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P2RY2-AKT activation is a therapeutically actionable consequence of XPO1 inhibition in acute myeloid leukemia

Nature Cancer volume 3, pages 837–851 (2022)Cite this article

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Abstract

Selinexor is a first-in-class inhibitor of the nuclear exportin XPO1 that was recently approved by the US Food and Drug Administration for the treatment of multiple myeloma and diffuse large B-cell lymphoma. In relapsed/refractory acute myeloid leukemia (AML), selinexor has shown promising activity, suggesting that selinexor-based combination therapies may have clinical potential. Here, motivated by the hypothesis that selinexor’s nuclear sequestration of diverse substrates imposes pleiotropic fitness effects on AML cells, we systematically catalog the pro- and anti-fitness consequences of selinexor treatment. We discover that selinexor activates PI3Kγ-dependent AKT signaling in AML by upregulating the purinergic receptor P2RY2. Inhibiting this axis potentiates the anti-leukemic effects of selinexor in AML cell lines, patient-derived primary cultures and multiple mouse models of AML. In a syngeneic, MLL-AF9-driven mouse model of AML, treatment with selinexor and ipatasertib outperforms both standard-of-care chemotherapy and chemotherapy with selinexor. Together, these findings establish drug-induced P2RY2-AKT signaling as an actionable consequence of XPO1 inhibition in AML.

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Fig. 1: Orthogonal functional genomic and proteomic analyses nominate AKT activation as an actionable consequence of selinexor treatment.
Fig. 2: Selinexor activates PI3K–AKT signaling in AML cells.
Fig. 3: FACS-based CRISPR/Cas9 screening identifies genetic determinants of selinexor-induced AKT activation.
Fig. 4: PI3Kγ promotes AKT activation upon selinexor-induced P2RY2 upregulation.
Fig. 5: Inhibition of AKT potentiates the anti-leukemic effect of selinexor.
Fig. 6: Preclinical efficacy of combined XPO1 and AKT inhibition in AML.

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Data availability

All data associated with this study are available in the main text or the supplementary materials or can otherwise be made available from the corresponding author on reasonable request. Raw counts table for both the CRISPR/Cas9 sensitizer and p-AKT T308 FACS-based screen are included as Supplementary Tables 9 and 10 and on GitHub as detailed below. RNA-seq data from OCI-AML2 and MOLM-13 cells treated with selinexor have been deposited in the Gene Expression Omnibus under accession code GSE181003. Source data for Figs. 1–6 and Extended Data Figs. 1, 2 and 4–10 have been provided as Source Data files. Source data are provided with this paper.

Code availability

Script and associated raw data for reanalyzing sensitizer and FACS-based CRISPR-Cas9 screens are available on GitHub (https://github.com/linkvein/selinexor_p2ry2_akt).

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Acknowledgements

We thank the members of the K. Wood and A. Puissant laboratories for their scientific input. In particular, we thank C. A. Martz, D. P. Nussbaum, G. R. Anderson and P. S. Winter for their insightful comments. This work was supported by Duke University School of Medicine start-up funds and support from the Duke Cancer Institute (K.C.W.), National Institutes of Health awards (R01CA207083 to K.C.W., F30CA206348 to K.H.L., K00CA245732-04 to J.H. and F30CA247323 to C.C.S.), the Duke Medical Scientist Training Program (T32 GM007171 to K.H.L., C.F.B., C.C.S. and S.T.K.), the Duke Undergraduate Research Support Office (to J.C.R. and A.X.), the National Science Scholarship for PhD studies from the Agency for Science, Technology and Research, Singapore (H.X.A), the ATIP/AVENIR French research program (to A.P. and G.S.) and the EHA research grant for Non-Clinical Advanced Fellow (to A.P.). A.P. is a recipient of support from the ERC Starting program (758848) and is supported by the St Louis Association for leukemia research and the FSER association. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the National Institutes of Health.

