A Mutant p53-Dependent Embryonic Stem Cell Gene Signature Is Associated with Augmented Tumorigenesis of Stem Cells Free

Tumor development is a multistage process that is accompanied by gradual gain of intratumoral heterogeneity (1, 2). One of the theories accounting for tumor heterogeneity is the existence of a rare subpopulation of cells known as the cancer stem cells (CSC) that reside within tumors and harbor a unique ability to regenerate a tumor and capacities to metastasize and to resist chemotherapy (2). To study the nature of these rare CSCs, several methods for their isolation were described, mainly by identification of specific CSC surface markers (3). Although previous studies identified different CSC markers in various tumors, novel and more broadly expressed markers, which can be useful for early diagnostic and even for cancer therapy, are still urgently needed.

Mutations in the p53 gene are the most frequent alterations in human tumors (4, 5) that correlate with undifferentiated high-grade tumors (6–8). Most of the p53 mutations are missense mutations that produce full-length mutant p53 proteins, which not only lack the p53 tumor suppressor activity, but also gain new oncogenic functions that acquire the cell with enhance malignant properties (4, 5). Ample reports indicate a possible mutant p53 gain-of-function (GOF) activity in the acquisition of dedifferentiation and stemness phenotype that might lead to tumorigenesis. For example, mutant p53 GOF activity was shown to enhance the reprogramming efficiency of mouse embryonic fibroblasts (MEF) and augment the tumorigenesis capacity of the reprogrammed cells (9). Moreover, mutant p53 accumulation specifically in neuronal progenitors led to gliomagenesis, indicating improper maturation of neural stem cells by mutant p53 (10). Notably, bone marrow mesenchymal stem cells (BM-MSC) harboring p53 mutation undergo malignant transformation that induces sarcomagenesis (11). All in all, these studies imply that mutant p53 might have a GOF activity in stem cell transformation and dedifferentiation but the molecular profile underlying these processes is still poorly understood.

Here we show that in vitro cultivation of mutant p53 BM-MSC–derived tumors, led to the establishment of aggressive MSC tumor lines (TL). These MSC-TLs exhibited an enhanced tumorigenic capacity compared with their parental cells, mutant p53 MSCs, as shown by their ability to form rapidly growing tumors by the injection of as few as 1 × 10² cells. By transcriptome profiling, we found that MSC-TLs express elevated levels of CSC markers and a unique gene signature consisting of embryonic stem cell (ESC) genes. These results suggest that MSC-TLs may represent a mesenchymal CSC-like population that reside within mutant p53 MSC–derived tumors. Knocking-out mutant p53 significantly reduced tumor development and tumorigenic cell frequency and also resulted in a reduction in the expression of CSC markers and the identified ESC MSC-TL signature. Importantly, analyses of human tumor datasets showed that the ESC MSC-TL signature–derived genes correlated with poor patient survival and were highly expressed in various human cancers harboring p53-hotspot missense mutations. Altogether, our data suggest a novel role of mutant p53 in expanding mesenchymal CSC-like cells that display expression of a unique mutant p53–dependent gene signature comprising of ESC genes. The fact that this mesenchymal CSC–like signature contains embryonic genes, which are not tissue specific, might suggests that these signature-derived genes may serve as prognostic markers and potential cancer stemness therapeutic targets of mutant p53–dependent tumors and tumors at large.

Bone marrow MSCs were isolated from p53 WT or p53 Mut (R172H) mice and characterized as described previously (11). The different MSC isolates were grown in MSC-specific medium [MesenCult MSC Basal Medium (Mouse), STEMCELL Technologies] supplemented with 20% murine MesenCult MSC stimulatory supplement (Mouse; STEMCELL Technologies), 60 mg/mL penicillin, 100 mg/mL streptomycin, and 50 mg/mL kanamycin. p53 Mut MSC-TLs were established as follows; tumors were extracted and mechanically disaggregated by utilizing a cell strainer (542070, Greiner Bio-One). The isolated MSCs as mentioned previously (11), were examined for their authentication by the examination of their ability to differentiate to the mesodermal lineages adipocytes and osteocytes and also by verifying that the cells do not express hematopoietic markers. Tumor-derived cells were cultured on agar-coated plates in DMEM supplemented with 15% (v/v) FCS, 1 mmol/L sodium pyruvate, 2 mmol/L l-glutamine, 0.1 mmol/L nonessential amino acids, 0.1 mmol/L β-mercaptoethanol, 1,000 U/mL leukemia-inhibitory factor [ESG1107; (BD Biosciences) at a ratio of 1:1]. Cells were incubated at 37°C in a humidified atmosphere of 5% CO₂. All cells were checked for Mycoplasma contamination and in all the analyses, we verify that the cells did not exceeded 20 in vitro passages.

C57BL/6 harboring p53 WT or p53 Mut (R172H; ref. 12), kindly provided by Professor Guillermina Lozano (MD Anderson Cancer Center, Houston, TX), athymic Nude-Foxn1^nu, and NOD.CB17-Prkdc^scid/NCrHsd (ENVIGO) were used. Animal protocols were approved by the Institutional Animal Care and Use Committee of the Weizmann Institute of Science (Rehovot, Israel).

