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Common germline variants of the human APOE gene modulate melanoma progression and survival

Abstract

Common germline variants of the APOE gene are major risk modifiers of neurodegenerative and atherosclerotic diseases1,2,3, but their effect on cancer outcome is poorly defined. Here we report that, in a reversal of their effect on Alzheimer’s disease, the APOE4 and APOE2 variants confer favorable and poor outcomes in melanoma, respectively. Mice expressing the human APOE4 allele exhibited reduced melanoma progression and metastasis relative to APOE2 mice. APOE4 mice exhibited enhanced anti-tumor immune activation relative to APOE2 mice, and T cell depletion experiments showed that the effect of APOE genotype on melanoma progression was mediated by altered anti-tumor immunity. Consistently, patients with melanoma carrying the APOE4 variant experienced improved survival in comparison to carriers of APOE2. Notably, APOE4 mice also showed improved outcomes under PD1 immune checkpoint blockade relative to APOE2 mice, and patients carrying APOE4 experienced improved anti-PD1 immunotherapy survival after progression on frontline regimens. Finally, enhancing APOE expression via pharmacologic activation of liver X receptors, previously shown to boost anti-tumor immunity4, exhibited therapeutic efficacy in APOE4 mice but not in APOE2 mice. These findings demonstrate that pre-existing hereditary genetics can impact progression and survival outcomes of a future malignancy and warrant prospective investigation of APOE genotype as a biomarker for melanoma outcome and therapeutic response.

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Fig. 1: Human APOE variants modulate progression of murine melanoma.
Fig. 2: Human APOE variants modulate the tumor immune microenvironment.
Fig. 3: APOE germline variants predict survival in human melanoma.
Fig. 4: APOE genotype modulates melanoma progression in the context of immunotherapy.

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Data availability

All data analyzed from published studies are referenced and publicly available under the following accession numbers: TCGA-SKCM, dbGaP accession phs000178.v10.p8; MDACC GWAS study, phs000187.v1.p1; Roh et al. anti-PD1 treatment study, dbGaP BioProject ID PRJNA369259; and Riaz et al. anti-PD1 treatment study, dbGaP BioProject ID PRJNA359359. scRNA-seq data have been deposited at the Gene Expression Omnibus under accession number GSE146613. All other data are available from the corresponding author upon reasonable request.

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Acknowledgements

We thank members of our laboratory and M. Tavazoie for comments on previous versions of the manuscript. We are grateful for assistance by Rockefeller University resource centers: S. Mazel and staff of the flow cytometry resource center, V. Francis and other veterinary staff of the Comparative Bioscience Center for animal husbandry and care, C. Zhao and staff at the genomics resource center for assistance with scRNA-seq and A. North and staff at the Bio-Imaging Resource Center. We express gratitude to M. Bosenberg (Yale University) for kindly providing the YUMM1.7 and YUMMER1.7 cell lines. We thank the groups of P. Sullivan and N. Maeda for generating the human APOE targeted-replacement mice and making them available through Taconic Biosciences. We are grateful to E. McMillan for early help with whole-exome sequencing analysis. We also thank M. Szarek and H. Mostafavi for statistical advice. This work was supported by National Institutes of Health grant RO1CA184804-01A2 (to S.F.T.). B.N.O. was supported by a Deutsche Forschungsgemeinschaft postdoctoral fellowship (OS 498/1-1). J.B. and K.N.T. were supported by scholarships from the German National Academic Foundation. N.A. was supported by Medical Scientist Training Program grant T32GM007739 from the National Institutes of Health. B.T. was supported by the Lucy Lee Chiles Fellowship from the Hope Funds for Cancer Research. R.D.V. was supported in part by grant UL1 TR001866 from the National Center for Advancing Translational Sciences, National Institutes of Health Clinical and Translational Science Award program. S.F.T. was supported by a Faculty Scholars grant from the Howard Hughes Medical Institute, the Black Family Metastasis Center at Rockefeller University and by the Reem-Kayden award.

