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Senescence-induced immune remodeling facilitates metastatic adrenal cancer in a sex-dimorphic manner

Nature Aging volume 3, pages 846–865 (2023)Cite this article

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Abstract

Aging markedly increases cancer risk, yet our mechanistic understanding of how aging influences cancer initiation is limited. Here we demonstrate that the loss of ZNRF3, an inhibitor of Wnt signaling that is frequently mutated in adrenocortical carcinoma, leads to the induction of cellular senescence that remodels the tissue microenvironment and ultimately permits metastatic adrenal cancer in old animals. The effects are sexually dimorphic, with males exhibiting earlier senescence activation and a greater innate immune response, driven in part by androgens, resulting in high myeloid cell accumulation and lower incidence of malignancy. Conversely, females present a dampened immune response and increased susceptibility to metastatic cancer. Senescence-recruited myeloid cells become depleted as tumors progress, which is recapitulated in patients in whom a low myeloid signature is associated with worse outcomes. Our study uncovers a role for myeloid cells in restraining adrenal cancer with substantial prognostic value and provides a model for interrogating pleiotropic effects of cellular senescence in cancer.

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Fig. 1: Following an initial phase of significant hyperplasia, ZNRF3-deficient adrenal glands regress over time.
Fig. 2: The switch from hyperplasia to regression is marked by activation of cellular senescence.
Fig. 3: Senescent Znrf3-cKO adrenal glands develop a functional SASP.
Fig. 4: scRNA-seq reveals activation of innate and adaptive immune systems in response to cellular senescence and the SASP.
Fig. 5: Senescence-mediated immune activation in male Znrf3-cKO mice is characterized by higher SASP induction.
Fig. 6: Androgen deprivation restricts immune infiltration in male adrenals.
Fig. 7: Following senescence-mediated remodeling of the tissue microenvironment, metastatic ACC tumors arise in a sex-dimorphic manner.
Fig. 8: A low myeloid response is associated with worse patient outcome in ACC.

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Data availability

All sequencing datasets have been deposited to the NCBI Gene Omnibus Database (accession code GSE201127 (GSE201125, bulk RNA-seq; GSE201126, scRNA-seq). Patient data analyzed from TCGA-ACC are publicly available using https://www.cbioportal.org/study/summary?id=acc_tcga_pan_can_atlas_2018. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.

Code availability

Code used for bulk RNA-seq and scRNA-seq analyses is freely available at https://github.com/HuntsmanCancerInstitute. Additional scRNA-seq packages used for analysis are available at https://github.com/atakanekiz/CIPR-Package.

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Acknowledgements

We thank H. Clevers and B.-K. Koo for providing Znrf3-floxed mice and the late K. Parker for providing SF1Cre transgenic mice. Research reported in this publication used the High-Throughput Genomics and Bioinformatic Analysis Shared Resource and the Biorepository and Molecular Pathology Shared Resource at the Huntsman Cancer Institute at the University of Utah and was supported by the National Cancer Institute of the National Institutes of Health under award P30CA042014. We also used the University of Utah Flow Cytometry Shared Resource supported by the Office of the Director of the NIH (award S10OD026959 and NCI award 5P30CA042014-24) and the Cell Imaging Core at the University of Utah. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We especially thank J. Marvin, O. Allen and M. Bridge for respective technical assistance with flow cytometry, 10x Genomics library preparation and confocal imaging. We also thank J. Gertz, B. Myers and S. Holmen for helpful scientific discussions and comments on the manuscript. This work was supported by funding from a Cancer Center Support Grant (P30CA040214, K.J.B.), the V Foundation (V2021-021, K.J.B.) and 5 For The Fight (K.J.B.).

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Authors and Affiliations

  1. Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA

    Kate M. Warde, Lorenzo J. Smith, Lihua Liu, Parker W. Willett, Guadalupe Castaneda-Hernandez, Sikiru O. Imodoye, Chenge Zhang, Kara D. Jones & Kaitlin J. Basham

  2. Bioinformatics Shared Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA

    Chris J. Stubben & Brian K. Lohman

  3. Department of Internal Medicine, Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, MI, USA

    Julia L. Ammer, Thomas J. Giordano & Gary D. Hammer

  4. Frankel Cardiovascular Center Physiology and Phenotyping Core, University of Michigan, Ann Arbor, MI, USA

    Kimber Converso-Baran

  5. Department of Molecular Biology and Genetics, Izmir Institute of Technology, Urla Izmir, Turkey

    H. Atakan Ekiz

  6. Department of Pathology, University of Utah, Salt Lake City, UT, USA

    Marc Barry

  7. Department of Pathology, University of Colorado School of Medicine at Colorado Anschutz Medical Campus, Aurora, CO, USA