Freshly bone marrow nucleated cells derived from two p53 WT or two p53 Mut (R172H) mice were plated at cell density of 5 × 10⁶ in 10-cm BD falcon plates (BD Biosciences). The cells were grown in MSC-specific medium as described above and refed once a week without further treatment. After 14 days, colonies of triplicates were stained with Giemsa and counted.

Cells were counted and plated (2.5 × 10⁴ cells per well for 12-well plate or 1.4 × 10⁵ cells for 6-well plate). Each day, cells in duplicate wells or plates were tripsinized and stained with Trypan blue, unstained cells were counted by using hemocytometer and light microscopy. The proliferation plots present results relative to day 1. Each curve represents p53 WT MSC or p53 Mut pMSC isolates or derived p53 Mut MSC-TLs accordingly.

Cells were lysed in TLB buffer (50 mmol/L Tris HCl, 100 mmol/L NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, 0.1% SDS) supplemented with Protease Inhibitor Cocktail (Sigma-Aldrich) for 15 minutes on ice, followed by centrifugation. Protein concentration was determined using BCA reagent (Thermo Fisher Scientific), 30–100 μg of protein extracts were separated by SDS-gel electrophoresis, and transferred to a nitrocellulose membrane at semi-dry conditions. Membranes were blocked using 5% dry milk in PBST (0.05% Tween in PBS), and incubated with anti-p53 (1c12, Cell Signaling Technology), anti-p21 (sc-397, Santa Cruz Biotechnology), anti-β-actin (sc-47778, Santa Cruz Biotechnology), anti-Sox2 (ab97959, Abcam), anti-Hmga1 (ab129153, ABCAM), anti-Slc16a1 (GTX54699, GeneTex), and anti-Etv5 (GTX5114394) followed by appropriate horseradish peroxidase–conjugated secondary antibodies and the signal was obtained by ECL Western Blotting Detection Reagent (Thermo Fisher Scientific) and ChemiDoc MP (Bio-Rad). In all the experiments, β-actin or GAPDH were used as a loading control.

For all the experiments, cells were imaged using multispectral imaging flow cytometry (ImageStreamX mark II imaging flow cytometer; Amnis Corp, part of EMD Millipore). Data were analyzed using image analysis software (IDEAS 6.2; Amnis Corp). Images were compensated for fluorescent dye overlap by using single-stained controls. Cells were gated for single cells, using the area and aspect ratio features, and for focused cells, using the Gradient RMS feature, as described previously (13).

For p53 staining, the cells were fixed with a fixation buffer (80% ethanol, 20% Hank's Balanced Salt Solution), washed and stained with a primary p53 antibody (Cell Signaling Technology, 1C12; 1 hour, 4°C, gentle agitation), and then washed once with PBS^−/− and DAPI for DNA staining. Nuclear staining p53 was verified using the Similarity feature (calculated as log-transformed Pearson correlation coefficient between the DAPI and p53 staining).

For cell-cycle analysis, we utilized Phase-Flow BrdU Cell Proliferation Kit (BioLegend, CA 92121). Cells after staining with antibody against BrdU were analyzed by multispectral imaging flow cytometry and the percentage of cells in each cell-cycle phase was determined according to level of staining intensity.

For CD44 staining, cells were incubated with the primary antibody for to detect CD44 (eBioscience, Clone IM7, 17-0441-81; 1 hour, 4°C, gentle agitation), washed once with PBS^−/− and Hoechst for DNA staining. Cells were imaged using the multispectral imaging flow cytometry. Approximately 1 × 10⁴ cells were collected from each sample and cells were then gated for high intensity of CD44 staining and their percentage was calculated and compared between samples. To identify small and circular cells, the area (the number of microns squared in a mask) and circularity (the degree of the object's deviation from a circle) were calculated (three isolates each in each group). The population of cells with low area and high circularity was gated and their percentage was calculated and compared between samples.

Cells were counted and plated (2,000 cells per well for 96-well plate). Each day, CellTiter-Glo kit reagent was added directly to cells (in triplicates) that lead to cell lysis and generation of a luminescent signal. The signal is proportional to the amount of ATP, which is considered to be directly proportional to the presence of metabolically active cells in the culture.

Cells were tripsinized, stained with Trypan blue (Sigma-Aldrich T8154), and live cells (unstained) were counted by using hemocytometer. Furthermore, cells were resuspended with PBS containing 1% of FCS and injected subcutaneously into Athymic Nude-Foxn1^nu or NOD.CB17-Prkdc^scid/NCrHsd (ENVIGO) between 6 and 8 weeks of age.

Cells were infected with pBABE-hygro retroviral vector–expressing luciferase, to monitor tumor growth. Immunodeficient mice were subcutaneous injected with 1 × 10²–10³ infected cells into the nape of the neck. After 1 week, from the inoculation, mice were anesthetized and injected with luciferin and monitored by IVIS2000 system. Exposure time was 30 seconds for 20 images that were taken for each tumor. We selected the highest peak of luminescence values and normalized it to adjacent background. Tumors were allowed to reach to maximal size of 1 cm² and then mice were sacrificed.

