Background
Breast cancer is the most common cancer in women worldwide and the second leading cause of cancer-related death. In breast cancer, metastatic disease progression carries a poor prognosis, with 5-year survival rates of below 20% [
1,
2]. The prognosis is even worse in the case of triple negative breast cancer (TNBC), which lacks the major targets of approved therapies, limiting treatment options to surgery, radiotherapy and/or systemic chemotherapy [
3].
Breast cancer, like many other malignant tumors, shows a great molecular and phenotypic heterogeneity, both at an inter- and intra-tumoral level [
4‐
6]. This heterogeneity may be understood to be due to the accumulation of molecular alterations from an initial clone that undergoes Darwinian selection. During this evolution, certain core molecular alterations will be largely governed by cell-extrinsic phenomena, such as environmental conditions, including the immune response [
7‐
12]. This mechanism of tumor evolution has been observed in multiple tumor types [
13‐
15]. Tumor heterogeneity can result in an incomplete or incorrect diagnosis when small tumor samples or biopsies are used; consequently, treatments may be directed against targets that are not expressed throughout the entire tumor [
16‐
18].
Furthermore, the genetic-based type of tumor evolution cannot fully explain how all the functional and phenotypic alterations required to fulfill Weinberg’s 10 hallmarks of cancer [
19] can accumulate within a single cell clone. For this reason, the theory of clonal cooperation asserts that tumor clones have complementary genetic alterations that synergistically contribute to tumor progression and metastasis [
20‐
27]. This clonal cooperation, together with the influence of the tumor stroma and the immune system, is more likely to give rise to a functional consortium capable of altering all the biochemical pathways required for tumor formation [
20].
We therefore reason that analysis of tumor heterogeneity should not only be based on genetic alterations (mutations, amplifications, and translocations, among others) but should be complemented with functional analysis based on protein expression and pathway analysis to reveal tumor heterogeneity at the phenotypic level [
15,
28‐
31]. Phenotypic heterogeneity may also be caused by non-genetic alterations such as epigenetic changes or factors secreted from other cells within the tumor or tumor environment [
14,
18,
27,
32,
33]. In addition, conditions within the tumor, such as hypoxia, oxidative stress or starvation are not reflected in genetic alterations, even though numerous adaptive changes (e.g. metabolism) can be observed within the affected cells [
28]. Since most of these changes are brought about by altered cell signaling pathways, the evaluation of expression levels and activity status (e.g. phosphorylation) of signaling factors is currently the best approach to monitor functional tumor heterogeneity [
14,
28,
32,
34].
In order to study intratumoral heterogeneity and clonal cooperation on a functional level, we characterized the phenotypic features of individual clones isolated from a breast carcinoma cell line, MDA-MB-231, and compared these phenotypes with the parental cell population. We observed differences in gene expression among the different clones and were able to link many of these changes to alterations in cytokine-mediated intercellular signaling pathways. The importance of these alterations at the cellular level was demonstrated by clone-specific phenotypes in vitro and the metastatic potential in vivo. Based on these results, we propose a model in which clone-specific secretion and reception of factors allow synergistic growth and ultimately contribute to tumor progression and metastasis.
Methods
Cell culture and reagents
The study was conducted using the MDA-MB-231 cell line. This is an epithelial human breast cancer cell line, established from a pleural effusion of a 51-year-old Caucasian woman with metastatic breast adenocarcinoma. The MDA-MB-231 breast cancer cell line was purchased from the American Type Culture Collection (ATCC) and authenticated by DNA profiling using short tandem repeat (STR) (GenePrint® 10 System, Promega) at Genomics Core Facility, Instituto de Investigaciones Biomédicas “Alberto Sols” CSIC-UAM. Viral, bacterial and parasitic pathogen analysis by RT-PCR/PCR was performed at Dynamimed Research Company: no genetic material was detected. Cells were maintained at 37 °C in a 5% CO2 humidified incubator (AutoFlow UN-5510, Nuaire), in Dulbecco’s modified Eagle’s medium (DMEM) (Life Technologies) supplemented with 10% heat-inactivated fetal bovine serum (FBS) (Biowest) and antibiotics (penicillin, streptomycin) (Gibco®-Invitrogen). Cells were trypsinized/passaged every 2–3 days using TrypLE reagent (ThermoFisher Scientific). Cells were automatically counted using Countess cell counting chamber slides (Invitrogen) and an Eve Automatic cell counter (NanoEntek), excluding dead cells by trypan blue (Invitrogen) staining.
