Chemotherapy and Stem Cell Transplantation Increase p16INK4a Expression, a Biomarker of T-cell Aging

Abstract

The expression of markers of cellular senescence increases exponentially in multiple tissues with aging. Age-related physiological changes may contribute to adverse outcomes in cancer survivors. To investigate the impact of high dose chemotherapy and stem cell transplantation on senescence markers in vivo, we collected blood and clinical data from a cohort of 63 patients undergoing hematopoietic cell transplantation. The expression of p16^INK4a, a well-established senescence marker, was determined in T-cells before and 6months after transplant. RNA sequencing was performed on paired samples from 8 patients pre- and post-cancer therapy. In patients undergoing allogeneic transplant, higher pre-transplant p16^INK4a expression was associated with a greater number of prior cycles of chemotherapy received (p=0.003), prior autologous transplantation (p=0.01) and prior exposure to alkylating agents (p=0.01). Transplantation was associated with a marked increase in p16^INK4a expression 6months following transplantation. Patients receiving autologous transplant experienced a larger increase in p16^INK4a expression (3.1-fold increase, p=0.002) than allogeneic transplant recipients (1.9-fold increase, p=0.0004). RNA sequencing of T-cells pre- and post- autologous transplant or cytotoxic chemotherapy demonstrated increased expression of transcripts associated with cellular senescence and physiological aging. Cytotoxic chemotherapy, especially alkylating agents, and stem cell transplantation strongly accelerate expression of a biomarker of molecular aging in T-cells.

Keywords: Aging; Exhaustion; Senescence.

Fig. 1

A hierarchical clustering of representative transcripts whose expression significantly changes with cancer therapy (3 pair of auto-HSCT samples or 5 pair of chemotherapy-treated samples) in peripheral blood T-cells (CD3 +). Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Genes of interest are ordered along the y-axis as described in the Results section, with color-coding indicated to the left of the heatmap (purple = senescence associated; light blue = telomere shortening; brown = effector; yellow = NK; orange = exhaustion). Sample numbers are shown below the heatmap, with an “A” prior to sample numbers indicating patients undergoing auto-HSCT. Samples without an “A” indicate patients treated with chemotherapy and not transplantation. Samples are ordered along the x-axis.

Fig. 2

A hierarchical clustering of all transcripts whose expression significantly changes with cancer therapy (3 pair of auto-HSCT samples or 5 pair of chemotherapy-treated samples) in peripheral blood T-cells (CD3 +). Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Sample numbers are shown below the heatmap, with an “A” prior to sample numbers indicating patients undergoing auto-HSCT. Samples without an “A” indicate patients treated with chemotherapy and not transplantation. Samples are ordered along the x-axis as in Fig. 1.

Fig. 3

A hierarchical clustering of transcripts from a Gene Set Enrichment Analysis Signature (GSE11057) with increased expression in memory CD4 + cells compared to naïve cells. Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Sample numbers are shown below the heatmap, with an “A” prior to sample numbers indicating patients undergoing auto-HSCT. Samples without an “A” indicate patients treated with chemotherapy and not transplantation. Samples are ordered along the x-axis as in Fig. 1.

Fig. 4

A hierarchical clustering of transcripts from a Gene Set Enrichment Analysis Signature (GSE26928) with increased expression in effector memory compared to central memory CD4 + cells. Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Sample numbers are shown below the heatmap, with an “A” prior to sample numbers indicating patients undergoing auto-HSCT. Samples without an “A” indicate patients treated with chemotherapy and not transplantation. Samples are ordered along the x-axis as in Fig. 1.

Fig. 5

A hierarchical clustering of transcripts from a Gene Set Enrichment Analysis Signature (GSE22045) with increased expression in regulatory T cells compared to conventional T cells. Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Samples are ordered along the x-axis as in Fig. 1.

Fig. 6

A hierarchical clustering of transcripts from a Gene Set Enrichment Analysis Signature (GSE36476) with increased expression of transcripts that are more highly expressed in T cells from old versus young donors. Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Samples are ordered along the x-axis as in Fig. 1.

Fig. 7

A hierarchical clustering of transcripts from a Gene Set Enrichment Analysis Signature (GSE9650) with a mixed pattern of expression of signatures associated with naïve versus exhausted CD8 + cells. Pre-treatment samples are on the left (grey bar above the heatmap) and post-treatment samples are on the right (blue bar). Sample numbers are shown below the heatmap, with an “A” prior to sample numbers indicating patients undergoing auto-HSCT. Samples without an “A” indicate patients treated with chemotherapy and not transplantation. Samples are ordered along the x-axis as in Fig. 1.