Short NK and naïve T-cell telomere length is associated with thyroid cancer in childhood cancer survivors: A report from the Childhood Cancer Survivor Study

Abstract

Background:

Survivors of childhood cancer are at risk for therapy-related subsequent malignant neoplasms (SMN), including thyroid SMN. Telomere length (TL) is associated with cancer risk, but the relationship between TL and SMN risk among survivors is less clear.

Methods:

We conducted a nested, matched case-control study of radiation-exposed 15-year+ adult survivors of childhood cancer with thyroid SMN (cases) and without SMN (controls). 46 cases were matched to 46 controls by primary diagnosis, chemotherapy (yes/no), radiation field, and follow-up duration. Lymphocyte TL (LTL) was measured by telomere flow-FISH cytometry using blood samples banked at a mean of 38.9 years (cases), 39.2 years (controls). Genetic variation in telomere genes was assessed by whole genome sequencing. Point estimates for LTL <10^th percentile were determined for cases and controls.

Results:

Cases had shorter median LTL than controls in three out of four leukocyte subsets. Cases were more likely to have NK cell LTL <10^th percentile (p=0.01), and 2.8-fold more likely to have naïve T-cell LTL <10^th percentile than controls (CI 1.07, 8.78). Five out of 15 cases with a rare indel or missense variant had naïve T-cell LTL <10^th percentile, compared with one out of 8 controls.

Conclusions:

Long-term survivors have shorter than expected LTL, a finding that is more pronounced among survivors with thyroid SMN.

Impact:

The long-term impact of childhood cancer treatment on immune function is poorly understood. Our findings support immune function studies in larger survivor cohorts to assess long-term deficits in adaptive and innate immunity that may underlie SMN risk.

Introduction

Subsequent malignant neoplasms (SMN) of the thyroid are an established late effect of childhood cancer treatment,¹ and are more common among females and children diagnosed at a younger age.² Radiation-exposed survivors are at especially high risk for SMN.³ However, not all survivors with at-risk exposures develop thyroid SMN, suggesting a role for genetic contributors. Telomeres are the repetitive DNA-protein structures at chromosome ends that protect chromosome integrity. Telomere length (TL) is genetically determined and further moderated by endogenous and exogenous (e.g. environmental) factors. TL is maintained in cell populations that express sufficient telomerase, but shortens with chronologic age in hematopoietic cells. Hematopoietic cells are highly sensitive to reductions in telomerase, so that a pathogenic variant in telomerase reverse transcriptase (TERT) and/or associated proteins produces progressive pronounced leukocyte telomere shortening over successive generations.⁴

In a meta-analysis of population studies, short leukocyte TL (LTL) was associated with gastrointestinal and head and neck cancers.⁵ Most population-based studies rely on high-throughput techniques that require a minimal amount of DNA, such as quantitative PCR (qPCR).⁶ This technique is performed on the diverse peripheral blood mononuclear cell fraction to determine the ‘average’ quantity of telomere DNA in leukocytes (telomere content), but does not account for differential shortening in leukocyte subsets. Cancer chemotherapy and radiation may further accelerate leukocyte telomere shortening via various pathways that include a heightened proliferative demand for hematopoietic reconstitution and direct damage to telomere DNA,^7,8 although rare studies have found an opposite, lengthening effect after chemotherapy alone.⁹ In a recent study conducted in the St. Jude Lifetime Cohort of childhood cancer survivors, shorter LTL was associated with an increased prevalence of chronic health conditions.¹⁰ We previously conducted a matched case-control study in the Childhood Cancer Survivor Study (CCSS), which identified less telomere content measured by qPCR in whole blood samples among radiation-exposed survivors with thyroid SMN, compared to radiation-exposed survivors without SMN.¹¹ Subsequent studies, also conducted in CCSS, indicated no association between genotypically-estimated LTL and thyroid SMN,¹² and an association between thyroid SMN and a common, low frequency POT1 variant.¹³ This study builds on our prior work, with the objective of assessing absolute TL in leukocyte subsets relative to normative data among survivors with and without thyroid SMN.

