@Investigation of DNA Damage Response Genes Validates the Role of DNA Repair in Pediatric Cancer Risk and Identifies SMARCAL1 as a Novel Osteosarcoma Predisposition Gene
Ninad Oak, PhD1 D; Wenan Chen, PhD2,3 (D); Alise Blake, MS, CGC1 D; Lynn Harrison, MPC, CCRP] [D; Martha O’Brien, MSc4,5,6; Christopher Previti, PhD4,5,6 (D); Gnanaprakash Balasubramanian, PhD4,5,6; Kendra Maass, PhD4,5,6,7; Steffen Hirsch, PhD4,8 [D ;
D; Olaf Witt, MD İD İD ; Uta Dirksen, MD ; Judith Penkert, MD9,10 (D; Barbara C. Jones, PhD4,6,7,11 (D); Kathrin Schramm, PhD4; Michaela Nathrath, PhD9,10 iD; Kristian W. Pajtler, MD4,5,6,7 [D David T.W. Jones, PhD4,6,7,11 4,6,7,12,13 14,15,16 ; Jiaming Li, MS17 İD Yadav Sapkota, PhD18 İD Kirsten K. Ness, PT, PhD, FAPTA18 (D); Lillian M. Guenther, MD1 D; Stefan M. Pfister, MD4,5,6,7; Christian Kratz, PhD9 D; Zhaoming Wang, PhD18,19 (D); Greg T. Armstrong, MD, MSCE18; Melissa M. Hudson, MD1,18 (D; Gang Wu, PhD2,20 [D Robert J. Autry, PhD4,5,6; Kim E. Nichols, MD1 (D; and Richa Sharma, MD21,22 [D ; ;
DOI https://doi.org/10.1200/JCO-25-01114
| ABSTRACT | ACCOMPANYING CONTENT | |
|---|---|---|
| PURPOSE | Recent studies reveal that 5%-18% of children with cancer harbor pathogenic variants in known cancer-predisposing genes. However, DNA damage repair (DDR) genes, which are frequently somatically altered in pediatric tumors, have not been systematically examined as a source of novel cancer-predisposing signals. | Data Sharing Statement Data Supplement Accepted October 6, 2025 |
| METHODS | To address this gap, we interrogated 189 DDR genes for presence of germline predisposing variants (PV) among 5,993 childhood cancer cases and 14,477 adult noncancer controls (discovery cohort). PV were determined using a tiered approach incorporating ClinVar annotations, InterVar classification, and in silico tools (REVEL, CADD, and MetaSVM). Using logistic and firth regression, we identified genes with PV statistically enriched in the germline of children with tumors and replicated findings among 1,497 additional childhood cancer cases across three independent cohorts. | Published October 9, 2025 J Clin Oncol 43:3833-3843 @ 2025 by American Society of Clinical Oncology View Online Article |
| RESULTS | Analysis across all cases with cancer revealed enrichment of TP53 PV. Cancer- specific analyses confirmed known associations including germline TP53 PV in adrenocortical carcinoma, high-grade glioma (HGG), and medulloblastoma (MB), PMS2 in HGG and non-Hodgkin lymphoma (NHL), MLH1 in HGG, BRCA2 in NHL, and BARD1 in neuroblastoma. In addition, four novel associations were uncovered, including BRCA1 in ependymoma, SPIDR in HGG, SMC5 in MB, and SMARCAL1 in osteosarcoma (OS). Importantly, the SMARCAL1:OS as- sociation was significant in the discovery (6/230, 2.6%, false discovery rate [FDR]logistic = 0.0189) as well as all three replication cohorts (Childhood Cancer Survivor Study: 8/275, 2.9%; PFisher < . 0001; Cancer Predisposition Syndrome- German Childhood Cancer Registry: 4/135, 3%, PFisher = . 002; Individualized Therapy for Relapsed Malignancies in Childhood: 4/217, 1.8%, PFisher = . 012). The remaining wild-type SMARCAL1 allele was deleted in three of four OS tu- mors with available data. | |
| CONCLUSION | Our study confirms the relevance DDR genetic variation in pediatric cancer risk and establishes SMARCAL1 as a novel OS predisposing gene, providing insights into tumor biology and creating opportunities to optimize care for patients with this challenging tumor. | Creative Commons Attribution Non-Commercial No Derivatives 4.0 License |
INTRODUCTION
Germline variants in cancer-predisposing genes (CPG) perturb cell growth and differentiation to set the stage for malignant transformation. Accordingly, the study of CPG
and associated hereditary syndromes provides critical in- sights into normal and cancer biology. To this end, recent sequencing studies have revealed that up to 18% of children with cancer harbor an underlying genetic predisposition.1-4 However, 40%-80% of children with cancer have family
CONTEXT
Key Objective
To comprehensively assess the contribution of germline predisposing variants in DNA damage repair (DDR) genes to pediatric cancer risk, using a large case-control cohort and stringent variant interpretation framework.