Color-coding (transfection), clone isolation and fluorescence confirmation
Ubc-StarTrack plasmids and the vector containing the hyperactive transposase of the PiggyBac system (hyPBase) were kindly provided by Dr. López-Mascaraque. Ubc-StarTrack plasmids were generated as previously described [
35]. MDA-MB-231 cells were treated with 20 μM chloroquine and transfected with 3.5 μg total UbC-StarTrack plasmid DNA plus 1.2 μg total HypBase (transposase) DNA, diluted in HBS (HEPES buffered saline). CaCl
2 was added to the medium to a final concentration of 150 mM. The medium was changed after six hours of incubation.
After transfection, the Ubc-StarTrack plasmids and the transposase under the control of the ubiquitous CMV promoter enter the nucleus. The Ubc-StarTrack plasmids are flanked by two terminal repeat sequences (ITRs) that are recognized and cut by the HypBase. The released sequence is integrated into the genome of the transfected cell at TTAA repeat regions, allowing the cell to stably produce the fluorescent 161 protein (Additional file
1: Figure S1A). This system allows tracking by color-coding of a complete population derived from the transfected cell.
Forty-eight hours after transfection, cells were trypsinized and isolated by fluorescence activated cell sorting (High Speed Cell Sorter FacsAria (Becton Dickinson)). We isolated cell clones expressing mT-Sapphire, EGFP, and monomeric Kusabira Orange (mKO) integrable plasmids. Cells were individually seeded in a 96 well plate to obtain clonal cell lines. Non-fluorescent cells were recovered to be used as a control (MDA-MB-231). The transfection efficiency was lower than 1%, showing that skewing of the parental cell line population was avoided. The clonal cell lines GFP C3, mKO E10, and Sapphire D7 and the MDA-MB-231 parental cell line were reauthenticated as described before. Fluorescence was confirmed on confocal microscopy (Spectral Confocal Microscope FV1000 (Olympus) and FV10-ASW 4.2 software. For every fluorescent protein the following excitation and emission wavelength settings were used: Ex.405-Em.520 (Sapphire), Ex.488-Em.520 (GFP), and Ex.515-Em.527 (mKO). After every trypsinization the percentage of fluorescent cells was determinate by flow cytometry (LSR Fortessa (BD), software FCS Express DeNovo), ruling out the possibility of fluorescent gene silencing.
Contrast phase image capture
Forty-eight hours after seeding, phase contrast images were taken using an Olympus FSX100 microscope (amplification 40X) and FSX-BSW software.
Cell count
Proliferation was evaluated by direct cell count. Fifty thousand cells were seeded in a six-well plate. Cells were trypsinized and automatically counted at the following time-points: 0 (24 h after seeding), 24, 48, and 72 h.
To calculate the cumulative population doublings (CPDs), 500,000 cells were seeded in a 100x17mm dish and trypsinized after 7 days in culture. Cells were counted and seeded again, repeating the same process for 4 weeks (28 days in culture). Cumulative population doublings were calculated using the following formula:
CPDs = [log(n° cells after 7 days) – log(n° seeded cells)] / log102.
Metabolic activity was evaluated by the MTT (3-[4,5-dimethylthiazol-25-yl]-2.5-diphenyl tetrazolium bromide; Panreac-AppliChem) assay. 2500 cells in 150 μL were seeded in 96-well plates in triplicate and the MTT assay was performed at time-point 0 (24 h after seeding), and at 24, 48 and 72 h. MTT was added to the medium to a final concentration of 0.5 mg/mL and incubated for 3 h at 37 °C. The medium was aspirated, and the formazan crystals were dissolved in 0.2 mL DMSO. Absorbance was measured at 595 nm using an Epoch Microplate Spectrophotometer (BioTek) and Gen 5 1.10 software.
3D proliferation was evaluated by sphere growth measurements at 1, 4 and 7 days after seeding. Ten thousand cells per well were grown in ultra-low attachment 96 well plates in the presence of 5% Matrigel® (v/v) after 10 min of centrifugation at 2000 rpm. Pictures were taken with an inverted microscope NIKON Eclipse TE2000–5 and processed by ImageJ software to measure volume growth.