Materials and Methods

Study Design and Sample Population

This nested case-control study was conducted in the CCSS, a multicenter, retrospective cohort with longitudinal follow-up of five-year survivors of childhood cancer diagnosed between 1970 and 1986.¹⁴ All participants to this study provided informed consent, and the study was approved at each participating institution by the local institutional review board. Blood samples were collected from consenting participants at a minimum of 15 years off therapy and banked for future use. Radiation-exposed survivors who developed thyroid SMN (cases) were ascertained through self-report questionnaires. SMNs were validated from pathology reports, medical records, or the National Death Index and confirmed by a CCSS pathologist. Survivors with thyroid SMN were matched 1:1 with survivors that did not have SMN (controls) by primary cancer diagnosis, chemotherapy (yes/no), radiation field (yes/no for brain/neck, chest/spine, abdomen/pelvis), and follow-up duration (exceeding time to SMN for the case) by incidence-density sampling. Stem cell transplant (SCT) recipients were excluded. The sample size was determined by the number of CCSS cases with available viable leukocyte samples and without history of SCT, and represents a subset of thyroid SMN cases included in our prior matched case-control study (which only required DNA).¹¹ The study was conducted in accordance with the Declarations of Helsinki. All subjects provided written consent to participate in CCSS, and each participating institution obtained approval to conduct this research through their respective institutional review board.

Flow cytometry

Median LTL was measured in duplicate for total lymphocytes, and in B cells, memory T-cells, naïve T-cells, and NK cells by telomere flow cytometry fluorescence in situ hybridization (telomere flow-FISH), using established procedures and with quality control measures as described previously (Repeat Diagnostics, Vancouver, BC).¹⁵ Briefly, LTL was assessed by denaturation in formamide at 87°C and quantitative hybridization with a Alexa488-conjugated (CCCTAA)₃ peptide nucleic acid (PNA) probe specific for telomere repeats (Panagene) with a bovine thymocyte quantitative reproducibility control. Flow cytometry was used to define leukocyte subsets by a gating strategy that first distinguished lymphocytes based on LDS751 DNA staining (Thermofisher) and forward and light scatter properties, and then further distinguished naïve T-cells, memory T-cells, B cells, and NK cells based on staining with anti-human CD45RA, CD20, and CD57.¹⁵ Median absolute LTL was determined for each subject for total lymphocytes and for each leukocyte subset. Age and sex-adjusted LTL percentiles for both total lymphocytes and for subsets were derived from normative data obtained from 400 healthy volunteers between the ages of 0-100 years.¹⁶

To further characterize the CD20−/CD57−/CD45RA+ cell population identified as naïve T-cells by telomere flow-FISH, a subset of viably frozen samples from case-control pairs were analyzed locally on a BD LSR-II flow cytometer to identify CD3 positive T-cells that co-expressed CD45RA and CD197 (CCR7) using the following antibodies: CD45RA-FITC, CD3 PerCP-Cy5.5, CD45 APC-H7, and CD197-V450, per manufacturer’s recommendation (BD Biosciences).

Whole genome sequencing

Genomic DNA was extracted from saliva and/or leukocytes isolated by the Ficoll method, using the appropriate Qiagen kit. Whole genome sequencing (WGS) was performed by the Baylor College of Medicine Human Genome Sequencing Center. Five hundred ng of subject DNA was prepared and sequenced on an Illumina Novaseq 6000 S4 platform with 30x coverage. Variant call format (VCF) specifications were generated from the Genome Reference Consortium Human Build 38 (GRCh38), trimmed, and filtered using VCFtools¹⁷ to remove variants that a) mapped to genomic regions outside chromosomes 1–22, X, and/or Y, b) failed standard quality control, c) had an allele fraction <0.25 and/or Q fraction <10. The filtered data were analyzed using Ensembl Variant Effect Predictor (VEP) v97.3¹⁸ with the dbNSFP plugin v2.9.1 to extract exome population minor allele frequency (MAF). Variants analyzed in VEP were then further annotated for pathogenicity in ClinVar (version 201904).¹⁹ Variants were included if they were designated as ‘pathogenic’ or ‘likely pathogenic,’ or if they had a MAF <1% in the Genome Aggregation Database (gnomAD) r2.1 (exome)²⁰ and/or the 1000 Genomes Project.²¹