Knowledge Generated
Through this investigation, we demonstrate the relevance of DDR pathway perturbations in childhood cancer risk by validating several known and discovering four novel DDR gene:cancer associations, including SMC5 in medulloblastoma, BRCA1 in ependymoma, SPIDR in high-grade glioma, and SMARCAL1 in osteosarcoma (OS). Among these, the SMARCAL1:OS association validated across three replication cohorts with evidence for biallelic inactivation in tumors, confirming SMARCAL1 as a novel OS predisposition gene.
Relevance (S. Bhatia)
These findings will inform future investigations aimed at developing targeted therapies as well as germline testing for prospective surveillance and early detection of OS .*
*Relevance section written by JCO Associate Editor Smita Bhatia, MD, MPH, FASCO.
histories and/or clinical features concerning for cancer predisposition but lack a causal genetic diagnosis.1,5 This observation suggests that additional CPG remain undis- covered and their association with cancer phenotypes fur- ther elucidated.
Previous investigations have primarily included children with specific tumor types (eg, high-risk solid or CNS tu- mors, relapsed cancers) and examined for pathogenic variants in known CPG. Nevertheless, expanding the scope of germline analyses to include children with a broader array of cancers and additional cancer-associated genes is crucial to identify the missing heritable factors underlying childhood tumor formation. The identification of novel CPG and predisposing variants (PV) is also central to improving the outcomes for affected children as it enables develop- ment of targeted cancer therapies, guides genetic coun- seling and testing of relatives, and informs cancer surveillance and risk reduction.6,7
Somatic alterations affecting DNA damage repair (DDR) genes are drivers of high-grade pediatric tumors.2 In ad- dition, germline PV affecting selected DDR genes have been linked to several highly penetrant childhood cancer predisposition syndromes (CPS), including Li-Fraumeni syndrome, ataxia telangiectasia, Fanconi anemia, and rep- lication repair deficiency.2,8 Germline PV in DDR genes have also been implicated in the development of subsequent malignant neoplasms in long-term survivors of childhood cancer, especially those previously exposed to higher doses of ionizing radiation, anthracyclines, or alkylating agents.9 Despite these previous observations, to the best of our knowledge, an unbiased assessment of DDR genes and their role in development of primary cancers in children has not been conducted.
To this end, we generated a harmonized data set of germline variants from 5,993 childhood cancer cases and 14,477 adult non-cancer controls. We then conducted rare variant gene burden analysis using a curated set of 189 DDR genes with the aim to identify novel CPG that could account for the missing heritability of childhood cancer. Novel gene-cancer asso- ciations were replicated using three independent pediatric cancer cohorts and available tumor data.
METHODS
Patient Cohorts
The discovery cohort consisted of 5,993 children with cancer across five large scale sequencing studies, including the Pediatric Cancer Genome Project (PCGP),10 National Cancer Institute Therapeutically Applicable Research to Generate Effective Treatments initiative (NCI-TARGET, phs000218),11 St Jude Lifetime Cohort Study (SJLIFE),12 Genomes for Kids (G4K),3 and St Jude Real-Time Clinical Genomics study (RTCG; Fig 1A, Data Supplement, Table S1, online only). The control cohort for discovery comprised 14,477 adults without cancer from the 1000 Genomes Project13 and Alzheimer’s Disease Sequencing Project (phs000572).14 For replication of novel CPG, we queried three independent pediatric cancer cohorts, including the Childhood Cancer Survivor Study (CCSS, phs001327),15 Individualized Therapy for Relapsed Malignancies in Childhood (INFORM),16 and the Cancer Predisposition Syndrome- German Childhood Cancer Reg- istry (CPS-GCCR). The controlcohort for replication included adults without cancer from gnomAD v2.1.17 This study was approved by the Institutional Review Board at St Jude Children’s Research Hospital (No. 20-0379) and informed consent was obtained from parents, guardians, or patients, as appropriate.