Caspase assay
Caspase activity was measured using the Caspase-Family Colorimetric Substrate Set (K132, Biovision). Five hundred thousand cells were seeded in a 100x17mm dish and trypsinized after 96 h in culture. The pellet was resuspended in Cell Lysis Buffer (Biovision) and protein was quantified by Pierce™ BCA Protein Assay Kit (23,225, Thermo Fisher). A positive control was included: MDA-MB-231 cell line treated with Camptothecin (208,925, Merck) to a final concentration of 25 μg/mL for 24 h. 100 μg protein and pNA conjugated substrate to a final concentration of 0.5 mg/mL were added to each well in triplicate and incubated overnight at 37 °C. Absorbance was measured at 405 nm with an Epoch Microplate Spectrophotometer (BioTek).
Spheroid invasion assay
3D invasion assay was performed by embedding 4-day-old spheres of each clone in a Matrigel-Collagen I mixture on a pre-coated 24-well plate with the same mixture. Sphere invasion was analyzed by measuring the invaded area at 24 and 48 h using the inverted microscope NIKON Eclipse TE2000–5 and ImageJ software.
Migration assay
Five hundred thousand cells were seeded per well in 24-well plates in triplicate. After 24 h, the medium was replaced by medium without FBS and maintained overnight. Then, a wound was made in the monolayer with a pipette tip, and the medium was replaced with complete medium. Pictures of the wounds were taken at 0 h and 8 h using an Olympus FSX100 microscope. Wound closure was measured using ImageJ software. Results represent the migrated distance between 0 and 8 h, expressed as a percentage relative to MDA-MB-231.
Transposon insertion event detection and characterization
Paired-end sequencing raw reads were first processed to remove PCR duplicates using Fastuniq. Then, we trimmed the specific Inverted Repeat (IR) associated with the transposon insertion process (GATTATCTTTCTAGGGTTAA, length = 20) with Trimmomatic [
36]. This step was required to later select those reads that were shorter than the original read length (151), implying that they were covering a transposition event. To map the reads, we aligned the reads to the human reference genome g1k_v37 [
37] using Bowtie 2 and allowing 1 mismatch [
38]. Later, we filtered the alignment with SAMtools [
39] to select paired reads mapped unambiguously with a minimum alignment quality of 30. The final step of the process relied on basic shell text processing tools (awk/grep/sed) to subset those pairs where one of the reads presented a length ≤ 131 (expected read length after removing the IR) and extract them from a specific position in the chromosome representing the first mapped genome base contiguous to the IR. This list of positions required an additional prioritization step as the IR sequence was endogenously found in the human genome. To differentiate these artefactual cases from genuine transposition events we took advantage of one of the transposase properties: they do not perform even cuts in both reverse/forward strands but a staggered cut that generates a duplication of 5 bases. A consequence of this is the representation of a specific insertion event at two positions: n and n + 5. This criterion was used to depict actual transposition events and define the set of insertion events that passed to the last step of characterization. In this last process, we used BEDTools map function and the annotation related to the human genome reference selected to map the specific insertion positions to their genomic context [
40].
Analysis of the transcribed genome
The microarray service was carried out at the High Technology Unit (UAT) at Vall d’Hebron Research Institute (VHIR), Barcelona (Spain). Affymetrix GeneTitan microarray platform and the Genechip Human Clariom D array cartridges were used for this experiment. This array analyzes gene expression patterns on a whole-genome scale on a single array with probes covering many exons on the target genomes, and thus permits an accurate summary of gene expression.
1.5 × 106 cells were seeded in a 100x17mm dish in triplicate. After 72 h cells were trypsinized and centrifuged. RNA was extracted using the PureLink™ RNA Mini Kit (ThermoFisher). Quantification and assessment of RNA purity was performed using a NanoDrop™ 2000/2000c Spectrophotometer and confirmed according to the RIN (RNA Integrity Number) using RNA 6000 Nano Kit and 2100 Bioanalyzer (Agilent). Starting material was 200 ng of total RNA of each sample. Briefly, sense ssDNA suitable for labelling was generated from total RNA with the GeneChip WT Plus Reagent Kit from Affymetrix (Thermofisher-Affymetrix) according to the manufacturer’s instructions. Sense ssDNA was fragmented, labelled and hybridized to the arrays with the GeneChip WT Plus Terminal Labeling and Hybridization Kit from the same manufacturer.
Bioinformatic analysis was performed at the Statistics and Bioinformatics Unit (UEB) of the Vall d’Hebron Research Institute (VHIR, Barcelona, Spain). A Robust Multi-array Average (RMA) algorithm [
41] was used for pre-processing microarray data. Background adjustment, normalization and summarization of raw core probe expression values were defined so that the exon level values were averaged to yield one expression value per gene. Data were subjected to non-specific filtering to remove low variability genes. Conservative thresholds were used to reduce possible false negative results. Selection of differentially expressed genes was based on a linear model analysis with empirical Bayes modification for the variance estimates [
42]. To account for multiple testing,
P-values were adjusted to obtain stronger control over the false discovery rate (FDR), as described by the Benjamini and Hochberg method. The analysis of biological significance was based on enrichment analysis against the Gene Ontology (GO;
http://www.geneontology.org) and KEGG (
http://www.genome.ad.jp/kegg/) databases.