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Contributions

B.N.O. and S.F.T. conceived the study, supervised all research and wrote the manuscript. B.N.O., J.B., N.A., K.N.T. and B.T. conducted experiments. B.N.O. analyzed whole-exome sequencing, scRNA-seq and clinical data. R.D.V. provided advice for statistical analysis.

Corresponding author

Correspondence to Sohail F. Tavazoie.

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Competing interests

S.F.T. and B.N.O. are inventors on a US provisional patent application encompassing aspects of this work. S.F.T. is a cofounder, shareholder and member of the scientific advisory board of Rgenix.

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Peer review information Javier Carmona was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Human APOE variants modulate metastatic progression of murine melanoma.

a, Relative expression of murine Apoe determined by qRT-PCR in B16F10 cells expressing shCtrl and shApoe hairpins and in YUMM1.7 cells (n = 3 cell culture replicates per group, graph represents mean values ± s.e.m.). b, Bioluminescence imaging of metastatic progression of murine melanoma B16F10-TR-shApoe cells intravenously injected into APOE knock-in mice (n = 10 mice per group; one-tailed Mann-Whitney test; graph represents mean values ± s.e.m.; representative of two independent experiments). Images correspond to representative mice on day 24 after injection.

Extended Data Fig. 2 Immunoprofiling of the tumor microenvironment in APOE2 versus APOE4 mice.

a-b, Representative flow cytometry plots from two independent experiments demonstrating the gating strategy to identify major myeloid (a) and lymphoid (b) cell subsets in the tumor microenvironment. c-d, Proportion of monocytic Ly6C + (c) and dendritic cell (d) subsets in the immune microenvironment of YUMM1.7 tumors in APOE2 and APOE4 mice (n = 8 and 9 mice for APOE2 and APOE4, respectively; representative of two independent experiments). e, Intratumoral CD8 + T cell infiltration in YUMM1.7 tumors from APOE2 and APOE4 mice (n = 7 and 9 mice for APOE2 and APOE4 groups, respectively). Images show representative sections (scale bar = 100 µm). All P values are based on two-tailed t-tests. Box plots show median, first and third quartiles, and whiskers represent minimum and maximum values.

Extended Data Fig. 3 Extended single cell RNA-sequencing data.

a, Uniform manifold approximation and projection (UMAP) plots illustrating the distribution of the expression of manually curated, lineage-defining genes. b, Paired quantile-quantile plots for the expression of Ifng and Gzmb in CD45 + cells infiltrating tumors in APOE2 and APOE4 mice (P values according to two-sided Wilcoxon rank-sum test). c, Uniform manifold approximation and projection (UMAP) plots illustrating the distribution of Ifng and Gzmb expression across immune cell clusters. d, Violin plots showing the distribution of Ifng and Gzmb expression across T and NK cell subsets from (b-c) (P values according to two-sided Wilcoxon rank-sum test adjusted for total number of clusters by FDR; plots extend from minimum to maximum values). A total of 10,050 cells were sequenced (n = 4,665 and 5,385 cells for APOE2 and APOE4 groups, respectively). Cells were harvested from n = 6 biologically averaged mice for each group.

Extended Data Fig. 4 Efficiency of in-vivo T cell depletion.

Representative flow cytometry plots of two independent experiments of samples from spleens, lymph nodes, and tumors of mice treated with PBS versus anti-CD4 and anti-CD8 antibodies.

Extended Data Fig. 5 APOE variants differentially impact cancer cell invasion and endothelial recruitment.

a, Matrigel invasion by 1 × 105 mouse melanoma B16F10-TR-shApoe cells treated with the indicated recombinant proteins (n = 4 biologically independent samples; one tailed t-test). b, Trans-well recruitment of 1 × 105 human umbilical vein endothelial cells treated with the indicated recombinant proteins by 5 × 104 human melanoma MeWo-LM2 cells (n = 4 biologically independent samples; one tailed t-tests). Data in (a-b) are representative of three independent experiments. c, Blood vessel density in YUMM1.7 tumors from APOE2 and APOE4 mice (n = 8 and 9 mice for APOE2 and APOE4 groups, respectively; two-tailed Mann-Whitney test; box plots show median, first and third quartiles, and whiskers represent minimum and maximum values.). Images show representative sections (scale bar = 100 µm).

