Role of mitochondria and cardiolipins in growth inhibition of
Transcript Of Role of mitochondria and cardiolipins in growth inhibition of
Terao et al. Journal of Experimental & Clinical Cancer Research https://doi.org/10.1186/s13046-019-1438-y
(2019) 38:436
RESEARCH
Open Access
Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid
Mineko Terao1†, Laura Goracci2,3†, Valentina Celestini1†, Mami Kurosaki1, Marco Bolis1, Alessandra Di Veroli2, Arianna Vallerga1, Maddalena Fratelli1, Monica Lupi4, Alessandro Corbelli5, Fabio Fiordaliso5, Maurizio Gianni1, Gabriela Paroni1, Adriana Zanetti1, Gabriele Cruciani2,3 and Enrico Garattini1*
Abstract
Background: All-trans-retinoic-acid (ATRA) is a promising agent in the prevention/treatment of breast-cancer. There is growing evidence that reprogramming of cellular lipid metabolism contributes to malignant transformation and progression. Lipid metabolism is implicated in cell differentiation and metastatic colonization and it is involved in the mechanisms of sensitivity/resistance to different anti-tumor agents. The role played by lipids in the anti-tumor activity of ATRA has never been studied.
Methods: We used 16 breast cancer cell-lines whose degree of sensitivity to the anti-proliferative action of ATRA is known. We implemented a non-oriented mass-spectrometry based approach to define the lipidomic profiles of each cell-line grown under basal conditions and following treatment with ATRA. To complement the lipidomic data, untreated and retinoid treated cell-lines were also subjected to RNA-sequencing to define the perturbations afforded by ATRA on the whole-genome gene-expression profiles. The number and functional activity of mitochondria were determined in selected ATRA-sensitive and –resistant cell-lines. Bio-computing approaches were used to analyse the high-throughput lipidomic and transcriptomic data.
Results: ATRA perturbs the homeostasis of numerous lipids and the most relevant effects are observed on cardiolipins, which are located in the mitochondrial inner membranes and play a role in oxidative-phosphorylation. ATRA reduces the amounts of cardiolipins and the effect is associated with the growth-inhibitory activity of the retinoid. Down-regulation of cardiolipins is due to a reduction of mitochondria, which is caused by an ATRAdependent decrease in the expression of nuclear genes encoding mitochondrial proteins. This demonstrates that ATRA anti-tumor activity is due to a decrease in the amounts of mitochondria causing deficits in the respiration/ energy-balance of breast-cancer cells.
Conclusions: The observation that ATRA anti-proliferative activity is caused by a reduction in the respiration and energy balance of the tumor cells has important ramifications for the therapeutic action of ATRA in breast cancer. The study may open the way to the development of rational therapeutic combinations based on the use of ATRA and anti-tumor agents targeting the mitochondria.
Keywords: Retinoic acid, Breast cancer, Lipidomics, Oxidative phosphorylation
* Correspondence: [email protected] Mineko Terao, Laura Goracci and Valentina Celestini equally contributed to the generation of the data and share the first-authorship. 1Laboratory of Molecular Biology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via La Masa 19, 20156 Milan, Italy Full list of author information is available at the end of the article
© The Author(s). 2019, corrected publication 2019. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Background All-trans-retinoic acid (ATRA) is a non-conventional and promising therapeutic agent acting on different types of solid/hematologic malignancies [1–5] and it is used in the treatment of acute-promyelocytic-leukemia (APL) [6]. In APL patients, ATRA induces the differentiation of leukemic cells, which is at the basis of its therapeutic activity. The unusual mechanism of action and the available pre-clinical data have raised interest in ATRA for the treatment of breast-cancer [7, 8].
Breast-cancer is a heterogeneous disease [9], although it is traditionally classified in three subgroups according to the presence/absence of the estrogen-receptor (ER), the progesterone-receptor (PR) and the HER2 protein. In addition, breast-cancers can be divided into luminal and basal tumors according to the morphological characteristics. Steroid hormone receptors are considered to be good therapeutic targets in luminal breast-cancer [10]. Recently, we demonstrated that a large proportion of luminal and ER+ mammary tumors are characterized by sensitivity to the anti-proliferative action of ATRA, while the triple-negative counterparts tend to be resistant [11, 12]. The biological activity of ATRA is mediated by specific steroid receptors (RARα, RARβ and RARγ), which act as ligand-dependent transcription factors under the form of heterodimers with other retinoid receptors known as RXRs (RXRα, RXRβ and RXRγ) [7, 13]. ATRA is a pan-RAR agonist, binding all RARs with the same affinity. In breast-cancer, we identified RARα as the retinoid receptor mediating the growth-inhibitory activity exerted by ATRA [11].
There is growing evidence that reprogramming of cellular lipid metabolism contributes to malignant transformation and progression [14–18]. In addition, lipids play a role in the mechanisms of sensitivity/resistance to different anti-tumor agents [19–22]. The involvement of lipids in the anti-tumor activity of ATRA has never been studied and this type of studies is now facilitated by the availability of technologies allowing the definition of the cellular lipidomic profiles [23–25]. The potential relevance of lipids for the anti-tumor action of ATRA is of interest given the role played in the growth, differentiation and metastatic spread, three processes affected by the retinoid [11, 26, 27].
Here, we evaluate the constitutive lipidomic profiles of breast-cancer cell-lines recapitulating the heterogeneity of the disease [11, 12] and the perturbations induced by ATRA. The lipidomic profiles of luminal and basal breast-cancer cell-lines are distinct. In addition, we identify cardiolipins (CLs) as the main lipid class modulated by ATRA in retinoid-sensitive breast-cancer cell-lines. Mechanistic and RNA-sequencing studies show that the ATRA-dependent down-regulation of CLs in sensitive cell-lines is accompanied by a reduction in the amounts and activity of mitochondria.
Materials and methods
Cell-lines The source and the characteristics of the 16 breastcancer cell-lines used are available in Additional file 1. The generation of the RARα over-expressing (RARA-C5) and relative control (Vect-C1) clones from MDA-MB453 cells as well as the RARα silenced (RARsA-sh18) and relative control (Vect-C6) clones from SK-BR-3 cells have been described [11]. The growth of cells was determined with the sulforhodamine assay [11].
Single-cell motility Single-cell motility assays were performed on coated culture wells by time-lapse microscopy, the Imaging Station CellRˆ (Olympus, Segrate, and the software Image J (Rasband W, National tutes of Health, Bethesda, MD).
BSAusing Italy) Insti-
Untargeted lipidomics Untargeted lipidomics studies were performed with Lipostar, a high-throughput software supporting targeted and untargeted liquid-chromatography/mass-spectrometry (LCMS) lipidomics [23, 28]. Further details on the methodological approach can be found in Additional file 1.
Mitochondrial studies Mitochondria were stained with MitoTarcker Deep Red FM (Invitrogen) according to the manufacturer instructions. Following staining, cells were fixed with 2% formalin and subjected to quantitative FACS analysis, using a fluorescence activated cell sorter (FACS, Becton and Dickinson). In the case of the experiments performed on the SK-BR-3, HCC-1419, MDA-MB-361 and HCC-202 lines, mitotracker stained cells were also subjected to quantitative microscopic analysis using the ImageJ software. Cells were counterstained with Hoechst 3342 (Thermofisher) for the determination of cell nuclei. For each experimental point, a minimum of 200 cells/field in at least 4 fields/experimental triplicate were quantitated. Mitochondria were isolated using a described protocol [29]. The enzymatic activity of mitochondrial complexes was determined on isolated mitochondria [30, 31]. The microviscosity of mitochondrial membranes was measured as described by M. Salmona et al. following staining with 1,6-diphenyl-1,3,5-hexatriene as a fluorescent probe [32].
RNA-sequencing studies
Three paired biological replicates of each breast-cancer cell-line were grown in DMEMF12 medium containing 5% charcolated FBS (Fetal Bovine Serum, Gibco) for 24 h. Cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for another 24 h. RNA was extracted with the mRNeasy Mini Kit (QIAGEN). RNA sequencing was
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performed using the Illumina TruSeq RNA librarypreparation kit and sequenced on the Illumina NextSeq500 with paired-end, 150 base pair long reads. The overall quality of sequencing reads was evaluated using FastQC [33]. Sequence alignments to the reference human genome (GRCh38) were performed using STAR (v.2.5.2a). Gene-expression was quantified using the comprehensive annotations available in Gencode [34]. Specifically, we used the v27 release of the Gene Transfer File (GTF). Raw-counts were further processed in the R Statistical environment and downstream differential expression analysis was performed using the DESeq2 pipeline. All the RNA-sequencing data relevant for this study were deposited in the EMBL-EBI Arrayexpress database (Accession No: E-MTAB-8408). Genes characterized by low mean normalized counts were filtered out by the Independent Filtering feature embedded in DESeq2 (alpha = 0.05). DESeq2-computed statistics were used as input for gene-set enrichment testing performed with the pre-ranked version of Camera. Statistical enrichments were determined for gene-sets obtained from the Hallmark (H), which are curated by the Molecular Signature DataBase (MSigDB).