DNA methylation analysis
Microarray-based DNA methylation analysis was conducted with the Infinium MethylationEPIC BeadChip microarray (Illumina, San Diego, CA), that covers over 850,000 CpG methylation sites (850 K). 1.5 × 10
6 cells were seeded in a 100x17mm dish in triplicate. After 72 h cells were trypsinized and centrifuged. Pellets were frozen until DNA extraction. DNA quality checks, bisulfite modification, hybridization, data normalization, statistical filtering, and beta (β) value calculations were performed as described elsewhere [
43,
44]. The DNA concentration of the samples was measured using the Quantifluor ONE dsDNA System (Promega). A total of 500 ng of DNA samples were selected for bisulfite conversion with the EZ DNA Methylation™ Kit (Zymo Research). The Illumina Infinium HD methylation protocol was followed for the hybridization to the Infinium MethylationEPIC BeadChips. Whole-genome amplification and hybridization were performed on the BeadChips and followed by single-base extension and analysis on a HiScan (Illumina, San Diego, CA) to assess the cytosine methylation states. The methylation score of each CpG was represented as β value, and previously normalized for color bias adjustment, background level adjustment and quantile normalization across arrays. Probes and sample filtering involved a two-step process for removing SNPs and unreliable betas with a high detection
P-value > 0.01. Sex chromosome probes were also removed. After this filtering, the remaining CpGs were considered valid for the study.
Cytokine quantification
1.5 × 106 cells were seeded in a 100x17mm dish in triplicate. After 72 h the medium was collected and filtered through 0.22 μm filters (Merck Millipore) to remove floating cells, apoptotic bodies and cell debris. The concentrations of the cytokines TNF alpha, IFN gamma, IL-1 beta, IL-2, IL-4, IL-5, IL-6, IL-8, IL-9, IL-10, IL-12p70, IL-13, IL-17A, GM-CSF, MCP1, MIP1a and MIP1b were determined using the FirePlex Human Key Cytokines - Immunoassay Panel (ab229791) by Abcam FirePlex Service Lab.
Complementation assays
To test the presence of factors that could increase proliferation and metabolic activity, the media where the parental cell line or a clone were cultured for several days were recovered. The medium was tested by two independent assays (MTT and cell count). Exosomes were tested by MTT. “Donors cells” were cultured as follows: 17,600 cells/cm2 (medium complementation) or 10,400 cells/cm2 (exosome complementation) were seeded in 0.17 or 0.1 mL complete medium/cm2, respectively. Twenty-four hours before treatment the “receptor cells” were seeded: 1250 cells in 150 μL were seeded in 96-well plates in triplicate (MTT assay) or 25,000 cells in 3 mL were seeded in 6-well plates in duplicate (cell count). Seventy-two hours after the “donor” seeding, the medium was recovered. The medium was filtered through 0.22 μm filters (Merck Millipore) to remove possible floating cells and added to the “receptor cells” (complete medium, CM). The medium was also ultracentrifuged to extract exosomes, the supernatant after two ultracentrifugations was recovered (soluble factors, SF) and the pellets were resuspended in PBS (exosomes). Exosome protein concentration was quantified by BCA Protein Assay kit (ThermoFisher).
To perform the direct cell count, donor medium was added to new medium to a final concentration of 0, 10, 25 and 50%. Cells were counted after 96 h’ treatment.
For the MTT assay, donor medium was added to new medium to a final concentration of 0, 25 and 50%. MTT assay was performed at time-point 0 (24 h after seeding), 72 and 96 h. To study the effect of exosomes on cell metabolic activity, cells were treated with 50% complete medium and 50% soluble factors as a control. Exosomes were added to a final concentration of 5, 10, 20, 40, 80 and 160 μg protein/mL. MTT assay was performed at 72 h.
Exosome isolation
Seventeen thousand six hundred cells/cm2 were seeded in 0.1 mL complete medium/cm2. After 72 h in culture, supernatant was recovered and sequentially centrifuged as follows: 500 rcf/10 min, 12,000 rcf/20 min and 100,000 rcf/90 min (× 2). Finally, each pellet was resuspended in PBS.
