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Checkpoint inhibitor immunotherapy diminishes oocyte number and quality in mice

Nature Cancer volume 3, pages 1–13 (2022)Cite this article

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Abstract

Loss of fertility is a major concern for female reproductive-age cancer survivors, since a common side-effect of conventional cytotoxic cancer therapies is permanent damage to the ovary. While immunotherapies are increasingly becoming a standard of care for many cancers—including in the curative setting—their impacts on ovarian function and fertility are unknown. We evaluated the effect of immune checkpoint inhibitors blocking programmed cell death protein ligand 1 and cytotoxic T lymphocyte-associated antigen 4 on the ovary using tumor-bearing and tumor-free mouse models. We find that immune checkpoint inhibition increases immune cell infiltration and tumor necrosis factor-α expression within the ovary, diminishes the ovarian follicular reserve and impairs the ability of oocytes to mature and ovulate. These data demonstrate that immune checkpoint inhibitors have the potential to impair both immediate and future fertility, and studies in women should be prioritized. Additionally, fertility preservation should be strongly considered for women receiving these immunotherapies, and preventative strategies should be investigated in future studies.

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Fig. 1: Immune checkpoint blockade impairs ovulation and expands intra-ovarian T cells in tumor-bearing mice.
Fig. 2: Immune checkpoint blockade diminishes the ovarian reserve and exerts long-term disruptions to ovulation and cycling in tumor-free mice.
Fig. 3: Immune checkpoint inhibitors exert immediate impacts on pre-ovulatory follicles and ovulation in tumor-free mice.
Fig. 4: Depletion of ovarian follicles by immune checkpoint blockade is immune cell-mediated.
Fig. 5: Immune checkpoint inhibition elevates circulating and intra-ovarian inflammatory cytokine levels.
Fig. 6: Checkpoint blockade-induced follicle loss occurs via BID-mediated apoptosis.

Data availability

Previously published microarray data that were re-analyzed here are available under accession code GSE38666. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

References

  1. Barr, R. D. Adolescents, young adults, and cancer—the international challenge. Cancer 117, 2245–2249 (2011).

    Article  PubMed  Google Scholar 

  2. Lambertini, M. et al. Fertility preservation and post-treatment pregnancies in post-pubertal cancer patients: ESMO Clinical Practice Guidelines. Ann. Oncol. 31, 1664–1678 (2020).

    Article  CAS  PubMed  Google Scholar 

  3. ESHRE Guideline Group on Female Fertility Preservation et al. ESHRE guideline: female fertility preservation. Hum. Reprod. Open 2020, hoaa052 (2020).

  4. Zhang, H. & Chen, J. Current status and future directions of cancer immunotherapy. J Cancer 9, 1773–1781 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Alesi, L. R., Winship, A. L. & Hutt, K. J. Evaluating the impacts of emerging cancer therapies on ovarian function. Curr. Opin. Endo. Metab. Res. 18, 15–28 (2021).

    Article  CAS  Google Scholar 

  6. Johnson, D. B., Chandra, S. & Sosman, J. A. Immune checkpoint inhibitor toxicity in 2018. JAMA 320, 1702–1703 (2018).

    Article  PubMed  Google Scholar 

  7. Postow, M. A., Sidlow, R. & Hellmann, M. D. Immune-related adverse events associated with immune checkpoint blockade. N. Engl. J. Med. 378, 158–168 (2018).

    Article  CAS  PubMed  Google Scholar 

  8. Vaddepally, R. K., Kharel, P., Pandey, R., Garje, R. & Chandra, A. B. Review of indications of FDA-approved immune checkpoint inhibitors per NCCN guidelines with the level of evidence. Cancers (Basel) 12, 738 (2020).

    Article  CAS  Google Scholar 

  9. Franasiak, J. M. & Scott, R. T. in Cancer & Fertility (ed. Sabanegh, J.E.S.) Ch. 2 (Springer International Publishing, 2016).

  10. Cui, W. et al. Assessment of ovarian function in phase 3 (neo)adjuvant breast cancer clinical trials: a systematic evaluation. J. Natl Cancer Inst. 113, 1770–1778 (2021).

  11. Kerr, J. B., Myers, M. & Anderson, R. A. The dynamics of the primordial follicle reserve. Reproduction 146, R205–R215 (2013).

