 10 × 10^3 viable cells were seeded in 200 µL medium
and cultivated at 37 °C with 5% CO[2] for 96 h to allow spheroid
formation, and then 100 µL medium was aspirated and exchanged for fresh
medium. After 192 h (8 days) of total incubation, the diameter of the
spheroids was measured, 100 µL of medium was exchanged for the
respective treatment solution and 24 h of incubation followed either
with the drug or with control medium. KP1339 was first dissolved in
DMSO, and stock solutions were prepared in the respective medium with
FCS and glutamine supplement. Oxaliplatin was dissolved freshly before
the experiments in the supplemented medium only.
4.1.2. Microscopy
An Olympus CKX41 (Olympus, Vienna, Austria) microscope was used to
measure the diameter of the spheroids in horizontal and vertical
directions with cellF 2.7 imaging software and the average diameter was
calculated.
4.1.3. Cell Number Estimation
Spheroids grown from 3 × 10^3 viable cells for 96 h were transferred
from the plate to Eppendorf-tubes as single spheroids. After washing
once with PBS, dissociation in 100 µL TrypLE Express (Gibco, Vienna,
Austria) followed for 15 min at 37 °C. Samples were thoroughly pipetted
to disperse any remaining cell aggregates, and 100 µL colorless McCoy’s
5a medium (Sigma-Aldrich) with 2% FCS were added followed by 0.8 mL
Guava ViaCount reagent (Merck/Millipore, Germany). Samples were
measured immediately by using a Guava Soft flow cytometer
(Merck/Millipore, Darmstadt, Germany).
4.2. Methods for Determining the Minimal Number of MTS Required for a
Metabolomics Experiment
4.2.1. Sampling 1, 5, 10, 15 Multicellular Tumor Spheroids
3D MTS were seeded with 3 × 10^3 cells in 200 µL McCoys medium and
cultivated for 4 days, reaching a diameter of 560 ± 30 µm. Upon
extraction, spheroids were transferred by pipetting to a Petri-dish,
where little droplets of PBS had been pre-pipetted. Each spheroid was
transferred sequentially into three fresh PBS droplets corresponding to
three washing steps. After that, each spheroid was transferred into a
conical screw cap vial (Bioquote Limited, York, United Kingdom). The
vial was put into liquid nitrogen in order to quench the enzymatic
activity and put on wet ice, while more spheroids were collected. As
soon as the last spheroid for a given sample was washed and sampled to
the vial, it was put on −20 °C. When all the samples were collected,
they were stored at −80 °C until boiling ethanol extraction.
4.2.2. Internal Standardization
A fully ^13C labeled yeast extract of Pichia pastoris (2 billion cells)
from ISOtopic Solutions e.U., (Vienna, Austria) was reconstituted in 2
mL of water and added in equal amounts to the samples. The final
dilution of the internal standard for the measurement was 1:10.
4.2.3. Boiling Ethanol Extraction for 1×-5×-10×-15× MTSs
The protocol was implemented from the works [[149]32,[150]33]. Shortly,
75% ethanol was prepared from ethanol, abs. 100%, HPLC grade (Chem-Lab,
Vienna, Austria), H[2]O (Sigma, Vienna, Austria, LC-MS-grade), and
pre-heated in a clean glass beaker in a 95 °C water bath. The 50 µL of
U^13C internal standard was added to samples. Once the ethanol–water
was boiling in the glass beaker, the hot extraction solvent was added
to the conical screw cap vials (Bioquote Limited, York, United Kingdom)
to dilute the internal standard amount 1:10 and, subsequently, a 5-min
incubation in the 95 °C water bath followed. The vials were closed,
vortexed, and centrifuged (14,000 rcf, 4 °C, 5 min). The supernatant
was carefully transferred to an MS-vial (Macherey-Nagel, Vienna,
Austria), without disturbing the pellet. Extracts were evaporated until
dryness. Extracts and resulting pellets were stored at −80 °C until
measurement.
4.2.4. Metabolomics Measurement of Extracts 1×-5×-10×-15× MTSs
Samples were reconstituted in 100 µL LC-MS-grade H[2]O and analyzed
with reversed phase liquid chromatography coupled to high-resolution
Orbitrap mass spectrometry. Waters Acquity HSS T3 (2.1 × 150 mm, 1.8
µm) column was used, mobile phase A was H[2]O (0.1% formic acid), and
mobile phase B was 100% methanol. The following gradient was used at a
flow rate of 0.3 mL min^−1 and 40 °C: 0.0–2.0 min 0% B, 2–6 min 0–40%
B, 6–8 min 40–100% B, 8–11 min 100% B, and at 11.1 min switch to 0% B,
11.1–15 min 0% B. The injection volume was 10 µL. The Vanquish Duo
UHPLC-system (Thermo Fisher Scientific) was used.