The gnomAD MAF of non-Finnish European, African, and East Asian/South Asian were used to identify rare variants in CEU, AFR, and ASN samples, respectively. Custom shell and R scripts were generated to process the results and calculate the unique gene and variant frequencies in the output files. Unique variants were determined based on reference sequence identifiers. We then further restricted our analyses to rare and/or pathogenic variants in 14 genes previously implicated in telomere biology disorders: ACD, CTC1, DKC1, NAF1, NHP2, NOP10, PARN, POT1, RTEL1, STN1, TERC, TERT, TINF2, WRAP53,²² including within a 5kbp flanking region. Sequence ontology was used to capture protein altering variants, including missense, in-frame insertion/deletion (indel), and frameshift variants.

Statistical Analysis

Median LTL, transformed to sex and age-adjusted percentiles based on the age at the time of sample collection, was the primary predictor considered in the analysis. The primary outcome was thyroid SMN. A paired t-test was used to compare median LTL between cases and controls for each leukocyte subset. McNemar’s test with continuity correction was used to compare proportions of survivor pairs with very low (VL, <1^st percentile) or low (L, ≥1^st to <10^th percentile) TL (exposed) vs. normal, high, or very high TL (unexposed). In consideration of the matched design, odds ratios (OR) for LTL <10^th percentile were calculated from the ratio of discordant pairs for each leukocyte subset. A Wilcoxon matched pairs signed rank test was used to compare proportions of each leukocyte subset relative to all leukocytes. All comparisons were conducted using matched analyses. A p value <0.05 was considered statistically significant.

Results

Out of 110 CCSS participants who developed thyroid SMN, 52 met inclusion criteria, had an available biospecimen, and were subsequently matched with 52 controls. However, for six of these pairs either the case failed quality control (insufficient cell count or viability for flow-FISH), or the control failed quality control and there were no suitable replacements available. The remaining final set of 46 matched controls were comparable in characteristics, including chemotherapy exposure (p=0.88), cancer diagnosis (matched), sex (p=0.06), race (p=0.30), age at diagnosis (0.35), and radiation exposure/site (matched), to the pool of potential controls that matched to cases, regardless of sample availability. Sufficient subject-level data were available to conduct all analyses. Four samples were collected prior to thyroid SMN diagnosis, and 42 after SMN diagnosis. Survivor pair characteristics, including age at sample collection, are shown in Table 1. Because chemotherapy matching was considered as a yes/no variable, 9 pairs were discordant for exposure to alkylators (5 pairs with only the control exposed, and 4 pairs with only the case exposed).

Table 1:

Distribution of characteristics in 46 survivor pairs with and without SMN^a

	Survivors with thyroid SMN	Survivors without SMN
Mean age in years at first cancer diagnosis (range)	9.9 (0.5-19.8)	9.6 (0.3-18.6)
Mean age at blood sample collection (range)	38.9 (19.8-56.2)	39.2 (24.9-55.4)
Mean time from first cancer diagnosis to blood sample collection (range)	29.0 (17.3-40.5)	29.6 (16.9-39.9)
Female sex, n (%)	29 (63)	26 (57)
Race, n (%)
White	46 (100)	42 (91)
Black	0	2 (4)
Asian	0	1 (2)
Other	0	1 (2)
Ethnicity, n (%)
Latino	2 (4)	0
Cancer type, n (%)
Hodgkin lymphoma	20 (44)
Acute lymphoblastic leukemia	13 (28)
CNS tumor	7 (15)
Non-Hodgkin lymphoma	3 (7)
Neuroblastoma	2 (4)
Renal tumor	1 (2)
Treatment
Chemotherapy-exposed	35 (76)
Alkylator-exposed (data from 45/46 cases and controls, 45/46 pairs), n (%)	29 (64)	30 (67)
Mean CED for alkylator-exposed (data from 24/29 cases and 28/30 controls), mean (range)	8670 (1426-16,761)	11980 (1050-27,799)
	Radiation-exposed	46 (100)
Brain/neck, n (%)	42 (91)
Chest/spine, n (%)	36 (78)
Abdomen/pelvis, n (%)	29 (63)