A
Discovery Cohorts
Variant Calling
Variant Filtering
Replication Cohorts
Cases (n = 5,993) PCGP (n = 687)
GATK joint genotyping (n = 20,470)
axiaa baba
St. Jude CCSS (n = 547)
G4K (n = 254)
189 DNA Repair Genes
RTCG (n = 1263)
SJLIFE (n = 2603) TARGET (n = 1186)
VC
VCF
F
Joint VCF
Rare (AF <0.05%) Clin Var P/LP
CPS-GCCR (n = 169)
Controls (n = 14,477) 1000 Genomes Project (n = 2630) ADSP (n = 11847)
Quality control and post hoc filtering
Nonsense, frameshift, splicing Missense (CADD >20, REVEL >0.7, MetaSVM)
INFORM (n = 781)
B
C
ALL-NOS
NHL
Hematologic
HL
5,993 pediatric cancer samples
TALL
AML
Passed QC
6,636,054
BALL
ATRT
ACPG
CNS
Frameshift, nonsense, missense, splice
2,536,772
EPD
LGG
HGG
MB
Rare (gnomAD AF <0.05%)
1,403,469
ACC
LIC
Solid
MEL
In DDR genes
10,368
GCT
EWS
RB
RMS
Predisposing variants
1,881
OS
WLM
NBL
0
100
200
300
400
500
1,700
1,800
No. of Germline Samples
D
E
ALL-NOS
I
NHL
I
HL
Hematologic
ACC
12
TALL
AML
2
AML
BALL
8
6
BALL
EPD
3
2
1
ATRT
EWS
2
1
2
1
ACPG
HGG
6
4
4
2
5
EPD
CNS
HL
4
LGG
LGG
2
1
2
HGG
MB
3
1
4
4
1
MB
NBL
6
2
3
5
3
ACC
NHL
5
1
4
1
LIC
OS
6
3
2
MEL
RB
3
1
GCT
RMS
1
EWS
I
TALL
2
RB
Solid
WLM
2
RMS
OS
ATM
BARD 1
BRCA 1
BRCA2
BRIP1
CUL4A
DDB 1
ERCC4
FANCE
FEN1
HELQ
INO80
MLH 1
MUS81
NHEJ1
OGG1 PARG
PARP2
PMS2
POLD 1
POLD2
POLL
POLM
RFC3
RMI 1
SMARCAL 1
SMC5
SPIDR
SSBP1
TDG
TP53
TP53BP1
UBE2T
XRCC3
XRCC4
WLM
NBL
-log10(FDR)
0
20
40
60
0 10 20 30
Germline Variants in DDR Genes (%)
FIG 1. (Continued). Among 5,993 pediatric cancer samples, 6,636,054 variants passed quality control. Filtering by predicted functional impact (frameshift, nonsense, missense, and splicing) yielded 2,536,772 variants, of which 1,403,469 were rare (gnomAD v2.1 AF <0.05%). Restriction to DDR genes identified 10,368 variants, with 1,881 meeting predisposing filtering criteria. (D) The prevalence of DDR PV across 22 pediatric cancers is shown as the fraction of samples in each cancer type harboring a PV in any of the 189 DDR genes. Median prevalence of DDR PV across the three cancer categories is shown with a dashed line. (E) Gene-level burden of pathogenic germline variants. All associations with FDRlogistic <0.25 are shown, whereas those that met significance threshold FDRlogistic <0.05 are highlighted with black border. Color intensity represents log10[FDRlogistic]. Number of variants for respective cancer:gene pairs are indicated. ACC, adrenocortical carcinoma; ACPG, adamantinomatous type craniopharyngioma; ADSP, Alz- heimer’s Disease Sequencing Project; AF, allele frequency; ALL-NOS, acute lymphoblastic leukemia- not otherwise specified; AML, acute myeloid leukemia; ATRT, atypical teratoid/rhabdoid tumor; BALL, B-cell ALL; CCSS, Childhood Cancer Survivorship Study; DDR, DNA damage repair; EPD, ependymoma; EWS, Ewing sarcoma; FDR, false discovery rate; G4K, Genomes4Kids; CPS-GCCR, Cancer Predisposition Syndrome-German Childhood Cancer Registry; GCT, germ cell tumor; HGG, high-grade glioma; HL, Hodgkin lymphoma; INFORM, Individualized Therapy for Relapsed Malignancies in Childhood; LGG, low-grade glioma; LIC, liver cancer; MB, medullo- blastoma; MEL, melanoma; NBL, neuroblastoma; NHL, non-Hodgkin lymphoma; OS, osteosarcoma; P/LP, pathogenic/likely path- ogenic; PCGP, Pediatric Cancer Genome Project; PV, predisposing variants; QC, quality control; RB, retinoblastoma; RMS, rhabdomyosarcoma; RTCG, St Jude Real-time Clinical Genomics; SJLIFE, St Jude Lifetime Cohort; TALL, T-cell acute lymphoblastic leukemia; WLM, Wilms tumor.
Variant Calling and Filtering for the Discovery Cohort
Germline variants in 189 DDR genes were identified through joint genotyping of whole exome sequencing (WES) data from cases and controls and filtered for rarity (minor allele frequency [AF] <0.05% in gnomAD v2.1 noncancer subset; Supplementary Methods and Data Supplement, Table S2).8,9,17 To identify PV, a tiered filtering strategy was employed using a combination of American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines as per ClinVar pathogenic/ likely pathogenic (P/LP) database (2025-06-23), InterVar automated classification tool (P/LP), and in silico predic- tions (REVEL >0.7, CADD >20, MetaSVM damaging; Sup- plementary Methods and Data Supplement, Fig S1).18,19 For replication analysis, an identical filtering strategy for germline PV was applied across replication cohorts (CCSS, INFORM, and CPS-GCCR) and adult noncancer controls (gnomAD v2.1).
