Human pluripotent stem cells recurrently acquire and expand dominant negative P53 mutations

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Abstract

Human pluripotent stem cells (hPS cells) can self-renew indefinitely, making them an attractive source for regenerative therapies. This expansion potential has been linked with the acquisition of large copy number variants that provide mutated cells with a growth advantage in culture1,2,3. The nature, extent and functional effects of other acquired genome sequence mutations in cultured hPS cells are not known. Here we sequence the protein-coding genes (exomes) of 140 independent human embryonic stem cell (hES cell) lines, including 26 lines prepared for potential clinical use4. We then apply computational strategies for identifying mutations present in a subset of cells in each hES cell line5. Although such mosaic mutations were generally rare, we identified five unrelated hES cell lines that carried six mutations in the TP53 gene that encodes the tumour suppressor P53. The TP53 mutations we observed are dominant negative and are the mutations most commonly seen in human cancers. We found that the TP53 mutant allelic fraction increased with passage number under standard culture conditions, suggesting that the P53 mutations confer selective advantage. We then mined published RNA sequencing data from 117 hPS cell lines, and observed another nine TP53 mutations, all resulting in coding changes in the DNA-binding domain of P53. In three lines, the allelic fraction exceeded 50%, suggesting additional selective advantage resulting from the loss of heterozygosity at the TP53 locus. As the acquisition and expansion of cancer-associated mutations in hPS cells may go unnoticed during most applications, we suggest that careful genetic characterization of hPS cells and their differentiated derivatives be carried out before clinical use.

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Figure 1: Acquisition and WES of 140 hES cell lines.
Figure 2: Identification of recurrent, cancer-associated TP53 mutations in hES cells.
Figure 3: TP53 mutations in hES cells are mosaic and confer strong selective advantage.
Figure 4: A substantial fraction of hPS cells in published studies harbour TP53 mutations.

Change history

  • 04 May 2017

    New references 29 and 30 were added, and subsequent citations were renumbered accordingly.

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Acknowledgements

We thank the many institutions and investigators world-wide that provided their cell lines and supported the publication of the results. We are indebted to D. Santos, M. Smith, K. Elwell, M. A. Yram, S. Ellender, L. Bevilacqua, and D. Gage for their assistance with the regulatory and logistical efforts required to acquire and sequence hES cell lines. We also thank K. Lilliehook for her comments, I. Yildirim for his assistance with the molecular modelling of P53 mutations, and C. Usher for help with figure schematics. We regret the omission of any relevant references or discussion due to space limitations. The Genomics Platform at the Broad Institute performed sample preparation, sequencing, and data storage. Y.A. is a Clore Fellow. N.B. is the Herbert Cohn Chair in Cancer Research and was partially supported by The Rosetrees Trust and The Azrieli Foundation. Costs associated with acquiring and sequencing hES cell lines were supported by HHMI and the Stanley Center for Psychiatric Research. F.T.M., S.A.M., and K.E. were supported by grants from the NIH (5P01GM099117, 5K99NS08371). K.E. was supported by the Miller consortium of the HSCI, and F.T.M. is currently supported by funds from the Wellcome Trust, the Medical Research Council (MR/P501967/1), and the Academy of Medical Sciences (SBF001\1016).

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Contributions

F.T.M., S.G., S.A.M., and K.E. conceived the project. F.T.M. and K.E. acquired hES cell lines with the assistance of M.C. and G.S., who also assisted with regulatory issues pertaining to sequencing and data distribution. F.T.M. cultured and banked hES cell lines, prepared them for sequencing, and coordinated efforts to interpret and visualize sequencing data with the assistance of S.G. S.G. performed computational data analysis and visualization with the help of G.G., R.E.H., and S.K. Y.A. preformed the analysis of TP53 mutations in the RNA-seq database with the assistance of S.B. and N.B. Data were interpreted by F.T.M., S.G., N.K., G.G., Y.A., S.B., N.B., S.A.M., and K.E. N.K., J.M., and C.M. designed, performed and analysed experiments to measure the mosaic nature and competitive expansion of TP53 mutations. S.M. derived HUES 68, 69, 70, 74, 75, and D.I. provided the KCL lines. F.T.M., S.G., S.A.M., and K.E. prepared drafts of the manuscript text and figures with contributions and comments from all authors.

Corresponding authors

Correspondence to Steven A. McCarroll or Kevin Eggan.