^aCriteria used in matching are shown as single column

CED = cyclophosphamide equivalent dose

Survivor median LTL falls below the population median for all leukocyte subsets

Telomere flow-FISH was performed for all 92 survivors. We were able to measure naïve T-cell and memory T-cell TL for all subjects, and B cell and NK cell TL for 91 and 84 subjects, respectively, due to limitations in either cell recovery or integrity. Figure 1 shows survivor sex/age-adjusted median LTL relative to population normative data indicating the 1^st, 10^th, 50^th, 90^th, and 99^th TL percentiles. Survivor LTL was downward distributed relative to normative data across all leukocyte subsets, suggestive of shorter TL compared to population norms. For example, seven out of 92 survivors (8%) had total lymphocyte TL <1^st percentile, and 28/92 (30%) had total lymphocyte TL <10^th percentile. Figure 2 illustrates the deviation of survivor median LTL below the population median, by SMN status. Median LTL was not associated with primary diagnosis, age at primary diagnosis, time between diagnosis and blood sample, educational achievement, or income.

Figure 1: Leukocyte telomere length in survivors of childhood cancer with and without thyroid SMN.

Leukocyte telomere length was obtained using telomere flow-FISH (n=92). Telomere length (kb) in lymphocytes, naïve T cells, memory T cells, B cells, and NK cells for each survivor is shown on age percentile curves according to survivor age at the time the sample was obtained. Survivors with thyroid SMN are shown in red, and survivors without any SMN are shown in black.

Figure 2: Median telomere length by leukocyte subset among survivors of childhood cancer.

Median TL in survivors with thyroid SMN is deviated further below the population median than TL in survivors without SMN. The zero line on the y-axis represents the general population median, indicated by the black dashed line. The density estimation of TL distribution is shown by violin plot, indicating the median, first, and third quartiles for each group. For each leukocyte subset, survivors with thyroid SMN are shown in red, and survivors without any SMN are shown in grey. *indicates a p value <0.05.

Survivors with thyroid SMN have shorter median LTL than survivors without SMN

The distribution of differences in survivor median LTL relative to the population median supported analysis of these data using parametric tests for all subsets (Supplemental Figure 1). When comparing differences in median LTL between cases and controls, cases had a greater negative deviation below the population median than controls. This difference reached statistical significance for total lymphocytes and for three out of four leukocyte subsets (Table 2, Figure 2). We then compared proportions of survivor pairs that had one, both, or neither survivor with sex/age-adjusted LTL <10^th percentile (Table 2). Eight survivors, all cases, had NK cell LTL <10^th percentile (p=0.01). Thirty three out of 92 survivors, 22 cases and 11 controls, had naïve T-cell LTL <10^th percentile. Cases were 2.83 times more likely to have naïve T-cell LTL <10^th percentile than controls (confidence interval [CI] 1.06, 8.78, p=0.04). All cases with VL NK cell TL had L or VL TL in all other subsets, as well as in total lymphocytes. All cases with L or VL NK cell TL also had L or VL naïve T cell TL.