Statistical Analysis
We performed a gene-based burden analysis for germline PV in pediatric cancer cohort versus noncancer controls using logistic regression (false discovery rate [FDR]logistic) and Firth regression (FDRFirth; Supplementary Methods). For replication analysis, Fisher exact test (PFisher) was used to calculate enrichment of germline PV in cases versus controls. Comparison of age at cancer diagnosis between DDR germline variant carriers and noncarriers was completed as described in the Supplementary Methods.
RESULTS
Germline Variants in DDR Genes Across Tumor Types
The discovery cohort included 5,993 children and adoles- cents with 22 cancer subtypes, classified as hematologic, solid, and CNS tumors (Figs 1A and 1B). The median age at
cancer diagnosis was 6 years (range, 4 days to 32 years) with most cases (67%) of European ancestry (Data Supplement, Table S3). Across cancers, 6,636,054 germline variants were analyzed to retain 1,881 rare, PV among 189 DDR genes (Fig 1C, Data Supplement, Table S4). Frequency of PV was similar across hematologic (27.6% [range, 24.8%-31.4%]), solid (29.3% [18.8%-59.3%]), and CNS cancers (27.2% [23.3%-34.5%]; P = . 9, Kruskal-Wallis test) but varied across cancer subtypes, such as rhabdomyosarcoma (19%) and adrenocortical carcinoma (ACC, 59%; Fig 1D).
Confirmation of Known Associations of Germline DDR PV With Childhood Cancers
Overall, 1,561 of 5,993 (26%) childhood cancer cases har- bored PV in one or more DDR genes. We observed a signif- icant enrichment of PV in TP53 compared with jointly called adult noncancer controls (n = 14,477; 37/5,993, 0.6%, FDRlogistic = 0.0013; odds ratio [OR], 3.2 [95% CI, 1.9 to 5.4]), supporting its critical role in maintaining genome stability (Data Supplement, Table S5). We next performed rare variant burden analysis to identify associations of DDR genes across children with pediatric cancers and observed several pre- viously described associations, which serve as an internal validation of our analytic pipeline. For example, TP53 PV were enriched in ACC (12/27, 44%, FDRlogistic < 0.0001; OR, 426.7 [95% CI, 182.1 to 999.5]), high-grade glioma (HGG; 5/ 206, 2.4%, FDRlogistic = 0.0011; OR, 12.5 [95% CI, 4.4 to 29.9]), and medulloblastoma (MB; 4/257, 1.6%, FDRlogistic = 0.0011; OR, 12.5 [95% CI, 4.4 to 29.9]; Figs 1E and 2A; Table 1; Data Supplement, Tables S5 and S6).2,20 Furthermore, we confirmed biallelic inactivation of TP53 in all corresponding tumors examined (Data Supplement, Fig S2).
Enrichment of PV was also observed in mismatch repair (MMR) genes, including PMS2 (4/206, 1.9%, FDRlogistic = 0.017; OR, 10.1 [3.2 to 24.9]) and MLH1 (4/206, 1.9%, FDRlogistic = 0.019; OR = 9.6 [3.0 to 23.5]) among HGG, as well as PMS2 in non- Hodgkin lymphoma (NHL; 4/239, 1.7%; FDRlogistic = 0.0366;
SMARCAL1 Germline Variation and Pediatric Osteosarcoma
A
R110Pfs*39
c.375+1G>A
E1035*
A938Pfs*21
V157F
N311Kfs*26
