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Age-associated clonal B cells drive B cell lymphoma in mice

Nature Aging (2024)Cite this article

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Abstract

Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells. Driven by c-Myc activation, promoter hypermethylation and somatic mutations, IgM+ ACBCs clonally expand independently of germinal centers and show increased biological age. ACBCs become self-sufficient and support malignancy when transferred into young recipients. Inhibition of mTOR or c-Myc in old mice attenuates pre-malignant changes in B cells during aging. Although the etiology of mouse and human B cell lymphomas is considered distinct, epigenetic changes in transformed mouse B cells are enriched for changes observed in human B cell lymphomas. Together, our findings characterize the spontaneous progression of cancer during aging through both cell-intrinsic and microenvironmental changes and suggest interventions for its prevention.

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Fig. 1: B cells increase in size and undergo clonal expansion driven by somatic mutations and epigenetic alterations during aging.
Fig. 2: Aged B cells acquire an epigenetic program of malignant cells, and scRNA-seq reveals them as clonal B cell populations.
Fig. 3: Longitudinal analysis and transplantation experiments reveal ACBCs as a cancerous B cell population that leads to animal fatalities, and co-culture experiments point to their origin.
Fig. 4: Myc deficiency and rapamycin treatment inhibit cell size increase and age-related clonal expansion of B cells.

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Data availability

Raw reads for RNA sequencing, whole-exome sequencing and reduced-representation bisulfite sequencing are available at the Sequence Read Archive (PRJNA694093). Raw and normalized proteomics data are provided in Supplementary Table 5. All other data supporting the findings of the study are available from the corresponding author upon reasonable request.

Code availability

Code can be found by the following GitHub link: https://github.com/AnastasiaShind/AnastasiaShind/tree/AnastasiaShind-NatAging-Bcells.

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Acknowledgements

We thank members of the Gladyshev laboratory for discussions. This study was supported by the Max Kade Foundation to J.P.C., National Institute on Aging grants to V.N.G. and National Institutes of Health R01DC020190 and R01DC017166 grants to A.A.I.

Author information

Author notes

  1. Margarita V. Meer

    Present address: San Diego Institute of Sciences, Altos Labs, San Diego, CA, USA

  2. These authors contributed equally: José P. Castro, Anastasia V. Shindyapina.

Authors and Affiliations

  1. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    José P. Castro, Anastasia V. Shindyapina, Kejun Ying, Alexander Tyshkovskiy, Csaba Kerepesi, Marco Mariotti, Margarita V. Meer, Yan Hu, Grigoriy Losyev & Vadim N. Gladyshev

  2. i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal

    José P. Castro, Mafalda Galhardo & Elsa Logarinho

  3. Aging and Aneuploidy Laboratory, Instituto de Biologia Molecular e Celular, Universidade do Porto, Porto, Portugal

    José P. Castro

  4. Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

    Alessandro Barbieri & John P. Manis

  5. Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA

    Olga S. Strelkova & Artur A. Indzhykulian

  6. Department of Otolaryngology – Head and Neck Surgery, Harvard Medical School, Boston, MA, USA

    Olga S. Strelkova & Artur A. Indzhykulian

  7. Department of Cell Biology, Harvard Medical School, Boston, MA, USA

    João A. Paulo & Steven P. Gygi

  8. Retro Biosciences, Redwood City, CA, USA

    Rico Meinl

  9. Institute for Computer Science and Control (SZTAKI), Loránd Eötvös Research Network, Budapest, Hungary

    Csaba Kerepesi

  10. Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA

    Anna P. Petrashen & John M. Sedivy

  11. Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain

    Marco Mariotti

  12. College of Natural Sciences, The University of Texas at Austin, Austin, TX, USA

    Alexander Karamyshev

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Contributions

J.P.C. and A.V.S. conceived the project, designed and performed experiments, analyzed the data and drafted the manuscript. A.B., O.S.S., J.A.P., C.K., A.P.P., M.M., M.V.M., M.G., E.L., R.M., Y.H., K.J., A.T., A.K. and G.L. performed experiments, analyzed the data and revised the manuscript. G.L., S.P.G., A.A.I. and J.M.S. provided research materials, assisted with experimental design and revised the manuscript. J.P.M. interpreted the data, designed experiments and provided research materials. V.N.G. supervised the study, obtained funding and revised the manuscript.

Corresponding author

Correspondence to Vadim N. Gladyshev.