Four-micron–thick paraffin-embedded tissue sections were deparaffinized, rehydrated, and pretreated for antigen retrieval. For Sox2, CD44, and PCNA, the antigen retrieval was done in citric acid (pH 6), for 10 minutes, by microwave. For ALDH1 and CD34 staining, the antigen retrieval was done in ice-cold acetone for 7 minutes, then washed in PBS and additional 10 minutes in citric acid (pH 6) by microwave. Sections were than blocked and incubated with primary antibodies for at least 24 hours as in 4°C, as follows; PCNA (FL-261; sc-7907, Santa Cruz Biotechnology), ALDH1 (AF5896 R&D Systems), Sox2 (ab97959, Abcam), CD44 (553131, BD Pharmingen), and CD34 (ACL8927AP, Accurate). Sections were washed and incubated with appropriate secondary biotinylated IgG and avidin–biotin complex (Elite-ABC kit, Vector Laboratories) followed by DAB reaction (Sigma-Aldrich). CD34 antibody incubation followed by incubation with secondary Cy3-conjugated antibody (1:100, Jackson ImmunoResearch) for 30–60 minutes and with DAPI for nuclear staining. Quantification of the staining was done utilizing Image Pro Plus software.

Three independent p53 Mut MSCs isolates and two individual p53 Mut MSC-TLs derived from primary tumors of each MSC isolate, as well as additional four p53 Mut MSC-TLs derived from secondary tumors (overall ten p53 Mut MSC-TLs) were subjected to RNA sequencing analysis. Cells were plated and when they reach to 80% confluent, RNA was extracted using Direct-zol RNA MiniPrep (ZYMO RESEARCH). Libraries preparation were done using the INCPM-RNA-seq. Briefly, polyA fraction (mRNA) was purified from 500 ng of total RNA following by fragmentation and generation of double-stranded cDNA. Then, end repair, A base addition, adapter ligation, and PCR amplification steps were performed.

Libraries were evaluated by Qubit and TapeStation. Sequencing libraries were constructed with barcodes to allow multiplexing of 22 samples in two lanes. A total of 18 million single-end 60-bp reads were sequenced per sample on Illumina HiSeq 2500 V4 instrument. Reads were trimmed using cutadapt (http://dx.doi.org/10.14806/ej.17.1.200) and mapped to mm10 genome (downloaded from igenomes) using TopHat (v2.0.10; http://dx.doi.org/10.1186/gb-2013-14-4-r36). Counting over refseq genes proceeded using htseq-count (http://dx.doi.org/10.1093/bioinformatics/btu638; intersection-strict mode). Differential expression analysis was performed using DESeq2 (http://dx.doi.org/10.1186/s13059-014-0550-8) with the betaPrior, cooks Cutoff and independent filtering parameters set to False. The data presented in this study have been deposited in NCBI's Gene Expression Omnibus (14) and are accessible through GEO series accession number GSE118173 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118173).

RNA was extracted using Direct-zol RNA MiniPrep (ZYMO RESEARCH). Reverse transcription and qRT-PCR were performed as described previously (11). The sequences of the specific gene primers are listed in Supplementary Table S1.

Cells were transfected with Px330 backbone–expressing sgRNA for targeting murine p53 and Cas9 by GeneExpresso in vitro DNA transfection reagent (EG-1031, Excellgen). The Px330 p53 plasmid was a gift from Tyler Jacks (Addgene plasmid 59910). After 48 hours from the infection, we plated 0.5 cell per well in a 96-well plate to generate single-cell clones. After the generation of single-cell clones, we analyzed all clones by Western blot analysis to detect p53 knockout clones. Two clones out of 71 clones were KO for mutant p53. We verified by DNA sequencing the DNA editing by the guided RNA molecule.

Three gene sets were collected form independent studies. First, a previous study from our laboratory performed a RNA sequencing analysis on ESCs upon differentiation induction by retinoic acid (15). We reanalyze the raw data and genes that were significantly downregulated upon differentiation (P_adj < 0.05, FC < 2, max reads > 10) were selected as the ESC genes list. For the second study performed using bioChIP-chIP analysis (16), we selected shared target genes of Nanog, Sox2, and Oct4. A third dataset was extracted from a study that performed a time course microarray experiment on reprogramed MEFs into induce pluripotent stem cells (iPSC) by infecting with retroviruses encoding for the four yamanaka reprogramming factors (Oct4, Sox2, klf4, and c-myc). We selected genes that had expression levels more 2-fold after 8 days of the reprogramming process compared with day 0) and excluded genes that were upregulated in the control (infection with retrovirus encoding for GFP; ref. 17).

First, for each comparison, we estimated the significant genes (P_adj < 0.05, FC > 2, max reads > 10). Moreover, from each dataset, we estimated the number of genes that had at least 10 reads (max) in our RNA sequencing analysis and analyzed whether those lists are enriched in the differential gene expression in every comparison. We utilized The GeneProf hypergeometric probability calculator (https://www.geneprof.org/GeneProf/tools/hypergeometric.jsp) to estimate the enrichment P value of the different gene sets. Gene set enrichment analysis (GSEA) was also performed by using GSEA software (http://software.broadinstitute.org/gsea/index.jsp). The enrichment of specific datasets was considered significant when the nominal (NOM) P value and FDR q value were less than 0.05.

