Netta Vidavsky1, Jennie A M R Kunitake1, Maria Elena Diaz-Rubio2, Aaron E Chiou3, Hyun-Chae Loh4, Sheng Zhang2, Admir Masic4, Claudia Fischbach3,5, Lara A Estroff1,5. 1. Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14850, United States. 2. Metabolomics Facility, Institute of Biotechnology, Cornell University, Ithaca, New York 14850, United States. 3. Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14850, United States. 4. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States. 5. Kavli Institute at Cornell for Nanoscale Science, Ithaca, New York 14850, United States.
Abstract
Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. In vitro, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience in vivo. Breast cancer cell lipid compositions were assessed in 2D and 3D culture models as a function of malignancy using liquid chromatography coupled with mass spectrometry. Further, the spatial distribution of lipids was examined using Raman chemical imaging and lipid staining. We show that with changes in the cellular microenvironment when moving from 2D to 3D cell cultures, total lipid amounts decrease significantly, while the ratio of acylglycerols to membrane lipids increases. This ratio increase could be associated with the formation of large lipid droplets (>10 μm) that are spatially evident throughout the spheroids but absent in 2D cultures. Additionally, we found a significant difference in lipid profiles between the more and less malignant spheroids, including changes that support de novo sphingolipid production and a reduction in ether-linked lipid fractions in the invasive spheroids. These differences in lipid profiles as a function of cell malignancy and microenvironment highlight the importance of coupled spatial and lipidomic studies to better understand the connections between lipid metabolism and cancer.
Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. In vitro, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience in vivo. Breast cancer cell lipid compositions were assessed in 2D and 3D culture models as a function of malignancy using liquid chromatography coupled with mass spectrometry. Further, the spatial distribution of lipids was examined using Raman chemical imaging and lipid staining. We show that with changes in the cellular microenvironment when moving from 2D to 3D cell cultures, total lipid amounts decrease significantly, while the ratio of acylglycerols to membrane lipids increases. This ratio increase could be associated with the formation of large lipid droplets (>10 μm) that are spatially evident throughout the spheroids but absent in 2D cultures. Additionally, we found a significant difference in lipid profiles between the more and less malignant spheroids, including changes that support de novo sphingolipid production and a reduction in ether-linked lipid fractions in the invasive spheroids. These differences in lipid profiles as a function of cell malignancy and microenvironment highlight the importance of coupled spatial and lipidomic studies to better understand the connections between lipid metabolism and cancer.
Cancer
cell metabolism differs from normal cell metabolism in ways
that support the biosynthetic, energy, and redox needs of tumors and
enable cell proliferation and survival under stressful conditions
such as nutrient limitation.[1] In such conditions,
lipids can serve as an alternative energy source through lipogenesis[2,3] or through fatty acid scavenging.[4] Altered
lipid metabolism is a hallmark of humancancer and may promote proliferation
by providing the energy and the membrane building blocks for rapid
growth.[5−7] Many cancer cells store excess lipids in intracellular
lipid droplets, organelles involved in lipid storage, transport, and
signaling that differ in composition, size, and distribution depending
on the cells or tissue in which they are found.[8,9] Recent
advances in imaging and analytical techniques such as Raman microscopy
and mass-spectrometry-based lipidomics[10−12] provide opportunities
for obtaining high resolution spatial maps of lipid distribution within
tissues coupled with detailed lipid composition profiles.[13,14] Here, we apply these techniques to assess lipid accumulation and
spatial distribution and compare the global lipid profiles in humanbreast cancer cell lines as a function of cell culture dimensionality
(2D vs 3D) and malignancy potential.Currently, in vitro models that employ lipid mapping[15] and
profiling[16] to
study the relationships between breast cancer progression and lipid
production use 2D cell cultures on substrates such as polystyrene.
In contrast, in a solid tumor, regions of cellular viability, in which
cells proliferate and interact in all directions, often transition
to diffusion-limited inner regions of hypoxia and cell death. With
varying nutrient availability, abnormal metabolic demands, and a continuing
need for energy to drive cancer cell proliferation, three-dimensional
tumor growth is dependent in part on lipid metabolism.[17,18] The complex 3D microenvironmental conditions to which cells are
exposed in vivo such as cell–cell and cell–extracellular
matrix interactions can be better mimicked by 3D cell cultures compared
to 2D cultures.[19,20] For example, 3D multicellular
spheroids have been shown to recapitulate some in vivo cancer behaviors, including cell death[21] and tumor progression[22] pathways. In
other work, we have used 3D multicellular spheroids of human breast
cancer cell lines of varying malignancy to study the formation of
breast microcalcifications.[23] Much like
ductal breast cancer, the spheroids develop necrotic cores with spatially
distinct viable cell and hypoxic areas. In addition, gene expression
changes induced by conditions affecting metabolism are differentially
regulated in 2D vs 3D cultures.[24] Thus,
cells cultured in 3D spheroids provide a biologically more relevant
model for exploring lipid distribution in a three-dimensional microenvironment
with variable access to nutrients and oxygen as well as exposure to
metabolites.The power of emerging lipid characterization techniques
such as
Raman microscopy and mass spectrometry-based lipidomics to provide
both spatial mapping and molecular identification of lipids has been
demonstrated in systems ranging from single-celled algae[10,14] to myelin distribution in brain tissue.[13] In cancer research, these techniques have shown differences in lipid
profiles among humanbreast cancer subtypes as well as between breast
cancer and normal cells[15,16,25−30] though, for the latter, these in vitro experiments
were carried out in 2D cultures. It remains unclear, however, the
extent to which changes in tissue dimensionality that may be mimicked
with 3D culture models can affect lipid profiles and spatial distribution.