Transmission electron microscopy ATRA-sensitive SK-BR-3 and ATRA-resistant HCC1419 cell lines were grown on plastic Petri dishes and fixed in phosphate buffer 0.12 M pH 7.4 containing 4% paraformaldehyde and 2% glutaraldehyde (Electron Microscopy Sciences, code #16220) for 10 min. Cells were scraped from the dishes, centrifuged at 13,000 rpm and kept in 0.12 M phosphate buffer containing 4% paraformaldehyde and 2% glutaraldehyde for 2 h. After postfixation in 0.12 M cacodylate buffer containing 1% OsO4 for 2 h and subsequent dehydration in graded series of ethanol, samples were cleared in propylene oxide, embedded in Epoxy medium (Epon 812 Fluka) and polymerized at 60 °C for 72 h. Ultrathin sections (70 nm thickness) were obtained with a Leica EM UC6 ultramicrotome, counterstained with uranyl acetate and lead citrate and examined with an Energy Filter Transmission Electron Microscope (EFTEM, ZEISS LIBRA® 120) equipped with a yttrium aluminium garnet (YAG) scintillator slow-scan charge-coupled device (CCD) camera (Sharp eye, TRS, Moorenweis, Germany). The numerical density of mitochondria (NV, n/μm3) was estimated by morphometrical analysis using 30 digitized electron microscope fields of cells for each group acquired by the iTem software (Olympus Soft Imaging Solutions, Germany) and digitally superimposing an orthogonal grid with ImageJ (1.52a version). Briefly, the mitochondrial profile area density (NA) was estimated by the ratio between the number of mitochondria and the cytoplasmic area. Mitochondrial volume density (VV) was determined by the ratio of grid
points falling over mitochondria divided by the total number of points of the grid contained in the cytoplasm. The numerical density of mitochondria (NV) was then estimated for each cell using the formula: NV = (1/β) (NA 3/2 / VV 1/2), where β is the shape coefficient for ellipsoidal mitochondria, calculated from the ratio of the armonic mean of major and minor axis of mitochondria sections measured on digital images. The mean mitochondrial volume was calculated for each cell as the ratio of mitochondrial volume density VV and numerical density NV.
Measurement of mitochondrial membrane microviscosity The microviscosity of mitochondrial membranes was measured as described by M. Salmona et al. following staining with 1,6-diphenyl-1,3,5-hexatriene as a fluorescent probe [3]. Isolated mitochondria containing an equal amount of proteins were incubated with 1,6diphenyl-1,3,5-hexatriene (2 × 10− 6 M) for 30 min at 37° and the fluorescence polarization values were determined using a fluorescence detector (Infinite F500, TECAN, Switzerland). The fluorescence polarization (FP) value is a function of the emission value (emission = 420 nm), which was detected through analyzers oriented in parallel (FP1) and perpendicular (FP2) to the direction of polarization of the excitation beam (excitation = 365 nm), according to the eq. FP = (FP2 - FP1 / FP2 + FP1).
Results
ATRA sensitivity and constitutive lipidomic profiles in luminal and basal breast-cancer cell-lines To conduct the study, we used 16 cell-lines whose degree of sensitivity to the anti-proliferative action of ATRA has been determined [11, 12]. Eight cell-lines come from triple-negative (TN) breast-cancers, while the other 8 cell-lines derive from luminal tumors characterized for HER2 and ER/PR expression. Consistent with the tumor origin, the constitutive gene-expression profiles determined by RNA-sequencing classify the celllines in two distinct basal and luminal groups (Fig. 1a). The 16 cell-lines are ranked according to their quantitative response to the anti-proliferative effect of ATRA using the continuous ATRA-score index (Fig. 1b) [11]. One basal (HCC-1599) and 4 luminal (SK-BR-3, HCC1500, CAMA1 and MDA-MB-361) cell-lines are classified as highly sensitive to ATRA. Three luminal (HCC202; MDA-MB-175VII; ZR75.1) and 3 basal (MB-157; MDA-MB-157; HS578T) cell-lines are endowed with intermediate sensitivity. One luminal (HCC-1419) and 4 basal (MDA-MB-231; CAL-851; HCC-1187; MDA-MB436) cell-lines show low sensitivity/resistance to ATRA.
We used a LC/MS-based approach [23] to define the lipidomic profiles of each cell-line grown under basal conditions. We generated a fingerprint composed of 530 chemical features identified as lipid species, some of them in multiple
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Fig. 1 Characteristics and sensitivity to ATRA of the breast cancer cell-lines used in the study. a The panel illustrates a dendrogram of the breast cancer cell-lines used in the study. Clustering of the cell-lines is based on the basal gene-expression profiles determined for each cell-line by NGS (Next Generation Sequencing). b The panel illustrates the sensitivity of each cell-line to the anti-proliferative action of ATRA defined by application of the ATRA-score model. The higher is the ATRA-score value the higher is the sensitivity of the cell-line to ATRA. The horizontal lines indicate the ATRA-score threshold values used to define the cell-lines characterized by high, intermediate and low sensitivity to ATRA. The celllines marked in blue are characterized by a basal phenotype, while the ones marked in red are endowed with a luminal phenotype. ER = Estrogen receptor; HER2 = Human epidermal growth factor receptor 2; TN = Triple negative
adduct forms. Lipid species were grouped in 23 classes according to their chemical structures. Each class contains a different number of chemical species (Fig. 2a
and Additional file 2: Table S1). For instance, Diacylglycerophosphocholines (PCs) consist of 203 features, while 40 cardiolipins (CLs) are identified. PCA of the
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Fig. 2 Basal lipidomic profiles of breast cancer cells. a The panel illustrates the complement of constitutive lipids determined in breast cancer cells growing under standard conditions. Lipids are classified in the indicated groups on the basis of their general chemical structure. The number of chemical species identified for each class of lipids are indicated on the vertical axis. b The diagram shows a bidimensional principal component analysis (PCA) of the constitutive lipidomic profiles determined in each cell-line exposed to DMSO. c The left PCA analysis illustrates the lipid species whose levels are significantly higher in luminal than basal (green points) and basal than luminal (red points) cell-lines. The right bar graph indicates the lipid classes whose levels are significantly higher in luminal (green bars) and basal (red bars) cell-lines. The data are expressed as in panel (A). o-TG/p-TG = alkyldiacylglycerols/1Z-alkenyldiacylglycerols; TG = triacylglycerols; DG = diacylglycerols; SE = steryl esters; Nglyco-SP = neutral glycosphingolipids; SM = sphingomyelins; CER = ceramides; DHCER = dihydroceramides; SPH/SP = sphingosines/sphinganines; CL = cardiolipins; LBPA/BMP = lysobisphosphatidic acid/ bis(monoacylglycero)phosphate; PS = phosphatidylserines; PI = phosphatidylinositols; PG = phosphatidylglycerol; p-PE = 1-alkyl-2-acylglycerophosphoethanolamines/1-alkenyl-2-acylglycerophosphoethanolamines; PE = phosphatidylethanolamines; o-PC/p-PC = 1-alkyl-2-acylglycerophosphocholines/1-alkenyl-2-acylglycerophosphocholines; PC = phosphatidylcholines; LPE = lysophosphatidylethanolamines; o-LPC/p-LPC = 1-alkyl-glycerophosphocholines/1-alkenyl-glycerophosphocholines; LPC = lysophosphatidylcholines; CAR = acylcarnitines; FA = fatty acids
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constitutive lipid profiles separates luminal from basal cell-lines (Fig. 2b). Thus, the two cell-line groups are characterized not only by different gene-expression patterns, but also by different complements of lipids. Compared to the luminal counterparts, basal cell-lines show greater amounts of many TGs, diacylglycerophosphoserines or phosphatidylserines (PSs) and PCs, some diacylglycerophosphoinositols or phosphatidylinositols (PIs), neutral glycosphingolipids (N-glyco-SPs), CLs, lysophosphatidylcholines (LPCs), sphingomyelins (SMs) and 1-alkyl-2-acylglycerophosphocholines/1-alkenyl-2acylglycerophosphocholines (o-PCs/ p-PCs), as well as all the identified steryl-esters (SEs), monoacylglycerophosphoethanolamines (lysophosphatidylethanolamines, LPEs) and 1-alkenyl-phosphatidylethanolamine (p-PE) (Fig. 2c). In contrast, the levels of 3 triacylglycerols (TGs), 2 PCs, 1 pPC, 1 ceramide (CER) and 1 diacylglycerophosphoethanolamine (phosphatidylethanolamine, PE) are higher in luminal than basal cell-lines. Although luminal and basal cell-lines show different complements of individual features, the average constitutive levels of the 23 classes of lipids do not vary in the two groups (Additional file 1: Figure S1 and Additional file 2: Table S1).