Author information

Author notes

  1. These authors contributed equally: Kevin H. Lin, Justine C. Rutter.

  2. These authors jointly supervised this work: Alexandre Puissant, Kris C. Wood.

Authors and Affiliations

  1. Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, USA

    Kevin H. Lin, Justine C. Rutter, Abigail Xie, Shane T. Killarney, Christopher F. Bassil, Jacob Hoj, Rachel Washart, Hazel X. Ang, Christian Cerda-Smith, Min Lu & Kris C. Wood

  2. Université de Paris, Génomes, Biologie Cellulaire et Thérapeutique U944, INSERM, CNRS, Paris, France

    Camille Vaganay, Chaima Benaksas, Frank Ling, Gaetano Sodaro, Paul-Arthur Meslin, Nina Fenouille, Antoine Forget, Raphael Itzykson, Lina Benajiba & Alexandre Puissant

  3. Université Côte d’Azur, Nice, France

    Paul Chaintreuil, Arnaud Jacquel & Patrick Auberger

  4. Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA

    Jiaxing Lin, Zhecheng Sheng & Kouros Owzar

  5. Center for Applied Proteomics and Molecular Medicine, School of Systems Biology, George Mason University, Manassas, VA, USA

    Mariaelena Pierobon & Emanuel Petricoin

  6. Department of Biomedical Engineering, Duke University, Durham, NC, USA

    Xinghai Li & Ashutosh Chilkoti

  7. Department of Medicine, Duke University Medical Center, Durham, NC, USA

    David A. Rizzieri

  8. Department of Internal Medicine, Section on Hematology and Oncology, Wake Forest Baptist Health, Winston-Salem, NC, USA

    Timothy S. Pardee

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  1. Kevin H. Lin
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Contributions

Conceptualization was carried out by K.H.L., J.C.R., A.P. and K.C.W. K.H.L., J.C.R., C.V., C.B. and J.L. were responsible for the methodology. Validation was the responsibility of K.H.L., J.C.R., A.X. and C.V. Formal analysis wasa conducted by K.H.L., J.C.R., A.X., P.M., L.B., A.F., J.L., Z.S., F.L., G.S., N.F., L.B., P. C., A. J., P. A. and M.P. Investigations were conducted by K.H.L., J.C.R., A.X., C.V., C.B., J.L., Z.S., X.L. and R.I. Y.R.A., R.T.S., M.P., P.C., A.J., P.A, T.S.P., E.P., A.P. and K.C.W. were responsible for resources. Data curation was conducted by K.H.L., J.C.R., A.X., A.F. and J.L. K.H.L., J.C.R. and K.C.W. were responsible for writing of the original draft of the manuscript. All authors reviewed the mansucript. K.H.L. and J.C.R. were responsible for visualization. A.C., K.O., D.A.R., T.S.P., L.B., E.P., A.P. and K.C.W. supervised the study. K.H.L., A.P. and K.C.W. were responsible for funding acquisition.

Corresponding authors

Correspondence to Alexandre Puissant or Kris C. Wood.

Ethics declarations

Competing interests

K.C.W. is a founder, consultant and equity holder at Tavros Therapeutics and Celldom and has performed consulting work for Guidepoint Global, Bantam Pharmaceuticals and Apple Tree Partners. T.S. Pardee has received research funding from Karyopharm and has served as a paid advisor to Karyopharm. R. Itzykson has received honoraria from Karyopharm for consulting. E.P. and M.P. are inventors on patent applications that cover aspects of the reverse-phase protein microarray; as inventors, they are entitled to receive royalties as provided by US Law and George Mason University policy. E.P. and M.P. receive royalties from and are consultants of TheraLink Technologies. E.P. is a shareholder of TheraLink Technologies and shareholder and consultant of Perthera. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 CRISPR/Cas9 and RPPA analyses reveal signaling pathways modulated by Selinexor treatment.

a) Scatter-plot depicting replicate selinexor depletion gene scores from CRISPR/Cas9 drug-modifier screen. Screens conducted as n = 2 independent replicates with n = 5 sgRNAs per gene. b) Gene ontology (GO) analysis of selinexor “resister” genes; performed using Enrichr. c) Selinexor depletion gene scores ranked from most depleted to most enriched in the selinexor versus vehicle-treated populations. Predicted genetic modifiers of selinexor sensitivity involved in G1/S cell cycle progression are annotated. d) Schematic relating G1/S cell cycle regulators to selinexor depletion gene scores and RPPA expression. Annotated as in Fig. 1d. e) GO analysis of selinexor “sensitizer” genes; performed using Enrichr. f) Schematic relating mTORC1 signaling to selinexor depletion gene scores and RPPA expression. Annotated as in Fig. 1d. g) Immunoblot depicting protein levels of phosphorylated and total S6K1 in five AML cell lines treated with DMSO or selinexor. B-actin included as loading control. Representative immunoblots of n = 2 independent experiments yielding similar results.