Although spatial differences in lipid accumulation may be key to tumorigenesis,[26,31] they are rarely assessed with micrometer-scale resolution due to
a shortage of methodologies allowing for this analysis. Furthermore,
systems harboring multiple cellular environments such as necrotic
and viable cell regions necessitate the use of techniques that venture
beyond the bulk. Raman microscopy is one such technique that enables
spatially mapping a multitude of chemical signatures (at submicrometer
resolution[32]) in biological materials without
staining or significant sample preprocessing.[33,34] At high enough concentrations, different types of lipids can be
readily detected and distinguished, as well as proteins (generally
and, in some cases, specifically), cells, extracellular matrix components,
sugars, and other chemical species. The information gained by coupling
Raman microscopy with lipidomics has the potential to offer a view
of biological lipid profiles encompassing both the physical distribution
of lipids and the diversity of lipid species.The aim of this
study is to understand the effect of cell culture
dimensionality on lipid metabolism and spatial distribution by using
breast cancer cell lines of a tumor progression series of nonmalignant,
precancer, and invasive cells. We employed ultrahigh performance liquid
chromatography coupled with state-of-the-art mass spectrometry (LCMS)
to analyze lipid production in both traditional 2D cell cultures and
3D multicellular spheroids. Histological staining and Raman mapping
are used in conjunction with LCMS to detail changes in the spatial
distribution of local lipid accumulation as a function of malignancy
and dimensionality. These experiments are designed to provide insights
into the relationships among lipid profiles, both spatial and compositional,
and cell microenvironment and malignancy potential.
Results
We represented tumor progression in our model by using the nonmalignant
human breast epithelial cell line MCF10A[35] and two additional cell lines that were derived from the parent
MCF10A to exhibit higher malignancy potential: the “precancer”
MCF10DCIS.com cell line[36,37] and the “invasive”
MCF10CA1a cell line.[38] Each of the three
cell lines was cultured using two different methods: as 2D cell monolayers
and as multicellular spheroids (3D).
Spatial Distribution of
Lipids Depends on the Dimensionality
(2D vs 3D) and Malignancy Potential of the Cells
Using hydrophobic
Oil-Red-O staining of the cell monolayers and of cryosections from
the spheroids, the nonpolar lipid distribution was observed for the
different malignancy potentials and culture dimensionalities. In both
2D and 3D cultures, the nonmalignant breast epithelial cells had low
lipid content (Figure a, d, g, j). In 2D, the majority of the lipid droplets in the precancer
and invasive cells had diameters smaller than 2 μm (Figure b, c, e, f). When
moving to 3D, the overall amount of lipid staining decreased compared
to 2D, and the nonmalignant spheroids presented small patches of lipids
that were not observed in 2D culture (Figure g). In the malignant 3D spheroids, increased
staining was observed in the spheroid cores, which contain necrotic
and apoptotic cells. In this region, distinguishable lipid bodies
had diameters (<1 μm) smaller than those found in 2D (see
magnified field of view in Supporting Figure S1). Additionally in 3D, large lipid droplets (with diameters larger
than 10 μm), with size and number varying from spheroid to spheroid,
were present throughout the sections and were more abundant in the
invasive spheroids (Figure h, i, k, l).
Figure 1
Relation between lipid amounts and the malignancy potential
of
breast cancer cells in 2D and 3D. Oil-Red-O lipid staining of cell
lines from the MCF10A-based breast cancer progression series cultured
in 2D (a–f) and as multicellular spheroids (g–l). (a,
d, g, j) Nonmalignant MCF10A cells; (b, e, h, k) precancer MCF10DCIS.com
cells; (c, f, i, l) invasive MCF10CA1a cells. Lipids are stained red,
and cell nuclei are stained purple. Arrows: lipid droplet aggregates
close to cell nuclei. For a high resolution version of Figure
1 see Supporting Data.
Relation between lipid amounts and the malignancy potential
of
breast cancer cells in 2D and 3D. Oil-Red-Olipid staining of cell
lines from the MCF10A-based breast cancer progression series cultured
in 2D (a–f) and as multicellular spheroids (g–l). (a,
d, g, j) Nonmalignant MCF10A cells; (b, e, h, k) precancer MCF10DCIS.com
cells; (c, f, i, l) invasive MCF10CA1a cells. Lipids are stained red,
and cell nuclei are stained purple. Arrows: lipid droplet aggregates
close to cell nuclei. For a high resolution version of Figure
1 see Supporting Data.
Lipid Profiling of Precancer and Invasive Cells in 2D and 3D
Culture
Oil-Red-O staining is a nonspecific stain for any
neutral lipid and, as such, does not provide any information about
how the lipid species are changing as a function of culture dimensionality
and malignancy potential. We hypothesize that the complex interactions
present in 3D cultures, as well as the malignancy potential, affect
the lipid profiles. To test this hypothesis, we characterized the
lipid profiles of the precancer and invasive cells cultured both in
2D and 3D using ultrahigh performance liquid chromatography coupled
with electrospray ionization mass spectrometry in positive mode (referred
to as LCMS for short). Because the nonmalignant cells presented very
small amounts of Oil-Red-O staining, which were hardly detectable
compared to the more malignant cells, their lipid profiles were not
studied by LCMS.
Lipid Amounts and Profiles Differ Significantly
Depending on
Dimensionality
From LCMS, a total of 660 unique lipid species
were detected (Figure and Supporting Figure S2). The lipid
amounts and profiles of both the precancer and invasive cells changed
when moving from 2D cultures to 3D multicellular spheroids (Supporting Table S1). Overall, cells cultured
in 3D had substantially less total lipid than those in 2D (3–6
× 107 normal peak area/μg protein in 3D and
2–4 × 109 normal peak area/μg protein
in 2D) (Supporting Figure S3, Table S1).