High-resolution mass spectrometry was done with a high field Thermo
Scientific™ Q Exactive HF™ quadrupole-Orbitrap mass spectrometer
equipped with an electrospray source. The ESI source parameters were
the following: sheath gas 40, auxiliary gas 3, spray voltage 2.8 kV in
negative and 3.5 kV in the positive mode, capillary temperature 280 °C,
S-Lens RF level 30 and auxiliary gas heater 320 °C. Spectral data were
acquired in profile mode. Resolution = 60.000, mass range = 60–900 m/z,
AGC target 10^6, both in positive and negative polarities.
Quantification was done through the areas of extracted ion
chromatograms of [M+H]^+ and [M-H]^− with 5 ppm mass tolerance on the
U^12C to U^13C ratio.
4.2.5. Acidic Hydrolysis of the Pellet and Amino Acid Analysis
Acidic hydrolysis of the pellet resulting from the boiling ethanol
extraction of samples of 1, 5, 10, and 15 spheroids pooled was based on
a procedure described in detail elsewhere [[151]53,[152]54]. In short,
1 mL 6 M hydrochloric acid (Fluka, TraceSELECT from ≥37%) was added to
the pellets, already in the conical screw cap vials (Bioquote Limited,
York, United Kingdom); screw caps were tightly closed and the samples
were hydrolyzed at 100 °C for 24 h. The hydrolyzed samples were
evaporated to dryness and stored at −80 °C until analysis. Procedural
blanks were also prepared to investigate possible background. Upon
measurement, samples were reconstituted in 1 mL H[2]O. A 1-to-10
dilution was done by taking 50 µL from the sample, adding 50 µL ISTD
and 400 µL acetonitrile. NIST SRM 2389a amino acid standard
(Sigma-Aldrich) was used to prepare an external calibration with
internal standard and achieve absolute concentrations. The eight amino
acids were subject to quantitative extraction and measurement according
to [[153]36] (alanine, arginine, glycine, histidine, lysine,
phenylalanine, proline, tyrosine) were measured with a method described
in detail elsewhere [[154]35]. Shortly, the Agilent Infinity LC-System
coupled to an Agilent 6490 triple quadrupole mass spectrometer was used
with a HILIC separation, Waters Acquity BEH Amide (1.7 µm, 100 × 0.786
mm) column with 10 mM ammonium formate (pH 3.25) as eluent A and 80%
acetonitrile 20% 10 mM ammonium formate (pH 3.25) as eluent B. Multiple
reaction monitoring transitions were acquired in positive polarity.
4.3. Methods for Comparison Boiling Ethanol (BE) and Cold Methanol (CM)
Extraction and Washing Procedures (OFF vs. ON) of 3D MTS
For this experiment, 3D MTS were grown as described above from 10 ×
10^3 cells for 96 h.
4.3.1. Transfer of Spheroids
Sampling and transfer of spheroids were carried out with a 200 µL
(Eppendorf, Vienna, Austria) pipette. The tip of the pipette tip was
cut with a scissor (washed before in methanol:H[2]O 50:50) so that the
opening was slightly enlarged. The spheroid was taken up with the
surrounding solution by the suction generated by the pipette and
transferred from the plate into an Eppendorf tube.
4.3.2. “BE-OFF” Sample Preparation
The spheroids were transferred from the plate into conical screw cap
vials (Bioquote Limited, York, United Kingdom), where they were washed
three times with phosphate-buffered saline (PBS, Sigma-Aldrich, Vienna,
Austria), quenched immediately with liquid nitrogen and stored at −80
°C until extraction. Upon extraction, 20 µL U^13C internal standard was
added as well as 180 µL 75% ethanol and put on 95 °C in the water bath
for 5 min. After 5 min of sonication, samples were vortexed and
centrifuged (14,000 rcf, 5 min, 4 °C) and supernatants transferred into
MS-vials. Samples were measured directly without evaporation.
4.3.3. “CM-OFF” Sample Preparation
The spheroids were transferred from the plate into an Eppendorf tube,
where they were washed three times with PBS and quenched immediately in
liquid nitrogen and stored at −80 °C until extraction. Upon extraction,
20 µL U^13C internal standard was added as well as 180 µL cold 80%
methanol (−20 °C). After 5 min of sonication, samples were vortexed and
centrifuged (14,000 rcf, 5 min, 4 °C) and supernatants transferred into
MS-vials. Samples were measured directly without evaporation.
4.3.4. “BE-ON” Sample Preparation
The medium of spheroids was carefully aspirated by a multichannel
pipette, while spheroids remained in the wells. Subsequently, the
spheroids were washed with 200 µL PBS and quenched by liquid nitrogen.