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Extended Data Fig. 2 Activation of AKT signaling is a specific consequence of XPO1 inhibition.

a) Immunoblot depicting protein levels of phosphorylated PRAS40, FOXO3a, and TSC2 following 24-hour treatment of OCI-AML2 cells with selinexor. b) Immunoblot depicting protein levels of phosphorylated AKT at T308 and S473 following 24-hour treatment of OCI-AML2 and MOLM-13 cells with eltanexor. c) Immunoblot depicting protein levels of phosphorylated AKT at T308 and S473 in OCI-AML2 cells treated with a panel of standard-of-care therapies for 24 hours. Representative immunoblots of n = 2-3 independent experiments yielding similar results. B-actin included as loading control.

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Extended Data Fig. 3 Gating strategy and Gene Ontology analysis of FACS-based CRISPR/Cas9 screen.

a) Scatter-plot depicting gating strategy to isolate live sgRNA library transduced OCI-AML2 cells based on forward-scatter (FSC) and side-scatter (SSC). b) Scatter-plot depicting gating strategy to isolate singlet sgRNA library transduced OCI-AML2 cells based on FSC. c) Gene ontology (GO) analysis table of scoring genes enriched in the bottom sort (FSGS of > 1.5). P values calculated by Enrichr using Benjamini-Hochberg correction for multiple hypothesis testing.

Extended Data Fig. 4 Selinexor-induced AKT activation requires the P2RY2 purinergic receptor.

a) GSEA plots for gene ontologies enriched in RNA-seq datasets upon selinexor treatment. b) GSEA plots for gene ontologies depleted in RNA-seq datasets upon selinexor treatment. c) Comparison of differential gene expression analysis in OCI-AML2 and MOLM-13 cells treated + /- selinexor. The genes in red are upregulated in both cell lines when treated with selinexor whereas the genes in blue are downregulated in both cell lines. d) Selinexor gene signature representation in AML patients with low versus high P2RY2 expression. ON versus OFF selinexor signatures were assigned for each patient based on the ES z score > 1 or < −1, respectively. The number of selinexor-ON patients in the P2RY2 high subset versus the P2RY2 low subset was compared; P values computed using two-sided Fisher’s t-test. e) Immunoblot depicting protein levels of phosphorylated AKT at T308 and S473 in OCI-AML2 and MOLM-13 cells treated with 50 μM ATP for 48 hours. f) As in (e) but cells were treated with UTP. g) Relative extracellular ATP concentration in OCI-AML2 cells treated with selinexor versus DMSO control for 36 hours. P values computed using Welch’s unpaired (two-sided) t-tests; data are presented as mean + /- s.e.m. for n = 6 biological replicates. h) Relative expression of P2RY2 in OCI-AML2 cells stably expressing indicated TetOn shRNA constructs following 48 hours of doxycycline treatment. i) Immunoblot depicting protein levels of total and phosphorylated AKT at T308 and S473 in OCI-AML2 cells expressing Cas9 and sgRNAs targeting GFP control or P2RY2 treated with selinexor or DMSO. B-actin included as loading control. j) Tide analysis of OCI-AML2 cells expressing sgP2RY2 to access knockout efficiency. k) Immunoblot depicting protein levels of total and phosphorylated AKT at T308 and S473 in OCI-AML2 cells overexpressing P2RY2 or empty vector in OCI-AML2 cells. B-actin included as loading control. l) Relative expression of P2RY2 in OCI-AML2 cells stably expressing either empty vector or P2RY2 ORF. Extended Data Fig. 4h, l P values computed using multiple unpaired (two-sided) t-tests; data presented as mean + /-s.e.m. for n = 6 biological replicates. Extended Data Fig. 4e,f,i,k Representative immunoblots of n = 2-3 biologically independent experiments yielding similar results. B-actin included as loading control.