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Competing interests

After the initial submission of this paper, A.V.S. had a change in employment status (Retro Biosciences). M.V.M. is currently employed by Altos Labs. Experimental work was completed before these employment changes. R.M. is a paid employee of and has equity interests in Retro Biosciences. The other authors declare no competing interests.

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Nature Aging thanks the anonymous reviewers for their contributions to the peer review of this work.

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Extended data

Extended Data Fig. 1 Age-related changes in cell size and immune cell composition in C57BL/6 mice.

(a) Number of immune cells in the spleens of young, old and old lymphoma-bearing mice as measured by FACS and calculated based on the total number of cells in the spleen. (b) Mean size of T cells or (c) myeloid cells in the spleens as measured by FACS forward scatter. (d) Number of B cells in the spleens of young, old and old lymphoma-bearing mice as measured by FACS and calculated based on the total number of cells in the spleen. (e) Mean cell size in the spleens of young, old and old lymphoma-bearing mice as measured by FACS normalized to T cell size from the same donors. (f) Gating strategy for total B cells, follicular, marginal zone, CD21-CD23-, germinal center B cells and plasma cells. (g) Correlation between age-related phenotypes of B cells measured in old C57BL/6 mice. Scale bar is a Pearson correlation coefficient. Asterisks indicate statistical significance. **** p-value < 0.0001, *** p-value < 0.005, ** p-value < 0.01, * p-value < 0.05. (h) Similarity score of the transcriptomic signature of mouse cancerous B cells versus publicly available datasets of different human and mouse cancers (left plot). Enrichment scores for the Hallmark MYC targets pathway for human and mouse cancers (right plot). (i) Correlation between the similarity score from (h) on the left plot and enrichment score (NES) from (h) on the right plot. R is a Pearson correlation coefficient. (j) Enrichment of differentially methylated promoters found in B cells from old or lymphoma-bearing mice against those found in human cancers. ‘Mouse lymphoma up’ and ‘Mouse lymphoma down’ gene lists were created from our DNA methylation dataset and used as positive control in the analysis. P-values were calculated by Clusterprofiler package GSEA function that used a permutation test. (k) Enrichment of genes mutated in mouse lymphoma against these mutated in human cancers. ‘Mouse lymphoma’ gene list was created from our genome sequencing dataset and used as a positive control in the analysis. P-values were calculated by Clusterprofiler package GSEA function that used a permutation test. P-values for all other plots were calculated with a two-sided Student t-test unless otherwise specified. Data distribution was assumed to be normal but this was not formally tested. Each dot is the data from one mouse.

Extended Data Fig. 2 Mouse and human B cells clonally expand with age, which leads to reduced Ig diversity.

(a) Correlation between B-cell size as measured by FACS and the size of top B-cell clone as measured based on reconstruction of CDR3 regions from RNA-seq data to estimate Ig (ChaoE_Mean) from FACS-sorted B cells from young and old mice. (b) (left) Proportion of somatic mutations per nucleotide within the CDR3 region in all clones compared to largest clones. (right) IgH isotype distribution across young, old and lymphoma samples. Light blue means ‘not detected’. (c) Correlation between top clone size (Ig) estimated from CDR3 sequencing and top clone size estimated by VAF from whole exome sequences. (d) Correlation of clone size for the same clones reconstructed from RNA and from genomic sequencing of CDR3 regions. (e) Scheme of the analysis of sorted splenic B cells from 27 months old mice by RNA-seq, Immunoseq and WES/WGS. Liver WES/WGS were used as a control to exclude germline somatic mutations. (f) Number of somatic mutations per sample identified with whole exome (upper plot) or genome (bottom, left plot) sequencing. (g) (h) (i) (j) and (k) reconstructed mutational signatures of total somatic mutations in B cells of old mice. (l) Scheme of the analysis of the GTEx dataset. RNA sequences from spleen and blood were used to reconstruct CDR3 regions, estimate Ig diversity (chaoE mean), and WGS of blood from the same subjects was used to predict somatic mutations. (l) Schematic representation of the samples used. Spleen RNA-seq data from the GTEx project was utilized to reconstruct CDR3 diversity (chaoE_mean). Similarly, blood RNA-seq data from the same source was used to assess CDR3 diversity (chaoE_mean) and additionally, WGS data was employed for somatic mutation prediction. (m) Ig diversity (chaoE_mean) in spleens of young and old GTEx subjects calculated from RNA-seq data. P-value was calculated with a two-sided Student t-test. (n) Correlation between Ig diversity (chaoE_mean) in blood of GTEx subjects and their age, in years. (o) Correlation between top clone (WES) and Ig clone sizes (sum of top 5 CDR3 clones) in blood of GTEx subjects. R is a Pearson correlation coefficient in each plot, unless otherwise specified. All boxplots were plotted with geom_boxplot function grom ggplot2 package in R. One side of the box represents the 25th percentile, the other end of the box represents the 75th percentile, line in the middle represents median, length of whiskers is between largest and smallest data points that lay within 1.5 to 3 time the interquartile range.