Data for the survival analyses were downloaded from The Cancer Genome Atlas (TCGA) via “Xena.” We examined whether the combined expression of each possible gene pair from the human orthologs of the MSC-TL ESC gene list, affected patient survival by Cox proportional-hazards model via the R package “survival.” We classified the expression level per gene per sample as “high” or “low,” using median of each gene value as cutoff. Next, to distill the genes that can predict poor prognosis, we first examined the combined expression of each possible gene pair from the ESC gene list and selected the pairs that significantly predicted poor survival in patients in each cancer type (FDR < 0.05; HR > 2). Next, we selected the significant genes derived from the pairwise survival analyses and performed multigene survival analyses via backward stepwise selection and arrived at a final survival model based on gene signatures that predicted poor patient survival. Next, we selected the most significant genes derived from the latter gene signatures and examined whether the combine expression of the selected genes can predict poor patient survival (by Cox proportional-hazards model).

Mutation and expression (RNA-seq) data was downloaded from TCGA via the R package “CGDSR.” We used the subset “3_way_complete,” which contains all tumor samples that have mRNA, CNA, and sequencing data. Differential expression between groups was tested using a t test on log₂-transformed normalized counts. The frequency of the gene expression was calculated and normalized to the overall gene expression by χ² test. The results shown here are based upon data generated by TCGA research network: http://cancergenome.nih.gov.

To examine the role of mutant p53 in stem cells transformation, we utilized a system containing BM-MSCs isolates harboring WT p53 or p53 R172H mutation, which is analogous to the frequent and known GOF hotspot mutation, R175H in human tumors (11). To corroborate whether mutant p53 MSCs isolates display loss of WT p53 activity, we examined the DNA damage response. As expected, upon doxorubicin treatment, p53 wild-type (p53 WT) MSCs showed an increase in nuclear p53 protein levels (Fig. 1A and B; Supplementary Fig. S1A) that was accompanied by the elevation of its target gene, p21 (Fig. 1A and C). In agreement with previous studies (4), mutant p53 was already accumulated in basal levels, regardless of the DNA damage response and there was no detection of p21 expression in p53-mutant (p53 Mut) MSCs upon doxorubicin treatment (Fig. 1A–C). Consistently, p53 Mut MSCs showed a higher proliferation rate compared with p53 WT MSCs (Fig. 1D). Therefore, no genuine p53 activity was detected in p53 Mut MSCs. As mentioned above, mutant p53 promote cancer development (4, 5). We further examined the tumorigenic potential. In agreement with our previous study (11), while all p53 Mut MSC isolates were able to form aggressive sarcomas, p53 WT MSCs lacked this ability (Supplementary Fig. S1B–S1D). Tumor-initiating capacity is ascribed to uncontrolled self-renewal pathways and acquisition of CSCs properties (18). Next, colony-forming unit-fibroblastic (CFU-Fs) assay showed that p53 Mut mice exhibited higher number of bone marrow stem cells compared with p53 WT mice (Fig. 1E), indicating a higher self-renewal ability of p53 Mut bone marrow–derived stem cells. Overall, mutant p53 enhanced the proliferation, tumorigenic potential, and the self-renewal of BM-MSCs.

Tumor intra-heterogeneity that has been accounted for tumor development, is attributed to the existence of multiple subclones within a tumor that have different tumorigenic abilities (1). To propagate the tumorigenic cells within p53 Mut MSC–derived tumors, we cultivated these tumors in vitro and established various MSC-TLs. p53 Mut MSC-TLs exhibited higher proliferation and viability capacity compared with their p53 Mut parental MSCs (pMSC; Fig. 2A; Supplementary Fig. S2A). Consistently, as expected, cell-cycle analysis revealed lower percentage of cells in the G₁ phase and higher percentage of cells in the S-phase in p53 Mut MSC-TLs compared with their parental cells, p53 Mut pMSCs (Supplementary Fig. S2B and S2C). Furthermore, we found that p53 Mut MSC-TL–derived cells are smaller in size and more circular compared with their parental cells (Fig. 2B; Supplementary Fig. S2D–S2F). Interestingly, stem cells and iPSCs are characterized by high proliferation rate, small cell size, and circular morphology (19, 20). To explore the possibility that the MSC-TLs exhibit stem cell features, we examine CD44 expression, a common marker for CSCs in various cancer models (21, 22). The percentage of CD44^high subpopulation in the p53 Mut MSC-TLs was higher compared with their parental cells (Fig. 2C). Next, an in vivo serial dilution transplantation assay showed higher tumor initiation capacity and tumorigenic cell frequency in p53 Mut MSC-TLs compared with their parental cells (Fig. 2D). Strikingly, as few as 1 × 10² cells from p53 Mut MSC-TLs were able to generate tumors within an average of 34.7 days, whereas subcutaneous injection of 3 × 10⁶ p53 Mut pMSCs gave rise to tumors within 97 days (mean; Fig. 2E; Table 1). Consistently, in vivo imaging enabled the detection of tumors, following subcutaneously injection of 1 × 10²–10³ cells derived from p53 Mut MSC-TL, already within 14 days. Injection of the same amount of pMSCs yielded no tumor development (Fig. 2F; Supplementary Fig. S2G), even following 6 months. Furthermore, tumors derived from MSC-TLs displayed peripheral nerves and blood vessels invasion, reflecting aggressive features that were not detected in the pMSC-derived tumors (Fig. 2G). MSC-TL–derived tumors also demonstrated higher expression of the proliferative marker, PCNA, and of another common CSC marker (23), aldehyde dehydrogenase isoform 1 (ALDH1), compared with the pMSC-derived tumors (Fig. 2H; Supplementary Fig. S2H and S2I). Altogether, these results suggest that upon cultivation of mutant p53 pMSC–derived tumors, we enriched for highly tumorigenic cell lines with CSC features.