    Article  CAS  PubMed  Google Scholar 

  12. Kerr, J. B. et al. The primordial follicle reserve is not renewed after chemical or γ-irradiation mediated depletion. Reproduction 143, 469–476 (2012).

    Article  CAS  PubMed  Google Scholar 

  13. Dunlop, C. E. & Anderson, R. A. The regulation and assessment of follicular growth. Scand. J. Clin. Lab. Invest. 74, 13–17 (2014).

    Article  CAS  Google Scholar 

  14. Gilchrist, R. B., Ritter, L. J. & Armstrong, D. T. Mouse oocyte mitogenic activity is developmentally coordinated throughout folliculogenesis and meiotic maturation. Dev. Biol. 240, 289–298 (2001).

    Article  CAS  PubMed  Google Scholar 

  15. Chaffin, C. L. & Van de Voort, C. A. Follicle growth, ovulation, and luteal formation in primates and rodents: a comparative perspective. Exp. Biol. Med. 238, 539–548 (2013).

    Article  CAS  Google Scholar 

  16. Gougeon, A. Dynamics of follicular growth in the human: a model from preliminary results. Hum. Reprod. 1, 81–87 (1986).

    Article  CAS  PubMed  Google Scholar 

  17. Bertolin, K. & Murphy, B. D. in The Guide to Investigation of Mouse Pregnancy (eds Croy, B. A. et al.) Ch. 7 (Academic Press, 2014).

  18. Coxworth, J. E. & Hawkes, K. Ovarian follicle loss in humans and mice: lessons from statistical model comparison. Hum. Reprod. 25, 1796–1805 (2010).

    Article  CAS  PubMed  Google Scholar 

  19. Wu, R., Van der Hoek, K. H., Ryan, N. K., Norman, R. J. & Robker, R. L. Macrophage contributions to ovarian function. Hum. Reprod. Update 10, 119–133 (2004).

    Article  PubMed  Google Scholar 

  20. Bukulmez, O. & Arici, A. Leukocytes in ovarian function. Hum. Reprod. Update 6, 1–15 (2000).

    Article  CAS  PubMed  Google Scholar 

  21. Best, C. L., Pudney, J., Welch, W. R., Burger, N. & Hill, J. A. Localization and characterization of white blood cell populations within the human ovary throughout the menstrual cycle and menopause. Hum. Reprod. 11, 790–797 (1996).

    Article  CAS  PubMed  Google Scholar 

  22. Komatsu, K., Manabe, N., Kiso, M., Shimabe, M. & Miyamoto, H. Changes in localization of immune cells and cytokines in corpora lutea during luteolysis in murine ovaries. J. Exp. Zool. A Comp. Exp. Biol. 296A, 152–159 (2003).

    Article  CAS  Google Scholar 

  23. Takaya, R. et al. Macrophages in normal cycling human ovaries; immunohistochemical localization and characterization. Hum. Reprod. 12, 1508–1512 (1997).

    Article  CAS  PubMed  Google Scholar 

  24. Cui, L. L., Yang, G., Pan, J. & Zhang, C. Tumor necrosis factor α knockout increases fertility of mice. Theriogenology 75, 867–876 (2011).

    Article  CAS  PubMed  Google Scholar 

  25. Lliberos, C., Liew, S. H., Mansell, A. & Hutt, K. J. The inflammasome contributes to depletion of the ovarian reserve during aging in mice. Front. Cell Dev. Biol. 8, 628473 (2020).

    Article  PubMed  Google Scholar 

  26. Lliberos, C. et al. Evaluation of inflammation and follicle depletion during ovarian ageing in mice. Sci. Rep. 11, 278 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Yamakami, L. Y. et al. Ovarian reserve in women with primary antiphospholipid syndrome. Lupus 23, 862–867 (2014).

    Article  CAS  PubMed  Google Scholar 

  28. Mont’Alverne, A. R. et al. Reduced ovarian reserve in patients with Takayasu arteritis. J. Rheumatol. 41, 2055–2059 (2014).

    Article  PubMed  Google Scholar 

  29. Mont’Alverne, A. R. et al. Diminished ovarian reserve in Behcet’s disease patients. Clin. Rheumatol. 34, 179–183 (2015).

