Impact of Tacrolimus,Sirolimus,Age,and Body Mass Index on the Occurrence of Skin Cancer and Islet Dysfunction After Transplantation

Abstract

Herein, we characterized the percentage of tacrolimus to the combined sirolimus and tacrolimus trough levels (tacrolimus %) observed during islet transplant-associated immune suppression therapy with post-transplant skin cancer. Although trough levels of tacrolimus and sirolimus were not different (P = 0.79, 0.73, respectively), high tacrolimus % resulted in a 1.32-fold increase in skin cancer odds when adjusting for age, sex, body mass index (BMI), and use of mycopheonlate mofetil (MMF; p = 0.039). Skin cancer patients were likely to have been older but not differ significantly (mean difference 12 years, P = 0.056), but age was significantly associated with a 1.22-fold increase in adjusted skin cancer odds (P = 0.046). BMI was inversely associated with skin cancer, with an adjusted odds ratio (OR) of 0.40 (P = 0.022). High tacrolimus % (>35) resulted in a 4.6-fold increase in skin cancer frequency, whereas sirolimus above 75% of the combined therapy led to a 5.2-fold increase in islet graft dysfunction (IGD) events/year. By calculating the maximum safe exposure (MSE) to tacrolimus % according to patient age and BMI, we found that cumulative months spent above MSE was predictive of skin cancer (1.20-fold increase, P = 0.003). Individuals exceeding the MSE for 1 year were 9.2 times more likely to develop skin cancer (P = 0.008). Results suggest that strategies targeting immunosuppression ratios based on age and BMI may minimize cancer risk while improving graft survival and function.

Graphical Abstract

Keywords

basal cell carcinoma squamous cell carcinoma melanoma tacrolimus sirolimus islet cell transplantation islet graft dysfunction

Introduction

Use of both the calcineurin inhibitor Tacrolimus (Prograf; Astellas Fujisawa, Osaka, Japan) and the mTOR inhibitors such as sirolimus (Rapamune; Pfizer, New York, NY, USA) were among 5 factors associated with favorable islet transplant outcome¹. However, treatment with immune suppression drugs post islet transplant (IT) can be associated with skin cancer and islet graft dysfunction (IGD) in IT recipients. Tacrolimus displayed a dose-dependent effect on tumor progression and upregulation of tumor growth factor (TGF)-β₁ in mice². Elevated cancer risk associated with increases in TGF-β₁ and vascular endothelial growth factor (VEGF) were also reported in clinical trials³. The prevalence of tacrolimus-associated skin cancer varies and is confounded by age, body mass index (BMI), race, gender, as well as difficulties in measuring UV exposure. Use of sirolimus can provide an alternative to calcineurin inhibitors but is also associated with adverse events. Despite the reported improved IT safety and efficacy with combined tacrolimus and sirolimus therapy⁴, optimized treatment regimens have not been reported. Clinical outcomes comparing each of the 2 immunosuppressants received as a monotherapy along with other immunosuppressive agents showed tacrolimus to be superior to sirolimus in reducing acute rejection⁵. Conversely, among individuals who developed posttransplant skin cancer, tumor growth was less in those who received sirolimus⁶. However, chronic rapamycin exposure decreased viability of rat and human islets⁷. Herein, we determined the impact of tacrolimus, sirolimus, BMI, and age on incidence of skin cancer and islet dysfunction after clinical transplantation and generated a therapeutic ratio of immunosuppressant agents that limits skin cancers and maximizes islet survival and function.

Materials and Methods

Subjects

Our study of the effects of combined sirolimus and tacrolimus on the onset of skin cancer included patients on a 2 drug (sirolimus and tacrolimus) or 3 drug (sirolimus, tacrolimus, and mycopheonlate mofetil (MMF)) regimens from patients on active treatment (on-study), long-term follow-up, and lost to follow-up. Patients with at least 6 months of on-study immunosuppression were included in the study. Informed consent was obtained from all individuals and studies were approved by the institutional IRB Committee (COH IRB# 1083, 12446, 18156).