Extended Data Fig. 3 Clonal expansions of B cells are supported by c-Myc and DNA methylation alterations.

(a) Mean DNA promoter methylation levels for genes encoding c-Myc targets. (b) Correlation between mean B cell size and the rDNA methylation age. (c) Correlation between the DNA methylation age calculated by the blood epigenetic clock36 and the size of top B cell clones. (d) Correlation of top Ig clone size and mean global DNA methylation of promoters and gene bodies in B cells of old mice. (e) c-Myc fold change in young, old and lymphoma FACS-sorted B cells normalized for DNA concentration and measured by qRT-PCR, p-values were calculated with a two-sided Student t-test. Each dot is a mouse in the young group, n = 6. Old and lymphoma groups contain a mixture of samples from regular-sized B cells and enlarged B cells that come from seven mice in the old group and three mice in the lymphoma group. (f) Correlation between Ptpn1 gene expression and mean DNA methylation of its promoter, dots are sized by size of the top clone of B cells in a sample. Correlations between two variables were evaluated using Pearson’s correlation coefficients (g) Same as (f) but for Id3 and Mitf genes. R is a Pearson correlation coefficient whenever R is indicated. Each dot is an independent biological replica. All boxplots were plotted with geom_boxplot function grom ggplot2 package in R, One side of the box represents the 25th percentile, the other end of the box represents the 75th percentile, line in the middle represents median, length of whiskers is between largest and smallest data points that lay within 1.5 to 3 times the interquartile range.

Extended Data Fig. 4 Single-cell RNA sequencing uncovers a clonal B-cell population and its relation to age-associated B cells (ABC).

(a) Enrichment plots of gene expression changes in ABC based on bulk public RNA-seq datasets for signatures from age-related B cell populations based on single-cell RNA-seq. (b) Correlation between clonality signature score estimated for each cell and clone size (% of reconstructed IgK) to which it belongs using two publicly available datasets36,37. (c) UMAP plots of single-cell RNA-seq of the spleens of old mice from the combined Kimmel dataset36 and Tabula Muris Senis dataset37 (left plot). Immune cell enrichment in mitotic genes clustered according to G1, G2M and S phases (right plot). (d) Proportion of cells predicted to be in G1, G2M or S mitotic phases across B cell populations. (e) c-Myc and Tbx21 fold change to Actnb measured with qRT-PCR in splenic follicular B cells, ABC and ACBC FACS-sorted from 25–27-month-old mice, p-value was calculated with a one-sided Student t-test. Data distribution was assumed to be normal but this was not formally tested. Each dot is data from one mouse. (f) Gating strategy for ABC and ACBC populations. (g) Cell sizes measured by FSC of follicular and ACBC in the spleens of young (n = 4) and old (n = 10) mice. (h) Representative images of follicular and ACBC cells immunolabeled for c-Myc and for DNA with DAPI (Scale bar - 10 μm). Quantification of cell sizes and mean c-Myc intensity for follicular and ACBC estimated from confocal images for two independent experiments. (i) Predicted interaction of immune cells by CellChat from single-cell RNA-seq of spleens from four mice coming from two datasets36,37. All boxplots were plotted with geom_boxplot function grom ggplot2 package in R, One side of the box represents the 25th percentile, the other end of the box represents the 75th percentile, line in the middle represents median, length of whiskers is between largest and smallest data points that lay within 1.5 to 3 time the interquartile range.

Extended Data Fig. 5 Age-associated clonal B cells infiltrate peripheral tissues.

(a) UMAP plots of single-cell RNA-seq from many combined tissues across mouse lifespan in months. Data was obtained from Tabula Muris Senis dataset37 (b) ACBC signature enrichment in B-cell populations in a multitude of tissues such as Brown adipose tissue (BAT), Gonadal Adipose Tissue (GAT), Kidney, Liver, Lung, Mesenteric adipose tissue (MAT), Bone marrow, Subcutaneous adipose tissue (SCAT) and spleen. All data was extracted from Tabula Muris Senis dataset37. Cell signature scores were performed by UCell and statistical analysis was performed based on Mann Whitney U statistic85.