    Article  PubMed  Google Scholar 

  30. Lawrenz, B. et al. Impact of systemic lupus erythematosus on ovarian reserve in premenopausal women: evaluation by using anti-Müllerian hormone. Lupus 20, 1193–1197 (2011).

    Article  CAS  PubMed  Google Scholar 

  31. Cui, L. et al. Chronic pelvic inflammation diminished ovarian reserve as indicated by serum anti Müllerian hormone. PLoS ONE 11, e0156130 (2016).

  32. Winship, A. L., Stringer, J. M., Liew, S. H. & Hutt, K. J. The importance of DNA repair for maintaining oocyte quality in response to anti-cancer treatments, environmental toxins and maternal ageing. Hum. Reprod. Update 24, 119–134 (2018).

    Article  CAS  PubMed  Google Scholar 

  33. Stringer, J. M., Winship, A., Liew, S. H. & Hutt, K. The capacity of oocytes for DNA repair. Cell. Mol. Life Sci. 75, 2777–2792 (2018).

    Article  CAS  PubMed  Google Scholar 

  34. Steinert, E. M. et al. Quantifying memory CD8 T cells reveals regionalization of immunosurveillance. Cell 161, 737–749 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Kumar, B. V. et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 20, 2921–2934 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Johnson, J. et al. Expression and T cell regulatory action of the PD-1 immune checkpoint in the ovary and fallopian tube. Preprint at bioRxiv https://doi.org/10.1101/2020.06.06.138123 (2020).

  37. Hailemichael, Y. et al. Cancer vaccine formulation dictates synergy with CTLA-4 and PD-L1 checkpoint blockade therapy. J. Clin. Invest. 128, 1338–1354 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Jost, P. J. et al. XIAP discriminates between type I and type II FAS-induced apoptosis. Nature 460, 1035–1039 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Scaffidi, C. et al. Two CD95 (APO-1/Fas) signaling pathways. EMBO J. 17, 1675–1687 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Schug, Z. T., Gonzalvez, F., Houtkooper, R. H., Vaz, F. M. & Gottlieb, E. BID is cleaved by caspase-8 within a native complex on the mitochondrial membrane. Cell Death Differ. 18, 538–548 (2011).

    Article  CAS  PubMed  Google Scholar 

  41. Strasser, A., Jost, P. J. & Nagata, S. The many roles of FAS receptor signaling in the immune system. Immunity 30, 180–192 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Dhodapkar, K. M. Role of tissue-resident memory in intra-tumor heterogeneity and response to immune checkpoint blockade. Front. Immunol. 9, 1655 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Park, S. L. & Mackay, L. K. Decoding tissue-residency: programming and potential of frontline memory T cells. Cold Spring Harb. Perspect. Biol. 13, a037960 (2021).

  44. Mackay, L. K. et al. Long-lived epithelial immunity by tissue-resident memory T (TRM) cells in the absence of persisting local antigen presentation. Proc. Natl Acad. Sci. USA 109, 7037–7042 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Sasson, S. C. et al. Interferon-gamma–producing CD8+ tissue resident memory T cells are a targetable hallmark of immune checkpoint inhibitor–colitis. Gastroenterology 161, 1229–1244.e1229 (2021).

    Article  CAS  PubMed  Google Scholar 

  46. Ebrahimi, M. & Akbari Asbagh, F. The role of autoimmunity in premature ovarian failure. Iran. J. Reprod. Med. 13, 461–472 (2015).

    PubMed  PubMed Central  Google Scholar 

  47. Matsuda-Minehata, F., Inoue, N., Goto, Y. & Manabe, N. The regulation of ovarian granulosa cell death by pro- and anti-apoptotic molecules. J. Reprod. Dev. 52, 695–705 (2006).

    Article  CAS  PubMed  Google Scholar 

  48. Yamamoto, Y. et al. Tumor necrosis factor alpha inhibits ovulation and induces granulosa cell death in rat ovaries. Reprod. Med. Biol. 14, 107–115 (2015).

    Article  CAS  PubMed  Google Scholar 

  49. Sasson, R., Winder, N., Kees, S. & Amsterdam, A. Induction of apoptosis in granulosa cells by TNFα and its attenuation by glucocorticoids involve modulation of Bcl-2. Biochem. Biophys. Res. Commun. 294, 51–59 (2002).