ATRA perturbs the lipidomic profiles of luminal and basal breast-cancer cell-lines We compared the mass-spectrometry data obtained in all the cell-lines exposed to DMSO or ATRA (10− 6 M) for 48 h. The selection of the retinoid concentration and exposure time is based on pilot studies conducted in SK-BR-3 cells. These studies demonstrate that maximal alterations in the lipidomic profiles are observed with 10− 6 M ATRA, while the 48-h exposure time precedes any significant effect on the number of cells [11].
ATRA causes significant alterations of the lipidomic profiles in all the cell-lines considered (PCA, Additional file 1: Figure S2 and Additional file 2: Table S1). The retinoid determines the largest perturbations in cell-lines characterized by high/intermediate ATRA-sensitivity, regardless of the luminal or basal phenotype. Indeed, the effects triggered by ATRA in low-sensitivity/resistant cells are less evident, which is consistent with an association between the changes in the lipidomic profiles and the retinoid-dependent antiproliferative effects (Additional file 1: Figure S2). We evaluated the effects exerted by ATRA on each of the 23 classes of lipids identified (Additional file 1: Figures S3-S5). For the majority of the classes, ATRA either triggers variable and cell-specific alterations in the total levels of the corresponding lipid components or causes no perturbation at all (Additional file 1: Figures S6-S8). The most interesting effects of ATRA are observed with N-glycoSPs, LPCs, PSs (Fig. 3) and CLs (Fig. 5).
N-glyco-SPs are a group of cell-membrane sphingolipids and participate in biological processes such as cell
adhesion and cell-cell interactions [35]. With the exception of retinoid-resistant HCC-1419 cells, ATRA increases N-glyco-SPs levels in all luminal cell-lines (Fig. 3, left). HCC-1187 is the only basal cell-line where a similar effect is observed. Hence, the ATRA-dependent increase of N-glyco-SPs is specific to luminal cells and it is not associated with the growth-inhibitory action exerted by ATRA in this breast cancer cell type. The point is illustrated by the low R2 correlation index calculated for the ATRA/DMSO ratio of the N-glyco-SP mean values determined in each cell-line and the corresponding ATRAScore (Fig. 3, right).
LPCs result from phospholipase A2-dependent partial hydrolysis of phosphatidylcholines, which removes one of the fatty acid groups [36]. Similar to what is observed with N-glycoSPs, there is a trend towards a retinoiddependent increase in the levels of LPCs in all luminal cell-lines, regardless of their sensitivity to ATRA (Fig. 3, left). The sole exception is represented by the ZR75.1 cell-line, which shows no alteration in the amounts of LPCs following exposure to ATRA. The effects observed in basal cell-lines are variable and devoid of any association with the ATRA-dependent anti-proliferative action. Taken together the data suggest that the perturbations afforded by ATRA on LPC levels are not involved in the antiproliferative action of the retinoid in either luminal or basal cell-lines. The conclusion is supported by the relatively low R2 correlation index between the ATRA/DMSO ratio of the LPC mean values and the ATRA-score (Fig. 3, right). The LPCs up-regulation observed in luminal cells may be related to ATRA metabolism and bio-disposition. In fact, LPCs are by-products of the transacylation reaction catalyzed by lecithin retinol acyl transferase (LRAT) which results in the conversion of all-trans retinol into all-trans retinyl ester, a storage form of Vitamin A [37].
PSs are cell membrane glycerophospholipids differing in their fatty acid composition and they are involved in cell-cycle signaling and apoptosis [38, 39]. In the four luminal and highly retinoid-sensitive SK-BR-3, HCC1500, CAMA1 and MDA-MB-361 cell-lines, ATRA causes a reproducible reduction in the total amounts of the PSs identified (Fig. 3, left). With the exception of ZR75.1, a similar effect is not observed in the other luminal cell-lines characterized by intermediate/low sensitivity to the growth-inhibitory action of ATRA. HCC-1599 is the only basal cell-line showing an ATRAdependent decrease in PSs. The data obtained result in a relatively elevated R2 coefficient of correlation between the ATRA/DMSO ratio of the PS mean values determined in each cell-line and the corresponding ATRAScore (Fig. 3, right). Taken together, our results suggest that the retinoid-dependent alterations in the levels of PSs play a role in the anti-proliferative effect exerted by ATRA predominantly in the context of luminal breast
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Fig. 3 ATRA effects on the levels of N-glyco-sphingolipids, lysophoshatidylcholines and phosphatidylserines. Biological triplicates of the indicated breast cancer cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for 48 h. The box plots show the median ± SD levels of neutral glycosphingosines (N-Glyco-SP), lysophoshatidylcholines (LPC) and phosphatidylserines (PS). The number of different molecules identified by mass-
spectrometry is indicated in parenthesis. Luminal cell-lines are marked in red and basal cell-lines are marked in blue. The luminal and basal celllines are ordered according to decreasing sensitivity to the anti-proliferative effect of ATRA from left to right, as indicated (decreasing ATRA-score). *Significantly different (p < 0.05) from the corresponding vehicle treated control using the Student’s t-test. **Significantly different (p < 0.01) from the corresponding vehicle treated control using the Student’s t-test. The diagrams on the right indicate the correlations between the ATRA/ DMSO ratio of the mean values calculated for the indicated lipid class in each cell-line and the corresponding ATRA-score
cancer cells. However, this hypothesis needs to be supported by further functional studies.
ATRA reduces the motility of cell lines which respond to ATRA with an increase in N-glyco-SPs Given the potential significance of N-glyco-SPs in cell adhesion and cell-cell interactions, the retinoid-dependent up-regulation of this particular subset of lipids in luminal breast cancer cells may have implications for the
anti-metastatic and anti-motility effect exerted by ATRA in this type of mammary tumor [27]. To support this idea, we performed studies on the effects exerted by ATRA on the random-motility of four cell lines. To this purpose, we selected the luminal MDA-MB-361 and MDA-MB-175VII cell lines, which are characterized by N-glyco-SP up-regulation upon ATRA exposure, as well as the luminal HCC-1419 and the basal MDA-MB-157 cells, which do not show a retinoid-dependent induction
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of the same type of lipids. Cells were pretreated with ATRA (10− 6 M) or vehicle (DMSO) for 16 h and subjected to a random-motility assay for another 24 h (Fig. 4). ATRA causes a significant reduction in the motility of MDA-MB361 and MDA-MB-175VII cells, while the retinoid does not alter the motility of HCC-1419 and MDA-MB-157 cells. In addition, we previously demonstrated [27] that ATRA reduces the directional motility of SK-BR-3, a luminal cell line whose N-glyco-SP levels are up-regulated by ATRA, although the up-regultaion does not reach statistical significance in our experimental conditions (Fig. 3).
Taken together, the cell-motility data support the idea that up-regulation N-glyco-SPs contribute to the antimotility and anti-metastatic action of ATRA in luminal breast cancer cells.