Protein extraction and immunoblotting
Total protein extracts were generated using RIPA Lysis Buffer System (sc24948, SantaCruz Biotechnology) supplemented with Protease Inhibitor Cocktail set III (539134) and Phosphatase Inhibitor Cocktail Set II (524625) from Calbiochem. Protein was quantified using a BCA Protein Assay kit (23,225, ThermoFisher). Protein extracts (10 μg per sample) were loaded onto SDS-PAGE gels and electrophoretically transferred to PVDF membranes. The following primary antibodies were used: CD81 (sc-166,028, SantaCruz Biotechnology), TSG101 (ab83, Abcam) and b-actin (JLA20, Calbiochem). Goat anti-rabbit and anti-mouse HRP secondary antibodies were from Pierce ThermoScientific (31460) and Calbiochem (JA1200), respectively. Immunodetection of proteins was performed using Amersham ECL Western Blotting Detection Reagent (GE Healthcare).
Transmission electron microscopy
Exosomes were characterized by transmission electron microscopy (TEM), using negative staining. Electron microscopy images were recorded on a T20-FEI Tecnai thermoionic microscope operated at an acceleration voltage of 200 kV. Negative stained samples were prepared by dropping 20 μL of sample onto carbon coated copper grids (200 mesh), which were then dried at room temperature and stained with phosphotungstic acid. Exosome size was measured using ImageJ software.
Co-culture assay
MDA-MB-231, GFP C3, mKO E10 and Sapphire D7 cell lines were cultured as individual cell lines and as combinations, with 2, 3 and 4 cell lines in co-culture. The co-cultures started with equal percentages of every clone. Five hundred thousand total cells were seeded in a 100x17mm dish and trypsinized after 7 days in culture. Cells were counted and seeded again, repeating the same process for 4 weeks (28 days in culture). After every trypsinization the percentage of every cell line per co-culture was determinate by flow cytometry (LSR Fortessa (BD), software FCS Express DeNovo). CPDs were calculated as previously described. Expected CPDs were calculated using data from the individual plates (single culture). Observed CPDs were calculated using data from every co-culture.
Arsenite resistance assay
Two hundred thousand total cells were seeded in a 60x17mm dish. 24 h after seeding, cells were treated for 90 min with 250 μM Arsenite (NaAsO2 in complete medium). After treatment, cells were washed twice with PBS and new complete medium was added. Cells were counted after 72 h.
The co-culture experiment was performed in the presence of arsenite. The co-cultures started with equal percentages of every clone (100,000 cells per clone): MDA-MB-231 + GFP C3 or MDA-MB-231 + mKO E10. 24 h after seeding, cells were treated as detailed before. The percentage of each cell line in the total population was detected by flow cytometry at seeding (day 0), 90 min (day 1) and 72 h (day 4) after treatment.
Invasion assay
8-μm pore inserts were covered with 65 μL Matrigel (356,231, Corning) at a final concentration of 1.5 mg/mL. Matrigel was incubated for 4 h at 37 °C. Once the Matrigel was polymerized over the Matrigel layer, 30,000 cells were seeded in 100 μL medium without FBS. Complete medium (supplemented with FBS, which stimulates the cells to cross the Matrigel layer) was added to the well under the insert, covering the bottom of the insert. Twenty-four hours after seeding, cells were fixed with PFA 4% and counterstained with Hoechst. The top of the insert was cleaned with a cotton bud to remove the Matrigel and any cells that did not cross the layer. Images were taken of the entire insert bottom where the invading cells were located, using an Olympus FSX100 microscope (amplification 4.2X) and FSX-BSW software.
Following the previous description, we performed two different invasion assays, with co-culture and with medium complementation. Modifications to the previous protocol are detailed as follows:
(1)
Co-culture: GFP C3 and mKO E10 were seeded as single cell lines and as an equal combination of both cell lines.
(2)
Medium complementation: GFP C3 and mKO E10 were seeded as single cell lines. Complemented complete medium was added to the well under the insert, covering the bottom of the insert. Complemented medium was obtained as detailed in “Complementation assays”.