    Article  CAS  PubMed  Google Scholar 

  50. Quirk, S. M., Porter, D. A., Huber, S. C. & Cowan, R. G. Potentiation of Fas-mediated apoptosis of murine granulosa cells by interferon-γ, tumor necrosis factor-α, and cycloheximide. Endocrinology 139, 4860–4869 (1998).

    Article  CAS  PubMed  Google Scholar 

  51. Lee, H. J. et al. Induction of Fas-mediated apoptosis by interferon-γ is dependent on granulosa cell differentiation and follicular maturation in the rat ovary. Dev. Reprod. 20, 315–329 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Morrison, L. J. & Marcinkiewicz, J. L. Tumor necrosis factor α enhances oocyte/follicle apoptosis in the neonatal rat ovary. Biol. Reprod. 66, 450–457 (2002).

    Article  CAS  PubMed  Google Scholar 

  53. Michot, J. M. et al. Immune-related adverse events with immune checkpoint blockade: a comprehensive review. Eur. J. Cancer 54, 139–148 (2016).

    Article  CAS  PubMed  Google Scholar 

  54. Letourneau, J. M. et al. Pretreatment fertility counseling and fertility preservation improve quality of life in reproductive age women with cancer. Cancer 118, 1710–1717 (2012).

    Article  PubMed  Google Scholar 

  55. Ruddy, K. J. & Partridge, A. H. The unique reproductive concerns of young women with breast cancer. Adv. Exp. Med. Biol. 732, 77–87 (2012).

    Article  PubMed  Google Scholar 

  56. Faubion, S. S., Kuhle, C. L., Shuster, L. T. & Rocca, W. A. Long-term health consequences of premature or early menopause and considerations for management. Climacteric 18, 483–491 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Mittendorf, E. A. et al. Neoadjuvant atezolizumab in combination with sequential nab-paclitaxel and anthracycline-based chemotherapy versus placebo and chemotherapy in patients with early-stage triple-negative breast cancer (IMpassion031): a randomised, double-blind, phase 3 trial. Lancet 396, 1090–1100 (2020).

    Article  CAS  PubMed  Google Scholar 

  58. Schmid, P. et al. Pembrolizumab for early triple-negative breast cancer. N. Engl. J. Med. 382, 810–821 (2020).

    Article  CAS  PubMed  Google Scholar 

  59. Stewart, T. J. & Abrams, S. I. Altered immune function during long-term host-tumor interactions can be modulated to retard autochthonous neoplastic growth. J. Immunol. 179, 2851–2859 (2007).

    Article  CAS  PubMed  Google Scholar 

  60. Kaufmann, T. et al. The BH3-only protein bid is dispensable for DNA damage- and replicative stress-induced apoptosis or cell-cycle arrest. Cell 129, 423–433 (2007).

    Article  CAS  PubMed  Google Scholar 

  61. Byers, S. L., Wiles, M. V., Dunn, S. L. & Taft, R. A. Mouse estrous cycle identification tool and images. PLoS ONE 7, e35538 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Cora, M. C., Kooistra, L. & Travlos, G. Vaginal cytology of the laboratory rat and mouse: review and criteria for the staging of the estrous cycle using stained vaginal smears. Toxicol. Pathol. 43, 776–793 (2015).

    Article  CAS  PubMed  Google Scholar 

  63. Jin, S. Y., Lei, L., Shikanov, A., Shea, L. D. & Woodruff, T. K. A novel two-step strategy for in vitro culture of early-stage ovarian follicles in the mouse. Fertil. Steril. 93, 2633–2639 (2010).

    Article  PubMed  Google Scholar 

  64. Winship, A. L., Sarma, U. C., Alesi, L. R. & Hutt, K. J. Accurate follicle enumeration in adult mouse ovaries. J. Vis. Exp. https://doi.org/10.3791/61782 (2020).