c. 1101-2A>G
R196*
V218M
G266E
R273C
E285V
R337H
NHL
K936Nfs*24
O
O
E1571Gfs*3
Q3066*
ACC
2
BRCA2 NM_000059
TP53
NM_000546
500
1,000
1,500
2,000
2,500
3,000
50
100
150
200
250
300
350
BRCA2 repeats
BRCA2_helical
BRCT
OB folds
HGG
R158H
C242F
R2480
R273C
V274Lfs#31
MB
EPD
T1684S G1788V
OG462R
TAD
P53
P53 tetramer
G245S
R2480
P250T
R273H
BRCA1
NM_007294
1611Nfs#2
200
400
600
800
1,000
1,200
1,400
1,600
1,800
HGG
RING
BRCT_assoc
BRCT
D414Rfs*44
2
Q643*
G750D
PMS2
NM_000535
HGG
NHL
100
200
300
400
500
600
700
800
Y208Kfs*18
Y383*
R199C
V306A
1611Nfs#2
R802*
SPIDR
NM_0010-
MutL
ATPase
PMS2 transducer
80394
100
200
300
400
500
600
700
800
900
A31C
DUF4502ª
DUF4503ª
HGG
R69K
G336D
K461*
MLH1
NM_000249
E126Vfs*12
c.380+1G>C
100
200
300
400
500
600
700
MutL
MLH1
MB
C417*
N940Y
L95Kfs#2 R112*
SMC5
NBL
NM_015110
Y180*
L447V
_480S
R641*
100
200
300
400
500
600
700
800
900
1,000
1,100
BARD1
P-loop NTPase
Coiled Coil
NM_000465
100
200
300
400
500
600
700
Frameshift
Splice
Missense
RING
ANK repeat
BRCT
Nonsense
B
Somatic Mutational Signatures
C
TP53:p.E285V
TP53:p.R337H
ACC
SMC5: wild-type
[0 - 138]
76
3
TP53:p.R337H
PMS2:p.Q643*
1
1
1
1
1
1
PMS2:p.I611Nfs*2
5
1
1
1
3
1
1
PMS2:p.D414Rfs*44
HGG
73
PMS2:p.G750D
SMC5:c.380+1G>C
MLH1:p.K461*
[0 - 88]
23
1 5
3
PMS2:p.I611Nfs*2
NHL
20
8 2
1
BARD1:p.L447V
BARD1:p.L480S
NBL
1
1
1
7
SMC5:c.380+1G>C
SMC5 [NM_015110]
21
SMC5:p.C417*
SMC5:p.N940Y
MB
Exon 1
Exon 2
+
Exon 3
Exon 4 Exon 5
0
25
50
75
100
%
☐ SBS1
Age
☐ SBS7b- UV exposure Late replication
☐ SBS 13- APOBEC activity
☐ SBS 18- ROS damage
☐ SBS5
☐ SBS8-
☐
☐ Artifact
errors
☐ SBS 14
☐ SBS 15
Defective MMR
☐ SBS31
Chemotherapy (platinum drugs)
Unassigned
☐ SBS35
☐ SBS26
TABLE 1. Enrichment of Known Associations in Pediatric Cancers From Discovery Cohorts
Discovery Analysis: Known Associations
| Gene | Cancer | Frequency in Cases | Frequency in Controls | Cancer Risk | ||
|---|---|---|---|---|---|---|
| OR (95% CI) | Plogistic | FDRlogistic | ||||
| TP53 | ACC | 12 in 27 (44.44%) | 27 in 14,477 (0.19%) | 426.7 (182.1 to 999.5) | 1.35E-43 | 4.86E-40 |
| TP53 | HGG | 5 in 206 (2.43%) | 27 in 14,477 (0.19%) | 12.5 (4.4 to 29.9) | 8.85E-07 | 0.001 |
| PMS2 | HGG | 4 in 206 (1.94%) | 39 in 14,477 (0.27%) | 10.1 (3.2 to 24.9) | 4.03E-05 | 0.017 |
| MLH1 | HGG | 4 in 206 (1.94%) | 42 in 14,477 (0.29%) | 9.6 (3.1 to 23.6) | 5.31E-05 | 0.019 |
| BARD1 | NBL | 6 in 485 (1.24%) | 31 in 14,477 (0.21%) | 6.3 (2.4 to 13.9) | 8.80E-05 | 0.023 |
| PMS2 | NHL | 4 in 239 (1.67%) | 40 in 14,477 (0.28%) | 8.1 (2.6 to 20) | 2.03E-04 | 0.037 |
| TP53 | MB | 4 in 257 (1.56%) | 28 in 14,477 (0.19%) | 8.2 (2.6 to 20.7) | 2.47E-04 | 0.040 |
| BRCA2 | NHL | 5 in 239 (2.09%) | 51 in 14,477 (0.35%) | 6.2 (2.2 to 14) | 2.62E-04 | 0.041 |
Abbreviations: ACC, adrenocortical carcinoma; FDR, false discovery rate; HGG, high-grade glioma; MB, medulloblastoma; NBL, neuroblastoma; NHL, non-Hodgkin lymphoma; OR, odds ratio.