Animal experimentation
Female athymic nude mice (Strain: Hsd:Athymic Nude-Foxn1nu) (ENVIGO, Spain) were kept in pathogen-free conditions and used at 7 weeks of age. Animals were randomly housed under Specific Pathogen Free (SPF) conditions in autoventilated racks in groups of six. Two enrichment elements were included, a cardboard tube and a square nestlet for nesting and thermoregulation. The housing temperature ranged from 23 °C to 25 °C, relative humidity ranged between 47 and 55%. The cycle gradually simulates twilight and sunset, giving 12 h of light with an intensity of 300 Lux and 12 h of darkness for each 24 h period. Food and water were provided ad-libitum. Animal care was handled in accordance with the Guide for the Care and Use of Laboratory Animals of the Vall d’Hebron University Hospital Animal Facility, and the experimental procedures were approved by the Animal Experimentation Ethics Committee at the institution (76/17 CEEA). Body weight and physical appearance of the animals were monitored twice a week. The animals were euthanized by cervical dislocation following the euthanasia standard operating procedure (SOP) of Laboratory Animals of the Vall d’Hebron University Hospital Animal Facility. All the in vivo studies were performed by the ICTS ‘NANBIOSIS’, more specifically, by the CIBER-BBN in vivo Experimental Platform of the Functional Validation & Preclinical Research (FVPR) area (Barcelona, Spain).
The implanted cells were the MDA-MB-231 parental cell line, three in vitro isolated clones (mKO E10, GFP C3 and Sapphire D7), both individually and as a mix of the four lines in a ¼ ratio. The parental cell line was included in the mix to provide factors probably not produced by the clonal cell lines and which may be needed for tumor growth and/or metastasis. All cell variants were confirmed to be negative for viral, bacterial (including mycoplasma) and parasitic pathogens (VHIR Screening Humano Completo). The test was performed by the external reference laboratory Dynamimed Research Company. Prior to the injection, the percentage of fluorescent cells was quantified by flow cytometry, to confirm the injected cells expressed the fluorophore and exclude the possibility of fluorescent gene silencing.
The tumor growth rate and invasive capacities were evaluated by implantation of 2.5 × 106 cells into the right abdominal mammary fat pad (i.m.p.f.) of twelve animals per group (five groups). The tumor volume was measured by caliper measurements twice a week and calculated according to the formula D × d2/2, where D is the largest diameter of the tumor and d the smallest one. All animals were euthanized 34 days after inoculation to compare the primary tumor size and composition and the number and extent of lung metastases between groups. The tumors and lungs were weighed, fixed with paraformaldehyde 4%, and later processed for histopathological analyses (hematoxylin and eosin staining).
The metastasis growth rate of the MDA-MB-231 and clonal cell lines was evaluated by intravenous (IV) injection of 2.5 × 106 cells into the caudal tail vein of 10 animals per group (five groups). All animals were euthanized 36 days after inoculation. Animals underwent gross necropsy consisting of a macroscopic evaluation. Lungs were excised, weighed, fixed and processed for histopathological analysis.
Immediately following dissection, the tumors and lungs were fixed for 24 h by immersion in paraformaldehyde 4%. After fixation, the tissue was dehydrated to enable embedding with paraffin. Five-micron-thick sections were cut from fixed, paraffin-embedded tissues and mounted on poly-L-lysine-coated glass slides. Sections were deparaffinized in xylene and rehydrated in graded alcohol. The presence of clonal cells in the primary tumor and metastases were detected by fluorescence on confocal microscopy (Spectral Confocal Microscope FV1000 (Olympus)). To avoid spectral overlapping of the different fluorescent proteins, a Lambda scan was performed from 470 to 635 nm followed by spectral deconvolution using FV10-ASW 4.2 software. Images were quantified using the program ImageJ.
In vivo zebrafish tumor xenograft assays
Zebrafish (Danio rerio) embryos were generated by natural mating of adult fish according to previously described procedures (Westerfield, 2000). In order to remove surface pigmentation, embryos were incubated with PTU (N-Phenylthiourea, Sigma) at a 0.003% w/v concentration and maintained at 28 °C. For xenograft experiments, 2 days postfertilization (dpf) zebrafish embryos were de-chorionized if necessary and anaesthetized with 0.003% tricaine (Sigma) w/v in E3 water and positioned on a 10 cm Petri dish coated with 1.5% agarose. Immediately prior to injection, single cell suspensions of MDA-MB-231-GFP C3 cells and MDA-MB-231-mKO E10 cells were labelled with the lipophilic fluorescent tracking dyes CM-DiD and CM-DiI (Invitrogen) respectively, according to manufacturer’s instructions. To remove unincorporated dye, cells were centrifuged and rinsed twice with Dulbecco’s phosphate-buffered saline (DPBS). Cells were kept on ice before implantation and implanted within 3 h. For microinjection, the individual cell populations (individual injection) or the combination of both at equal numbers (co-injection) were loaded in borosilicate glass capillary needles (1 mm O.D. × 0.58 mm I.D, Harvard Apparatus) and approximately 300 cells were injected into the duct of Cuvier (DoC) using a micromanipulator and an IM 300 microinjector (Narishige) with an output pressure of 10 psi and 0.03 ms injection time. After injection, embryos were examined for the presence of a fluorescent cell mass at the injection site in the DoC, and then transferred to fresh PTU-containing E3 water and placed into an incubator at 34 °C for up to 3 days post injection (dpi). Zebrafish embryos were photographed at 0 h post injection (hpi) and 72 hpi with a fluorescent microscope DMi8 (Leica) to determine tumor cell dissemination. The number of tumor cells disseminated in the tail vein of the fish was analyzed with the software ImageJ Fiji. For each condition, data are representative of at least three independent experiments, with at least 30 embryos per group.