ATRA causes a specific down-regulation of CLs in sensitive breast-cancer cell-lines The most interesting pattern of lipid perturbations afforded by ATRA involves CLs, a set of glycerophospholipids consisting of two phosphatidic acid moieties connected to a glycerol backbone (Additional file 1: Figure S9). Given the presence of 4 distinct alkyl chains, the potential complexity of CL individual species is
enormous. However, in most animal tissues, CLs contain 18-carbon fatty alkyl chains each characterized by 2 unsaturated bonds [40]. Our lipidomic analysis identifies 40 CL species whose constitutive levels vary in each cell-line and are differentially modulated by ATRA (Additional file 2: Table S1). Across our panel of cell-lines, CLs show the highest levels of correlation with ATRA anti-proliferative effects. In fact, ATRA reduces the overall amounts of CLs in the luminal and highly sensitive, SK-BR-3, HCC-1500, CAMA1 and MDA-MB-361 cells. A similar ATRA-dependent reduction is observed in basal HCC-1599 and MDA-MB-157 cells (Fig. 5a, left). In addition, the ATRA/DMSO ratio of the CL mean-values in each cell-line is inversely correlated with the corresponding ATRA-scores and shows a high R2 index (Fig. 5a, right). The observed association supports the idea that the reduction in the overall amounts of CLs contributes to the anti-proliferative action of ATRA in both luminal and basal cell-lines. We evaluated the time and concentration dependence of the CLs decrease induced by ATRA in luminal and retinoid-sensitive SK-BR-3 cells (Additional file 3: Table S2). In this cellular context, the effect of ATRA is relatively late and long-lasting, as a significant reduction in CL levels is evident only at 24 h and it is maintained until 72 h (Fig. 5b). In addition, CLs down-regulation is concentration
Fig. 4 Effect of ATRA on the random motility of breast cancer cells. Biological triplicates of the indicated luminal (MDA-MB-361, MDA-MB-175VII and HCC-1419; marked in red) and basal (MDA-MB-157; marked in blue) cell lines. Cells were pre-treated with vehicle (DMSO) or ATRA. Each point is the Mean + SD of 40 cells. ***Significantly lower than the vehicle curve (p < 0.001 following two-way ANOVA Bonferroni post-test)
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Fig. 5 ATRA effects on the levels of cardiolipins. a Biological triplicates of the indicated breast cancer cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for 48 h. Left: The box plots show the median ± SD levels of cardiolipins (CLs). The number of different CL molecules identified by
mass-spectrometry is indicated in parenthesis. Luminal cell-lines are marked in red and basal cell-lines are marked in blue. The luminal and basal
cell-lines are ordered according to decreasing sensitivity to the anti-proliferative effect of ATRA from left to right, as indicated (decreasing ATRA-
score). Right: The diagram indicates the correlations between the ATRA/DMSO ratio of the mean values calculated for CLs in each cell-line and the corresponding ATRA-score. b Biological triplicates of SK-BR-3 cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for the indicated
amounts of time. The box plot shows the median ± SD levels of cardiolipins (CLs). c Biological triplicates of SK-BR-3 cells were treated with vehicle
(DMSO) or the indicated concentrations of ATRA for 48 h. The box plot shows the median ± SD levels of cardiolipins (CLs). *Significantly different (p < 0.05) from the corresponding vehicle treated control using the Student’s t-test. **Significantly different (p < 0.01) from the corresponding vehicle treated control using the Student’s t-test
dependent, as indicated by the results obtained following exposure of SK-BR-3 cells to increasing amounts of ATRA (Fig. 5c).
The ATRA-dependent decrease in CL levels is accompanied by down-regulation of genes involved in mitochondrial oxidative phosphorylation We focused our attention on the specific downregulation of CLs afforded by ATRA in sensitive cell-
lines. CLs are part of the composite glycerophospholipid metabolic pathway (https://www.genome.jp/kegg/pathway.html). To obtain insights into the mechanism underlying the ATRA-dependent down-regulation of CLs, we evaluated the RNA-sequencing data obtained in all the 16 cell-lines exposed to ATRA (10− 6 M) or vehicle for 24 h (M. Bolis et al., Array Express ref. No: EMTAB-8408). Using these data, we determined the effects of ATRA on the expression of the 77 genes
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involved in the glycerophospholipid metabolic pathway (Additional file 1: Figure S10).
Although specific genes are significantly up- or downregulated by ATRA in single cell-lines (for instance see the expression pattern of MBOAT1, Additional file 1: Figure S10), there is no significant correlation (low R2 values) between the ATRA/DMSO expression ratio of any of these genes and the ATRA-score values. The results support the idea that the ATRA-dependent CLs decrease observed in retinoid sensitive cell-lines cannot be explained by up-regulation of specific genes controlling the catabolism of CLs or down-regulation of genes involved in their biosynthesis. CLs are predominantly located in the inner membrane of mitochondria, where they are involved in oxidative phosphorylation [41]. This suggests that the anti-proliferative effect exerted by ATRA in sensitive cell-lines may be accompanied by perturbations in mitochondrial homeostasis. Pathway enrichment analysis of the RNA-sequencing data supports this idea. In fact, “Oxidative Phosphorylation” lays in third position among the 4 top Hallmark gene-sets enriched for genes down-regulated by ATRA in sensitive luminal and basal cell-lines (Fig. 6a). The other 3 top gene-sets collectively down-regulated by ATRA are “Myc Targets”, “E2F Targets” and “G2M Checkpoint”. The down-regulation of these gene-sets, which control cellcycle and proliferation, is likely to be associated with the growth-inhibitory action exerted by ATRA in sensitive cell-lines.
The “Oxidative Phosphorylation” gene-set consists of 135 genes coding for mitochondrial proteins [42]. The vast majority of mitochondrial proteins are encoded by nuclear genes. Oxidative Phosphorylation is responsible for the production of ATP from NADH via the activity of 5 large protein complexes (mitochondrial complexes I-V) situated in the inner mitochondrial membrane. ATRA down-regulates approximately half of the “Oxidative Phosphorylation” genes in the luminal and basal cell-lines characterized by high/intermediate sensitivity to the retinoid (see black square brackets in Fig. 6b). In these cell-lines, the level of down-regulation correlates with retinoid-sensitivity. Indeed, the highest downregulation is observed in basal HCC-1599 and luminal SK-BR-3 cells, which are characterized by the 2 top ATRA-scores. With the exception of ND6, all the genes down-regulated by ATRA in sensitive cells are of nuclear origin. Down-regulation of the “Oxidative Phosphorylation” gene-network by ATRA is a relatively early event, as indicated by the RNA-sequencing data obtained in HCC-1599 cells exposed to ATRA (10− 6 M) for 8 h (Fig. 6b). In fact, a significant decrease in the levels of most of the downregulated genes is already evident at this time point. This is consistent with the idea that ATRA causes a rapid transcriptional repression of various nuclear genes coding for mitochondrial proteins.
ATRA-dependent reduction of CLs is associated with a
decrease in the number and activity of mitochondria Given the observed down-regulation of CLs and the expression of multiple genes involved in oxidative phosphorylation, we evaluated the action of ATRA on the amounts and function of mitochondria in selected luminal cell-lines characterized by sensitivity and resistance to the anti-proliferative effects of the retinoid. We focused our attention on two couples of homogeneous luminal and HER2+ cell-lines (SK-BR3/HCC-1419 and MDA-MB-361/HCC-202). Indeed, PCA demonstrates that the constitutive lipidomic profiles of the ATRA-sensitive SK-BR-3 and the ATRA-insensitive HCC1419 cell-lines are very similar (Fig. 2b). Similar constitutive lipidomic profiles are also observed in ATRA-sensitive MDA-MB-361 cells and the much less responsive HCC-202 counterparts.
To determine the amounts of mitochondria, SK-BR-3 and HCC-1419 cells were exposed to ATRA (10− 6 M) for 24, 48 and 72 h, stained with Mitotracker and subjected to quantitative fluorescence microscopy (Fig. 7a and Fig. 7c). In SK-BR-3 cells, ATRA causes a significant reduction in Mitotracker-associated fluorescence, which is already evident at 24 h and it is maintained at 48 and 72 h (Fig. 7a). The results obtained at 48 h are confirmed by FACS analysis of the Mitotracker-stained cells (Fig. 7b, left). These data are consistent with an ATRA-triggered decrease in the amounts of mitochondria. The phenomenon is validated by measurement of the total amounts of mitochondrial proteins (Fig. 7b, right). The decrease in the amounts of mitochondria caused by ATRA in SK-BR-3 cells is dose-dependent and the phenomenon is already evident at 10− 8 M ATRA (Fig. 7e). The reduction in the number of mitochondria is likely to be one of the mechanisms at the basis of the anti-proliferative action exerted by ATRA, as indicated by the results obtained in HCC-1419 cells. In fact, exposure of this ATRA-insensitive cell-line to the retinoid causes an early and paradoxical increase in Mitotrackerassociated fluorescence, which is observed at 24 h and reverts to baseline by 48 h (Fig. 7c). In addition, FACS analysis shows no difference between HCC-1419 cells exposed to vehicle or ATRA for 48 h (Fig. 7d, left) and the amounts of total mitochondrial proteins are not altered by the retinoid (Fig. 7d, right). The results of the SK-BR-3/HCC-1419 cell pair are consistent with what is observed in the MDAMB-361/HCC-202 counterpart exposed to 10− 6 M ATRA for 48 h. In fact, the data obtained with the use of quantitative immuno-histochemical (Fig. 7f/g, lower leftmost diagrams) and FACS (Fig. 7f/g, lower rightmost diagrams) analyses demonstrate a reduction in the amounts of mitochondria only in the sensitive MDA-MB-361.