OR = 8.1 [2.6 to 20.0]).21,22 Analysis of tumor data revealed that six of the 10 MMR PV carriers (5 HGG and 1 NHL) exhibited an ultra/hypermutator phenotype and somatic mutational signatures consistent with defective MMR (SBS14, SBS15, and SBS26; Fig 2B, Supplementary Table S6), whereas four cases did not exhibit defective MMR and tumor data were unavailable for two. Of the six ultra/ hypermutator cases, five had constitutional MMR defi- ciency and HGG, while the sixth case was a PMS2 carrier with NHL, whose tumor exhibited a second PMS2 hit. Germline PV in BARD1, a recently identified neuroblastoma (NBL) predisposition gene, were also identified (6/485, 1.2%; FDRlogistic = 0.0227; OR, 6.3 [95% CI, 2.4 to 13.9]; Fig 2A).23 Two of the six BARD1 carriers with available tumor data exhibited somatic mutational signature pre- viously observed in NBL (SBS18; Fig 2B).24 Finally, we observed enrichment for BRCA2 PV in NHL (5/239, 2.1%, FDRlogistic = 0.0411; OR, 6.2 [95% CI, 2.2 to 14.0]; Fig 2A), an association previously described in long-term survivors of childhood cancer.25
Novel Associations of Germline DDR PV With Childhood Cancers
In addition to known associations, we identified four novel associations, including BRCA1 in ependymoma (EPD), SPIDR
in HGG, SMC5 in MB, and SMARCAL1 in osteosarcoma (OS; Table 2, Data Supplement, Table S5). To this end, three cases of EPD carried BRCA1 PV (3/146, 2.1%; FDRlogistic = 0.0366; OR, 11.6 [95% CI, 3.1 to 31.6]). All three missense variants were within the BRCT and BRCT-associated domains (Fig 2A). Tumor WES showed no second hits in any of these tumors, and RNA expression of BRCA1 in carriers was comparable with EPD lacking germline CPG PV (Data Supplement, Fig S3). Next, heterozygous truncating variants in SPIDR, a gene that encodes a scaffold protein involved in homologous recombination, were identified in two HGG (2/ 206, 1%; FDRlogistic = 0.0366; OR, 25.2 [95% CI, 4.5 to 101.1]; Fig 2A). Analysis of tumor WES and RNAseq from the SPIDR: p.Y383* mutated case revealed two somatic TP53 mutations and reduced SPIDR RNA expression (Data Supplement, Figs S2 and S3). No tumor whole genome sequencing (WGS) data were available to determine whether there was loss of heterozygosity (LOH) at the SPIDR locus. Next, germline PV in SMC5, the gene encoding Structural Maintenance of Chromosome 5, were enriched in MB (4/257, 1.6%; FDRlogistic = 0.0005; OR, 21.6 [95% CI, 6.4 to 60.1]; Fig 2A). SMC5 is important for chromosome maintenance with biallelic germline alterations associated with the rare neurodevelopmental disorder, Atelis syndrome-2.26 All four germline SMC5 mutant cases were of the group 3 MB subtype and the SMC5:MB association was even stronger
| Gene | Cancer | Frequency in Cases | Frequency in Controls | Cancer Risk | ||
|---|---|---|---|---|---|---|
| OR (95% CI) | Plogistic | FDRlogistic | ||||
| SMC5 | MB | 4 in 257 (1.56%) | 12 in 14,477 (0.08%) | 21.6 (6.4 to 60.1) | 2.70E-07 | 4.87E-04 |
| SMARCAL1 | OS | 6 in 230 (2.61%) | 59 in 14,477 (0.41%) | 6.3 (2.5 to 13.6) | 6.54E-05 | 0.019 |
| BRCA1 | EPD | 3 in 146 (2.05%) | 35 in 14,477 (0.24%) | 11.6 (3.1 to 31.6) | 1.77E-04 | 0.037 |
| SPIDR | HGG | 2 in 206 (0.97%) | 6 in 14,477 (0.04%) | 25.2 (4.5 to 101.1) | 1.91E-04 | 0.037 |
Abbreviations: EPD, ependymoma; FDR, false discovery rate; HGG, high-grade glioma; MB, medulloblastoma; OR, odds ratio; OS, osteosarcoma.
when only group 3/4 MB were included in the analysis (4/88 cases, 4.5%; FDRlogistic < 0.0001; OR, 54.6 [95% CI, 16.0 to 156.0]; Data Supplement, Table S5). Tumor RNAseq and WES data were available for all four SMC5 germline variant carriers, whereas WGS was available for three. The MB tumor associated with the germline c.380+1G>C alteration showed exon 3 skipping in approximately 50% of SMC5 transcripts, resulting in an out-of-frame tran- script accompanied with reduced SMC5 expression (Fig 2C, Data Supplement, Fig S3). The p.N940Y germline carrier exhibited a second somatic hit in the tumor, SMC5: p.Q357K, but we could not establish allelic configuration of the two variants. This tumor also exhibited SBS8, a DNA mutational signature associated with late replication er- rors (Fig 2C), suggesting altered SMC5 function during mitotic progression.27
Finally, SMARCAL1 PV were enriched within OS cases (6/230, 2.6%; FDRlogistic = 0.0189; OR, 6.3 [95% CI, 2.5 to 13.6]; Fig 3A, Data Supplement, Tables S5 and S6). SMARCAL1 encodes the SNF2-related chromatin remodeling annealing helicase, which resolves stalled replication forks.28 Germline biallelic SMARCAL1 inactivation causes Schimke immuno- osseous dysplasia (SIOD) typified by skeletal, renal, and hematologic clinical abnormalities. We identified four protein-truncating variants (p.R114Qfs*4, p.L139Efs*3, p.L397Rfs*40, and p.Q653*) and two missense variants (p.R820H and p.R490C) located in the helicase domain (Figs 3B and 3C, Data Supplement, Table S6). Considering that OS is commonly observed in Li-Fraumeni syndrome, we confirmed the absence of germline TP53 mutations in the six germline SMARCAL1-mutated cases. Matched tumor WES and RNAseq data were available for two cases, which did not reveal a somatic second hit in SMARCAL1. The germline p.R114Qfs*4-mutated OS harbored a somatic ATRX:p.P717Hfs*4 mutation. Tumor RNAseq from this case showed unaffected SMARCAL1 expression, while the germline p.Q653 *- mutated case demonstrated reduced SMARCAL1 RNA expression (Data Supplement, Fig S3). However, additional genomic alterations associated with this reduced SMARCAL1 expression could not be ascertained in the absence of tumor WGS data.