Immunosuppression

Individuals transplanted from 2004 to 2011 received glucocorticoid-free immunosuppression (islet transplant alone; ITA) adapted from the Edmonton protocol⁴ to include induction with either basiliximab (Simulect; Novartis, Basel, Switzerland) for first islet transplant or daclizumab (Zenapax; Roche) for repeat transplant, and etanercept (with each infusion). Immunosuppressive maintenance included tacrolimus, sirolimus, and/or mycophenolate mofetil, as described³. From 2015 to 2021, another group received T-cell depleting immunosuppression induction (T-cell depletion; TCD), including 1.5 mg/kg of antithymocyte globulin (rATG) on days 0, 1, 3, and 5, with methylprednisolone, ibuprofen, and diphenhydramine premedication to reduce hypersensitivity reactions. The induction regimen also included treatment with 50 mg of Etanercept (antitumor necrosis factor-alpha) on day 0 (intravenously) and 25 mg on days 3, 7, and 10 (subcutaneously) post-transplant and 100 mg/day of Anakinra (IL-1 receptor antagonist) on days 0–6. From 2019 to 2024 under the gastrin protocol, patients were treated with immunosuppression induction as described above (rATG, etanercept, & anakinra) with 2 30-day gastrin courses starting from 1 day prior to transplant to 2 days post-transplant, and month 6 post-transplant.

In all cases, the immunosuppression maintenance regimen included tacrolimus twice daily starting on day 0 to achieve 12-hr target trough levels between 8 and 12 ng/ml during the first 8 weeks. MMF (Cellcept; Roche Laboratories, Nutely, NJ) was also started on day 0 at an initial dose of 0.5 g twice daily and adjusted based on hematologic parameters and clinical presentation. Sirolimus was initiated at approximately 8 weeks post-transplant to achieve a target range of 6–12 ng/ml. Tacrolimus was reduced to a range of 3–9 ng/ml after starting sirolimus. In both protocols, tacrolimus and sirolimus levels have been adjusted above or below target if graft rejection was suspected, or to provide immunosuppressive coverage if the patient was unable to tolerate targeted serum levels of the other agent. One individual received 2 transplants under the first protocol and went on to receive a third islet transplant under the T-cell depleting protocol. Patient immunosuppression levels were reviewed weekly by the clinical management team. Drug trough levels deemed questionable by the team were removed from the analysis.

Statistical Analysis

Data were collected from April 2004 to May 2024. Explanatory variables considered included tacrolimus and sirolimus trough levels, age, sex, use of MMF, BMI, and duration of immunosuppression. The total observation period was, beginning with the first transplant, defined as the on-study and long-term follow-up periods. After the final transplant, individuals were followed while on study for 2 years under ITA, 5 years under TCD, and 1 year under gastrin before transitioning to long-term follow-up. Dependent variables included the occurrence and frequency of confirmed skin cancer in IT recipients under a combined tacrolimus-sirolimus or tacrolimus-sirolimus-MMF regimen. Age was defined at the beginning of the transplant activity. BMI was averaged over the study for each patient. The tacrolimus % used to estimate skin cancer onset was calculated using monthly percentages of tacrolimus/(tacrolimus + sirolimus) trough levels.

Prediction of skin cancer was then estimated using patient age at the time of the first transplant, BMI averaged over the study period, and tacrolimus % averaged from observed drug trough levels during the study by logistic regression (EQ 1) using a binomial general linear model (GLM):

\ln (\frac{P}{1 - P}) = t a c β_{0} + a g e β_{1} + B M I β_{2} + β_{3}

Equation 1

P = \frac{e^{t a c β_{0} + a g e β_{1} + B M I β_{2} + β_{3}}}{1 + e^{t a c β_{0} + a g e β_{1} + B M I β_{2} + β_{3}}}

Equation 2

where P is the probability of developing skin cancer, tac is the tacrolimus %, defined as 100*tacrolimus level/(tacrolimus level + sirolimus level), age is patient age at first transplant and BMI is the patient BMI. Terms represent the calculated model coefficients for tacrolimus % (β₀), age (β₁), BMI (β₂), and confounders and intercept value (β₃). Coefficients for confounding variables were estimated using data set averages. Results of the logistic regression model were then used in a receiver operating characteristic (ROC) analysis to define the best-predictive cut-off value (above which individuals had skin cancer and below which they did not) to define disease risk. Using this cutoff, we calculated the maximum safe exposure (MSE) of tacrolimus per individual according to age and BMI:

{t a c}_{m s e} = \frac{L_{c} - a g e β_{1} - B M I β_{2} - β_{3}}{β_{0}}

Equation 3

where L_c = ln(P_c/1 − P_c), P_c = best predictive cut-off value, and ${t a c}_{m s e}$ = MSE of tacrolimus %. ROC analysis was used to find the highest number of cumulative months each individual could remain above the MSE before being at risk. Frequency of skin cancer was calculated as the number of diagnosed skin cancers over time, starting from the date of the first diagnosis to the end of the follow-up period. IGD events were defined for insulin independent patients as 3 post-prandial (at least 2 hours post-meal) blood glucose readings over 180 mg/dl or 3 pre-prandial blood glucose readings over 140 mg/dl in any 1-week period, and for insulin dependent patients as a 50% increase in daily reported insulin intake of at least 5U/day or an increase of 10 units/day over any 1- to 2-week period⁸. Group comparison of explanatory variables between cancer and non-cancer groups was performed using the Student’s t test. Non-parametric analyses were performed using the Wilcoxon rank sum test. Data analysis, statistics, and plotting was performed in R. Survival plot and SC frequency to IGD bar plot was created using GraphPad Prizm.

Results

Under the ITA, T-Cell Depleting, and Gastrin (GAS) studies, 34 patients (17 ITA, 9 TCD, and 8 GAS) given either a 2 drug (sirolimus and tacrolimus) or 3 drug (sirolimus, tacrolimus, and MMF) regimen were followed from 2004 to 2024. A single patient who took Campath (alemtuzumab) was excluded due to insufficient sample size. Patients with data consisting of less than 6 months of on-study tacrolimus/sirolimus levels (TCD = 3, ITA = 3, GAS = 4) were excluded from the analysis, resulting in 21 patients (1 skin cancer patient received 2 transplants under the ITA protocol and a third under the TCD protocol, and another received 1 transplant under the ITA protocol and a second under the TCD protocol) consisting of 11 males, 10 females used in the analysis. A single patient lived in Alaska, 1 patient lived in Arizona, and 1 patient lived in Northern California; the remaining 18 patients studied lived in Southern California during the total observation period. The skin cancer group included 6 individuals (4 males, 2 females), 3 of whom received 2 transplants, and 3 received 3 transplants, and each patient had ≥2 reported skin cancers. The remaining 15 subjects had no confirmed skin cancer diagnosis (7 males, 8 females). Age at the start of study ranged from 20 to 67 years (Table 1). All transplant recipients were Caucasian, with the exception one Black patient. Differences in UV exposure due to occupation and lifestyle were not assessable. The frequency of skin cancers ranged from 0.36 to 1.65 per year. The median duration of immunosuppression from the start of study to the first skin cancer diagnosis was 4.5 years. Length of drug exposure between cancer and non-cancer subjects did not reach significance (P = 0.53). To ensure that results from outside labs were consistent with those performed in-house, 18 tacrolimus and sirolimus samples were run in parallel, and resulted in an R² of 0.9671 for tacrolimus and 0.8894 for sirolimus. Tacrolimus and sirolimus trough level differences between skin cancer versus non-skin cancer individuals did not reach statistical significance (mean ± SD 4.81 ± 0.66 ng/ml versus 4.65 ± 0.72 ng/ml, P = 0.79 for tacrolimus, respectively, and 9.4 ± 2.2 ng/ml versus 10.8 ± 4.1 ng/ml, P = 0.73 for sirolimus, respectively, Table 1).

Table 1.

Patient On-Study Characteristics.