Hierarchical cluster analysis performed on lipids identified in 2D
and 3D cultures of precancer and invasive cells by LCMS shows clear
differences between the two groups (Figure a, Supporting Figure S2, and Supporting Table S1). Across
conditions, membrane lipids (i.e., glycerophospholipids) make up the
highest fraction of lipid type, followed by either sphingomyelins
in 2D or neutral glycerolipids (i.e., acylglycerols) in 3D (Figures b and S2). Broadly, the lipid profiles of 3D cultures
show larger variation than those of the 2D cultures both across biological
replicates and between malignancies, possibly due to the more complex
microenvironmental conditions and signaling cues that the cells are
exposed to in 3D culture and consequential changes in tumor cell heterogeneity.
Figure 2
Lipid
profiles in 2D and 3D culture of precancer and invasive cells
detected using LCMS. (a) Heatmap showing the clustering of lipid species
in 2D and 3D cultures of MCF10DCIS.com (precancer) and MCF10CA1a cells
(invasive). Color bar indicates the scaled distance from the row mean
of the normalized transformed data. For assessment of the variation
within each group, the biological replicates for each condition are
shown. For the 2D samples, each group consists of three biological
replicates, and for the 3D samples, each group consists of four biological
replicates. Lipid classes are color coded as indicated. Coenzyme
Q10 is shown in white. To the right, representative example lipid
structures of the color-coded lipid classes in part a are shown. (b)
Lipid class distribution in precancer and invasive 2D and 3D cultures
as detected with LCMS, calculated from areas in LCMS normalized per
microgram of protein in the sample and presented as a fraction of
total lipids in the sample. Error bars are the standard error of the
mean. 34 Cs = summed acyl chain and sphingoid base chain lengths of
34 carbons. See Supporting Figure S2 for
a version of this figure with individual lipid identifiers associated
with the heat map.
Lipid
profiles in 2D and 3D culture of precancer and invasive cells
detected using LCMS. (a) Heatmap showing the clustering of lipid species
in 2D and 3D cultures of MCF10DCIS.com (precancer) and MCF10CA1a cells
(invasive). Color bar indicates the scaled distance from the row mean
of the normalized transformed data. For assessment of the variation
within each group, the biological replicates for each condition are
shown. For the 2D samples, each group consists of three biological
replicates, and for the 3D samples, each group consists of four biological
replicates. Lipid classes are color coded as indicated. Coenzyme
Q10 is shown in white. To the right, representative example lipid
structures of the color-coded lipid classes in part a are shown. (b)
Lipid class distribution in precancer and invasive 2D and 3D cultures
as detected with LCMS, calculated from areas in LCMS normalized per
microgram of protein in the sample and presented as a fraction of
total lipids in the sample. Error bars are the standard error of the
mean. 34 Cs = summed acyl chain and sphingoid base chain lengths of
34 carbons. See Supporting Figure S2 for
a version of this figure with individual lipid identifiers associated
with the heat map.
Neutral Glycerolipids Are
Significantly Increased in 3D Compared
to 2D
On further inspection of the cluster analysis (Figure a), there are clear
differences in lipid populations between 2D and 3D cultures: the relative
amounts of certain lipid classes, saturations, and number of carbons
differ (Supporting Table S1). In the 3D
cultures as compared to 2D, neutral lipids make up significantly more
of the total lipid composition (Figure b). Neutral lipids, including triradylglycerols (TGs,
majority triacylglycerols with minor contributions from ether linked
species), are proportionally higher in 3D than in 2D and higher in
the invasive cells than in the precancer cells. In 2D, TGs account
for <2% of the total detected lipid population, whereas in 3D they
make up on average 13 ± 5% of lipids in precancer and 18 ±
4% in invasive. It is likely that it is these neutral lipids that
are evident in the Oil-Red-O staining. Similarly, <2% of total
lipids are diacylglycerols (DAGs) and monoacylglycerols (MAGs) in
2D, yet in 3D, they make up 9 ± 4 and 14 ± 3% of lipids
detected in precancer and invasive cells, respectively.
Alkyl and Alkenyl
Ether Lipid Fractions Are Significantly Increased
in 3D
Out of total lipids, cells cultured in 2D contain a
higher percentage of both phosphatidylethanolamine (PE) and phosphatidylcholine
(PC) relative to the same cells cultured in 3D (Figure b). The fraction of ether-linked, as opposed
to ester-linked, PCs and PEs, however, differs depending on culture
dimensionality and cell malignancy. The largest difference arises
in PEs that contain an alk-1-enyl ether linkage (P-PEs, i.e., plasmalogens
and plasmenyl). The percentage of PEs that are P-PE is substantially
higher in 3D compared to 2D and differs strongly between malignancies
(∼30% in 2D independent of malignancy, 52 ± 1.5 and 68
± 0.95% in 3D invasive and precancer, see Supporting Table S1). The percentage of alkyl ether PEs (O-PEs,
i.e., plasmanyl) in 3D is also higher when compared to that in 2D.
Alkyl ether linked PCs (O-PCs) make up 5–20% of PCs, and P-PCs
make up 5–10% of PCs, depending on the group. Percentages of
both types of PCethers were highest in 2D and 3D precancer and lowest
in 3D invasive.
Sphingomyelin and Lysophosphatidylcholine
Show Differences between
2D and 3D Based on Number of Carbons
Sphingomyelin (SM) fractions
are similar for the 2D precancer and invasive cells and for the 3D
invasive spheroids (∼6–8%) with a decrease in the precancer
spheroids (∼3%). The fraction of sphingomyelins consisting
of <34 carbons is increased in 3D. There is an increase in lysophosphatidylcholine
(LPC) amount in 3D, and the makeup of LPCs differs significantly depending
on chain length (Supporting Table S1).