To validate and extend the data obtained on mitochondria, we performed quantitative morphological studies on these organelles following isolation from the retinoidsensitive SK-BR-3 and the retinoid-resistant HCC-1419 cell
(2019) 38:436
RESEARCH
Open Access
Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid
Mineko Terao1†, Laura Goracci2,3†, Valentina Celestini1†, Mami Kurosaki1, Marco Bolis1, Alessandra Di Veroli2, Arianna Vallerga1, Maddalena Fratelli1, Monica Lupi4, Alessandro Corbelli5, Fabio Fiordaliso5, Maurizio Gianni1, Gabriela Paroni1, Adriana Zanetti1, Gabriele Cruciani2,3 and Enrico Garattini1*
Abstract
Background: All-trans-retinoic-acid (ATRA) is a promising agent in the prevention/treatment of breast-cancer. There is growing evidence that reprogramming of cellular lipid metabolism contributes to malignant transformation and progression. Lipid metabolism is implicated in cell differentiation and metastatic colonization and it is involved in the mechanisms of sensitivity/resistance to different anti-tumor agents. The role played by lipids in the anti-tumor activity of ATRA has never been studied.
Methods: We used 16 breast cancer cell-lines whose degree of sensitivity to the anti-proliferative action of ATRA is known. We implemented a non-oriented mass-spectrometry based approach to define the lipidomic profiles of each cell-line grown under basal conditions and following treatment with ATRA. To complement the lipidomic data, untreated and retinoid treated cell-lines were also subjected to RNA-sequencing to define the perturbations afforded by ATRA on the whole-genome gene-expression profiles. The number and functional activity of mitochondria were determined in selected ATRA-sensitive and –resistant cell-lines. Bio-computing approaches were used to analyse the high-throughput lipidomic and transcriptomic data.
Results: ATRA perturbs the homeostasis of numerous lipids and the most relevant effects are observed on cardiolipins, which are located in the mitochondrial inner membranes and play a role in oxidative-phosphorylation. ATRA reduces the amounts of cardiolipins and the effect is associated with the growth-inhibitory activity of the retinoid. Down-regulation of cardiolipins is due to a reduction of mitochondria, which is caused by an ATRAdependent decrease in the expression of nuclear genes encoding mitochondrial proteins. This demonstrates that ATRA anti-tumor activity is due to a decrease in the amounts of mitochondria causing deficits in the respiration/ energy-balance of breast-cancer cells.
Conclusions: The observation that ATRA anti-proliferative activity is caused by a reduction in the respiration and energy balance of the tumor cells has important ramifications for the therapeutic action of ATRA in breast cancer. The study may open the way to the development of rational therapeutic combinations based on the use of ATRA and anti-tumor agents targeting the mitochondria.
Keywords: Retinoic acid, Breast cancer, Lipidomics, Oxidative phosphorylation
* Correspondence: [email protected] Mineko Terao, Laura Goracci and Valentina Celestini equally contributed to the generation of the data and share the first-authorship. 1Laboratory of Molecular Biology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via La Masa 19, 20156 Milan, Italy Full list of author information is available at the end of the article
© The Author(s). 2019, corrected publication 2019. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Background All-trans-retinoic acid (ATRA) is a non-conventional and promising therapeutic agent acting on different types of solid/hematologic malignancies [1–5] and it is used in the treatment of acute-promyelocytic-leukemia (APL) [6]. In APL patients, ATRA induces the differentiation of leukemic cells, which is at the basis of its therapeutic activity. The unusual mechanism of action and the available pre-clinical data have raised interest in ATRA for the treatment of breast-cancer [7, 8].
Breast-cancer is a heterogeneous disease [9], although it is traditionally classified in three subgroups according to the presence/absence of the estrogen-receptor (ER), the progesterone-receptor (PR) and the HER2 protein. In addition, breast-cancers can be divided into luminal and basal tumors according to the morphological characteristics. Steroid hormone receptors are considered to be good therapeutic targets in luminal breast-cancer [10]. Recently, we demonstrated that a large proportion of luminal and ER+ mammary tumors are characterized by sensitivity to the anti-proliferative action of ATRA, while the triple-negative counterparts tend to be resistant [11, 12]. The biological activity of ATRA is mediated by specific steroid receptors (RARα, RARβ and RARγ), which act as ligand-dependent transcription factors under the form of heterodimers with other retinoid receptors known as RXRs (RXRα, RXRβ and RXRγ) [7, 13]. ATRA is a pan-RAR agonist, binding all RARs with the same affinity. In breast-cancer, we identified RARα as the retinoid receptor mediating the growth-inhibitory activity exerted by ATRA [11].
There is growing evidence that reprogramming of cellular lipid metabolism contributes to malignant transformation and progression [14–18]. In addition, lipids play a role in the mechanisms of sensitivity/resistance to different anti-tumor agents [19–22]. The involvement of lipids in the anti-tumor activity of ATRA has never been studied and this type of studies is now facilitated by the availability of technologies allowing the definition of the cellular lipidomic profiles [23–25]. The potential relevance of lipids for the anti-tumor action of ATRA is of interest given the role played in the growth, differentiation and metastatic spread, three processes affected by the retinoid [11, 26, 27].
Here, we evaluate the constitutive lipidomic profiles of breast-cancer cell-lines recapitulating the heterogeneity of the disease [11, 12] and the perturbations induced by ATRA. The lipidomic profiles of luminal and basal breast-cancer cell-lines are distinct. In addition, we identify cardiolipins (CLs) as the main lipid class modulated by ATRA in retinoid-sensitive breast-cancer cell-lines. Mechanistic and RNA-sequencing studies show that the ATRA-dependent down-regulation of CLs in sensitive cell-lines is accompanied by a reduction in the amounts and activity of mitochondria.
Materials and methods
Cell-lines The source and the characteristics of the 16 breastcancer cell-lines used are available in Additional file 1. The generation of the RARα over-expressing (RARA-C5) and relative control (Vect-C1) clones from MDA-MB453 cells as well as the RARα silenced (RARsA-sh18) and relative control (Vect-C6) clones from SK-BR-3 cells have been described [11]. The growth of cells was determined with the sulforhodamine assay [11].
Single-cell motility Single-cell motility assays were performed on coated culture wells by time-lapse microscopy, the Imaging Station CellRˆ (Olympus, Segrate, and the software Image J (Rasband W, National tutes of Health, Bethesda, MD).
BSAusing Italy) Insti-
Untargeted lipidomics Untargeted lipidomics studies were performed with Lipostar, a high-throughput software supporting targeted and untargeted liquid-chromatography/mass-spectrometry (LCMS) lipidomics [23, 28]. Further details on the methodological approach can be found in Additional file 1.
Mitochondrial studies Mitochondria were stained with MitoTarcker Deep Red FM (Invitrogen) according to the manufacturer instructions. Following staining, cells were fixed with 2% formalin and subjected to quantitative FACS analysis, using a fluorescence activated cell sorter (FACS, Becton and Dickinson). In the case of the experiments performed on the SK-BR-3, HCC-1419, MDA-MB-361 and HCC-202 lines, mitotracker stained cells were also subjected to quantitative microscopic analysis using the ImageJ software. Cells were counterstained with Hoechst 3342 (Thermofisher) for the determination of cell nuclei. For each experimental point, a minimum of 200 cells/field in at least 4 fields/experimental triplicate were quantitated. Mitochondria were isolated using a described protocol [29]. The enzymatic activity of mitochondrial complexes was determined on isolated mitochondria [30, 31]. The microviscosity of mitochondrial membranes was measured as described by M. Salmona et al. following staining with 1,6-diphenyl-1,3,5-hexatriene as a fluorescent probe [32].
RNA-sequencing studies
Three paired biological replicates of each breast-cancer cell-line were grown in DMEMF12 medium containing 5% charcolated FBS (Fetal Bovine Serum, Gibco) for 24 h. Cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for another 24 h. RNA was extracted with the mRNeasy Mini Kit (QIAGEN). RNA sequencing was
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performed using the Illumina TruSeq RNA librarypreparation kit and sequenced on the Illumina NextSeq500 with paired-end, 150 base pair long reads. The overall quality of sequencing reads was evaluated using FastQC [33]. Sequence alignments to the reference human genome (GRCh38) were performed using STAR (v.2.5.2a). Gene-expression was quantified using the comprehensive annotations available in Gencode [34]. Specifically, we used the v27 release of the Gene Transfer File (GTF). Raw-counts were further processed in the R Statistical environment and downstream differential expression analysis was performed using the DESeq2 pipeline. All the RNA-sequencing data relevant for this study were deposited in the EMBL-EBI Arrayexpress database (Accession No: E-MTAB-8408). Genes characterized by low mean normalized counts were filtered out by the Independent Filtering feature embedded in DESeq2 (alpha = 0.05). DESeq2-computed statistics were used as input for gene-set enrichment testing performed with the pre-ranked version of Camera. Statistical enrichments were determined for gene-sets obtained from the Hallmark (H), which are curated by the Molecular Signature DataBase (MSigDB).