Characteristic	Skin cancer		Without skin cancer			All studies			Diff
Characteristic	ITA, N = 5	TCD, N = 1	GAS, N = 3	ITA, N = 9	TCD, N = 3	Skin Cancer, N = 6	Without Skin Cancer, N = 15	P value^a	Difference	95% CI^b
Tacrolimus trough level (ng/ml)	4.98 (0.58)	3.99 (−)	4.76 (0.79)	4.79 (0.71)	4.09 (0.60)	4.81 (0.66)	4.65 (0.72)	0.8	0.16	−0.56, 0.89
Sirolimus trough level (ng/ml)	9.89 (2.07)	7.04 (−)	5.8 (1.0)	13.7 (2.5)	7.3 (1.0)	9.4 (2.2)	10.8 (4.1)	0.7	−1.4	−4.3, 1.5
Age at start of study	49 (10)	67 (−)	45 (9)	38 (5)	38 (16)	52 (12)	39 (9)	0.056	12	−0.36, 25
Duration of Immunosuppression, (Months)	56 (37)	34 (−)	39 (19)	43 (45)	44 (20)	53 (34)	42 (35)	0.5	10	−27, 48
Gender								0.6
Female	2/5(40%)	0/1(0%)	2/3(67%)	5/9(56%)	1/3(33%)	2/6(33%)	8/15(53%)
Male	3/5(60%)	1/1(100%)	1/3(33%)	4/9(44%)	2/3(67%)	4/6(67%)	7/15(47%)
BMI	21.70 (2.29)	25.68 (−)	26.80 (1.11)	23.64 (2.97)	26.00 (2.69)	22.36 (2.62)	24.74 (2.88)	0.055	−2.4	−5.3, 0.51
Glomerular filtration rate	87 (14)	77 (−)	76 (12)	78 (21)	78 (12)	85 (13)	78 (15)	0.6	7.1	−9.6, 24
Immunologic markers
Absolute lymphocyte cell count	1.52 (0.43)	0.59 (−)	− (−)	1.38 (0.38)	0.54 (0.36)	1.36 (0.54)	1.17 (0.52)	0.67	0.19	−0.41, 0.79
Immunoknow	465 (222)	218 (−)	611 (−)	291 (117)	277 (44)	416 (222)	316 (135)	0.6	100	−170, 370

Wilcoxon rank sum exact test; Wilcoxon rank sum test; Fisher’s exact test. ^bCI = confidence interval.

Terms included in the final regression model were tacrolimus %, patient age at the start of study, BMI, and MMF usage, sex, and duration of immunosuppression, represented as a simplified equation (supplemental Eq. 1). Results showed that individuals with increased tacrolimus % had higher odds of developing skin cancer (adjusted OR = 1.32 95% CI 1.01 to 2.28, P = 0.039, Table 2), yet absolute lymphocyte cell count (ALC) and CD4+ T cell activity, assessed by ATP levels⁸ were not significantly different between skin cancer and non-skin cancer groups (P = 0.67) seen in Table 1. The odds of developing skin cancer also increased with age (unadjusted OR = 1.11 95% CI = 1.01–1.22, P = 0.015 and adjusted OR = 1.22, 95% CI: 1.00–1.74, P = 0.046). Furthermore, a high tacrolimus % (>35) resulted in a 4.6-fold increase in the frequency of skin cancer when compared with ratios where tacrolimus was below 35% of the combined tacrolimus and sirolimus serum concentration (P = 0.014) (Fig. 1). In contrast, immune suppression primarily with sirolimus (tacrolimus < 25%) was associated with a 5.2-fold increase in the number of IGD events per year (P = 0.032, Fig. 1). Individuals who had an average tacrolimus % between 25 to 35 after transplantation experienced fewer IGD events per year (Mean = 22.04 ± 10.55) with a low frequency of skin cancer (Mean = 0.28 ± 0.22) per year. Although exposure to lower tacrolimus % was associated with a lower occurrence of skin cancer, the association was likely to be influenced by the age and BMI of the individual as well.

Table 2.

Odds Ratio of Skin Cancer Based on Immunosuppression Exposure and Other Risk Factors.

Factors	Unadjusted Model		Multivariable-adjusted for risk factors
Factors	OR (95% CI)	P value	OR (95% CI)	P value
Tacrolimus %^a	1.07 (0.94 to 1.23)	0.28	1.32 (1.01 to 2.28)	0.039
Age at start of study	1.11 (1.01 to 1.22)	0.015	1.22 (1.00 to 1.74)	0.046
BMI	0.75 (0.46 to 1.04)	0.08	0.40 (0.04 to 0.91)	0.022
Months above MSE^b during study	1.09 (1.03 to 1.16)	0.002	1.20 (1.05 to 1.49)	0.003
Duration of on-study immunosuppression, (months)	1.02 (0.99 to 1.06)	0.21	0.97 (0.90 to 1.03)	0.34

Adjusted for additional risk factors including patient race, gender, duration of immunosuppression. OR = odds ratio, CI = confidence interval.

Percentage of tacrolimus to the combined sirolimus and tacrolimus trough levels. Significant P-values shown in bold.

MSE: maximum safe exposure.

Figure 1.