To identify gene networks that underlie the accentuated oncogenic activity of p53 Mut MSC-TLs, we subjected three independent parental p53 Mut MSCs isolates, two individual p53 Mut MSC-TLs derived from primary tumors of each MSC isolate, as well as additional four p53 Mut MSC-TLs derived from secondary tumors, which exhibited similar tumorigenic capacity as the primary MSC-TLs (Supplementary Fig. S3A) to transcriptome profiling. While the principal component analysis and hierarchical clustering revealed transcriptional variances between individual p53 Mut MSC-TLs, the largest transcriptome variation was observed between p53 Mut pMSCs and their derived MSC-TLs (Supplementary Fig. S3B and S3C). This finding indicates a tumorigenic transcriptional core that is shared between all p53 Mut MSC-TLs. The aggressive nature of p53 Mut MSC-TLs led us to examine whether they express a CSC signature. We utilized a defined murine CSC signature derived from head and neck squamous cell carcinoma (24). We found that this CSC signature was enriched (P = 2.2 × 10⁻¹⁶) and the CSC signature–derived genes were more frequent in the upregulated gene fraction of p53 Mut MSC-TLs compared with their parental cells (χ² test, P = 0.0003; Fig. 3A; Supplementary Table S2). Next, GSEA showed that p53 Mut MSC-TL signature was enriched for stemness and undifferentiated cancer gene sets (Fig. 3B). Epithelial-to-mesenchymal transition (EMT) was shown to be associated with acquisition of stemness and CSC phenotype (25). We further found that an EMT gene signature is enriched in p53 Mut MSC-TLs compared with their parental cells, p53 Mut pMSCs (Fig. 3B). Analyzing the genes that were upregulated in p53 Mut MSC-TLs compared with their parental cells, by Ingenuity Pathway Analysis (IPA) tool (26) linked them to biological functions including cell movement, proliferation, and survival, whereas this analysis showed downregulation of genes associated with organismal death and growth failure (Fig. 3C; Supplementary Table S3). The activated canonical pathways in the p53 Mut MSC-TLs, according to IPA, unveiled cancer-associated pathways including paxilin, Gα12/13, PAK, integrin, and CDK5 signaling (Supplementary Table S3). Interestingly, IPA also highlighted the activation of stem cell upstream regulators in the p53 Mut MSC-TLs that are involved in different developmental pathways, including Wnt, Hedgehog, and Notch pathways (Fig. 3D; Supplementary Table S3). Furthermore, the activated upstream regulators also included oncogenic pluripotency regulators, Myc and Klf4, as well as embryonic stem cells regulators including EZH2 and BRG1. On the contrary, upstream regulators that were inhibited in the p53 Mut MSC-TLs comprised of tumor suppressors including CDKN1B, TSC2, STK11, mir-141-3p, and mir-34a-5p (Fig. 3D; Supplementary Table S3). Notably, mir-34-5p was shown to negatively regulate the Wnt signaling pathway (27, 28). Furthermore, IPA analysis, identified, as the highest scored network in p53 Mut MSC-TLs, a gene network associated with cellular, embryonic, and organismal development (Supplementary Fig. S3D; Supplementary Table S3). To further examine these observations, we obtained murine ESC signature datasets from three independent published studies (Supplementary Table S2). A hypergeometric probability test was aimed to examine whether the differential genes between p53 Mut MSC-TLs and p53 Mut pMSCs, contained higher number of genes than randomly expected, from a particular ESC dataset, indicating ESC dataset enrichment. To that end, we obtained a dataset from a previous comparative analysis of p53 WT murine ESCs before and after retinoic acid–induced differentiation (15). We focused on genes that were downregulated during ESCs differentiation, because these genes, most likely, represent the ESC expression signature. This gene set was enriched in p53 Mut MSC-TLs and included 129 overexpressed genes as compared with the parental MSCs (P = 0.02). A second gene set was extracted from a published study identifying target genes of embryonic transcription factors (16). Shared target gene list of the ESC transcriptional factors; Nanog, Sox2, and Oct4 yielded a significant enrichment score in the upregulated gene fraction of p53 Mut MSC-TLs compared with their parental cells (P = 0.005). Finally, we analyzed a gene set comprising of genes that were upregulated upon induction of iPSCs (17). This list contained genes that showed, at least, 2-fold increase in their expression following 8 days of pluripotency induction. Consistently, the reprogramming gene set contained 39 overexpressed genes in the p53 Mut MSC-TLs and yielded a significant enrichment score (P = 1.23 × 10⁻⁷). However, enrichment analysis of the downregulated genes in the p53 Mut MSC-TLs compared with their parental cells did not yielded a significant P value in any ESC dataset. Overall, we detected 184 ESC genes derived from the three datasets that were upregulated in the p53 Mut MSC-TLs (Fig. 3E; Supplementary Table S2). The ESC transcription factor, Sox2, known to be essential for maintaining pluripotency of ESCs, was shared by all the ESC datasets and was highly expressed in the p53 Mut MSC-TLs as compared with their parental cells (Fig. 3F and G). The expression of additional ESC signature–derived genes were validated (Supplementary Fig. S3E). Interestingly, ESC gene signature derived genes that were downregulated in p53 Mut MSC-TLs were associated with promoting apoptosis and attenuating cell proliferation (Supplementary Fig. S3F). Overall, p53 Mut MSC-TLs highly expressed cancer and CSC-associated genes and an ESC gene signature.