Extended Data Fig. 6 Increased B cell clonality and enrichment for ABC and ACBC signatures in aged human donors.

(a) UMAPs showing ABC, ACBC and Myc targets enrichment across age gradient. (b) UMAPs showing the distribution of cells with ‘no’ and ‘yes’ for B cell clonality (c) IgH isotype distribution in ACBC enriched B cells. Single-cell RNA sequencing data was acquired from39 and the corresponding metadata from the Gene Expression Omnibus (GEO) database (GSE158055). Cells with available BCR sequences (‘BCR single cell sequencing’ == ‘Yes’) were selected from 19 healthy donors and retained only B cells or cells with an assigned BCR clone ID.

Extended Data Fig. 7 Longitudinal analysis reveals B-cell size and CD21−CD23− B cells as predictors of lifespan, and co-culture experiments point to their origin.

(a) Schematic representation of the longitudinal experiment. Blood was collected from the tails of C57BL/6 female mice across seven timepoints for FACS analysis. (b) and (c) changes in blood cell composition with age starting with 25 mice at 20 months of age, and 11 mice surviving by 31 months of age. (d) c-Myc transcript levels measured by RT-PCR in young (YF) and old follicular (OF) B cells incubated with i) age-associated B cells (ABC) from old spleens, ii) immune cells (CD45+) from young spleens excluding B cells (yEE), or iii) immune cells (CD45+) from old spleens excluding B cells (oEE). Results shown are from three independent experiments, three biological replicas of mice in two experiments, and four in the third experiment. P-values for all other plots were calculated with a two-sided Student t-test. Data distribution was assumed to be normal but this was not formally tested. Follicular and ABC as well as cells excluding CD19+ cells (EE) were sorted from different spleens to recover enough cells per replica. (e) Boxplot of log2FC of ABC (darkred) and ACBC (darkblue) upregulated genes in WT B cells and the same genes in CD22KO GC B cells from light zone (LZ, pale red and marine green) and dark zone (DZ, red and cyan) of CD22KO mice (Supplementary Table 2, PMID: 52943874). Each dot represents a gene from either the ABC or ACBC signature. Wilcoxon non-parametric test for comparing means of independent samples with the greater alternative, **** p-value < 0.0001, *** p-value < 0.005, ** p-value < 0.01, * p-value < 0.05. All boxplots were plotted with geom_boxplot function grom ggplot2 package in R. One side of the box represents the 25th percentile, the other end of the box represents the 75th percentile, line in the middle represents median, length of whiskers is between largest and smallest data points that lay within 1.5 to 3 time the interquartile range.

Extended Data Fig. 8 Effects of c-Myc deficiency and overexpression on immune cell composition and premalignant phenotypes of B cells.

(a) c-Myc expression fold change normalized to DNA concentration in B cells, (b) spleen weight normalized by body weight, and (c) the RNA to DNA concentration ratio in B cells, (d–f) splenic cell sizes from Myc+/− mice and their wild type (Wt) siblings. (g) Cell composition of immune cells (CD45+) and B-cell populations (h, i) in the spleens of old Wt and Myc+/− mice, gated as in Extended Data Fig. 1f,g. (j) Analysis of Emu-Myc mice. (k) Total RNA/DNA ratio in FACS-sorted splenic B cells from non-carrier (NC) controls and Emu-Myc mice. n = 3 mice in each Wt and Eu-Myc groups, Eu-Myc points are a mixture of regular-sized B cells and enlarged B cells summing up to two samples per mouse. (l) Mean size of B and T cells measured by FACS in the spleens of NC and Emu-Myc mice. (m) Mean cell size of B-cell populations measured by FACS in the bone marrow of NC and Emu-Myc mice. (n) Ig diversity (chaoE_mean) of splenic B cells from NC and Emu-Myc mice, calculated from RNA-seq data using mixcr and VDJtools software, n = 3 mice in each Wt and Eu-Myc groups, Eu-Myc points are a mixture of regular-sized B cells and enlarged B cells summing up to two samples per mouse. All boxplots were plotted with geom_boxplot function grom ggplot2 package in R. One side of the box represents the 25th percentile, the other end of the box represents the 75th percentile and represent interquartile range, line in the middle of the box represents median, length of whiskers is between largest and smallest data points that lay within 1.5 to 3 times the interquartile range. All p-values were calculated using one-sided T-test. Each dot is a mouse unless specified otherwise.

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Castro, J.P., Shindyapina, A.V., Barbieri, A. et al. Age-associated clonal B cells drive B cell lymphoma in mice. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00671-7

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