Clinical Features Associated With Germline DDR Gene Variants
Patients with germline CPG PV are often younger at tumor onset than individuals with sporadic cancers. Therefore, we analyzed the ages of cancer onset in DDR PV carriers versus noncarriers and identified only one association with a significant difference, namely, a younger age of onset of TP53 carriers with ACC (Data Supplement, Table S7). Overall, family history was available for 37 of 59 PV patients and was positive for 14 of these cases with a mix of related and unrelated malignancies (Data Supplement, Table S6). For four OS cases with germline SMARCAL1 variants, we did not identify any renal, skeletal, or im- munodeficiency abnormalities typically seen in SIOD;
however, in two cases, we observed simple renal cysts (Bosniak I/II).
Replication of SMARCAL1 as a Novel OS Predisposition Gene
To replicate the four novel associations, we queried three additional pediatric cancer cohorts (CCSS, CPS-GCCR, and INFORM). Two associations reached significance in only one of the three cohorts: BRCA1:EPD in INFORM (2/143; 1.4%; PFisher = . 018; OR, 10.02 [95% CI, 1.2 to 37.1]) and SMC5:MB in CPS-GCCR (1/31; 3.2%; PFisher = . 028; OR, 36.6 [95% CI, 0.9 to 215.2]; Data Supplement, Table S8). Importantly, enrich- ment of SMARCAL1 in OS was significant across all three cohorts: CCSS (8/275 cases; 2.9%; PFisher < . 0001; OR, 7.4 [95% CI, 3.1 to 14.7]); CPS-GCCR (4/135 cases; 3%; PFisher = .002; OR, 7.5 [95% CI, 2.0 to 19.6]); and INFORM (4/217 cases; 1.8%; PFisher = . 012; OR, 4.6 [95% CI, 1.3 to 12.0]). In total, 12 unique germline SMARCAL1 PV were identified among 16 individuals, of which two were also observed in the discovery cohort (p.L139Efs*3 and p.L397Rfs*40). Among the 10 remaining variants, three were protein- truncating (p.F941Lfs*31, p.R563*, and p.E848*), three were canonical splice-site (c.863-2A>G, c.1335-2A>T, and c.2070+2dup) and four were missense (p.F801V, p.A838T, p.G857R, and p.F279S) variants located in functionally rele- vant domains (Fig 3).28 Germline TP53 variants were not found among any SMARCAL1 variant carriers; however, two cases harbored PV in NF2 and MLH1 (Fig 3B).29 In sum, the prev- alence of germline PV in OS cases was 16/627 or 2.6% (PFisher < .0001, OR, 6.4 [95% CI, 3.6 to 10.6]), which is similar to the 2.6% prevalence in the discovery cohort (Figs 3A and 3B; Data Supplement, Tables S8 and S9).
Tumor WGS data were available for all four INFORM cases. We observed SMARCAL1 LOH in three relapsed OS tumors because of copy-number deletion (Data Supplement, Fig S4). Three of four tumors also had RNAseq data available, two of which (c.1335-2A>T and p.E848*) exhibited low SMARCAL1 expression (Data Supplement, Fig S5). Loss of SMARCAL1 has been associated with alternative lengthening of telo- meres (ALT).28 To this end, we observed all four OS tumors in the replication cohort to be ALT-positive as determined by TelomereHunter (Data Supplement).3º In addition, we assessed tumor genomic data in these four cases for alter- ations in ALT-associated genes ATRX, DAXX, and H3F3A, and did not observe somatic or germline mutations (N = 4 WES) or reduction in RNA expression (N = 3 RNAseq) in these genes (Fig 3B, Data Supplement, Fig S5). These data suggest that loss of SMARCAL1 function may induce ALT, a potential mechanism for promoting OS.