The gain of oncogenic activities by mutant p53 that promote tumor development is a well-accepted notion (4, 5). To determine whether the enhanced tumorigenic capacity of MSC-TLs is mutant p53 dependent, we knocked out mutant p53 in a MSC-TL (Supplementary Fig. S4A). Knockout (KO) of mutant p53 resulted in a significant reduction in tumor-initiating capacity, tumor development and tumorigenic cell frequency (Fig. 4A–D). Tumors derived from p53 KO MSC-TL subclones were significantly smaller compared with tumors derived from p53 Mut MSC-TL subclones, exemplified by tumor weight and size (Fig. 4A and B). Furthermore, tumor latency was longer upon mutant p53 KO (Fig. 4C). Notably, injection of as low as 1 × 10² showed significant reduction in the incidence of tumors upon KO of mutant p53 (Fig. 4D). Furthermore, injection of 10 cells, yielded tumors only upon injection of mutant p53 expressing MSC-TL subclones (Fig. 4C and D), indicating a mutant p53 GOF activity in expanding tumorigenic cell population. Tumors derived from mutant p53 KO MSC-TL subclones displayed wider area of tumor necrosis, as well as a reduction in tumor vascularization, as determined by CD34 staining, compared with tumors derived from mutant p53 MSC-TL subclones (Fig. 4E; Supplementary Fig. S4B). This phenomenon is in line with the notion that mutant p53 exhibits a GOF in angiogenesis (4, 29). Furthermore, upon mutant p53 KO there was a significant reduction in the expression of the two CSC markers, CD44 and ALDH1, which were shown to be highly expressed in p53 Mut MSC-TLs compared with their parental cells (Fig. 4F and G). Altogether, these results suggest that mutant p53 enhances tumor growth, angiogenesis, survival, expression of CSC markers, and most importantly expansion of tumor-initiating cells within the MSC-TLs.

Next, we examined whether the reduction in tumorigenicity following mutant p53 KO is associated with a decrease in the ESC gene signature expression, described above. Therefore, we subjected mutant p53 MSC-TLs and the corresponding mutant p53 KO MSC-TL subclones to a transcriptome profiling by RNA sequencing (Supplementary Table S4). IPA analysis of the differential genes upon KO of mutant p53 in the MSC-TLs revealed increase of biological functions such as organismal death, morbidity, and mortality and decrease of cell migration and proliferation (Fig. 5A; Supplementary Table S5). Interestingly, we identified inactivation of several cancer-related pathways upon mutant p53 KO. These included integrin, paxilin, Gα12/13, PAK, and CDK5 signaling pathways that were previously shown to be activated in the MSC-TLs compared with their parental cells. Additional cancer-related pathways that were inhibited upon mutant p53 KO included RhoA, CXCR4, PDGF, ILK, and VEGF signaling pathways. Mutant p53 abolishment also led to the downregulation of genes associated with mouse ESC pluripotency pathway (Supplementary Table S5). Finally, we detected downregulation of two reprogramming regulators Myc and Klf4 following mutant p53 depletion (Fig. 5B). Furthermore, we found that the p53 Mut MSC-TL ESC signature was significantly downregulated upon mutant p53 abolishment (P = 5 × 10⁻⁸; Fig. 5C; Supplementary Table S4). Notably, the ESC genes, shown to be downregulated upon retinoic acid differentiation induction (15), yielded a further enrichment in the downregulated genes upon mutant p53 knockout (P = 5.9 × 10⁻⁹; Fig. 5D; Supplementary Table S4).

The polycomb repressive complex 2 (PRC2) regulates the pluripotency of ESCs by repressing development-associated genes (30). We found that a gene set of PRC2-repressed target genes (31) was enriched and more frequent in the upregulated gene fraction following mutant p53 KO (Enrichment P = 1 × 10⁻¹⁵, χ² test P = 0.02; Fig. 5E and F; Supplementary Table S4). This might suggest that in p53 Mut MSC-TL subclones PRC2 is active, thus contributing to the ESC signature expression phenotype. Moreover, the expression of Sox2, previously shown to be elevated in the different MSC-TLs compared with their parental cells, was downregulated following mutant p53 KO (Fig. 5G and H). We validated the downregulation of additional ESC signature derived genes following mutant p53 KO (Fig. 5G and H; Supplementary Fig. S5A). By utilizing BindDB tool (32), we showed that the proximal promoters of mutant p53 MSC-TL–dependent genes are enriched for chromatin transcriptional activation marks in ESCs (Supplementary Fig. S5B). These findings suggest that mutant p53 induces the expression of ESC gene signature in MSC-TLs.