    Michael R. Clay

  8. Division of Endocrinology, Metabolism and Diabetes, Department of Medicine, University of Colorado School of Medicine at Colorado Anschutz Medical Campus, Aurora, CO, USA

    Katja Kiseljak-Vassiliades

  9. Department of Pathology, University of Michigan, Ann Arbor, MI, USA

    Thomas J. Giordano

  10. Endocrine Oncology Program, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA

    Thomas J. Giordano & Gary D. Hammer

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Contributions

Conceptualization, K.M.W., G.D.H., K.J.B.; experimentation, K.M.W., L.J.S., L.L., P.W.W., J.L.A., G.C.-H., S.O.I., C.Z., K.D.J., K.C.-B., K.J.B.; methodology, L.J.S.; data analysis, K.M.W., L.J.S., J.L.A., G.C.-H., S.O.I., K.C.-B., K.J.B.; bioinformatic analysis, K.M.W., C.J.S., B.K.L., H.A.E.; data curation, K.M.W., C.J.S., K.K.-V., K.J.B.; resources (patient tissue), M.B., M.R.C., K.K.-V.; pathologic review, M.B., M.R.C., T.J.G.; funding acquisition, G.D.H., K.J.B.; project administration, K.J.B.; data visualization, K.M.W., K.J.B.; writing (original draft), K.M.W., K.J.B.; writing (review and editing), all authors.

Corresponding author

Correspondence to Kaitlin J. Basham.

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The authors declare no competing interests.

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Nature Aging thanks Curtis Henry and Ashani Weeraratna for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Ultrasound imaging provides an accurate measure of adrenal size in real-time.

(a) Images of adrenal ultrasound area, ultrasound volume, and gross histology from representative animals with adrenals of varying size. Scale bars, 1 mm. (b) Adrenal area and (c) adrenal volume are significantly correlated with adrenal weight. Ultrasound imaging was performed 24-hours prior to necropsy. All data shown is from female mice. Each dot represents an individual animal. Statistical analysis was performed using simple linear regression.

Extended Data Fig. 2 Znrf3 cKO adrenals activate cellular senescence during adrenal regression.

(a, b) Apoptotic cell death as measured by cleaved caspase 3 (CC3) is not significantly increased in female or male Znrf3 cKO adrenals compared to controls during the initial phase of tissue regression. Quantification of CC3-positive cells was performed using QuPath digital image analysis based on the number of positive cells and normalized to total adrenal cortex nuclei. Arrows indicate CC3-positive cells. Dashed line indicates histological boundary between adrenal cortex and medulla. Scale bars, 100 μm. (c) DNA damage as measured by 53BP1 foci is significantly increased in male Znrf3 cKO adrenals compared to controls at 4- and 6-weeks of age. Quantification of 53BP1 foci was performed using QuPath digital image analysis based on the number of positive foci and normalized to total nuclei. Asterisks indicate 53BP1-positive foci. Scale bars, 10 μm. (d) p21, (e) p16INK4a, and (f) senescence-associated beta-galactosidase (SA-β-gal) are significantly increased in 9-week male Znrf3 cKO adrenals compared to controls. Scale bars, 100 μm. Quantification of p21 and p16INK4a IHC was performed using QuPath digital image analysis based on the number of positive cells per high powered field (HPF). Representative SA-β-gal images obtained from analysis of 3 independent mice is shown. Each dot represents an individual animal. Error bars represent mean ± s.e.m. Statistical analysis was performed using two-way ANOVA followed by Tukey’s multiple comparison’s test.

Extended Data Fig. 3 Senescent female Znrf3 cKO adrenal glands activate production of cytokines and growth factors.

(a) URA using RNA-seq data predicts significantly activated and inhibited cytokines in 9-week and (b) 12-week female Znrf3 cKO adrenal tissue compared to 6-week, p < 0.05. (c) URA predicts significantly activated and inhibited growth factors in 9-week and (d) 12-week female Znrf3 cKO adrenal tissue compared to 6-week, p < 0.05. Data is representative of 4 biological replicates per group, statistical analysis in IPA was performed using a right-tailed fishers exact test, p < 0.05.

Extended Data Fig. 4 Sex- and stage-specific differences in gene expression in control and Znrf3 cKO adrenals.

Bulk RNA-seq analysis reveals the top DEGs based on (a-c) sex or (d-f) phenotypic stage in control and Znrf3 cKO adrenals. Heatmaps of the top 50 DEGs are shown, statistical analysis was perform using the Wald test, p adj <0.05. Known sex-linked genes were excluded from the analysis.