Balance trade-off of immunosuppressive therapy in islet transplantation. Analysis of on-study graft dysfunction and frequency of diagnosed skin cancers following islet transplantation suggest an inverse relationship mediated by the ratio of tacrolimus to sirolimus. Individuals in excess of 35% tacrolimus during the post-transplant period experienced a 4.6-fold increase in the frequency of skin cancer per year (1.04 ± 0.31), compared to those whose tacrolimus % was below 35 during the study period (0.21 ± 0.13). In contrast, subjects with exceedingly low tacrolimus (<25% of the combined therapy) had a 5.2-fold increase in graft dysfunction events per year (75.89 ± 34.73) relative to individuals with tacrolimus % above 25 (14.72 ± 7.7). Islet graft dysfunction events were defined as 3 postprandial (at least 2 hours post meal) blood glucose readings over 180 mg/dl, or 3 pre-prandial blood glucose readings over 140 mg/dl in a 1-week period. Data are expressed as mean and standard error of mean (SEM).

Using receiver operator characteristic analysis, prediction of skin cancer onset was determined to be best represented by a predictive model output cutoff ( $P_{c},$ Eq. 3) of 34%. Using this value, the MSE of tacrolimus % for each individual according to age was calculated ( ${t a c}_{m s e},$ eq. 3, supp. eq. 1). Using this equation to calculate the MSE for a patient with an average study age of 43 and a BMI of 25 resulted in an MSE of 45.5%. With a practical range of clinical therapy estimated using the lowest, average, and highest observed tacrolimus trough levels of 3.4, 4.7, and 6.3 ng/ml, the corresponding sirolimus levels were 3.6, 5.4, and 7.2 ng/ml, respectively. Figure 2 shows the predicted probability of skin cancers according to tacrolimus % and age, with the range of MSE for each age shown in green using an average study BMI of 24. To characterize how the length of time spent above the MSE relates to skin cancer onset, the number of monthly averages where the tacrolimus % was above the MSE were totaled. The number of months an individual spent above MSE during the observation period was highly significant in increasing skin cancer odds (unadjusted OR = 1.09, 95% CI = 1.03–1.06, P = 0.002; adjusted OR = 1.20, 95% CI = 1.05–1.49, P = 0.003), while overall time on immunosuppression alone failed to reach significance (unadjusted OR = 1.02, 95% CI = 0.99–1.06, P = 0.17; adjusted OR = 0.97, 95% CI: 0.90–1.03, P = 0.34) (Table 2). The ROC analysis using counts from monthly averages of tacrolimus % was extended to find the most predictive number of total months that individuals could remain above the MSE before being at risk. Survival curve showed individuals above the MSE for 1 year were approximately 9.2 times more likely to develop skin cancer over the long-term follow-up period (Mantel-Haenszel HR = 9.2, 95% CI = 1.79–47.06, P = 0.008) (Fig 3).

Figure 2.

Observed skin cancer and predicted probability based on age and exposure to immunosuppression. Differences in maximum safe exposure (MSE) of tacrolimus for a given patient according to age is shown by the green shaded area.

Figure 3.

Skin cancer in individuals from cumulative exposure to low or high tacrolimus. Groups were defined according to whether they exceeded the maximum safe exposure (MSE) for a cumulative total of at least 1 year. Individuals exceeding the MSE for at least 1 year were estimated to be 9 times more likely to develop skin cancer over the long-term follow-up period (Mantel-Haenszel HR = 9.2).

Discussion

The relationship between the use of tacrolimus and sirolimus to the onset of skin cancer was reported^2,6,9,10, yet to our knowledge, this study is the first to characterize the appropriate use of relative dosing by describing target ratios of immunotherapeutic reagents to optimize safety and graft function in islet and solid organ transplantation. Organ transplantation in which tacrolimus was used as the primary immunosuppressive agent was associated with a significant increase in basal and squamous cell carcinoma^3,11 as well as malignant melanoma to a lesser extent³. In mouse studies, administration of tacrolimus dose-dependently increased transforming growth hormone (TGF-β₁), a marker for tumor invasion and metastasis². Calcineurin inhibitors, as proliferative agents, were proposed to increase the rates of basal and squamous cell carcinoma and melanoma. However, we found no difference in the actual trough levels of tacrolimus between individuals with and without skin cancer when performing a univariate analysis, and multivariate analysis to test the effects of tacrolimus trough levels on skin cancer when adjusting for sirolimus were also non-significant (P = 0.4292). Although this type of analysis can be hindered by collinearity, trough levels of sirolimus and tacrolimus were weakly correlated, and did not reach the level of significance (R = 0.31, P = 0.17). The higher % of sirolimus-to-tacrolimus in non-skin cancer patients may suggest a potential role of sirolimus in inhibiting skin cancer onset. In line with this, organ transplant recipients treated with, or switched to, sirolimus had a significantly lower cumulative incidence of reported secondary skin cancer compared to those who were not⁵. Furthermore, restricting immunosuppression therapy to sirolimus alone was associated with fewer squamous cell carcinomas versus without restriction, whereas minimization to calcineurin alone had no effect on skin cancer numbers⁵.