Transmission electron microscopy ATRA-sensitive SK-BR-3 and ATRA-resistant HCC1419 cell lines were grown on plastic Petri dishes and fixed in phosphate buffer 0.12 M pH 7.4 containing 4% paraformaldehyde and 2% glutaraldehyde (Electron Microscopy Sciences, code #16220) for 10 min. Cells were scraped from the dishes, centrifuged at 13,000 rpm and kept in 0.12 M phosphate buffer containing 4% paraformaldehyde and 2% glutaraldehyde for 2 h. After postfixation in 0.12 M cacodylate buffer containing 1% OsO4 for 2 h and subsequent dehydration in graded series of ethanol, samples were cleared in propylene oxide, embedded in Epoxy medium (Epon 812 Fluka) and polymerized at 60 °C for 72 h. Ultrathin sections (70 nm thickness) were obtained with a Leica EM UC6 ultramicrotome, counterstained with uranyl acetate and lead citrate and examined with an Energy Filter Transmission Electron Microscope (EFTEM, ZEISS LIBRA® 120) equipped with a yttrium aluminium garnet (YAG) scintillator slow-scan charge-coupled device (CCD) camera (Sharp eye, TRS, Moorenweis, Germany). The numerical density of mitochondria (NV, n/μm3) was estimated by morphometrical analysis using 30 digitized electron microscope fields of cells for each group acquired by the iTem software (Olympus Soft Imaging Solutions, Germany) and digitally superimposing an orthogonal grid with ImageJ (1.52a version). Briefly, the mitochondrial profile area density (NA) was estimated by the ratio between the number of mitochondria and the cytoplasmic area. Mitochondrial volume density (VV) was determined by the ratio of grid
points falling over mitochondria divided by the total number of points of the grid contained in the cytoplasm. The numerical density of mitochondria (NV) was then estimated for each cell using the formula: NV = (1/β) (NA 3/2 / VV 1/2), where β is the shape coefficient for ellipsoidal mitochondria, calculated from the ratio of the armonic mean of major and minor axis of mitochondria sections measured on digital images. The mean mitochondrial volume was calculated for each cell as the ratio of mitochondrial volume density VV and numerical density NV.
Measurement of mitochondrial membrane microviscosity The microviscosity of mitochondrial membranes was measured as described by M. Salmona et al. following staining with 1,6-diphenyl-1,3,5-hexatriene as a fluorescent probe [3]. Isolated mitochondria containing an equal amount of proteins were incubated with 1,6diphenyl-1,3,5-hexatriene (2 × 10− 6 M) for 30 min at 37° and the fluorescence polarization values were determined using a fluorescence detector (Infinite F500, TECAN, Switzerland). The fluorescence polarization (FP) value is a function of the emission value (emission = 420 nm), which was detected through analyzers oriented in parallel (FP1) and perpendicular (FP2) to the direction of polarization of the excitation beam (excitation = 365 nm), according to the eq. FP = (FP2 - FP1 / FP2 + FP1).
Results
ATRA sensitivity and constitutive lipidomic profiles in luminal and basal breast-cancer cell-lines To conduct the study, we used 16 cell-lines whose degree of sensitivity to the anti-proliferative action of ATRA has been determined [11, 12]. Eight cell-lines come from triple-negative (TN) breast-cancers, while the other 8 cell-lines derive from luminal tumors characterized for HER2 and ER/PR expression. Consistent with the tumor origin, the constitutive gene-expression profiles determined by RNA-sequencing classify the celllines in two distinct basal and luminal groups (Fig. 1a). The 16 cell-lines are ranked according to their quantitative response to the anti-proliferative effect of ATRA using the continuous ATRA-score index (Fig. 1b) [11]. One basal (HCC-1599) and 4 luminal (SK-BR-3, HCC1500, CAMA1 and MDA-MB-361) cell-lines are classified as highly sensitive to ATRA. Three luminal (HCC202; MDA-MB-175VII; ZR75.1) and 3 basal (MB-157; MDA-MB-157; HS578T) cell-lines are endowed with intermediate sensitivity. One luminal (HCC-1419) and 4 basal (MDA-MB-231; CAL-851; HCC-1187; MDA-MB436) cell-lines show low sensitivity/resistance to ATRA.
We used a LC/MS-based approach [23] to define the lipidomic profiles of each cell-line grown under basal conditions. We generated a fingerprint composed of 530 chemical features identified as lipid species, some of them in multiple
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Fig. 1 Characteristics and sensitivity to ATRA of the breast cancer cell-lines used in the study. a The panel illustrates a dendrogram of the breast cancer cell-lines used in the study. Clustering of the cell-lines is based on the basal gene-expression profiles determined for each cell-line by NGS (Next Generation Sequencing). b The panel illustrates the sensitivity of each cell-line to the anti-proliferative action of ATRA defined by application of the ATRA-score model. The higher is the ATRA-score value the higher is the sensitivity of the cell-line to ATRA. The horizontal lines indicate the ATRA-score threshold values used to define the cell-lines characterized by high, intermediate and low sensitivity to ATRA. The celllines marked in blue are characterized by a basal phenotype, while the ones marked in red are endowed with a luminal phenotype. ER = Estrogen receptor; HER2 = Human epidermal growth factor receptor 2; TN = Triple negative
adduct forms. Lipid species were grouped in 23 classes according to their chemical structures. Each class contains a different number of chemical species (Fig. 2a
and Additional file 2: Table S1). For instance, Diacylglycerophosphocholines (PCs) consist of 203 features, while 40 cardiolipins (CLs) are identified. PCA of the
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Fig. 2 Basal lipidomic profiles of breast cancer cells. a The panel illustrates the complement of constitutive lipids determined in breast cancer cells growing under standard conditions. Lipids are classified in the indicated groups on the basis of their general chemical structure. The number of chemical species identified for each class of lipids are indicated on the vertical axis. b The diagram shows a bidimensional principal component analysis (PCA) of the constitutive lipidomic profiles determined in each cell-line exposed to DMSO. c The left PCA analysis illustrates the lipid species whose levels are significantly higher in luminal than basal (green points) and basal than luminal (red points) cell-lines. The right bar graph indicates the lipid classes whose levels are significantly higher in luminal (green bars) and basal (red bars) cell-lines. The data are expressed as in panel (A). o-TG/p-TG = alkyldiacylglycerols/1Z-alkenyldiacylglycerols; TG = triacylglycerols; DG = diacylglycerols; SE = steryl esters; Nglyco-SP = neutral glycosphingolipids; SM = sphingomyelins; CER = ceramides; DHCER = dihydroceramides; SPH/SP = sphingosines/sphinganines; CL = cardiolipins; LBPA/BMP = lysobisphosphatidic acid/ bis(monoacylglycero)phosphate; PS = phosphatidylserines; PI = phosphatidylinositols; PG = phosphatidylglycerol; p-PE = 1-alkyl-2-acylglycerophosphoethanolamines/1-alkenyl-2-acylglycerophosphoethanolamines; PE = phosphatidylethanolamines; o-PC/p-PC = 1-alkyl-2-acylglycerophosphocholines/1-alkenyl-2-acylglycerophosphocholines; PC = phosphatidylcholines; LPE = lysophosphatidylethanolamines; o-LPC/p-LPC = 1-alkyl-glycerophosphocholines/1-alkenyl-glycerophosphocholines; LPC = lysophosphatidylcholines; CAR = acylcarnitines; FA = fatty acids
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constitutive lipid profiles separates luminal from basal cell-lines (Fig. 2b). Thus, the two cell-line groups are characterized not only by different gene-expression patterns, but also by different complements of lipids. Compared to the luminal counterparts, basal cell-lines show greater amounts of many TGs, diacylglycerophosphoserines or phosphatidylserines (PSs) and PCs, some diacylglycerophosphoinositols or phosphatidylinositols (PIs), neutral glycosphingolipids (N-glyco-SPs), CLs, lysophosphatidylcholines (LPCs), sphingomyelins (SMs) and 1-alkyl-2-acylglycerophosphocholines/1-alkenyl-2acylglycerophosphocholines (o-PCs/ p-PCs), as well as all the identified steryl-esters (SEs), monoacylglycerophosphoethanolamines (lysophosphatidylethanolamines, LPEs) and 1-alkenyl-phosphatidylethanolamine (p-PE) (Fig. 2c). In contrast, the levels of 3 triacylglycerols (TGs), 2 PCs, 1 pPC, 1 ceramide (CER) and 1 diacylglycerophosphoethanolamine (phosphatidylethanolamine, PE) are higher in luminal than basal cell-lines. Although luminal and basal cell-lines show different complements of individual features, the average constitutive levels of the 23 classes of lipids do not vary in the two groups (Additional file 1: Figure S1 and Additional file 2: Table S1).