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Extended data figures and tables

Extended Data Figure 1 Replicates of cell competition assays carried out at earlier starting passages.

Note that while the mutant allelic fractions for lines CHB11 and WA26 approach fixation, that the fraction of mutant cells unexpectedly decreases for ESI035 over several passages, indicating a potential selective disadvantage that co-segregates with the TP53 mutation in this experiment. The number of replicate wells is indicated in each graph. Values depict the mean and error bars depict s.e.m.

Extended Data Figure 2 Summary of all observed P53 mutations.

a, b, Graphical representation of each of the 9 mutated bases in P53 observed across the 252 whole-exome sequenced (WES) and RNA-seq hPS cell lines depicting their allele frequency in ExAC (a) and the incidence with which the relevant codons are mutated in human cancer (b). c, The 15 instances of these mutations in 12 distinct cell lines and the method used to detect them are pictured. Although the M237I event is seen in two distinct hiPS cell lines, it is conservatively counted as a single event as the two affected clones may be derived from a common reprogrammed progenitor.

Extended Data Figure 3 Analysis of loss of heterozygosity in RNA sequencing samples.

a, Polymorphic sites on chromosome 17 in different hPS cells with mutations in TP53. WIBR3 cells with H193R mutation and H9 cells with both P151S and R248Q mutations show less polymorphism in the distal part of chromosome 17p compared to the proximal part of 17p and 17q. Asterisk indicates samples with less than 25 reads. b, Ratio between the fraction of polymorphic alleles in the distal part of chromosome 17p or the reminder of chromosome 17 (proximal 17p + 17q) compared to that fraction for the entire chromosome 17. Values shown depict mean. Where present, error bars depict s.e.m. for 2–22 replicate samples. ***P < 0.001, one-sided Z-score test for the two population proportion. WIBR3 cells with H193R mutation and H9 cells with both P151S and R248Q mutations have a significantly different proportion between the two parts of the chromosome, implying LOH. c, A schematic representation of possible allele states of TP53 in cultured hPS cells with all observed mutations depicted. Depending on the percentage of mutant reads in a culture, one can deduce if the culture is homogenous or mosaic for a mutation, and whether, in addition to a point mutation, LOH has occurred in the TP53 locus. MAF, minor allele frequency.

Extended Data Figure 4 Culture and passaging method employed for samples bearing P53 mutations.

a, P53 mutations were observed in hPS cells grown in a broad array of culture media including media supplemented with knockout serum replacement (KOSR), and defined, commercial media such as E8. b, P53 mutations were observed from cells grown with feeder cells or under feeder-free conditions. c, As passaging hPS cells can introduce stresses or clonal bottlenecks, we examined whether P53 mutations were consistently seen when a particular passaging method was used and observed a wide variety of passaging methods associated with these mutations. Note that the interpretation of these data are complicated by the fact that the culture methods employed in the final published study may not reflect the previous culture history of that cell line, which may have previously passed through multiple laboratories, as well as by the lack of detail about culture methods present in some published studies. d, P53 mutations are seen in studies that either include or exclude supplements such as the rock inhibitor Y-27632 (10 μM) at the time of passaging.

Supplementary information

Supplementary Table 1

Considered and whole exome sequenced hESC lines. Tab 1. We considered hESC lines for WES if they were listed on the NIH Human Embryonic Stem Cell Registry (http://grants.nih.gov/stem_cells/registry/current.htm) or if they were prepared under GMP conditions. Cell lines were typically excluded from consideration if they were unavailable for distribution or contained known karyotypic abnormalities in more than 10% of analyzed cells or disease-causing mutations identified by PGD. Cell lines with MTAs that restricted our ability to work with the cell lines, that could not be recovered upon thawing, or proved to be unavailable upon request were also excluded. Passage number at the time of request, the number of passages and time in culture from thaw to passaging, and the passaging method, media, and substrate, are provided, as is mean sequencing coverage and % cross sample contaminated per cell line. GMP, good manufacturing practice; MTA, material transfer agreement; PGD, pre-implantation genetic diagnosis; WES, whole exome sequencing. Tab 2. Summary of number of cells considered and sequenced, including reasons for exclusion. These data are presented graphically in Figure 1b-e. (XLSX 57 kb)