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Extended Data Fig. 5 Isoform-specific dependency on PI3Kγ for Selinexor-induced AKT activation.

a) Immunoblot depicting protein levels of p110-gamma and p101 in OCI-AML2 cells harboring doxycycline-inducible shRNAs targeting PIK3CG (encoding for p110-gamma) and PIK3R5 (encoding for p101) versus scrambled control. B-actin included as loading control. b) Immunoblot depicting protein levels of phosphorylated AKT at T308 in OCI-AML2 cells harboring doxycycline-inducible shRNAs targeting PIK3CA, PIK3CB and PIK3CD versus scrambled control following treatment with selinexor for 36 hours. B-actin included as loading control. c) Immunoblot depicting protein levels of p110α, p110β and p110δ in OCI-AML2 cells harboring doxycycline-inducible shRNAs targeting PIK3CA, PIK3CB and PIK3CD versus scrambled control. B-actin included as loading control. d) Immunoblot depicting protein levels of total and phosphorylated AKT at T308 and S473 in OCI-AML2, MV4;11 and OCI-AML3 cells treated with BYL-719 (PI3K-alpha inhibitor), TGX-221 (PI3K-beta inhibitor), CAL-101 (PI3K-delta inhibitor) or IPI-549 (PI3K-gamma inhibitor) with or without selinexor for 36 hours. OCI-AML2 cells were treated with 500 nM of PI3K inhibitors and MV;411 and OCI-AML3 cells were treated with 100 nM of PI3K inhibitors. B-actin included as loading control. e) Immunoblot depicting protein levels of catalytic PI3K isoforms in OCI-AML2 cells treated with selinexor or DMSO. B-actin included as loading control. f) Immunoblot depicting protein levels of phospho-substrates of PKA or PKC in OCI-AML2 cells treated with selinexor or DMSO. B-actin included as loading control. Representative immunoblots of n = 2-4 biologically independent experiments yielding similar results. B-actin included as loading control.

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Extended Data Fig. 6 The activity and requirement of Ras for complete Selinexor-induced AKT activation.

a) Immunoblot depicting active Ras following co-immunoprecipitation of Ras-GTP with GST-Raf1-Ras-binding domain (RBD) fusion proteins in a panel of selinexor-treated AML cell lines. Total Ras in input shown as control. b) Immunoblot depicting active Ras as in (c) in OCI-AML2 cells treated with AR-C 118925XX (2.5 μM) and Selinexor (200 nM), alone and in combination. Total Ras in input shown as control. c) Immunoblot depicting protein levels of immunoprecipitated GTP-bound Ras in OCI-AML2 cells with doxycycline-inducible shRNAs targeting P2RY2 versus scrambled shRNA control. Cells were exposed to doxycycline (75 ng/mL) for 48 hours and treated with either vehicle or selinexor for 36 hours. Total Ras in input shown as control. d) Immunoblot depicting protein levels of phosphorylated AKT at T308 and S473 in OCI-AML2 cells co-expressing doxycycline-inducible shRNAs against NRAS and KRAS versus scrambled shRNA control. Cells were exposed to doxycycline (75 ng/mL) for 48 hours and treated with either vehicle or selinexor for 36 hours. e) Immunoblot depicting protein levels of phosphorylated AKT at T308 and S473 in OCI-AML2 cells expressing doxycycline-inducible shRNAs against NRAS or KRAS. Cells were exposed to doxycycline (75 ng/mL) for 48 hours and treated with either vehicle or selinexor for 36 hours. f) Relative 72 h selinexor GI50 and dose–response curves in OCI-AML2 cells expressing GFP or Luciferase control or activating constructs of Ras or AKT. P values computed using one-way ANOVA with Tukey’s method for multiple comparisons; data are presented as mean + /-s.e.m. for n = 3 biological replicates. g) Genetic dependency of AML cell lines on XPO1 as defined by the DepMap dataset. P values computed using unpaired (two-sided) t-test. Extended Data Fig. 6a-e Representative immunoblots of n = 2−4 biologically independent experiments yielding similar results. B-actin included as loading control.