Lipid Profiles Differ between Precancer and Invasive in 3D Spheroids
In breast cancer, both lipid quantity and the expression of fatty
acid synthase increase with malignancy,[39−43] motivating us to further compare lipid profiles between
precancer and invasive cell lines. The lipid profile difference between
cells of varied malignancy potentials is more profound within 3D samples
compared to 2D samples (Figure ). Given that spheroids more closely model tumor microenvironmental
conditions in vivo,[19−22] we performed further analysis
of the LCMS data for the 3D spheroids as a function of tumor cell
malignancy (Figure ).
Figure 3
Heat map showing clustering of the 25 lipid species with the most
significant changes, selected by t-test, across 3D
cultures of MCF10DCIS.com (precancer) and MCF10CA1a (invasive) cells
as detected with LCMS. Each group consists of four biological replicates.
So(d18:0) = sphinganine. Color bar indicates the scaled distance from
the row mean of the normalized transformed data.
Heat map showing clustering of the 25 lipid species with the most
significant changes, selected by t-test, across 3D
cultures of MCF10DCIS.com (precancer) and MCF10CA1a (invasive) cells
as detected with LCMS. Each group consists of four biological replicates.
So(d18:0) = sphinganine. Color bar indicates the scaled distance from
the row mean of the normalized transformed data.The precancer spheroids contain more lipids than the invasive
spheroids
(Supporting Figure S3, Figure b) and differ considerably
in their lipid profiles; there is an increase in the percentage of
acylglycerols and SMs in the invasive spheroids and an increase in
PCs in the precancer spheroids (Figure b). A heat map showing the clustered top 25 lipids
with the most significant changes across spheroid malignancies is
shown in Figure .
Almost all are membrane lipids. The species increased in the invasive
spheroids include polyunsaturated PCs (diacyl), SMs with ≤34
carbons, one DAG species, and sphinganine. In the precancer spheroids,
O-PCs and P-PCs are the species most significantly increased. Additional
increased species include a P-PE, a PC (monounsaturated), and two
very long chain LPCs (>26 carbons). In addition, between the 3D
spheroids,
more LPCs were detected in invasive, though the fraction of LPCs with
chain lengths >26 carbons was larger in precancer spheroids.
Mapping Spatial Distribution of Lipids and Other ECM Components
in 3D Spheroids Using Raman Microscopy
While the LCMS cluster
analysis of precancer versus invasive spheroids
shows that the lipid amount and profiles vary significantly (Figure ), the Oil-Red-O
staining suggests that there is also a change in neutral lipid distribution
between these two cell lines (Figure ). Cross-polarized light microscopy images of unwashed
sections of spheroids show that some lipid-containing areas in the
spheroids have strong birefringence, suggesting an anisotropic molecular
ordering (Figure a–d).
Raman microscopy was used to map the spatial distribution of chemical
species, including lipids, proteins, and glycogen, within the precancer
and invasive spheroids (Figure e–g). The Raman maps can provide insight into how the
biochemical differences revealed by the lipidomics analysis are spatially
distributed within the spheroids.
Figure 4
Characterization of the lipid droplets
formed in 3D multicellular
spheroids of malignant cell lines. (a, b, e) Precancer spheroid cross
sections. (c, d, g) Invasive spheroid cross sections. Asterisks show
the necrotic core. (a, c) Oil-Red-O lipid staining showing lipid accumulation
in the necrotic core area of the spheroids as well as lipid droplets
in the invasive spheroid (arrows). (b, d) Cross-polarized light images
of the spheroid cross sections showing birefringence (arrows in
part d point at the same areas as in part c). (e, g) Overlaid
spatial distribution maps of key basis spectra resultant from NMF
multivariate analysis of Raman mapping. (f) Corresponding NMF basis
spectra (precancer: black, invasive: gray). The precancer overlay
map (e) shows an increase in lipid content toward the spheroid center,
while the invasive overlay map confirms the birefringent
regions are lipid-rich droplets (cyan). Arrows indicate the same bodies
as in parts c and d.
Characterization of the lipid droplets
formed in 3D multicellular
spheroids of malignant cell lines. (a, b, e) Precancer spheroid cross
sections. (c, d, g) Invasive spheroid cross sections. Asterisks show
the necrotic core. (a, c) Oil-Red-Olipid staining showing lipid accumulation
in the necrotic core area of the spheroids as well as lipid droplets
in the invasive spheroid (arrows). (b, d) Cross-polarized light images
of the spheroid cross sections showing birefringence (arrows in
part d point at the same areas as in part c). (e, g) Overlaid
spatial distribution maps of key basis spectra resultant from NMF
multivariate analysis of Raman mapping. (f) Corresponding NMF basis
spectra (precancer: black, invasive: gray). The precancer overlay
map (e) shows an increase in lipid content toward the spheroid center,
while the invasive overlay map confirms the birefringent
regions are lipid-rich droplets (cyan). Arrows indicate the same bodies
as in parts c and d.An unsupervised multivariate approach, non-negative matrix
factorization
(NMF), was employed to reduce each hyperspectral Raman map into a
basis set consisting of chemically meaningful, separable spectral
signatures (i.e., basis spectra). Each basis spectrum has a corresponding
heat map, in which the value of each pixel is the calculated contribution
of the given basis spectrum, effectively showing the relative spatial
distributions of each basis. This unsupervised method was validated
using a supervised peak area-based approach to ensure that basis maps
and basis spectra are comparable to results obtained from standard
univariate analysis (Supporting Figures S4–S8, Supporting Table S2). Figure e and g show overlaid false-colored
maps of the most spatially and spectrally clear biological bases (substrate
signatures and spatially or spectrally noisy signatures are not shown).