ATRA perturbs the lipidomic profiles of luminal and basal breast-cancer cell-lines We compared the mass-spectrometry data obtained in all the cell-lines exposed to DMSO or ATRA (10− 6 M) for 48 h. The selection of the retinoid concentration and exposure time is based on pilot studies conducted in SK-BR-3 cells. These studies demonstrate that maximal alterations in the lipidomic profiles are observed with 10− 6 M ATRA, while the 48-h exposure time precedes any significant effect on the number of cells [11].
ATRA causes significant alterations of the lipidomic profiles in all the cell-lines considered (PCA, Additional file 1: Figure S2 and Additional file 2: Table S1). The retinoid determines the largest perturbations in cell-lines characterized by high/intermediate ATRA-sensitivity, regardless of the luminal or basal phenotype. Indeed, the effects triggered by ATRA in low-sensitivity/resistant cells are less evident, which is consistent with an association between the changes in the lipidomic profiles and the retinoid-dependent antiproliferative effects (Additional file 1: Figure S2). We evaluated the effects exerted by ATRA on each of the 23 classes of lipids identified (Additional file 1: Figures S3-S5). For the majority of the classes, ATRA either triggers variable and cell-specific alterations in the total levels of the corresponding lipid components or causes no perturbation at all (Additional file 1: Figures S6-S8). The most interesting effects of ATRA are observed with N-glycoSPs, LPCs, PSs (Fig. 3) and CLs (Fig. 5).
N-glyco-SPs are a group of cell-membrane sphingolipids and participate in biological processes such as cell
adhesion and cell-cell interactions [35]. With the exception of retinoid-resistant HCC-1419 cells, ATRA increases N-glyco-SPs levels in all luminal cell-lines (Fig. 3, left). HCC-1187 is the only basal cell-line where a similar effect is observed. Hence, the ATRA-dependent increase of N-glyco-SPs is specific to luminal cells and it is not associated with the growth-inhibitory action exerted by ATRA in this breast cancer cell type. The point is illustrated by the low R2 correlation index calculated for the ATRA/DMSO ratio of the N-glyco-SP mean values determined in each cell-line and the corresponding ATRAScore (Fig. 3, right).
LPCs result from phospholipase A2-dependent partial hydrolysis of phosphatidylcholines, which removes one of the fatty acid groups [36]. Similar to what is observed with N-glycoSPs, there is a trend towards a retinoiddependent increase in the levels of LPCs in all luminal cell-lines, regardless of their sensitivity to ATRA (Fig. 3, left). The sole exception is represented by the ZR75.1 cell-line, which shows no alteration in the amounts of LPCs following exposure to ATRA. The effects observed in basal cell-lines are variable and devoid of any association with the ATRA-dependent anti-proliferative action. Taken together the data suggest that the perturbations afforded by ATRA on LPC levels are not involved in the antiproliferative action of the retinoid in either luminal or basal cell-lines. The conclusion is supported by the relatively low R2 correlation index between the ATRA/DMSO ratio of the LPC mean values and the ATRA-score (Fig. 3, right). The LPCs up-regulation observed in luminal cells may be related to ATRA metabolism and bio-disposition. In fact, LPCs are by-products of the transacylation reaction catalyzed by lecithin retinol acyl transferase (LRAT) which results in the conversion of all-trans retinol into all-trans retinyl ester, a storage form of Vitamin A [37].
PSs are cell membrane glycerophospholipids differing in their fatty acid composition and they are involved in cell-cycle signaling and apoptosis [38, 39]. In the four luminal and highly retinoid-sensitive SK-BR-3, HCC1500, CAMA1 and MDA-MB-361 cell-lines, ATRA causes a reproducible reduction in the total amounts of the PSs identified (Fig. 3, left). With the exception of ZR75.1, a similar effect is not observed in the other luminal cell-lines characterized by intermediate/low sensitivity to the growth-inhibitory action of ATRA. HCC-1599 is the only basal cell-line showing an ATRAdependent decrease in PSs. The data obtained result in a relatively elevated R2 coefficient of correlation between the ATRA/DMSO ratio of the PS mean values determined in each cell-line and the corresponding ATRAScore (Fig. 3, right). Taken together, our results suggest that the retinoid-dependent alterations in the levels of PSs play a role in the anti-proliferative effect exerted by ATRA predominantly in the context of luminal breast
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Fig. 3 ATRA effects on the levels of N-glyco-sphingolipids, lysophoshatidylcholines and phosphatidylserines. Biological triplicates of the indicated breast cancer cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for 48 h. The box plots show the median ± SD levels of neutral glycosphingosines (N-Glyco-SP), lysophoshatidylcholines (LPC) and phosphatidylserines (PS). The number of different molecules identified by mass-
spectrometry is indicated in parenthesis. Luminal cell-lines are marked in red and basal cell-lines are marked in blue. The luminal and basal celllines are ordered according to decreasing sensitivity to the anti-proliferative effect of ATRA from left to right, as indicated (decreasing ATRA-score). *Significantly different (p < 0.05) from the corresponding vehicle treated control using the Student’s t-test. **Significantly different (p < 0.01) from the corresponding vehicle treated control using the Student’s t-test. The diagrams on the right indicate the correlations between the ATRA/ DMSO ratio of the mean values calculated for the indicated lipid class in each cell-line and the corresponding ATRA-score
cancer cells. However, this hypothesis needs to be supported by further functional studies.
ATRA reduces the motility of cell lines which respond to ATRA with an increase in N-glyco-SPs Given the potential significance of N-glyco-SPs in cell adhesion and cell-cell interactions, the retinoid-dependent up-regulation of this particular subset of lipids in luminal breast cancer cells may have implications for the
anti-metastatic and anti-motility effect exerted by ATRA in this type of mammary tumor [27]. To support this idea, we performed studies on the effects exerted by ATRA on the random-motility of four cell lines. To this purpose, we selected the luminal MDA-MB-361 and MDA-MB-175VII cell lines, which are characterized by N-glyco-SP up-regulation upon ATRA exposure, as well as the luminal HCC-1419 and the basal MDA-MB-157 cells, which do not show a retinoid-dependent induction
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of the same type of lipids. Cells were pretreated with ATRA (10− 6 M) or vehicle (DMSO) for 16 h and subjected to a random-motility assay for another 24 h (Fig. 4). ATRA causes a significant reduction in the motility of MDA-MB361 and MDA-MB-175VII cells, while the retinoid does not alter the motility of HCC-1419 and MDA-MB-157 cells. In addition, we previously demonstrated [27] that ATRA reduces the directional motility of SK-BR-3, a luminal cell line whose N-glyco-SP levels are up-regulated by ATRA, although the up-regultaion does not reach statistical significance in our experimental conditions (Fig. 3).
Taken together, the cell-motility data support the idea that up-regulation N-glyco-SPs contribute to the antimotility and anti-metastatic action of ATRA in luminal breast cancer cells.