Pre-transplant rapamycin improved¹¹ and worsened¹² insulin sensitivity. Sirolimus degraded β-cell function and decreased survival^7,13,13as well. Tacrolimus decreased proapoptotic and proinflammatory mediators such as TNFα and IL-6¹⁴. These data suggest a need to titrate such agents to minimize graft dysfunction and skin cancer risk. We found tacrolimus trough levels between 25% and 35% of total immunosuppression drug levels to be ideal and was associated with lower skin cancer risk and minimal graft dysfunction. A tacrolimus % <25 was associated with decreased islet graft function, while >35% was associated with more skin cancers. Interestingly, absolute lymphocyte count and T cell activation were not significantly varied between skin cancer and non-cancer groups. This is consistent with post-mortem analysis that found no significant allo- or auto-immune activity associated with long-term islet graft loss under the standard 2 drug regimen¹⁵. Comparisons between IGD and absolute lymphocyte count in our cohort were inconclusive. It has however been reported that regulators of glucose homeostasis and insulin gene signaling, such as PDX-1 and Glut2, were downregulated after rapamycin treatment^12,16. These observations led us to label the deterioration in glucose control seen in individuals with high sirolimus-to-tacrolimus ratios as graft dysfunction due to drug toxicity, rather than the result of islet graft loss.

This study has several limitations. The study cohort was small and non-randomized. Our results showed important hazard rate differences which were significantly higher in patients with extended high tacrolimus usage over the study, but also had larger confidence intervals which may have been curtailed with a larger sample set. Our limited dataset precluded the possibility to do more robust longitudinal analysis on the correlation of immunosuppression exposure and age with time to onset of skin cancer. Since immunosuppression data from skin cancer patients were used up until the first SC diagnosis, duration of immunosuppression was not directly comparable with non-skin cancer patients. Finally, while differences in overall sun exposure would be curbed to an extend since most of our patients lived in a similar geographic region, we recognized that variations in lifestyle and occupation prevent us from dismissing actual UV exposure as a confounding factor.

Age and BMI as Indicators of UV Exposure

The association of age with ultraviolet exposure and skin cancer onset is both intuitive and well documented¹⁷, yet the relationship between BMI and skin cancer is not as well understood. Multiple centers report an inverse association between BMI and NMSCs, with individuals classified as overweight or obese (BMI > 25) being less susceptible than those in the normal range^18,19. While this inverse relationship has been attributed to physiological effects such as protection from estrogen induced adipose tissue²⁰, many studies fail to discount UV exposure as a potential confounder due to the difficulty in accurately estimating exposure. Obesity and increased body weight have been shown to be correlated with a lack of overall physical activity²¹, and some explained the lower incidence of skin cancer by the tendency of this group to be less prone to chronic UV from sun exposure22. Our data show both age and BMI to be predictive of skin cancer outcome, and while effectively quantifying UV exposure is traditionally challenging, the combination of these factors may provide a proxy for estimating cumulative UV exposure.

Study Relevance and Cohort Size

The primary challenge of reporting on a study with a small cohort is ensuring that the sample size is representative of the target population. As this study was predominately comprised of individuals living in Southern California over the course of the study, many of the conclusions made are most applicable to persons with higher-than-average UV exposure. Studies comprised of cohorts with high UV exposure have reported incidence rates which are comparable to what is reported herein. A study in Victoria, Australia which included 142 renal transplant recipients reported non-melanoma skin cancer rates of 0.45 and 0.79 SC/patient per year for individuals under immunosuppression for 0–5 years and 5–9 years, respectively²². Our results for 0–5 and 5–9 years were 0.11 and 0.55 NMSC cases/patient per year, respectively. Minor estimate differences may be due to the use of sirolimus in our cohort, whereas a majority of patients from the Australian study were on either a calcineurin-based (53%) or azathioprine-based (27%) immunosuppression, the latter of which has also been reported to be carcinogenic.