Table 2:

Survivor telomere length relative to the population median, and percentile distribution by case/control status for each leukocyte subset

Leukocyte subset	Number of pairs	Deviation from age-based population median (kb ± SD)		P value	Distribution of case/control pairs by TL <10th percentile yes (+) or no (−)				OR (CI)	P value
		With thyroid SMN	Without SMN		+/+	+/−	−/+	−/−
Total lymphocytes	46	−0.80 ± 1.22	−0.27 ± 1.21	0.039	3	15	7	21	2.14 (0.82, 6.21)	0.136
Naïve T cells	46	−1.19 ± 1.52	−0.51 ± 1.25	0.019	5	17	6	18	2.83 (1.07, 8.78)	0.037
Memory T cells	46	−0.55 ± 1.10	−0.24 ± 1.18	0.19	4	10	7	25	1.43 (0.49, 4.42)	0.628
B cells	45	−0.72 ± 1.15	−0.07 ± 1.16	0.014	2	11	3	29	3.67 (0.97, 20.47)	0.061
NK cells	39	−0.76 ± 1.42	−0.05 ± 0.94	0.012	0	8	0	31	Inf	0.013

Given that many blood samples were obtained from cases after the SMN diagnosis, a sensitivity analysis was conducted for total lymphocytes and subsets that were significant in our initial comparison, limited to case-control pairs in which the case’s blood sample was obtained within 5 years of the SMN diagnosis (n=23). Similar trends were observed, with the difference in NK cell TL remaining significant (difference in median TL between cases and controls, p=0.012; eight survivors, all cases, with NK cell LTL <10^th percentile, p=0.013, Table 3).

Table 3:

Sensitivity analysis^* of survivor telomere length relative to the population median, and percentile distribution

Leukocyte subset	Number of pairs	Deviation from age-based population median (kb ± SD)		P value	Distribution of case/control pairs by TL <10th percentile yes (+) or no (−)				OR (CI)	P value
		With thyroid SMN	Without SMN		+/+	+/−	−/+	−/−
Total lymphocytes	12	−1.07 ± 1.35	−0.46 ± 1.34	0.139	2	9	5	7	1.80 (0.54, 6.84)	0.423
Naïve T cells	12	−1.62 ± 1.66	−0.74 ± 1.39	0.059	5	8	3	7	2.67 (0.64, 15.61)	0.228
B cells	11	−0.94 ± 1.13	−0.28 ± 1.19	0.113	1	8	2	11	4.00 (0.80, 38.67)	0.114
NK cells	10	−1.25 ± 1.60	−0.28 ± 0.75	0.033	0	7	0	13	Inf	0.023

^*Including only those survivor pairs where the case had a blood sample obtained within 5 years of SMN diagnosis

Shorter LTL identified in naïve T-cells by telomere flow-FISH (CD45RA+/CD20-) corresponded with a lower percentage of naïve T-cells relative to all lymphocytes (cases: median 24%, interquartile range 19-32%, vs. controls: median 39%, interquartile range 30-50%, p=0.002), suggestive of accelerated aging-related naïve T-cell LTL decline among cases. We conducted additional CCR7 immunophenotyping of the CD45RA+ cell population in a subset of 8 matched survivor pairs with L and VL LTL (n=16) to further distinguish naïve T-cells from other potential CD45RA expressing cells, such as effector memory T-cells that re-express CD45RA (TEMRA cells), which are characterized by very short telomeres (Supplemental Table 1).²³ Out of all CD45RA+ T-cells, approximately half were CCR7-defined naïve T-cells across all subjects tested (mean 49%, median 47%). Cases had an equivalent proportion of CCR7-defined naïve T-cells relative to controls (cases: mean 46%, median 47% vs. controls: mean 53%, median 50%), suggesting that a disproportionate admixture of CD45RA+ T-cells was not a strong contributing factor to the differences in naïve T cell TL observed between the groups (Figure 3).

Figure 3: Representative flow cytometry results from a matched pair of survivors of childhood acute lymphoblastic leukemia, with and without thyroid SMN.

CD3 positive T cells co-expressing CD45RA and CD197 (CCR7) are shown.