Supplementary Table 2

Identification of candidate mosaic variants present in sequenced hESCs. Tab 1. Filters used to identify likely mosaic variants among all heterozygous variants present among the sequenced exomes of 140 hESCs. Tab 2. List of 263 candidate mosaic variants passing quality control filters and present no more than two times among the 140 sequenced hESC lines. Variants are arranged by chromosome position and annotated by likely functional impact and frequency in the general population (ExAC AC). Tab 3. Variants from the list in Tab 2 predicted to have either a high or damaging impact on gene function based on a consensus of 7 bioinformatic algorithms. See Materials and Methods for further details. Tab 4. In addition to mosaic variants identified using these stringent filters, we provide an inclusive list of all high confidence somatic variants (n=36,396) that pass the binomial test with a P value of <0.01. SNP, single nucleotide polymorphism; CHROM, chromosome number; POS, genomic position (hg19); REF, reference allele; ALT, alternate allele; HESC, human embryonic stem cell line; REFC, count of reference alleles; ALTC, count of alternate alleles; FILTER, high confidence variant score; EXACAC, allele count in the Exome Aggregation Consortium (ExAC) database; IMPACT, predicted effect of mutation; HESCAC, allele count in hESCs; TOTALC, REFC+ALTC; AF, allelic faction (ALTC/TOTALC); P, P value for binomial test on allelic fraction. (XLSX 4082 kb)

Supplementary Table 3

Characteristics of TP53 mutations identified in hESCs by WES and RNAseq. Tab 1. Summary of all 15 instances of TP53 mutations observed by WES and RNAseq with details of read depth, allelic fraction, P value, reference, and culture method. Note that all observed mutations are frequently seen in human cancer, and that most mutations have evidence of mosaicism, indicating that they were likely culture-derived. bFGF, basic fibroblast growth factor (FGF2); COSMIC, Catalogue of Somatic Mutations in Cancer (http://cancer.sanger.ac.uk/cosmic); ExAC, Exome Aggregation Consortium (http://exac.broadinstitute.org/); Freq., frequency; GMP, good manufacturing practice, IARC, International Agency for Research on Cancer (http://p53.iarc.fr/); ICGC, International Cancer Genome Consortium (http://icgc.org/); MEF, mouse embryonic fibroblast; Seq., sequencing; SNL, SNL mouse fibroblast feeder cell line; WES, whole exome sequencing. Errors denote SEM. Tab 2. Breakdown of the incidence of P53 mutations by culture media, substrate, and passaging method. (XLSX 51 kb)

Supplementary Table 4

Primer and probe sequences used for ddPCR-based determination of P53 variant allele frequency. (XLSX 30 kb)

Supplementary Table 5

Calculation of selective advantage conferred by three distinct TP53 variants. The allelic fraction of TP53 variants was measured at several passages by ddPCR in hESCs cultured under standard conditions. Replicate experiments per passage are shown in grey, and average values are shown in black. The observed increase in allelic frequency of each of the variants across time in culture is consistent with a substantial growth or survival advantage in all but one instance. See Materials and Methods for details on ddPCR and the calculation of the effect per passage. (XLSX 39 kb)

Supplementary Table 6

Large copy number variants in hESCs identified by the human Psych Array. Tab 1. Summary of hESC lines with large copy number variants (>500kb) as ascertained by SNP array analysis. Two of the five cell lines with acquired TP53 mutations harbored large structural alternations (HUES71 and MShef10). Five separate cell lines (CSES25, ESI051, MShef3, UM78-1 and WA21) had an amplification at the pericentromeric region of chromosome 20 (Chr20q11.21). Tab 2. Complete list of large deletions or duplications (>500kb) identified across the 140 hESC lines. (XLSX 57 kb)

Supplementary Table 7

Identification of TP53 mutations in hPSCs by RNA sequencing and WES. Tab 1. List of all RNA sequenced samples from hPSCs. Five of these samples (cell2-7) were removed since they were from single stem cells rather than cell lines. Tab 2. Summary of the number of samples and studies generated from each cell line. Tab 3. List of all samples harboring TP53 mutations, their chromosomal location, and the relevant study. Tab 4. Summary of all affected cell lines and studies. Tab 5. Summary of affected samples, cell lines, and number of mutations seen in hESCs and hiPSCs by WES and RNAseq. (XLSX 68 kb)

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Merkle, F., Ghosh, S., Kamitaki, N. et al. Human pluripotent stem cells recurrently acquire and expand dominant negative P53 mutations. Nature 545, 229–233 (2017). https://doi.org/10.1038/nature22312

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