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Extended Data Fig. 7 The anti-leukemic effect of AKT inhibition combined with Selinexor in cell line models of AML.

a) Bliss synergy analysis 2D plots for a panel of AML cell lines treated with a dilution series of selinexor and MK-2206. Delta scores indicate synergy (red) and antagonism (green) across the drug-dilution matrix. b) Relative MK-2206 GI50 values in OCI-AML2 cells harboring doxycycline (dox)-inducible shRNAs targeting XPO1 versus scrambled shRNA control. Cells treated with dox for 48 hours prior to incubation with MK-2206 drug-dilution series. Relative MK-2206 GI50 value defined as (GI50 MK-2206 -dox) / (GI50 MK-2206 + dox). c) Time-to-progression assay of OCI-AML2 cells treated with 200 nM selinexor, 5 μM ipatasertib, or the two drugs in combination. d) Selinexor dose–response curves in OCI-AML2 and MOLM-13 cell lines treated with everolimus (50 nM or 100 nM) in the background. e) Relative selinexor GI50 values in OCI-AML2 cells harboring doxycycline-inducible shRNAs targeting P2RY2 versus scrambled shRNA control. Cells were pre-treated with dox for 48 hours prior to incubation with selinexor drug-dilution series. Relative selinexor sensitivity values defined as (GI50 selinexor-dox) / (GI50 selinexor + dox). f) Relative selinexor GI50 values in OCI-AML2 cells co-treated with 5 μM AR-C or DMSO. g) Relative GI50 values of selinexor in combination with PI3K-α/β/δ/γ-specific inhibitors across a panel of AML cell lines. Relative selinexor GI50 value defined as (GI50 selinexor + PI3K inhibitor) / (GI50 selinexor alone). Background PI3K inhibitors dosed by cell line (OCI-AML2, 1 μM; HL-60, 4 μM; MOLM-13, 2 μM; MV4;11, 2 μM; THP-1, 1 μM). h) Immunoblot depicting protein levels of CASPASE 3 and cleaved CASPASE 3 in OCI-AML2 cells treated with selinexor (200 nM), ipatasertib (5 μM), or the combination. Vinculin shown as control. i) Drug-treated induction of annexin positivity in OCI-AML2 cells, as measured by flow cytometry, relative to baseline annexin positivity elicited with DMSO treatment. j) Immunoblot depicting protein levels of BAX in OCI-AML2 cells expressing hairpins targeting BAX or GFP control. B-actin shown as loading control. k) Bliss synergy landscape for two healthy donor cord blood-derived CD34 + cells treated with selinexor versus ipatasertib across a drug-dilution matrix. Extended Data Fig. 7b-g, i data are presented as mean + /-s.e.m. for n = 3 biologically independent replicates. Extended Data Fig. 7b,e-h,i P values computed using multiple unpaired (two-sided) t-tests. Extended Data Fig. 7h,j Representative immunoblots of n = 2 biologically independent experiments yielding similar results.

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Extended Data Fig. 8 The effect of Selinexor combined with AKT inhibition on mouse weight and hematopoietic cell compartment.

a) Dose-escalation study assessing mouse weight in disease naïve C57BL/6 mice. Mice were treated until Day 4 with indicated treatment regimens (n = 3 biologically independent mice). P values calculated using a two-way ANOVA; data are presented as + /- mean s.d. b) Dose-escalation study assessing white blood cell count in disease naïve C57BL/6 mice. Mice were treated until Day 4 with indicated treatment regimens (n = 3 biologically independent mice). P values calculated using a two-way ANOVA; data are presented as + /- mean s.d. c) Immunoblot depicting protein level of Tp53 in DsRed+ MLL-AF9 cells from mice treated in vivo with Selinexor for indicated duration. Each timepoint representants an independent biologic replicate. Representative immunoblots of n = 2 biologically independent experiments yielding similar results. Vinculin shown as loading control. d-n) Flow cytometric measurement of various hematopoietic cell types, each defined by gating strategies labeled on respective y-axes, in C57BL/6 mice treated with vehicle, chemotherapy (1 mg/kg doxorubicin and 100 mg/kg cytarabine), or the combination of 65 mg/kg ipatasertib and 15 mg/kg selinexor. Data are presented as mean + /- s.d. for n = 4 biologically independent replicates. Where indicated, P values computed using unpaired (two-sided) t-test.