3A. For the case, 25.4% of all CD45+ cells were CD3+/CD45RA+, and 13.3% were also CD197+ (naïve T cells). Naïve T cells, defined as CD3+/CD45RA+/CD197+, composed 52% of all CD45RA+ T cells (CD3+/CD45RA+).

3B. For the matched control, 29.5% of all CD45+ cells were CD3+/CD45RA+, and 20.1% were also CD197+ (naïve T cells). Naïve T cells, defined as CD3+/CD45RA+/CD197+, composed 68.1% of all CD45RA+ T cells (CD3+/CD45RA+).

No survivors had a rare, pathogenic variant in a telomere biology gene

WGS data were available for 88 survivors, who were largely of CEU ancestry (85 CEU, 2 AFR, 1 ASN). WGS data identified coding sequence indel and missense variants with MAF < 1% in 23 survivors: 1 indel (in one case and one control) and 19 heterozygous missense variants (in 14 cases and 7 controls). None of the variants were designated as pathogenic. Seven out of 15 cases with indels/missense variants had L or VL TL in at least one of four subsets, compared with only one out of 8 controls (Supplemental Table 2). Five out of 88 survivors sequenced had a rare missense or indel TERT variant (6%), comparable to the frequency of germline TERT variants we previously observed in a childhood AML cohort.²⁴

Discussion

Adaptive and innate immunity decline with aging, due to a progressive reduction in naïve T-cells, T-cell receptor diversity, and NK cell function. In survivors of childhood cancer, the long-term impact of cancer treatment on the immune system is understudied.²⁵ There is some evidence of impaired immune reconstitution following treatment, but studies are limited by small sample size and short follow-up duration.^26–28 Exposure to chemotherapy in childhood depletes CD45RA+ naïve T-cells during active therapy,²⁹ an effect that extends to off-therapy survivors, e.g. children ≥18 months following leukemia therapy evidenced ongoing naïve T-cell depletion and quantitative deficiencies in NK cells.³⁰ In that study, in vitro gene expression response to radiation also showed a reduction in DNA damage response compared with sibling controls. Further, there is strong evidence that exposure to ionizing radiation accelerates thymic involution and aging, even after a low dose exposure.³¹ Together, these observations suggest that cancer treatment may induce defects in both adaptive and innate immunity, findings that at least persist into the early years after cancer treatment and coincide with an impaired DNA damage response. No studies to date have examined the long-term (15 years+) effects of childhood cancer therapy on immune function.

Our results suggest excess LTL shortening in 15+ year survivors of childhood cancer (mean age 39 years) that may be associated with the development of thyroid SMN. These observations are suggestive of premature immunosenescence, or, at minimum, a premature decline in LTL with age. Our findings are in line with prior reports of physical and molecular indicators of premature, accelerated aging in survivors of childhood cancer,^32,33 and expand on prior work evaluating TL associations in specific leukocyte subsets. Here, we show that survivors have shorter than expected LTL relative to sex/age-based norms, and nearly a third have TL at the <10^th percentile. Cases had shorter mean LTL than matched controls in total lymphocytes, and in three out of four leukocyte subsets. Naïve T-cell and NK cell LTL <10^th percentile were significantly associated with thyroid SMN.

NK cells play a key role in cancer immunosurveillance and cytotoxicity, particularly with respect to the control of hematologic malignancies and solid tumor metastases.³⁴ Naïve T-cells can also differentiate into various functional subsets with anti-tumor activity.³⁵ Aging-related decline in NK cell function, naïve T-cell number, and capacity for tumor neo-antigen expression contribute to the rising cancer incidence in the elderly.^36,37 In our study, naïve T-cell TL shortening corresponded with an overall decrease in the naïve T-cell population more pronounced among cases compared with controls. This difference did not appear to be related to differences in the CD45RA+/CD20-cell admixture, as equivalent proportions in a subset of cases and controls expressed CCR7, a characteristic naïve T-cell surface marker. Our results suggest a pattern of naïve T-cell TL shortening and population decline in long-term cancer survivors, warranting further investigation of decline in adaptive and/or innate immunity in survivors relative to risk for SMN.