For the precancer and invasive spheroids, similar emergent biological
bases (Figure f) are
mapped to reveal spatial distributions of chemical species: lipid-rich
(cyan, a lipid-dominated spectral signature characterized by a strong
lipid peak at 2850 cm–1, among others), protein–lipid
(blue, a combination of protein and lipid signatures in which protein
was increased compared to the lipid-rich signature), cellular (yellow,
a combination of protein and DNA signatures), and glycogen (red).
Raman
Mapping Localizes Multiple Signatures: Lipids, Proteins,
Cells, Glycogen, and Cytochrome c
The Raman
overlay images provide a sensitive, chemically rich landscape of the
precancer (Figure e) and invasive (Figure g) spheroid sections. Cellular signatures (yellow) are clear
amidst a backdrop of the ubiquitous protein–lipid signature
(blue). The morphologies and positions of cell signatures in the Raman
maps correspond almost exactly to the stained cell nuclei processed
afterward on the same samples (Figure a and c), although fewer cells are observed in the
Raman maps compared to staining, most likely due to focal limitations
of Raman microscopy. In the invasive spheroid, a strong signature
for the polysaccharideglycogen is evident throughout the section.
Additionally, a cytochrome c basis is present and
appears associated with many of the lipid bodies (Supporting Figure S4) as well as cells, which could suggest
local apoptosis.[44] Peaks associated with
cytochrome c are present in precancer spectra as
well but they did not emerge as independent bases by NMF for the sample
shown in Figure (Supporting Figure S7). Raman maps taken of a
separate precancer spheroid produced clear glycogen and cytochrome c basis spectra.
Raman Mapping Shows That Lipid Droplets Are
Consistent with
Unsaturated Acylglycerols
The spatial distribution of the
lipid-rich signature differs markedly between the malignancies. In
precancer (Figure e), there is a gradual increase from periphery to core that is not
easily discernible in the Oil-Red-O image from the same section (Figure a) though is consistent
with results shown in Figure . In the invasive spheroid section (Figure g), the lipid-rich basis appears amidst cells
but is additionally concentrated in large bodies or droplets, consistent
with the Oil-Red-O staining and polarized light images (Figure c, d). The birefringent areas,
which are indicative of molecular order, are colocalized with locally
distinct lipid–protein Raman signatures. The lipid-rich basis
spectrum represents a mixture of lipids (with protein contributions
as well), and the spectral features from both malignancy potentials
are consistent with unsaturated acylglycerols in the liquid state
(Supporting Table S2).[45] There is a notable lack of substantial peaks in the 700–760
cm–1 range, ruling out the otherwise spectrally
similar lipidsphosphatidylcholine and phosphatidylethanolamine as
well as cholesterol or cholesterol esters (in agreement with the LCMS
findings) as large contributors to these spectra (Supporting Table S2).
Raman Mapping of a Clinical
Sample Shows Spatially Distinct
Distribution of Lipids within DCIS
To validate the potential
relevance of our in vitro findings with a clinical
sample, confocal Raman mapping was performed on a human duct presenting
comedo-type ductal carcinoma in situ (DCIS, a precancer)
(Figure ). A hematoxylin
and eosin stained cryo-section of the specimen (H&E, Figure a) shows the general
morphology of the analyzed tissue. The duct is filled with both living
cancer cells and a large necrotic region. From Raman, the localization
and distribution of multiple chemical species is evident (Figure b). Using a partially
supervised component analysis approach, collagen, cellular, protein,
and lipid signatures are clearly distinguished (Figure , and Supporting Figure S9). The ECM-rich tissue surrounding the duct contains abundant
collagen consistent with the presence of stromal fibroblasts, while
a DNA-rich protein signature (cellular, likely nuclei) is primarily
located to the right side of the duct, as in the H&E image. Cellular
features become cross-sectionally smaller and disappear completely
within the protein-rich necrotic region. Two major noncollagenous
protein signatures are present: one that appears more associated with
cellular signatures and includes cytochrome c and
a second that appears more associated with necrosis. The lipid component
lacks any distinguishing peaks associated with membrane lipids and
is consistent with a saturated neutral lipid signature that includes
cholesterol ester (Supporting Table S2).
This neutral lipid signature is more prevalent in the necrotic region
of the duct compared to the viable cell areas and is often concentrated
within domains with diameters larger than 2 μm (Figure b), consistent with features
found in precancer and invasive spheroids (Figures and 4).
Figure 5
Spatial characterization
of DCIS (precancer) from human tissue.
(a) H&E stained cryo-section showing the duct cross section containing
cells (purple), necrosis (dark pink and purple), and surrounding stromal
tissue (pink). (b) Confocal Raman mapping and component analysis of
a serial section from the same duct in part a, showing the spatial
distribution of the tissue components. Lipids, cyan; collagen, green;
protein/cytochrome c, magenta; noncollagenous proteins,
blue; cells, yellow. A distinct lipid signature consistent with neutral
lipids, including cholesterol ester(s), is observed in the necrotic
regions and occurs in spatially discrete domains (arrow). (c) The
corresponding Raman component spectra for the Raman map in part b.
Spatial characterization
of DCIS (precancer) from human tissue.
(a) H&E stained cryo-section showing the duct cross section containing
cells (purple), necrosis (dark pink and purple), and surrounding stromal
tissue (pink). (b) Confocal Raman mapping and component analysis of
a serial section from the same duct in part a, showing the spatial
distribution of the tissue components. Lipids, cyan; collagen, green;
protein/cytochrome c, magenta; noncollagenous proteins,
blue; cells, yellow. A distinct lipid signature consistent with neutral
lipids, including cholesterol ester(s), is observed in the necrotic
regions and occurs in spatially discrete domains (arrow). (c) The
corresponding Raman component spectra for the Raman map in part b.