ATRA causes a specific down-regulation of CLs in sensitive breast-cancer cell-lines The most interesting pattern of lipid perturbations afforded by ATRA involves CLs, a set of glycerophospholipids consisting of two phosphatidic acid moieties connected to a glycerol backbone (Additional file 1: Figure S9). Given the presence of 4 distinct alkyl chains, the potential complexity of CL individual species is
enormous. However, in most animal tissues, CLs contain 18-carbon fatty alkyl chains each characterized by 2 unsaturated bonds [40]. Our lipidomic analysis identifies 40 CL species whose constitutive levels vary in each cell-line and are differentially modulated by ATRA (Additional file 2: Table S1). Across our panel of cell-lines, CLs show the highest levels of correlation with ATRA anti-proliferative effects. In fact, ATRA reduces the overall amounts of CLs in the luminal and highly sensitive, SK-BR-3, HCC-1500, CAMA1 and MDA-MB-361 cells. A similar ATRA-dependent reduction is observed in basal HCC-1599 and MDA-MB-157 cells (Fig. 5a, left). In addition, the ATRA/DMSO ratio of the CL mean-values in each cell-line is inversely correlated with the corresponding ATRA-scores and shows a high R2 index (Fig. 5a, right). The observed association supports the idea that the reduction in the overall amounts of CLs contributes to the anti-proliferative action of ATRA in both luminal and basal cell-lines. We evaluated the time and concentration dependence of the CLs decrease induced by ATRA in luminal and retinoid-sensitive SK-BR-3 cells (Additional file 3: Table S2). In this cellular context, the effect of ATRA is relatively late and long-lasting, as a significant reduction in CL levels is evident only at 24 h and it is maintained until 72 h (Fig. 5b). In addition, CLs down-regulation is concentration
Fig. 4 Effect of ATRA on the random motility of breast cancer cells. Biological triplicates of the indicated luminal (MDA-MB-361, MDA-MB-175VII and HCC-1419; marked in red) and basal (MDA-MB-157; marked in blue) cell lines. Cells were pre-treated with vehicle (DMSO) or ATRA. Each point is the Mean + SD of 40 cells. ***Significantly lower than the vehicle curve (p < 0.001 following two-way ANOVA Bonferroni post-test)
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Fig. 5 ATRA effects on the levels of cardiolipins. a Biological triplicates of the indicated breast cancer cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for 48 h. Left: The box plots show the median ± SD levels of cardiolipins (CLs). The number of different CL molecules identified by
mass-spectrometry is indicated in parenthesis. Luminal cell-lines are marked in red and basal cell-lines are marked in blue. The luminal and basal
cell-lines are ordered according to decreasing sensitivity to the anti-proliferative effect of ATRA from left to right, as indicated (decreasing ATRA-
score). Right: The diagram indicates the correlations between the ATRA/DMSO ratio of the mean values calculated for CLs in each cell-line and the corresponding ATRA-score. b Biological triplicates of SK-BR-3 cells were treated with vehicle (DMSO) or ATRA (10− 6 M) for the indicated
amounts of time. The box plot shows the median ± SD levels of cardiolipins (CLs). c Biological triplicates of SK-BR-3 cells were treated with vehicle
(DMSO) or the indicated concentrations of ATRA for 48 h. The box plot shows the median ± SD levels of cardiolipins (CLs). *Significantly different (p < 0.05) from the corresponding vehicle treated control using the Student’s t-test. **Significantly different (p < 0.01) from the corresponding vehicle treated control using the Student’s t-test
dependent, as indicated by the results obtained following exposure of SK-BR-3 cells to increasing amounts of ATRA (Fig. 5c).
The ATRA-dependent decrease in CL levels is accompanied by down-regulation of genes involved in mitochondrial oxidative phosphorylation We focused our attention on the specific downregulation of CLs afforded by ATRA in sensitive cell-
lines. CLs are part of the composite glycerophospholipid metabolic pathway (https://www.genome.jp/kegg/pathway.html). To obtain insights into the mechanism underlying the ATRA-dependent down-regulation of CLs, we evaluated the RNA-sequencing data obtained in all the 16 cell-lines exposed to ATRA (10− 6 M) or vehicle for 24 h (M. Bolis et al., Array Express ref. No: EMTAB-8408). Using these data, we determined the effects of ATRA on the expression of the 77 genes
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involved in the glycerophospholipid metabolic pathway (Additional file 1: Figure S10).
Although specific genes are significantly up- or downregulated by ATRA in single cell-lines (for instance see the expression pattern of MBOAT1, Additional file 1: Figure S10), there is no significant correlation (low R2 values) between the ATRA/DMSO expression ratio of any of these genes and the ATRA-score values. The results support the idea that the ATRA-dependent CLs decrease observed in retinoid sensitive cell-lines cannot be explained by up-regulation of specific genes controlling the catabolism of CLs or down-regulation of genes involved in their biosynthesis. CLs are predominantly located in the inner membrane of mitochondria, where they are involved in oxidative phosphorylation [41]. This suggests that the anti-proliferative effect exerted by ATRA in sensitive cell-lines may be accompanied by perturbations in mitochondrial homeostasis. Pathway enrichment analysis of the RNA-sequencing data supports this idea. In fact, “Oxidative Phosphorylation” lays in third position among the 4 top Hallmark gene-sets enriched for genes down-regulated by ATRA in sensitive luminal and basal cell-lines (Fig. 6a). The other 3 top gene-sets collectively down-regulated by ATRA are “Myc Targets”, “E2F Targets” and “G2M Checkpoint”. The down-regulation of these gene-sets, which control cellcycle and proliferation, is likely to be associated with the growth-inhibitory action exerted by ATRA in sensitive cell-lines.
The “Oxidative Phosphorylation” gene-set consists of 135 genes coding for mitochondrial proteins [42]. The vast majority of mitochondrial proteins are encoded by nuclear genes. Oxidative Phosphorylation is responsible for the production of ATP from NADH via the activity of 5 large protein complexes (mitochondrial complexes I-V) situated in the inner mitochondrial membrane. ATRA down-regulates approximately half of the “Oxidative Phosphorylation” genes in the luminal and basal cell-lines characterized by high/intermediate sensitivity to the retinoid (see black square brackets in Fig. 6b). In these cell-lines, the level of down-regulation correlates with retinoid-sensitivity. Indeed, the highest downregulation is observed in basal HCC-1599 and luminal SK-BR-3 cells, which are characterized by the 2 top ATRA-scores. With the exception of ND6, all the genes down-regulated by ATRA in sensitive cells are of nuclear origin. Down-regulation of the “Oxidative Phosphorylation” gene-network by ATRA is a relatively early event, as indicated by the RNA-sequencing data obtained in HCC-1599 cells exposed to ATRA (10− 6 M) for 8 h (Fig. 6b). In fact, a significant decrease in the levels of most of the downregulated genes is already evident at this time point. This is consistent with the idea that ATRA causes a rapid transcriptional repression of various nuclear genes coding for mitochondrial proteins.
ATRA-dependent reduction of CLs is associated with a
decrease in the number and activity of mitochondria Given the observed down-regulation of CLs and the expression of multiple genes involved in oxidative phosphorylation, we evaluated the action of ATRA on the amounts and function of mitochondria in selected luminal cell-lines characterized by sensitivity and resistance to the anti-proliferative effects of the retinoid. We focused our attention on two couples of homogeneous luminal and HER2+ cell-lines (SK-BR3/HCC-1419 and MDA-MB-361/HCC-202). Indeed, PCA demonstrates that the constitutive lipidomic profiles of the ATRA-sensitive SK-BR-3 and the ATRA-insensitive HCC1419 cell-lines are very similar (Fig. 2b). Similar constitutive lipidomic profiles are also observed in ATRA-sensitive MDA-MB-361 cells and the much less responsive HCC-202 counterparts.
To determine the amounts of mitochondria, SK-BR-3 and HCC-1419 cells were exposed to ATRA (10− 6 M) for 24, 48 and 72 h, stained with Mitotracker and subjected to quantitative fluorescence microscopy (Fig. 7a and Fig. 7c). In SK-BR-3 cells, ATRA causes a significant reduction in Mitotracker-associated fluorescence, which is already evident at 24 h and it is maintained at 48 and 72 h (Fig. 7a). The results obtained at 48 h are confirmed by FACS analysis of the Mitotracker-stained cells (Fig. 7b, left). These data are consistent with an ATRA-triggered decrease in the amounts of mitochondria. The phenomenon is validated by measurement of the total amounts of mitochondrial proteins (Fig. 7b, right). The decrease in the amounts of mitochondria caused by ATRA in SK-BR-3 cells is dose-dependent and the phenomenon is already evident at 10− 8 M ATRA (Fig. 7e). The reduction in the number of mitochondria is likely to be one of the mechanisms at the basis of the anti-proliferative action exerted by ATRA, as indicated by the results obtained in HCC-1419 cells. In fact, exposure of this ATRA-insensitive cell-line to the retinoid causes an early and paradoxical increase in Mitotrackerassociated fluorescence, which is observed at 24 h and reverts to baseline by 48 h (Fig. 7c). In addition, FACS analysis shows no difference between HCC-1419 cells exposed to vehicle or ATRA for 48 h (Fig. 7d, left) and the amounts of total mitochondrial proteins are not altered by the retinoid (Fig. 7d, right). The results of the SK-BR-3/HCC-1419 cell pair are consistent with what is observed in the MDAMB-361/HCC-202 counterpart exposed to 10− 6 M ATRA for 48 h. In fact, the data obtained with the use of quantitative immuno-histochemical (Fig. 7f/g, lower leftmost diagrams) and FACS (Fig. 7f/g, lower rightmost diagrams) analyses demonstrate a reduction in the amounts of mitochondria only in the sensitive MDA-MB-361.
To validate and extend the data obtained on mitochondria, we performed quantitative morphological studies on these organelles following isolation from the retinoidsensitive SK-BR-3 and the retinoid-resistant HCC-1419 cell