Prior studies detected rare variants in telomere biology disorder genes in individuals with thyroid cancer that impact LTL.^38,39 Our study was not designed to detect differences in the frequency of rare variants between survivor cases and controls, but the frequency of rare variants approximated the frequency observed in conditions within the telomere biology disorder spectrum. Of note, the TERT p.H412Y variant that occurred in two cases has been associated with telomere biology disorders,⁴⁰ but is designated in ClinVar as benign. We and others have shown that p.H412Y telomerase activity and processivity is similar to wild type.²⁴ However, the location of this variant in TERT may affect TERT-TERC binding, which would not be detected in activity and processivity assays and supports follow-up studies to assess the functional impact of this variant on telomere maintenance and extension.

Limitations to our study include lack of baseline LTL pre-primary cancer diagnosis and the inability to assess LTL over time, which would inform our understanding of LTL attrition post-cancer therapy. Second, case/control matching was considered by chemotherapy yes/no rather than by individual agents, but in settings of lower radiation dose, exposure to alkylators may affect risk for thyroid SMN.⁴¹ However, only 4 out of 46 pairs were discordant for alkylator exposure so that the case was exposed and the control was not. Third, only half of thyroid SMN cases had a biospecimen available, and the majority were obtained after the diagnosis of thyroid SMN. In our study, all survivors had shorter than expected LTL, likely related to the long-term impact of primary cancer treatment on telomere shortening over time. Regarding the shorter TL we observed among survivors with thyroid SMN, we cannot exclude the possibility of reverse causation, i.e. that the SMN diagnosis led to the excess TL shortening observed in cases compared with controls. However, sensitivity analyses of these data limited to only those pairs with cases whose blood was drawn within 5 years of the SMN diagnosis showed similar trends as the larger sample set, retaining significance for the differences observed in NK cell TL. Recognizing the limitations of biospecimens collected in CCSS (the majority of specimens obtained following the SMN diagnosis), for this study we deliberately limited our outcome comparison to thyroid SMN vs. no SMN, given that the standard approach to thyroid cancer treatment is localized and often limited to surgical excision and/or radioiodine ablation, rather than systemic.

LTL is a convenient proxy for TL in other tissues, highly correlated between tissues obtained from the same individual,^42,43 and is associated with a variety of clinical outcomes. Our own data also support correlation of LTL between leukocyte subsets. In our study, LTL was not associated with primary diagnosis, age at diagnosis, time between diagnosis and blood sample, or demographic and socioeconomic factors. The degree of LTL shortening experienced by survivors may depend on LTL at baseline (prior to diagnosis) and vary by cellular response to intensive chemotherapy and radiation, among other factors. Prospective studies that include biobanking of leukocyte specimens are needed to further elucidate the relationship between LTL and risk for SMN and other late effects of primary cancer treatment. Our findings suggest that telomere flow-FISH may facilitate screening survivors at risk for thyroid SMN. The flow-FISH method has been adopted as the gold standard for clinical screening of telomere biology disorders. Specifically, lymphocyte TL <1^st percentile has an 85% positive predictive value (PPV) for correctly diagnosing dyskeratosis congenita, a prototypic disorder of telomere biology.⁴⁴ In our study, NK cell TL <10^th percentile has a high specificity for detecting thyroid SMN. Considering a thyroid SMN prevalence of approximately 2% among survivors of childhood cancer,⁴⁵ our data suggest a 100% PPV of NK cell TL <10^th percentile detecting thyroid SMN, with a 98% negative predictive value (CI 98.1, 98.5). Replicating these findings in a larger cohort of survivors may support use of this test to inform clinical decision-making regarding the need for ultrasound-based screening and fine needle aspiration among radiation-exposed survivors with nodules detected on physical exam.⁴⁶