  65. Sarma, U. C., Winship, A. L. & Hutt, K. J. Comparison of methods for quantifying primordial follicles in the mouse ovary. J. Ovarian Res. 13, 121 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Molania, R., Gagnon-Bartsch, J. A., Dobrovic, A. & Speed, T. P. A new normalization for Nanostring nCounter gene expression data. Nucleic Acids Res. 47, 6073–6083 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors acknowledge the technical support of the Monash Animal Research Platform, Monash Histology Platform, Monash FlowCore Platform, Monash Micro Imaging Facility, Peter MacCallum Cancer Centre Animal Research Platform and Peter MacCallum Cancer Centres Flow Facility. We thank P. Bouillet and WEHI Bioservices for the provision of large numbers of BID-deficient mice. We also thank H. Thorne, E. Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, the National Breast Cancer Foundation of Australia (NBCF), Cancer Australia and the National Institutes of Health (USA) for their contributions to this resource, and the many families who contribute to kConFab. Fig. 6h and the Supplementary Fig. 1 were created using BioRender.com. This work was made possible through Victorian State Government Operational Infrastructure Support and the Australian Government National Health and Medical Research Council (NHMRC) IRIISS. This work was supported by NBCF funding grant no. IIRS-22-092. A.L.W. is supported by DECRA funding grant no. DE21010037 from the Australian Research Council (ARC). L.R.A. is supported by an Australian Government Research Training Program Scholarship and a Monash Graduate Excellence Scholarship. K.-A.P. is an NHMRC Leadership Fellow. S.L. is supported by the NBCF. A.S. is supported by an NHMRC Program Grant no. 1113133, NHMRC Fellowship no. 1116937 and NHMRC Investigator Grant no. 2007887. K.J.H. is supported by an ARC Future Fellowship grant no. FT190100265.

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Author notes

  1. These authors contributed equally: Amy L. Winship, Lauren R. Alesi, Sneha Sant, Sherene Loi, Karla J. Hutt.

Authors and Affiliations

  1. Development and Stem Cell Program and Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

    Amy L. Winship, Lauren R. Alesi, Jessica M. Stringer, Aldana Cantavenera, Teharn Hegarty, Carolina Lliberos Requesens, Seng H. Liew, Urooza Sarma, Meaghan J. Griffiths, Nadeen Zerafa & Karla J. Hutt

  2. Division of Research, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Victoria, Australia

    Sneha Sant, Stephen B. Fox, Emmaline Brown, Franco Caramia & Sherene Loi

  3. Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia

    Sneha Sant, Stephen B. Fox, Emmaline Brown, Kelly-Anne Phillips & Sherene Loi

  4. Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

    Pirooz Zareie & Nicole L. La Gruta

  5. The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia

    Andreas Strasser

  6. Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia

    Andreas Strasser

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Contributions

A.L.W. and K.J.H. conceived and designed the study. A.L.W., L.R.A., S.S., A.C., J.M.S., C.L.R., S.H.L., P.Z., E.B., S.B.F., U.S., M.J.G., T.H. and N.Z. performed experiments. L.R.A., A.L.W., A.C., P.Z., K.J.H., S.S., S.L., K.-A.P. and F.C. analyzed and interpreted the data. S.S., P.Z., S.L., N.L.G. and A.S. contributed materials and reagents. A.L.W., L.R.A. and K.J.H. wrote the manuscript. All authors edited the manuscript.

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Correspondence to Sherene Loi or Karla J. Hutt.

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Extended data

Extended Data Fig. 1 Flow cytometry gating strategy for tumor-bearing mice.

Gating strategy used to identify ovarian immune cell populations of tumor-bearing mice 4 d after the following final immunotherapy treatment.

Extended Data Fig. 2 Immune checkpoint molecules are expressed in both mouse and human ovary.

CD69 and PD-1 expression in the ovary of healthy WT non-tumor bearing mice was assessed by flow cytometry. (A) The proportions of ovarian CD69+CD4+ and CD69+CD8+ of total effector memory T cells and (B) PD-1+CD4+ and PD-1+CD8+ T cells were quantified in healthy, tumor-free WT mice (n = 3 animals/group). Data are presented as mean ± s.e.m. (C) Log2 expression of PDCD1, CD8A, CD3D, CD274 and CTLA4 in normal human ovary epithelia from n = 12 women and ovarian cancer epithelia from n = 18 women. Data are presented as mean (centre) ± s.e.m. (bounds) of box plots and minima and maxima of whiskers; two-tailed unpaired t-test. (D) Representative immunohistochemical localisation of (i) CD4+ T cells, (ii) CD8+ T cells, (iii) PD-1 and (iv) PD-L1 in human ovarian cortex from n = 4 healthy pre-menopausal women. Arrows indicate ovarian follicles, bars=50 μm.

Source data

Extended Data Fig. 3 Ovarian and splenic immune cell numbers in tumor-free mice, 21 days post-final treatment, and flow cytometry gating strategy.