Statistics
Prism 5.0 software (GraphPad Software Inc., La Jolla, CA) was used for statistics and data representation. Significant differences were determined using unpaired t-test with Welch’s correction (equal SDs not assumed) and ANOVA (Tukey’s multiple comparisons test). Individual figure legends specify the test used in each case. Asterisks indicate significant differences when P-values are < 0.05 (*), < 0.01 (**), and < 0.001 (***).
Graphics
Graphics were created using Prism 5.0 software and Adobe® Illustrator CC.
Discussion
Breast cancer is the most frequently diagnosed neoplasm in women and a leading cause of cancer death [
1,
2]. Intertumor heterogeneity is one of the greatest issues in oncology, but it is not the only factor that makes patient treatment difficult: variation within a single tumor – intratumor heterogeneity – is also a key factor in determining the best treatment [
51].
Cellular heterogeneity in established breast cell lines, including the MDA-MB-231 cell line, has been described previously [
45,
52]. In this study we corroborate clonal heterogeneity in the MDA-MB-231 cell line of breast carcinoma, after the selection of clones marked with fluorochromes, using the StarTrack system (Additional file
1: Figure S1c). Clonal cell lines were selected to study the relevance of clonal communication in tumoral heterogeneity. The results from the experiments in vivo and in vitro demonstrated that despite all the observed phenotypic differences, the parental cell line, composed of a mix of an undetermined high number of clones, was equal or superior in terms of malignancy (tumor composition and metastasis) to the individual clonal cell lines in all tested conditions. Because the parental cell line is a mix of different clones, these results led us to the hypothesis that the interplay between different clonal populations within a heterogeneous population, by intercellular communication and/or feature complementation, provides advantages over isolated clonal cell lines.
Our results show that the mix of three clonal cell lines did not recover the features of a multiclonal population. For the study of tumor heterogeneity, the subcloning method limits the number of clones and makes reconstitution of a highly multiclonal population difficult. Therefore, the mix of several clones cannot be equated to a multiclonal population; rather, a parental cell line must be included to provide a true multiclonal population. However, subcloning may be a suitable method for the independent study of the single clones that constitute a cancer cell line or tumor.
Selected clonal cell lines showed variations in cell morphology (Fig.
1a, Additional file
2: Figure S2a), just as pathologists observe variation between different regions of the same tumor [
53,
54]. The clonal cell lines also showed differences at the biological (Fig.
1), tumorigenic (Figs.
2,
3, Additional file
3: Figure S3) and molecular levels, and in gene expression (Fig.
4), DNA methylation pattern (Fig.
5) and cytokine expression (Fig.
6), with clear functional heterogeneity. Parental cells showed a faster growth rate (Fig.
1b-e) and biological aggressiveness – a greater presence in metastases – than the clones we studied (Fig.
3, Additional file
3: Figure S3). Our results show that the phenotypes of the single derived clones were heritable in the conditions used in this study; however, culturing subclones for a longer time could induce phenotypic changes if molecular or epigenetic alterations accumulated. In such a situation, heritability could be tested by studying the phenotype of sub-clones derived from the original clones, having cultured the original clones for several months.
Moreover, in co-culture (Fig.
7, Additional file
5: Figure S4a-c) the parental cells grew faster than the single clones, indicating that the parental cell line harbors a sum of clones that may outperform single clones through local or secreted factors, as yet not identified. These findings support the concept of
the whole is greater than the sum of its parts and describe a model where the interplay of clones confers aggressiveness, and which may allow the identification of factors involved in cellular communication and metastasis. Thus, clonal heterogeneity allows the malignant cell line to acquire the greatest malignant potential.