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Extended Data Fig. 9 Analysis of engraftment, tolerability, and efficacy of Selinexor combined with AKT inhibition in mouse models of AML.

a) Confirmation of PDX engraftment by measurement of circulating human CD45 + cells transplanted into NOG–EXL mice (n = 6 biologically independent mice per group); data are presented as mean + /- s.d. b) Bliss synergy analysis 2D plots for PDX model of AML treated with a dilution series of selinexor and ipatasertib. Delta scores indicate synergy (red) and antagonism (green) across drug-dilution matrix. c) Weight of C57BL/6 mice treated with vehicle or selinexor (15 mg/kg) plus ipatasertib (65 mg/kg). d) Weight of C57BL/6 mice treated with vehicle or chemotherapy (doxorubicin 1 mg/kg, cytarabine 100 mg/kg). e) Weight of C57BL/6 mice treated with vehicle or selinexor (15 mg/kg) plus chemotherapy (doxorubicin 1 mg/kg, cytarabine 100 mg/kg). f) Weight of C57BL/6 mice treated with vehicle or selinexor (7.5 mg/kg) plus chemotherapy (doxorubicin 1 mg/kg, cytarabine 100 mg/kg). g) Measurement by flow cytometry of the proportion of DsRed+ MLL-AF9 cells taken from bone marrows (n = 5 biologically independent mice per group) two days following treatment with vehicle, 15 mg/kg selinexor plus 65 mg/kg ipatasertib, chemotherapy (1 mg/kg doxorubicin and 100 mg/kg cytarabine), or 7.5 mg/kg selinexor plus chemotherapy; P values calculated using unpaired Mann-Whitney test; data are presented as mean + /- s.d. h) Measurement by flow cytometry of DsRed+ MLL-AF9 cells taken from bone marrows at the point of relapse observed in chemotherapy-treated mice (n = 5 biologically independent mice per group except in the chemotherapy-treated subgroup in which n = 4). P values calculated using unpaired Mann-Whitney test; data are presented as mean + /- s.d. i) Selinexor dose–response in OCI-AML2 and MOLM-13 cells treated with cytarabine (50 nM) or daunorubicin (5 nM) in the background; data are presented as mean + /- s.e.m. for n = 3 biologically independent experiments. Extended Data Fig. 9c-f Dosing schedule shown at bottom left. (D) = mouse demise.

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Extended Data Fig. 10 Efficacy of Selinexor combined with AKT inhibition on leukemia initiating cells.

a) Leukemic burden of mice (n = 3 biologically independent mice per group) prior to sorting and engraftment for extreme limiting dilution assay. P values calculated using unpaired two-sided Welch’s test; data are presented as mean + /-s.d. b) FACS plots depicting gating strategy to isolate dsRed+ MLL-AF9 cells prior to engraftment for extreme limiting-dilution assay. c) Kaplan–Meier curves showing overall survival of secondary recipient mice (n = 5 biologically independent mice) from each group in limiting dilution assay for determining LIC frequency. Statistical significance determined by log-rank (Mantel-Cox) test. n.s, not significant.

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Supplementary information

Reporting Summary

43018_2022_394_MOESM2_ESM.xlsx

Supplementary Table 1. CRISPR/Cas9 selinexor sensitizer screen in OCI-AML2 cells. Supplementary Table 2. RPPA protein expression analysis at three selinexor treatment time points and normalized to DMSO control. Supplementary Table 3. FACS screen gene score (FSGS) indicating enrichment in bottom sort versus top sort of selinexor-treated, full-genome sgRNA library containing OCI-AML2 cells FACS sorted by p-AKT T308 expression. Supplementary Table 4. RNA-seq analysis showing differential gene expression in selinexor- versus vehicle-treated OCI-AML2 and MOLM-13 cells. Supplementary Table 5. Clinical features of patients with AML. Supplementary Table 6. qRT–PCR primers. Supplementary Table 7. shRNA sequences. Supplementary Table 8. Sequencing primers. Supplementary Table 9. CRISPR/Cas9 selinexor sensitizer screen in OCI-AML2 cells; raw counts. Supplementary Table 10. CRISPR/Cas9 selinexor FACS screen OCI-AML2 cells; raw counts

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Lin, K.H., Rutter, J.C., Xie, A. et al. P2RY2-AKT activation is a therapeutically actionable consequence of XPO1 inhibition in acute myeloid leukemia. Nat Cancer 3, 837–851 (2022). https://doi.org/10.1038/s43018-022-00394-x

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