Numbers of ovarian (A) CD4+ T cells, (B) CD8+ T cells and (C) macrophages; and splenic immune cells, including (D) CD4+ T cells, (E) CD8+ T cells and (F) macrophages were analysed by flow cytometry in mice 21 d after the final indicated treatment. Data are presented as mean ± s.e.m.; n = 5 animals/group. (G) Gating strategy used to identify mouse ovarian and splenic immune cell populations 24 h or 21 d following immunotherapy treatment.

Source data

Extended Data Fig. 4 Estrous cycling is disrupted in immune checkpoint inhibitor-treated tumor-free mice.

Estrous cycling was monitored by vaginal cytology for a 14-day period following the final indicated treatment in the 21 d cohort of animals administered with 10 mg/kg anti-PD-L1, anti-CTLA-4 or control antibody (IgG). Plots depict the estrous cycles of each individual animal. Vertical axes represent the phase of estrous cycle (P, proestrus; E, estrus; M, metestrus; D, diestrus). Red highlights disrupted phases of the cycle in some anti-PD-L1 or anti-CTLA4 animals; n = 5 animals/group.

Source data

Extended Data Fig. 5 Ovarian follicles and ovulation are disrupted even with lower-dose immune checkpoint inhibitor treatment.

Adult female C57BL6/J mice received 5 mg/kg anti-PD-L1, anti-CTLA-4 or control antibody (IgG) on d 1, 4 and 7. Ovaries were collected either 24 h or 14 d later (n = 6/group). At both time points, total numbers of (A) primordial, transitional and primary follicles; Kruskal-Wallis test: *p = 0.0453; one-way ANOVA: ***p = 0.0008, (B) secondary and antral follicles, **p = 0.001, ****p < 0.0001, **p = 0.0017, *p = 0.0204, *p = 0.0429 and (C) corpora lutea were quantified; one-way ANOVA: *p = 0.0454; Kruskal-Wallis test: *p = 0.0353. All data are presented as mean ± s.e.m.

Source data

Extended Data Fig. 6 Primordial follicles remain significantly depleted 100 days post-treatment, even after local ovarian cytokine production has returned to control levels.

Adult female C57BL6/J mice received 10 mg/kg anti-PD-L1, anti-CTLA-4 or control antibody (IgG) on d 1, 4 and 7. Ovaries were collected 100 d later (n = 6 animals/group). Total numbers of (A) primordial follicles were quantified. (B) Cytokine mRNA levels in the ovary 100 d after the final indicated treatment were analysed by RT-qPCR (IgG n = 5, anti-PD-L1 n = 4, anti-CTLA-4 n = 6 animals). Data are presented as mean ± s.e.m.; one-way ANOVA; **p = 0.0039, ***p = 0.0003.

Source data

Extended Data Fig. 7 Ovarian and splenic immune cell numbers in tumor-free mice, 24 hours post-final treatment.

Numbers of ovarian (A) CD4+ T cells, (B) CD8+ T cells and (C) macrophages; and splenic immune cells, including (D) CD4+ T cells, (E) CD8+ T cells and (F) macrophages were analysed by flow cytometry in mice 24 h after the final indicated treatment. Data are presented as mean ± s.e.m.; one-way ANOVA; *p < 0.05; n = 5 animals/group.

Source data

Extended Data Fig. 8 Estrous cycling is not disrupted following immune checkpoint blockade in Bid-/- mice.

(A) Estrous cycling was monitored by vaginal cytology for a 15-day period following the final indicated treatment in the 21-day cohort of Bid-/- animals that had been administered with 10 mg/kg anti-PD-L1 (n = 4) or control antibody (n = 5). Plots depict the estrous cycles of each individual animal. Vertical axes represent the phase of estrous cycle (P, proestrus; E, estrus; M, metestrus; D, diestrus). (B) Compilation of primordial follicle numbers from wild-type and genetic knockout mouse models.

Source data

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Winship, A.L., Alesi, L.R., Sant, S. et al. Checkpoint inhibitor immunotherapy diminishes oocyte number and quality in mice. Nat Cancer 3, 1–13 (2022). https://doi.org/10.1038/s43018-022-00413-x

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  • Issue Date:

  • DOI: https://doi.org/10.1038/s43018-022-00413-x

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