The spheroids still in the wells were stored at −80 °C until
extraction. Plates were kept on ice during extraction. Upon extraction,
20 µL U^13C internal standard was added to the well, then 80 µL 75%
ethanol (room temperature, not hot yet) was added; in this amount, the
spheroid was transferred to conical screw cap vials (Bioquote Limited,
York, United Kingdom). One hundred µL more 75% ethanol was added to
wash the well and transferred to the conical screw cap vials (Bioquote
Limited, York, United Kingdom). Samples were kept on ice until the
extraction of all samples was completed. Samples were vortexed and put
on 95 °C in the water bath for 5 min, then 5 min of sonication
followed. Finally, samples were centrifuged (14,000 rcf, 5 min, 4 °C),
and supernatants were transferred into MS-vials. Samples were measured
directly without evaporation.
4.3.5. “CM-ON” Sample Preparation
The medium of spheroids was carefully aspirated by a multichannel
pipette, while spheroids remained in the wells. Subsequently, the
spheroids were washed with 200 µL PBS and quenched by liquid nitrogen.
The spheroids still in the wells were stored at −80 °C until
extraction. Plates were kept on ice during extraction. Upon extraction,
20 µL of the U^13C internal standard was added, then 80 µL cold 80%
methanol was added (−20 °C); in this amount, the spheroid was
transferred to an Eppendorf-tube and 100 µL more cold 80% methanol was
added to wash the well and transferred to the Eppendorf tube. Samples
were kept on ice until the extraction of all samples was completed.
After 5 min of sonication, samples were vortexed and centrifuged
(14,000 rcf, 5 min, 4 °C), and the supernatants were transferred into
MS-vials. Samples were measured directly without evaporation.
4.3.6. LC-MS Method Applied for Proof of Principle Experiment with
Metallodrugs
The metabolite standards were purchased from Sigma-Aldrich or Fluka
(Vienna, Austria) except for malic acid which was purchased from Merck
(Vienna, Austria). The metabolomics experiment also included an
external calibration with a calibration mix of 133 substances and
internal standardization with U^13C-labeled yeast extract. Within every
10 injections, a blank was injected, as well as a pooled QC from
extracts (all four groups represented in each: 200 µM KP1339-treated,
20 µM oxaliplatin-treated, control, control with 0.5% dimethylsulfoxid
(DMSO)). We used high resolution Orbitrap MS coupled to Vanquish UPLC
and with a HILIC separation, as described elsewhere [[155]37]. MS-data
were acquired with positive–negative switching and the extracted ion
chromatograms were evaluated with Thermo Trace Finder, with the help of
external calibration and the internal standard, absolute amounts were
calculated in pmol. The normalization with total protein content
resulted in pmol metabolite per µg protein.
4.3.7. Total Protein Content Determination
The protein concentration was assessed from the precipitate dissolved
in 200 µL 0.05 M NaOH. For that purpose, the commercially available
micro BCA protein assay kit (Thermo Fisher Scientific, Pierce
Biotechnology, Rockford, IL, USA) was employed, according to the
manufacturer’s instructions.
4.4. Data Analysis
4.4.1. Targeted Metabolomics Data Treatment and Normalization
Targeted data evaluation of high-resolution mass spectrometry data of
metabolites was performed in Thermo Trace Finder 4.1, while for the
triple quadrupole data of amino acids hydrolyzed from pellet Agilent
MassHunter was used. ^13C internal standardization using external
calibration was employed for metabolites. All calibration curves were
linear.
The dataset with absolute metabolite amounts and total protein contents
was exported to Python, where the normalization with protein content
was carried out, as well as filtering the dataset based on the
performance of pooled quality control samples. (Missing values > 50%,
relative standard deviation above 30%).
4.4.2. Exploratory Data Analysis
The MetaboAnalyst 4.0 Statistical Analysis module was used for further
exploratory data analysis of dataset with absolute metabolite amounts
normalized to total protein content. The default missing values
imputation was used with a small number; autoscaling was applied before
multivariate analysis.
4.4.3. Pathway Analysis
The MetaboAnalyst 4.0 [[156]46] Pathway Analysis module was used, which
combines pathway enrichment analysis and pathway topology analysis to
identify the most relevant pathways involved in the conditions under
study. As data input, the whole dataset with protein content normalized
concentrations was used. Normalized concentrations were autoscaled;
missing values imputed with a small number. The following parameters
were used: pathway enrichment with “global test”, pathway topology
analysis with “relative-betweenness centrality”, pathway library was
homo sapiens KEGG, KEGG version Oct 2019.
Acknowledgments