Herein, a relation between combination immunosuppressive therapy trough level ratios and skin cancer risk was revealed. These findings provide new insights and build upon other reports of adverse events associated with sirolimus and tacrolimus in islet and organ transplantation. They also provide a rationale for optimum titration of these combination immunotherapies to limit islet graft toxicity and skin cancer risk.

Supplemental Material

sj-docx-1-cll-10.1177_09636897241309412 – Supplemental material for Impact of Tacrolimus, Sirolimus, Age, and Body Mass Index on the Occurrence of Skin Cancer and Islet Dysfunction After Transplantation

Supplemental material, sj-docx-1-cll-10.1177_09636897241309412 for Impact of Tacrolimus, Sirolimus, Age, and Body Mass Index on the Occurrence of Skin Cancer and Islet Dysfunction After Transplantation by Christopher Orr, Jeannette Stratton, Mohamed El-Shahawy, Elena Forouhar, Alice Peng, Gagandeep Singh, Keiko Omori, Meirigeng Qi and Fouad Kandeel in Cell Transplantation

Footnotes

Acknowledgements

The authors thank the City of Hope Islet Transplant team and the Arthur Riggs Diabetes and Metabolism Research Institute for their contributions to the study.

Author Contributions

C.O. was involved in data acquisition, conceptualization, data analysis and visualization, and drafting of the manuscript; F.K. was involved in investigation, conceptualization, methodology, drafting and critical revision of the manuscript; J.S. was involved in data acquisition, interpretation, and critical discussion; M.S., E.F., A.P., G.S., K.O., and M.Q. were involved in investigation

Ethical Approval

Studies were approved by the Institutional Review Board at City of Hope (COH IRB#01083 on 11/27/2021, IRB#12446 on 05/16/2013, and IRB#18156 on 07/05/2018); ClinicalTrials.gov registration Identifiers: NCT00706420, NCT01909245, NCT03746769), and conducted in accordance with the Declaration of Helsinki.

Statement of Informed Consent

Written informed consent was obtained from all individuals prior to study entry. After completing participation on the original therapeutic protocol, participants were invited provide additional written informed consent to participate in a long-term follow-up observational study, approved separately by the Institutional Review Board at City of Hope (IRB#07066), which included separate written informed consent and visits in person or by phone approximately every 6 months.

Data Availability Statement

Data sets generated for this study are available upon request from the corresponding author.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is supported by the National Institutes of Health (National Center for Research Resources, National Institute of Diabetes and Kidney Diseases, U42-RR16607).

ORCID iD

Christopher Orr

Supplemental Material

Supplemental material for this article is available online.

References

Hering

Ballou

Bellin

Payne

Kandeel

Witkowski

Alejandro

Rickels

Barton

. Factors associated with favourable 5 year outcomes in islet transplant alone recipients with type 1 diabetes complicated by severe hypoglycaemia in the Collaborative Islet Transplant Registry. Diabetologia. 2023;66(1):163–73. doi: 10.1007/s00125-022-05804-4

Maluccio

Sharma

Lagman

. Tacrolimus enhances transforming growth factor-beta1 expression and promotes tumor progression. Transplantation. 2003;76:597–602.

Engels

Jennings

Kemp

Chaturvedi

Pinto

Pfeiffer

Trotter

Acker

Onaca

Klintmalm

. Circulating TGF-beta1 and VEGF and risk of cancer among liver transplant recipients. Cancer Med. 2015;4(8):1252–57.

Shapiro

Ricordi

Hering

Auchincloss

Lindblad

Robertson

Secchi

Brendel

Berney

Brennan

Cagliero

, et al. International trial of the Edmonton protocol for islet transplantation. N Engl J Med. 2006;355(13):1318–30.

Dantal

Morelon

Rostaing

Goffin

Brocard

Tromme

Broeders

Del Marmol

Chatelet

Dompmartin

Kessler

, et al. Sirolimus for secondary prevention of skin cancer in kidney transplant recipients: 5-year results. J Clin Oncol. 2018;36:2612–20.