To assess the relevance of the murine MSC-TL ESC signature in human patients with cancer, we utilized datasets provided by TCGA. We focused on the human orthologs of ESC gene signature, which was detected in the MSC-TLs, and additional mutant-dependent ESC genes. We identified unique gene signatures, whose combined expression predicted poor patient survival in several cancer types (Fig. 6A; Supplementary Fig. S6; Supplementary Table S6, detailed in Material and Methods section). Of note, a single-gene survival analysis yielded lower HRs compared with the combined expression of genes, indicating the importance of analyzing the combined expression of genes (Supplementary Table S6). Furthermore, the combined expression of four transcription factors, derived from the MSC-TL ESC gene signature, E2F2, HMGA1, SOX2, and ZIC2 predicted poor patient survival in various cancer types (Supplementary Fig. S6; Supplementary Table S6).

To explore a correlation between p53 hotspot mutations and the expression of the ESC gene signature we performed a pan-cancer gene expression analysis according to TCGA datasets. Datasets derived from different cancer types that includes tumor samples with a characterized p53 status were studied (Supplementary Table S7). As described previously, missense mutations in the p53 gene are the most common mutations found in human cancers and usually occur in six hotspot amino acids in the DNA-binding domain of the protein. These mutations produce full-length mutant p53 proteins that were shown to exhibit oncogenic GOF (4, 5). Similar to the IARC p53 database, these six hotspot mutations were highly frequent in the TCGA database (Supplementary Fig. S7). Of note, we compared between tumor samples harboring one of the p53-hotspot missense mutations and the entire tumor samples that harbor other p53 mutations or WT p53. We assumed that tumors expressing WT p53 probably entailed inactivation of p53-associated pathways, due to mutations in other downstream genes (33). The frequency of highly expressed MSC-TL ESC genes in tumors harboring hotspot missense p53 mutations was significantly higher compared with the rest of tumor samples (Fig. 6B; Supplementary Table S8;χ² test P = 0.01). By analyzing a previously described human ESC signature (30), we found a higher proportion of human ESC–derived genes that were highly expressed in tumors harboring one of the six p53 hotspot missense mutations compared with the rest of tumor samples (χ² test P = 0.004; Fig. 6C; Supplementary Table S8). Importantly, SOX2 was upregulated in p53-hotspot missense mutations tumor samples. Box plot of SOX2 and additional ESC genes are presented (Fig. 6D; Supplementary Fig. S8). These analyses indicated that like in our mouse model, expression of mutant p53 proteins in human tumors correlated with the expression of the presently described p53 Mut MSC-TL–associated ESC gene signature and human ESC signature.

p53 mutations are the most common alterations in human tumors that lead to the gain of oncogenic traits, which promote cancer development (4, 5). CSCs were suggested to be an important milestone underlying oncogenicity. The intrinsic stemness potential of adult stem cells, together with their long life span, enabling mutations accumulation, make them suitable candidates to be the cell of origin of CSCs. p53 was shown maintaining the normal equilibrium between self-renewal and differentiation of stem cells (21, 34). Various studies support the notion that loss of WT p53 in stem cells leads to tumor initiation (21). Here, we demonstrate that BM-MSCs derived from p53-mutant mice exhibit an augmented sarcomagenesis and higher self-renewal capacity. This is in agreement with previous studies showing that p53 preserves the genomic integrity of MSCs and prevents their malignant transformation (11, 35). Cultured MSCs, similarly to cancer cells, exhibit intra-population heterogeneity with variable proliferation and differentiation capacities and display a repertoire of surface markers (36). Accordingly, the low frequency of tumorigenic cells seen within the parental p53 Mut MSCs may account for intra-population heterogeneity with a restricted number of tumorigenic cells within the population (Fig. 2D). Our data shows that by culturing mutant p53 MSC–derived tumors, we enriched for aggressive TLs. These MSC-TLs exhibited CSC expression markers and an augmented tumorigenic capacity, by the injections of as few as 1 × 10². Notably, under the same conditions, no tumors were evident upon the injection of their parental p53 Mut MSCs. Transcriptome analysis revealed that the augmented tumorigenic capacity of the established p53 Mut MSC-TLs was associated with the expression of CSC gene signature and a unique gene signature consisting of ESC genes. ESC genes that were downregulated in p53 Mut MSC-TLs were linked with positive regulation of apoptosis and cell proliferation attenuation. These results indicate that the aggressive p53 Mut MSC-TLs adopt only a part of the ESC signature, which favors tumorigenesis, but suppress the part of the ESC signature that negatively regulates the tumorigenic processes. MSC-TLs derived from identical parental MSCs were clustered together. This transcriptional clustering and the shared tumorigenic phenotype by all p53 Mut MSC-TLs in conjunction with intra-population heterogeneity in MSCs (36) might indicate the existence of a common origin within the mutant p53 MSC population rather than a stochastic event. Overall, these results suggest that in vitro cultivation of the mutant p53 MSC–derived tumors indeed selected for a CSC-like population that reside within MSC-derived tumors. This led to the identification of a mesenchymal CSC gene signature.

p53 inactivation in human breast tumors were shown to correlate with expression of an ESC signature (37). Furthermore, WT p53 was shown to negatively regulate the expression of ESC transcription factors (21). These findings suggest that the ESC signature expression in tumors lacking WT p53 activity may result from the absence of a p53-mediated repression of ESC factors' expression.