Conventional models propose that each metastasis originates from a single tumor cell [
55‐
57]. However, recent studies using mouse models of cancer have demonstrated that multiple subclones undergo polyclonal seeding and demonstrate interclonal cooperation between multiple subclones [
7,
58]. Our results confirm (Fig.
3d) that metastasis could be formed either by a single (Fig.
3e) or several clonal cell lines (Fig.
3d). However, even in cases of metastasis formed by several clonal cell lines, each metastasis contained one predominant clone (Fig.
3d). Comparative studies indicate monoclonal patterns of seeding, suggesting that clones compete to metastasize. However, polyclonal seeding, in which multiple clones from the primary tumor seed the same metastasis, is also observed, indicating subclones might cooperate as well as compete to metastasize [
7,
59]. In our model the cells were injected as a mix of single cells, therefore the metastasis formed by more than one cell line originated from several cells that reached the lung together, demonstrating that the cells physically interact to form the metastasis.
Several studies call into question the theory of clonal progression by the progressive accumulation of genetic alterations and selection of more aggressive clones, supporting instead the proposed theory of clonal cooperation between tumor clones [
20‐
23,
25‐
27]. Tumor multiclonality is also supported by the field cancerization theory [
60,
61], which states that there are many genetic alterations in the normal tissue surrounding tumors that can give rise to independent clones. Similarly, supporting interpretations can be drawn from the stem cell hypothesis, as diverse clones can derive from more than one pluripotent stem cell [
62,
63], and the Big Bang model of colorectal tumor growth where the tumor grows predominantly as a single expansion populated by numerous intermixed subclones [
64]. Clonal cooperation has recently been suggested in studies of single cell sequencing [
62,
65,
66]. The present study further supports the idea that there are several clones that together confer the properties of malignancy, thus strengthening the concept of clonal cooperation, whereby clones synergistically provide certain selective advantages for proliferation, resistance to apoptosis, induction of angiogenesis, and interaction with environmental factors and inflammatory cells [
20,
21,
30,
63].
Our results show that cells are able to interact and the coexistence of clonal cell lines resulted in a positive effect (Fig.
7c-h). We could conclude that physical interaction between clones (Fig.
7c-h) and secreted factors (Fig.
7e, Fig.
8a-e) favored the tumorigenic capacities of the cells. Cells are able to secrete factors (Fig.
6a) and send messages to surrounding and distant cells (paracrine signaling). Studies of cellular communication in breast cancer have demonstrated tumor cells’ abilities to secrete factors increasing breast cancer cell proliferation and metastasis [
67,
68].
Recently, interesting discoveries have been made in the field of paracrine signaling. Extracellular vesicles (EVs) have been postulated as a highly efficient method to transform cells. Several groups have demonstrated that EVs upregulate prometastatic and tumor angiogenesis pathways [
69], even transforming normal cells into cancer cells [
70,
71]. Our complementation assay confirmed intercellular communication via factors released from the cells, but we could not distinguish between soluble factors (such as cytokines) or released EVs. Our results showed that exosomes were able to modify growth rate (Fig.
8e). However, the soluble factors seemed to be more efficient than EVs, as the effect of exosomes was dose-dependent.
Our results demonstrate how some clones, via soluble factors, EVs and physical interactions, are able to induce increased aggressiveness in other clones. Therefore, we can conclude that the Darwinian clonal progression theory should be complemented with a “cooperative model”, where clones are able to interact and transfer “properties” among one another.
In our study, the biological differences observed between the different clones have been corroborated by clear differences in the RNA expression arrays (Fig.
4), which were complemented with methylomic studies (Fig.
5). We have also demonstrated clonal communication (Figs.
7,
8), and the challenge now is to identify the factors released by the parental cells that enhance survival and metastasis. The identification of factors and cytokines that modulate cellular communication and enhance malignant properties will be essential to understand the formation of clonal clusters and prevent metastasis. We propose the term
functional heterogeneity to highlight the different expression between clones due to extracellular factors and epigenetic changes. This approach opens the way to new paradigms in the development of metastases, including central factors at an intracellular level, and factors involved in the communication between tumor cells and microenvironmental or inflammatory cells.
In summary, these data support that functional clonal heterogeneity does not always reflect genetic heterogeneity. Inhibition of clonal cooperation, by blocking cytokines or other factors involved in the formation of clusters and the interplay with environmental cells may represent a change in the therapeutic paradigm to prevent the development of metastasis [
21].
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