Separate and combined effects of advanced age and obesity on mammary adipose inflammation, immunosuppression and tumor progression in mouse models of triple negative breast cancer

Abstract

Introduction: Advanced age and obesity are independent risk and progression factors for triple negative breast cancer (TNBC), which presents significant public health concerns for the aging population and its increasing burden of obesity. Due to parallels between advanced age- and obesityrelated biology, particularly adipose inflammation, we hypothesized that advanced age and obesity each accelerate mammary tumor growth through convergent, and likely interactive, mechanisms.

Methods: To test this hypothesis, we orthotopically transplanted murine syngeneic TNBC cells into the mammary glands of young normoweight control (7 months), young diet-induced obese (DIO), aged normoweight control (17 months), and aged DIO female C57BL/6J mice.

Results: Here we report accelerated tumor growth in aged control and young DIO mice, compared with young controls. Transcriptional analyses revealed, with a few exceptions, overlapping patterns of mammary tumor inflammation and tumor immunosuppression in aged control mice and young DIO mice, relative to young controls. Moreover, aged control and young DIO tumors, compared with young controls, had reduced abundance ofcytotoxic CD8 T cells. Finally, DIO in advanced age exacerbated mammary tumor growth, inflammation and tumor immunosuppression.

Discussion: These findings demonstrate commonalities in the mechanisms driving TNBC in aged and obese mice, relative to young normoweight controls. Moreover, we found that advanced age and DIO interact to accelerate mammary tumor progression. Given the US population is getting older and more obese, age- and obesity-related biological differences will need to be considered when developing mechanism-based strategies for preventing or controlling breast cancer.

Keywords: advanced age; breast cancer; inflammation; obesity; tumor immunosuppression.

Figure 1

Advanced age and DIO increase mammary tumor growth in a metM-Wnt^lung cell transplant model of TNBC. (A) Body weight, (B) percent body fat mass and (C) percent lean mass measured prior to tumor engraftment. (D) In vivo tumor volume. (E) Ex vivo primary tumor mass. (F) Percentage of cells stained positive for Ki67 via immunohistochemistry, analyzed using QuPath. Data presented as mean ± SD. Differences across all groups analyzed using one-way ANOVA and Tukey post hoc test. Asterisks indicate differences in significance: *p < 0.05, **p < 0.01, ***p < 0.001. ns, non-significant.

Figure 2

Advanced age and DIO induce convergent inflammatory alterations within the tumor-adjacent mammary adipose in a metM-Wnt^lung cell transplant model of TNBC. (A) Hallmark gene sets commonly enriched in tumor-adjacent mammary fat pad (TA-MFP) of aged control versus young control and young DIO vs young control mice determined following gene set enrichment analysis (GSEA). (B) Leading edge analysis (LEA) of immune-related Hallmark gene sets commonly enriched. (C) Frequency of genes occurring in the leading edge of commonly enriched, immune-related Hallmark gene sets versus gene rank. (D) C7 Immunologic gene sets commonly enriched in TA-MFP of aged control vs young control and young DIO vs young control micedetermined following GSEA. (E) LEA of all C7 gene sets commonly enriched. (F) Frequency of genes occurring in the leading edge of commonly enriched C7 gene sets versus gene rank. (G) Heat map of select leading edge genes. Significantly enriched gene sets defined as FDR q-value <0.05. Significance in overlap of leading edge genes analyzed using hypergeometric test. Correlation between the gene rank of leading edge contributors calculated by the Spearman test. Asterisks denote significance: **< 0.01, ***< 0.001.

Figure 3

Advanced age and DIO promote immunosuppression within the tumor microenvironment and decreased CD8 T cell surveillance. (A) Hallmark gene sets commonly underrepresented in mammary tumors of aged control versus young control and young DIO versus young control mice determined following gene set enrichment analysis (GSEA). (B) Leading edge analysis (LEA) of immune-related Hallmark gene sets commonly underrepresented. (C) Frequency of genes occurring in the leading edge of commonly underrepresented, immune-related Hallmark gene sets versus gene rank. (D) C7 Immunologic gene sets commonly underrepresented in mammary tumor of aged control versus young control and young DIO versus young control mice determined following GSEA. (E) LEA of all C7 gene sets commonly underrepresented. (F) Frequency of genes occurring in the leading edge of underrepresented C7 gene sets versus gene rank. (G) Heat map of select leading edge genes. (H) Percentage of cells stained positive for CD3 and (I) CD8 analyzed using QuPath and presented as mean ± SD. Significantly enriched gene sets defined as FDR q-value <0.05. Significance in overlap of leading edge genes analyzed using hypergeometric test. Correlation between the gene rank of leading edge contributors calculated by the Spearman test. Immunohistochemical staining analyzed relative to young control using one-way ANOVA and Dunnet post hoc test. Asterisks denote significance: *< 0.05, **< 0.01, ***< 0.001.

Figure 4

MetM-WNT^lung tumor growth is constrained by CD8 T cell immune surveillance. (A) Study schematic and in vivo tumor volume. (B) Representative flow cytometry plot quantifying CD8+ T cells from IgG treated (red) and anti-CD8 antibody treated (blue) mice. (C-F) Flow cytometric analysis of splenic and tumoral CD45+CD3+CD8+ T cell populations at interim timepoint and study end point. (G, H) Flow cytometric analysis of splenic and tumoral CD45+CD8+ cells at study endpoint. (I-K) Ex vivo tumor mass measured days 13, 17, 21, and 25 following tumor injections. Data presented as mean ± SD. Differences across three groups analyzed using one-way ANOVA and Tukey post hoc test. Statistical differences across two groups determined by t test. Asterisks denote significance: *p< 0.05, **p< 0.01, ***p< 0.001.

Figure 5

Advanced age and DIO exert a combined effect on mammary tumor progression in a E0771 cell transplant model of TNBC. (A) Body weight at tumor inoculation. (B) % body fat mass and (C) % lean mass measured at study endpoint. (D) In vivo tumor volume following E0771 cell injection. (E) Percentage of mice that developed palpable mammary tumors, analyzed using Fisher’s exact test. (F) Ex vivo tumor mass. Only one mouse in the young control group developed a tumor, so no data is shown for that group. (G) Percentage of mice that developed at least one metastatic lesion in the lung, statistical difference analyzed using Fisher’s exact test. Only one mouse in the young control group developed a primary tumor with no metastatic lesions,so no data is shown for that group. (H) R epresentative image of GFP stained metastatic lesion (arrow). Data presented as mean ± SD. Differences across groups analyzed using one-way ANOVA and Tukey post hoc test, unless otherwise specified. Asterisks indicate differences in significance. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 6

The combination of advanced age and DIO exacerbates tumor immune suppression. (A-F) Serum cytokines measured in serum collected prior to tumor inoculation. (G) Hallmark gene sets commonly enriched and underrepresented in mammary tumor of aged DIO versus aged control mice determined using gene set enrichment analysis (GSEA). (H) Heat map of select leading edge genes. Data presented as mean ± SD. Differences across groups analyzed using one-way ANOVA and Tukey post hoc test, unless otherwise specified. Significantly enriched gene sets defined as FDR q-value <0.05. Asterisks indicate differences in significance. *p < 0.05, **p < 0.01, ***p < 0.001.