Extended Data Fig. 5 Inflammation and cytokine production in male senescent Znrf3 cKO adrenal glands is further enhanced at 9-weeks.

(a) IPA identifies the most significantly altered canonical pathways in 12- vs 6-week female Znrf3 cKO adrenals. Similar pathways are altered earlier in male Znrf3 cKOs, consistent with the more accelerated phenotype in males. (b) IPA identified the top activated and inhibited cytokines in 9- vs 4-week male Znrf3 cKO adrenals, p < 0.05. (c) GSEA for inflammatory signatures (IL6/JAK/STAT3 signaling, chemokine signaling, the inflammatory response, and the innate immune system) identifies positively enriched genes in 9- vs 4-week male Znrf3 cKO mice. Data is representative of 4 biological replicates per group and, statistical analysis in IPA was performed using a right-tailed fishers exact test, p < 0.05.

Extended Data Fig. 6 Androgen deprivation restricts immune infiltration in early and late models of castration in male adrenals.

Markers of (a) neutrophils (Ly6g) and (b) T cells (CD3e) are reduced in castrated male Znrf3 cKO mice compared to sham controls. Scale bars 20μM. Castration was performed at 4-weeks of age and analysis was performed at 9-weeks of age. To further tease apart a role for androgens in the early (cell cycle arrest) versus late (immune) senescent response, (c) male Znrf3 cKO mice were castrated at 6-weeks of age when hyperproliferation has normally already been suppressed. (d-e) At 12-weeks of age, adrenal glands from castrated mice were significantly larger than sham-operated controls. (d) Representative gross histology images. Scale bars 1 mm. (e) Normalized adrenal weight. Relative fold change is indicated below each group. (f) Senescence markers (Ki67, p16, and p21) and (g) myeloid immune markers (CD68, CD11c, CD11b, and F4/80) in adrenals from sham versus castrated animals. Representative images are shown for each group. Scale bars 20 μM. Quantification was performed using QuPath digital image analysis based on the number of positive cells normalized to total nuclei. Each dot represents an individual animal. Box and whisker plots indicate the median (line) within the upper (75%) and lower (25%) quartiles, and whiskers represent the range. Statistical analysis was performed using two-tailed Student’s t-test.

Extended Data Fig. 7 Immune cell recruitment in the adrenal gland is sex- and age-dependent.

(a, b) Histological evaluation of female control and Znrf3 cKO adrenal tissue based on H&E. Female Znrf3 cKOs continue to accumulate histiocytes with advanced aging at 44- and 52-weeks of age. (c-d) Male Znrf3 cKOs sustain high levels of histiocytes previously observed as early as 24-weeks of age. Quantification was performed using QuPath digital analysis based on the proportion of histiocyte area normalized to total adrenal cortex area. Scale bars, 100 µm. Data from 4- to 24-weeks of age was previously shown in Fig. 3f-i, and is included as reference. (e-f) In situ validation of myeloid cell accumulation based on IHC for CD68 in control and Znrf3 cKO adrenal tissue from female and (g-h) male cohorts at 44- and 52-weeks of age. Data from 4- to 24-weeks of age was previously shown in Fig. 4e-h, and is included as reference. Quantification was performed using QuPath digital analysis based on the number of positive cells normalized to total nuclei. Each dot represents an individual animal. Box and whisker plots indicate the median (line) within the upper (75%) and lower (25%) quartiles, and whiskers represent the range. Statistical analysis was performed on log2 transformed data using two-way ANOVA followed by Tukey’s multiple comparison’s test. Scale bars, 100 µm. (i) At 78-weeks of age, atrophic Znrf3 cKO adrenal glands have a significantly lower Ki67-index and higher CD68-index compared to age-matched controls. (j) In 78-week-old benign Znrf3 cKO adrenals, nodules have a significantly higher Ki67-index and lower CD68-index compared to the background gland. Each dot represents an individual animal. Box and whisker plots represent mean with variance across quartiles. Statistical analysis was performed using two-tailed Student’s t-test.

Extended Data Fig. 8 A low myeloid response score (MRS) is associated with worse patient outcome in female ACC.

(a) Low adrenal myeloid response score (AMRS) is associated with shorter progression-free survival in female TCGA-ACC patients. Statistical analysis was performed using Log-rank Mantel-Cox test.

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Supplementary Tables 1–5 and Figures 1–4.

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Supplementary Data 3

Experimental sample sizes for all animal studies.

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Warde, K.M., Smith, L.J., Liu, L. et al. Senescence-induced immune remodeling facilitates metastatic adrenal cancer in a sex-dimorphic manner. Nat Aging 3, 846–865 (2023). https://doi.org/10.1038/s43587-023-00420-2

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