Extended Data Fig. 6 Distribution of APOE genotype in the TCGA-SKCM study.

a-b, Proportion of APOE2 and APOE4 carrier status (a) and bi-allelic genotype (b) in the Atherosclerosis Risk in Communities study (ARIC) and in patients with stage II/III melanoma in the TCGA-SKCM study (P = 0.0017 and 0.0066, respectively; χ2 test).

Extended Data Fig. 7 Clinical characteristics of stage II/III patients in the TCGA-SKCM study.

a, Sex proportions were not significantly different between APOE carrier groups (P = 0.46, χ2 test). b, Age at diagnosis was not significantly different between APOE carrier groups (P = 0.45, Kruskal-Wallis rank sum test). c, Tumor stage at diagnosis was not significantly different between APOE carrier groups (P = 0.4, χ2 test). d, Melanoma Clark level at diagnosis was not significantly different between APOE carrier groups (P = 0.95, χ2 test). e, Breslow depth was not significantly different between APOE carrier groups at diagnosis (P = 0.24, Kruskal-Wallis rank sum test). f, APOE carrier status was not significantly associated with common tumor mutations (P = 0.93, χ2 test). g, APOE carrier status was not significantly associated with transcriptomic cluster (P = 0.55, χ2 test). h, Univariate analysis of the impact of clinical and molecular characteristics on survival of stage II/III melanoma patients (P values according to univariate Cox proportional hazards model). i, Multivariable analysis of the impact of clinical and molecular characteristics with significant impact in univariate analysis on survival of stage II/III melanoma patients (P values according to multivariable Cox proportional hazards model). For (h-i), the number of patients with available information for a given characteristic is indicated in column “n”, and plots represent hazard ratios with 95% confidence intervals. Hinges of boxplots represent the first and third quartiles, whiskers extend to the smallest and largest value within 1.5 × interquartile ranges of the hinges, and points represent outliers.

Extended Data Fig. 8 APOE genotype in normal tissue versus tumor samples of stage II/III patients in the TCGA-SKCM study.

a, Proportion of APOE2 and APOE4 carrier status in normal tissue and tumor samples of patients with stage II/III melanoma in the TCGA-SKCM study (P = 0.8899; χ2 test). b, Chord diagram of APOE carrier status as identified in paired normal and tumor tissue samples of stage II/III melanoma patients in the TCGA-SKCM study.

Extended Data Fig. 9 Characteristics of the MDACC GWAS study and comparison to TCGA-SKCM.

a-b, Distribution of APOE carrier status in the Atherosclerosis Risk in Communities study (ARIC) and the MDACC melanoma study before (a) and after (b) imputation of APOE genotype (P < 2.2 × 10−16 and P = 1.82 × 10−11, respectively; χ2 test). c-g, Survival of melanoma patients in the MDACC study stratified by local melanoma stage and APOE genotype (two-sided log-rank tests). h, Survival of stage II/III melanoma patients in the MDACC and TCGA-SKCM studies (two-sided log-rank test). i-k, Distribution of age (i), melanoma Clark level (j), and sex (k) in stage II/III patients of the MDACC and TCGA-SKCM melanoma studies (respective significance tests: P = 6.42 × 10−9, Kruskal-Wallis rank sum test; P = 0.0005, χ2 test; P = 0.052, χ2 test). Hinges of boxplots represent the first and third quartiles, whiskers extend to the smallest and largest value within 1.5 × interquartile ranges of the hinges, and points represent outliers.

Extended Data Fig. 10 Association of APOE genotype with outcome in upfront anti-PD1 immunotherapy-treated melanoma patients.

Survival of melanoma patients treated with anti-PD1 therapy with no prior checkpoint therapy from the Riaz et al. study (P value according to two-sided log-rank test).

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Ostendorf, B.N., Bilanovic, J., Adaku, N. et al. Common germline variants of the human APOE gene modulate melanoma progression and survival. Nat Med 26, 1048–1053 (2020). https://doi.org/10.1038/s41591-020-0879-3

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