Discussion
We
used a series of MCF10A-based cell lines to study the individual
and combined effects of breast cancer malignancy and culture dimensionality
on lipid spatial distribution (Raman microscopy) and global lipid
profiles (LCMS). The cells were cultured in multicellular spheroids
(3D) to mimic breast cancer microenvironmental conditions more closely
than cells traditionally cultured on polystyrene substrates. The total
amount of lipid decreased significantly when moving from 2D to 3D
culture, though larger lipid droplets were observed in 3D regardless
of malignancy. In 3D spheroid cultures, in addition to malignancy-dependent
changes in lipid profiles, spatial distribution of lipids was both
malignancy and microenvironment-dependent. Spheroids cultured using
the invasive cell line showed relative increases in neutral lipids
(DAGs and TGs), sphingolipids, and sphingoid bases (sphingomyelin,
dihydroceramide, sphinganine, and sphingosine), while PCs and ether-linked
lipid fractions decreased compared to precancer spheroid cultures.
Taken together, these differences suggest that malignancy potential,
together with culture dimensionality and thus microenvironmental conditions,
can have a significant impact on lipid biogenesis in cancer with potential
implications for lipid biophysics, signaling, and metabolism (Figure ). Below, we discuss
the differences in lipid profiles and spatial distribution and their
potential biological implications going from the macroscale (cell
culture dimensionality) to the microscale (the formation of large
lipid droplets, microenvironment-dependent lipid distribution within
the spheroids), and finally to the molecular scale (malignancy- and
dimensionality-dependent changes in sphingolipids and ether-linked
lipid levels).
Figure 6
A scheme describing the effects of dimensionality (top
left) and
the cell malignancy potential (bottom left) on lipid species amounts
in the MCF10A breast cancer in vitro model. Lipid-rich
areas (red) are observed in the necrotic core with decreasing amounts
toward the spheroid periphery alongside large lipid droplets at the
periphery. The observed increase in the ratio of neutral to membrane
lipid species in 3D versus 2D may be related to large lipid droplet
formation through TG synthesis and/or lipid droplet coalescence (top
right). The observed increase in sphingolipid species in invasive
versus precancer spheroids could be due to enhancement of the de novo sphingolipid synthesis pathway (bottom right, adapted
from Ogretmen[46]). Species of lipids increased
out of total lipids in 3D invasive spheroids are underlined. CoA =
coenzyme A, SPT = serine palmitoyltransferase, KDSR = 3-ketosphinganine
reductase, CERS = (dihydro)ceramide synthases, DES = dihydroceramide
desaturase, SMS = sphingomyelin synthase, CDase = ceramidases.
A scheme describing the effects of dimensionality (top
left) and
the cell malignancy potential (bottom left) on lipid species amounts
in the MCF10Abreast cancer in vitro model. Lipid-rich
areas (red) are observed in the necrotic core with decreasing amounts
toward the spheroid periphery alongside large lipid droplets at the
periphery. The observed increase in the ratio of neutral to membrane
lipid species in 3D versus 2D may be related to large lipid droplet
formation through TG synthesis and/or lipid droplet coalescence (top
right). The observed increase in sphingolipid species in invasive
versus precancer spheroids could be due to enhancement of the de novo sphingolipid synthesis pathway (bottom right, adapted
from Ogretmen[46]). Species of lipids increased
out of total lipids in 3D invasive spheroids are underlined. CoA =
coenzyme A, SPT = serine palmitoyltransferase, KDSR = 3-ketosphinganine
reductase, CERS = (dihydro)ceramide synthases, DES = dihydroceramide
desaturase, SMS = sphingomyelin synthase, CDase = ceramidases.
Cell Culture Dimensionality Affects Lipid
Production and Distribution
When moving from 2D to 3D cultures,
total lipids decreased, and
lipid spatial distributions differed. Even though it is now relatively
well-established that culture dimensionality affects the phenotype
of cancer cells at multiple levels, including their transcriptome
and proteome,[47,48] it remains largely unclear what
effect(s) 3D microenvironmental conditions have on the lipidome of
cancer cells. Two-dimensional cultures, where cells effectively grow
as a monolayer with equal access to nutrients from the media, including
carbon sources required for lipid synthesis, contain substantially
more lipids compared to 3D, as qualitatively seen by the increased
density and intensity of staining in Oil-Red-O (Figure ) and quantitatively demonstrated by the
lipid profiling (Supporting Figure S3).
Furthermore, the LCMS lipid profiles in 2D, though different between
malignancies, are well-conserved across biological replicates.In the 3D spheroids, the reduction in lipid amounts may be related
to alterations in cell metabolism due to changes in cell–microenvironment
interactions (e.g., cell–cell and cell–extracellular
matrix interactions) and/or because the supply of carbon sources for
biosynthetic pathways is subject to diffusion-limited transport, much
like in tumors in vivo. Importantly, both metabolism
and nutrient diffusion are interdependent because differences in oxygen
and nutrient transport can directly influence the cellular microenvironment
and vice versa. Collectively, these changes may affect the cells’
ability to synthesize lipids, which could potentially contribute to
the observed reduction in total lipids in 3D. While the increased
amount of total lipids found in 2D could be accounted for by the presence
of a large number of small lipid droplets (Figure , often hundreds of lipid droplets per cell),
differences in plasma membrane or organelle membranes could also exist.
In addition, spheroid cultures may have lower proliferation rates
than in 2D[49] and hence may exhibit a decreased
demand for energy and/or biosynthetic building blocks contained in
stored lipid droplets.