As mentioned above, p53 hotspot missense mutations are the most common alteration in human tumors that produce mutant p53 proteins that exhibit oncogenic traits that are beyond the abrogation of the normal tumor suppressor activity (4, 5). We and others have shown a mutant p53 GOF activity in promoting EMT (38, 39). Notably, the EMT was shown to exert stem cell characteristics (25). Furthermore, mutant p53 was shown to induce dedifferentiation of a human osteosarcoma cell line (40). In addition, mutant p53 was shown to facilitate the reprogramming process and to generate iPSCs with tumorigenic ability (9). Recently, we reported that mutant p53 upregulate the expression of CSC markers in colon cell lines (41). These observations might indicate a mutant p53 GOF activity in enhancing cancer plasticity and stemness phenotype, thus promoting the malignant process. However, the molecular profiling of endowing cells with stemness phenotype by mutant p53 protein remains to be elucidated.

The observation that p53 knockout in p53 Mut MSC-TL led to a reduction of tumorigenesis and CSC markers' expression indicates a role of mutant p53 in expanding the CSC population. As expected, we found downregulation of cancer-associated genes following mutant p53 KO. Interestingly, the ESC signature, which was identified in the p53 Mut MSC-TLs, was also downregulated following mutant p53 abrogation. This ample change in ESC gene signature expression, regulated by the presence of mutant p53 protein, rather than loss of WT p53 function, is novel. The significant differences in transcriptome profile between p53 Mut MSC-TL and p53 Mut KO MSC-TL subclones implies an involvement of a broader transcriptional regulation, such as an epigenetic regulation. Indeed, we showed that promoters of the mutant p53 MSC-TL–dependent genes are enriched for chromatin transcriptional activation marks in ESCs. Furthermore, we found that Polycomb Repressive Complex 2 (PRC2) target genes are downregulated in p53 Mut MSC-TL subclones. This may indicate that, as in ESC cells, PRC2 is active in p53 Mut MSC-TL subclones and accordingly can negatively regulate the expression of different development-associated genes by histone methyltransferase activity. Altogether, these analyses may imply that one possible mechanism in which mutant p53 regulates the expression of the ESC derive genes is by regulating the epigenetic mark state. Furthermore, the BindDB tool allowed us also to identify transcription factors that bind to the promoters of the mutant p53 MSC-TL–dependent genes, thus suggesting that they may be involved in mechanisms in which mutant p53 regulates the ESC gene signature (Supplementary Fig. S5B). In all, we suggest a novel mutant p53 GOF activity in upregulating the expression of a mesenchymal CSC-like signature that comprised of ESC genes.

Core developmental transcription programs were shown to be shared between human and mouse species (42). Therefore, it was of interest to examine the human relevance of the p53 Mut MSC-TLs ESC gene signature. We identified specific gene signatures, derived from the human orthologs of p53 Mut MSC-TL ESC gene signature, which predicted poor patient survival in different cancer types. When performing pan-cancer expression analyses, we found that the human orthologs of the identified MSC-TL ESC signature were preferentially expressed in human cancers harboring p53 hotspot missense mutations. Furthermore, analyzing a previously defined human ESC signature, which was shown to correlate with high-grade breast tumors with poor clinical outcome (30), showed similar preferential expression. These observations might explain the association between p53 mutations, and high-grade tumors with poor prognosis (6–8, 43, 44).

In conclusion, our study demonstrates that mutant p53 GOF activity is associated with the enrichment of mesenchymal CSC-like population along with upregulation of a unique signature containing ESC genes. This ESC gene signature was also relevant to patient outcome and to human tumors harboring p53-hotspot missense mutations. Notably, carcinomas occasionally undergo epithelial-to-mesenchymal transition, a process that was also associated with acquisition of stemness traits (25). Thus, our data might suggest that the specific genes in the ESC signature, identified in our MSC model, can be regarded as a broader signature of CSCs and tumor progression toward advanced disease. Gene members of this newly defined signature may therefore serve as prognostic biomarkers and new therapeutic targets for targeting cancer stemness and CSCs in tumors, thereby preventing cancer recurrence.

No potential conflicts of interest were disclosed.

Conception and design: G. Koifman, H. Solomon, A. Molchadsky, V. Rotter

Development of methodology: G. Koifman, V. Rotter

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): G. Koifman, Y. Shetzer, V. Rotter

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): G. Koifman, Y. Shetzer, R. Rotkopf, V. Rotter

Writing, review, and/or revision of the manuscript: G. Koifman, H. Solomon, A. Molchadsky, V. Rotter

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): G. Koifman, V. Rotter

Study supervision: V. Rotter

Other (performing and analyzing the in vivo experiments): S. Eizenberger

Other (performing experiments): G. Lonetto

Other (assisted in performing experiments): N. Goldfinger

We thank Dr. Tali Shalit and Dr. Gil Hornung for RNA sequencing analysis. We also thank Dr. Raya Eilam and Dr. Ori Brenner for their help with IHC and pathologic analyses, respectively. In addition, we thank Dr. Ziv Porat for his help with Multispectral imaging flow cytometry (IFC) data analysis. We would like to acknowledge TCGA research network for providing TCGA datasets. The work by V. Rotter was supported by a Center of Excellence Grant from the Israel Science Foundation, a Center of Excellence Grant from the Flight Attendant Medical Research Institute, and the Israel Cancer Research Fund (ICRF). V. Rotter is the incumbent of the Norman and Helen Asher Professorial Chair of Cancer Research at The Weizmann Institute.

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