Karia

Azzi

Heher

Hills

Schmults

. Association of sirolimus use with risk for skin cancer in a mixed-organ cohort of solid-organ transplant recipients with a history of cancer. JAMA Dermatol. 2016;152:533–40.

Bell

Cao

Moibi

Greene

Young

Trucco

Gao

Matschinsky

Deng

Markman

Naji

, et al. Rapamycin has a deleterious effect on MIN-6 cells and rat and human islets. Diabetes. 2003;52:2731–39.

Collaborative Islet Transplant Registry. Seventh Annual 3. Report of the Collaborative Islet Transplant Registry (CITR). 2011. https://www.citregistry.org/system/files/07th_CITR_Network_Report_Allograft_2011.pdf

Barlow

Nicholson

Herbert

. Evidence for rapamycin toxicity in pancreatic β-cells and a review of the underlying molecular mechanisms. Diabetes. 2013;62(8):2674–82.

10.

Benedini

Ermetici

Briganti

Codella

Terruzzi

Maffi

Caldara

Secchi

Nano

Piemonti

Alejandro

, et al. Insulin-mimetic effects of short-term rapamycin in type 1 diabetic patients prior to islet transplantation. Acta Diabetol. 2018;55(7):715–22.

11.

Deepa

Walsh Hamilton

Pulliam

Shi

Hill

Van Remmen

. Rapamycin modulates markers of mitochondrial biogenesis and fatty acid oxidation in the adipose tissue of db/db mice. Biochem Pharmacol. Res. 2013;1:114–23.

12.

Zhang

Tse

Bottino

Balamurugan

Bromberg

Dong

. Sirolimus is associated with reduced islet engraftment and impaired beta-cell function. Diabetes. 2006;55:2429–36.

13.

Fraenkel

Ketzinel-Gilad

Ariav

Pappo

Karaca

Castel

Berthault

Magnan

Cerasi

Kaiser

Leibowitz

. mTOR inhibition by rapamycin prevents beta-cell adaptation to hyperglycemia and exacerbates the metabolic state in type 2 diabetes. Diabetes. 2008;57:945–57.

14.

Del Castillo

García-Martín

Arias-Díaz

Giné

Vara Cantero

. Antiapoptotic effect of tacrolimus on cytokine-challenged human islets. Cell Transplant. 2009;18(10–11):1237–46.

15.

Smith

Kent

Nagle

Selig

Iafrate

Najafian

Hafler

Auchincloss

Orban

Cagliero

. Pathology of an islet transplant 2 years after transplantation: evidence for a nonimmunological loss. Transplantation. 2008;86:54–62.

16.

Yang

Lee

Young

Tien

Rowson-Baldwin

Shu

Jan

. Rapamycin induces glucose intolerance in mice by reducing islet mass, insulin content, and insulin sensitivity. J Mol Med. 2012;90:575–85.

17.

Sinikumpu

Jokelainen

Keinänen-Kiukaanniemi

Huilaja

. Skin cancers and their risk factors in older persons: a population-based study. BMC Geriatr 2022;22:269. doi:10.1186/s12877-022-02964-1

18.

Zhou

Luo

. Body mass index and risk of non-melanoma skin cancer: cumulative evidence from prospective studies. Sci Rep 2016;6:37691. https://doi.org/10.1038/srep37691

19.

Pothiawala

Qureshi

Han

. Obesity and the incidence of skin cancer in US Caucasians. Cancer Causes Control. 2012;23(5):717–26. doi: 10.1007/s10552-012-9941-x

20.

Gerstenblith

Rajaraman

Khaykin

Doody

Alexander

Linet

Freedman

. Basal cell carcinoma and anthropometric factors in the U.S. radiologic technologists cohort study. Int J Cancer. 2012;131(2):E149–55. doi:10.1002/ijc.26480

21.

Martínez-González

Martínez

Gibney

Kearney

. Physical inactivity, sedentary lifestyle and obesity in the European Union. Int J Obes 1999;23:1192–1201. https://doi.org/10.1038/sj.ijo.0801049

22.

Cumming

Leung

Chong

. Accrual of non-melanoma skin cancer in renal-transplant recipients: experience of a Victorian tertiary referral institution. Australas J Dermatol. 2014;55:43–48.

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