Lipid Composition and Distribution in Multicellular
Spheroids
May Relate to Energy Storage in Nutrient Deprived Conditions
In the spheroids, multiple cellular niches coexist due to nutrient
and oxygen diffusion limits[23] (e.g., necrotic,
apoptotic, and viable cell areas; high and low nutrient levels). As
revealed by Oil-Red-O staining and Raman microscopy, lipid spatial
distribution appears to depend on the specific microenvironmental
conditions, with lipids mostly localized in the spheroid core and
in large birefringent droplets, which are more common in the invasive
spheroids (Figures and 4). When the spatial distribution of
lipids in the spheroids is compared to a clinical sample, we observe
that in both the spheroids and the human tissue sample, neutral lipids
are concentrated in spatially distinct domains with diameters >2
μm.
In the spheroids, at least two lipid droplet and/or body populations
exist: diffuse signatures where lipid bodies or droplets are very
small and Raman mapping cannot resolve them (<1 μm), and
large (10s of micrometers), birefringent concentrations of lipids
that appear in close proximity to cell nuclei and do not necessarily
occur within the spheroid core. While these concentrated regions could
be accumulations of smaller droplets similar to what is seen for some
cells in 2D, their appearance is consistent with larger droplets.Lipid droplets are known to be composed primarily of neutral lipids
such as TGs or cholesterol esters as well as proteins encapsulated
by a glycerophospholipid monolayer.[50−54] From the lipidomics in this study, the fraction of
detected neutral lipids requiring storage in lipid droplets (TGs and
DAGs) is significantly higher in 3D and also substantially more variable
among 3D biological replicates. Lipid spectra obtained by Raman mapping
of the large lipid domains in the 3D spheroid sections lack peaks
associated with cholesterol esters. These lipid spectra are consistent
with unsaturated TGs and DAGs, and in contrast to the DCIS clinical
sample, which contains a signature of saturated cholesterol esters.
In spheroids, the absence of cholesterol or cholesterol esters is
consistent with the LCMS results. The increase in DAGs and TGs is
most likely associated with the formation and coalescence of lipid
droplets. The increase could also suggest that cells within spheroids
are structurally able to accommodate large volume droplets, unlike
2D cultures that are essentially a cell monolayer. Further, the sporadic
presence of larger droplets within the spheroid sections could explain
both the pronounced relative increase in neutral lipids from 2D to
3D compared to membrane lipids, as well as the higher variability
of TG and DAG amounts between replicates within the same group. The
formation of the larger lipid droplets in 3D is also consistent with
a decrease in membrane lipids compared to neutral lipids and increased de novo triglyceride synthesis, where the necessary enzymes
are localized to the droplet monolayer[52] (Figure , top right).In other systems, it was shown that cancer cells can use lipids
stored in neighboring adipocytes to fuel their own growth[55,56] or use lipid droplets as a reservoir of lipid building blocks for
new membrane formation.[57] The increase
in lipid accumulation and formation of larger lipid droplets in central
regions of both the spheroids and the clinical DCIS sample may be
related to the development of cellular stress or hypoxia in these
areas. Indeed, Raman microscopy of central regions of spheroids also
identified glycogen, which increases in cancer cells exposed to hypoxia.[58−60] Furthermore, cytochrome c signatures are evident
in both spheroids and the clinical sample, suggesting that cells may
be undergoing apoptosis, possibly due to environmental stresses.[61] Taken together, these observations could be
related to cancer cells’ adaptive energy storage in conditions
of limited exogenous nutrients and oxygen.[62]
Sphingolipid de Novo Synthesis Is Upregulated
in Invasive Cells
De novo sphingolipid synthesis
is related to cellular lipid homeostasis and to the regulation of
cell processes associated with disease conditions.[63] The sphingolipid profile of the invasive spheroids is markedly
different from that of precancer spheroids and is consistent with
activation of the de novo sphingolipid synthesis
metabolic pathway (Figure ). Species involved in the one-way de novo biosynthesis of sphingolipids, including sphinganine and dihydroceramides,
are increased in invasive spheroids (Figure ) as well as possible downstream products:
sphingosine, ceramides, and sphingomyelins. Interestingly, conversion
of ceramide to sphingomyelin entails removal of a PC headgroup to
yield DAGs,[46] which are also increased
in invasive spheroids, though DAGs can be produced via numerous pathways.[64] Further evidence of de novo synthesis comes from work that shows the invasive cell line used
here, MCF10CA1a, has substantially increased expression levels of
the gene C3orf57 compared to the parent cell line.[65] C3orf57, currently known as serine palmitoyltransferase
small subunit B (SPTSSB), is a protein involved in the first committed
step of sphingolipid metabolism.[66]The apparent sphingolipid de novo synthesis in invasive
spheroids raises the question: is upregulation of sphingolipid biosynthesis
connected to invasiveness and/or cell survival pathways? Elevated
sphinganine has been reported in endometrial cancer tissue[67] and was thought to be associated with de novo sphingolipid synthesis. Many sphingolipid species
have been found to influence tumor progression through cell death
and survival signaling depending on their ratios in membrane lipid
rafts.[68] Sphingoid bases such as sphingosine
and its derivatives, which are increased in the invasive spheroids,
can also impact the cell cycle and apoptosis.[69] Finally, ceramides, which are increased in invasive spheroids, are
thought to mediate cell death and tumor suppression. Ceramides are
known to be elevated in response to cellular stress have been found
to play important context-dependent roles in cancer cell death and
survival pathways.[46]
Ether Lipid
Fractions Depend on Both Malignancy and Dimensionality
Dysregulation
of ether lipids has been implicated in a number of
diseases, including cancer,[70,71] and inhibition of etherlipid synthesis may have anticancer effects,[72] but their exact roles remain elusive. When looking at our results,
the differences in ether lipid content as a function of culture dimensionality
and malignancy, particularly plasmalogens, are striking. At least
two interesting trends are observed: (1) a drastic increase in P-PE
fraction in 3D compared to 2D and (2) a less-drastic, but still substantial,
difference in P-PE fraction in invasive versus precancer that only
emerges in 3D. Physiologically, different tissues have varying but
characteristic ether lipid fractions. In humans, the percentage of
PEs that are P-PEs, for example, is as high as 84% in white matter
brain tissue and as low as 8% in the liver.[73] Here, in 2D, both invasive and precancer cell lines maintain a P-PE/PE
fraction of ∼30%. However, in 3D, this fraction increases up
to 52% for invasive (about the level of heart)[73] and 68% for precancer (as high as human neutrophils) (Supporting Table S1). The dimensional disparity
is as large as the difference between a liver and a kidney cell. Although
they make up a significant portion of cell membranes and clearly impact
lipid metabolism, roles of ether PCs and PEs are not fully understood.[73,74] Whether the increase in etherPE fractions in 3D is related to cellular
stress within the spheroids and/or metabolic or biophysical changes
in 3D is unknown.The differences among ether lipids in general
between precancer and invasive spheroids are also considerable. Fourteen
of the 25 most significantly different lipid species across malignancies
are ether lipids (Figure ), primarily O- and P-PCs. P-PEs are also substantially decreased
in invasive spheroids, and almost all other ether lipid types are
also relatively decreased. Our data suggest a malignancy-dependent
shift in the ether lipid balance in general through either enhancement
of biosynthetic pathways that produce ether lipids or reduction of
consumptive pathways. The large change in P-PE fractions between malignancies,
which only occurs when cells are cultured as spheroids, suggests a
complexity of function that has yet to be explored.Taken together,
our results present many interesting new research
directions regarding lipid metabolism and distribution in cancer.
Future studies will be aimed at identifying differences in lipid metabolism
that could be responsible for the changes in lipid composition and
distribution detected in this work. Such studies could include analysis
of expression levels and localization of key de novo lipid synthesis proteins, including TG synthesis enzymes, to inform
lipid droplet formation mechanisms and enzymes involved in sphingolipid
synthesis to determine how regulation of these lipids impact cancer
cell stress and survival. Lipids, including sphingolipids, DAGs, and
polyunsaturated PCs, take part in many important signaling pathways[17] and affect membrane sensing by proteins.[75,76] To examine whether differences in the amounts of these lipid species
between the precancer and invasive spheroids are indeed related to
cancer signaling, further studies are required. Finally, Raman mapping
of a clinical sample shows that the spatial distribution of neutral
lipids within precancer ducts varies depending on the local tissue
components with an increase in necrotic regions, similar to the observations
in the spheroid model. Much like in the spheroid model, neutral lipid
domains are formed within the duct and appear accumulated in the necrotic
region. To further establish the clinical relevance of the 3D spheroid
model to humanbreast tumors, analogous studies, combining Raman microscopy
and advanced lipidomic techniques, will be performed using patient
samples.[77] Through such studies, we will
explore the functional impact of the observed differences in lipid
profile on tumor progression.To conclude, by combining the
spatial resolution of Raman mapping
with the chemical resolution of liquid chromatography mass spectrometry
lipidomics, we show that lipid accumulation, profiles, and spatial
distribution depend on breast cancer cell culture dimensionality and
malignancy potential. Lipidomics revealed that there are significant
changes in 3D spheroids versus 2D monolayer culturing dimensions.
While the inherent metabolic differences between the cell lines themselves
likely play a large part, the marked changes in lipid profiles between
2D and 3D could be attributed to several factors. These factors include
the existence of multiple microenvironments in 3D with varying states
of lipid accumulation and possibly lipid metabolism, the formation
of large lipid droplets to house an increased supply of neutral lipids
as an energy source, and alterations in the plasma membrane composition,
all of which are interconnected. Lipid profiles between precancer
and invasive cells cultured as 3D spheroids were also significantly
different. Specifically, these differences suggest enhancement of
the de novo sphingolipid metabolic pathway in the
invasive spheroids. Additionally, lipid species that are less well
understood, including ether PCs and PEs and very long chain LPCs,
were decreased in the invasive spheroids compared to precancer spheroids.
This work highlights the power of correlative analysis techniques
to study tumor microenvironments and reveal qualitative and quantitative
differences of breast-cancer-associated lipid profiles in different
culture models. As our ability to resolve and identify unique lipid
species improves, further combinations of lipidomics and Raman mapping
could lead to new insights surrounding the complex network of functional
imbalances that supports and enables cancer cell survival, growth,
and metastasis.
Authors: Paraic A Kenny; Genee Y Lee; Connie A Myers; Richard M Neve; Jeremy R Semeiks; Paul T Spellman; Katrin Lorenz; Eva H Lee; Mary Helen Barcellos-Hoff; Ole W Petersen; Joe W Gray; Mina J Bissell Journal: Mol Oncol Date: 2007-06 Impact factor: 6.603
Authors: S J Santner; P J Dawson; L Tait; H D Soule; J Eliason; A N Mohamed; S R Wolman; G H Heppner; F R Miller Journal: Breast Cancer Res Treat Date: 2001-01 Impact factor: 4.872
Authors: Jeremy P Koelmel; Michael P Napolitano; Candice Z Ulmer; Vasilis Vasiliou; Timothy J Garrett; Richard A Yost; M N V Prasad; Krystal J Godri Pollitt; John A Bowden Journal: Metabolomics Date: 2020-04-19 Impact factor: 4.290
Authors: Fernando Tobias; Julie C McIntosh; Gabriel J LaBonia; Matthew W Boyce; Matthew R Lockett; Amanda B Hummon Journal: Anal Chem Date: 2019-12-06 Impact factor: 6.986