DISCUSSION
Highly penetrant CPS result from germline variations in DDR genes. To date, comprehensive studies investigating the germline landscape of DDR alterations in pediatric cancers have been lacking, in part because of limited case-control
A
R114Qfs*4
L139Efs*3
L397Rfs*40
R490C
Q653*
R820H
Discovery Cohort
SMARCAL 1 NM_014140
100
200
300
400
500
600
700
800
900
Replication Cohort
☒
2
☒
L139Efs*3
F279S
c.863-2A>G
L397Rfs*40
c. 1335-2A>T
R563*
c.2070+2
4
F801V
A838T
E848*
G857R
F941Lfs*31
RBD
HARP
Helicase
☒ Frameshift
☒ Nonsense
☒ Splice
☒ Missense
B
Discovery
Replication
INFORM
CCSS
CPS-GCCR
Clin Var classification
Variant type
ClinVar
☐ Missense
Cancer Relapse
☐ P
☐ LP
☐ Stopgain
Tumor Availability
☐ VUS
☐ Frameshift
☐ Splicing
gnomADv4.1 AF
☐ NA
☐ Inframe InDel
REVEL Score
1
Relapse ☐ Yes
☐ Deletion
0.5
gnomAD (v4.1) AF
CADD Score
0 50
☐ No
☐ <0.001%
Tumor availability
☐ 0.001%-0.01%
SMARCAL 1
0
☐ 0.1%-0.5%
☐ Yes
Pathogenic Germline
MLH1
☐ No
Variants
NF2
RB1
Biallelic in tumor ☒ Biallelic
CDKN2A/B
Pathogenic Somatic Variants
TP53
☐ Monoallelic
BAP1
NF2
ATRX
C
D
R490C
R820Hª
2.6% carrier frequency in osteosarcoma
Osteosarcoma development
Wild-type SMARCAL1
Somatic second hit in ALT genes (SMARCAL1, ATRX, etc)
F801Vª
Germline variants in SMARCAL 1
G857Rª
A838T
Genomic integrity
Genomic instability
F279Sª
Efficient DNA replication and repair
Replication stress High DNA repair demand
Replication fork breaks Double-strand breaks High DNA damage
FIG 3. (Continued). annotations for biallelic status (\), tumor relapse status, and tumor availability. (C) SMARCAL1 protein structure predicted by AlphaFold. Missense variants in discovery (green) and replication (purple) cohorts are shown. Protein domains HARP: HepA- related protein (blue) and helicase (red) are shown. (D) Proposed model of SMARCAL1-mediated OS predisposition. SMARCAL1 is im- portant for accurate DNA replication and repair to reinforce genome integrity. Approximately 2.6% of OS cases carry a predisposing variant in SMARCAL1, negatively affecting SMARCAL1 function and exacerbating genome instability with tumor acquisition of somatic second hits in genes known to permit ALT (SMARCAL1 LOH, ATRX inactivation), resulting in OS development. ªVariants predicted as LP by Alpha- Missense. AF, allele frequency; ALT, alternative lengthening of telomeres; CCSS, Childhood Cancer Survivorship Study; CPS-GCCR, Cancer Predisposition Syndrome-German Childhood Cancer Registry; INFORM, Individualized Therapy for Relapsed Malignancies in Childhood; LOH, loss-of-heterozygosity; NA, not available; OS, osteosarcoma; P/LP, pathogenic/likely pathogenic; PV, predisposing variants; VUS, variants of uncertain significance.
designs that harmonize batch effects from library prepa- ration, sequencing platforms, and variant calling pipelines necessary for identifying novel CPG. We remapped raw sequencing data and performed joint genotype calling across 5,993 pediatric cancer cases and 14,477 adult non- cancer controls, followed by stringent filtering for rare, protein-damaging variants. Through this approach, we established a 26% prevalence of putative damaging vari- ants in DDR genes across childhood cancers. Statistical testing confirmed known associations, including germline TP53 in ACC, HGG, and MB, PMS2 in HGG and NHL, MLH1 in HGG, BARD1 in NBL, and BRCA2 in NHL. We also discovered four novel associations, including BRCA1 in EPD, SPIDR in HGG, SMC5 in MB, and SMARCAL1 in OS. Notably, among these, we confirmed statistical enrichment of germline SMARCAL1 PV across all three of our replication cohorts, providing compelling evidence for its role as a novel OS predisposition gene.
Germline SMARCAL1 variants were found in 2.6% of all OS cases, with two thirds predicted to cause haploinsufficiency because of protein truncation and one third composed of putative damaging missense variants. Ballinger et al pre- viously reported germline truncating SMARCAL1 variants in 19 sarcoma cases including two OS, while Akhavanfard et al identified SMARCAL1 in three OS cases from the SJLIFE cohort.31,32 Ballinger et al also reported LOH in five of 19 sarcomas with germline SMARCAL1 variants.31 Importantly, a recent study identified 1.8% of osteosarcoma cases to harbor germline SMARCAL1 variants, strengthening our finding.38 Two cases of OS have been reported in individuals with SIOD, suggesting that OS is associated with SMARCAL1 dysfunc- tion.33 Genotype-level comparison of germline SIOD and OS PV reveals overlap (Data Supplement, Fig S6); however, the rarity and short lifespan (median age of death: 11 years) of individuals with SIOD preclude us from accurately assessing the prevalence and penetrance of OS in this context. No other germline alterations in OS-relevant CPG were iden- tified in our cases, which supports SMARCAL1 as an inde- pendent risk factor for OS.34 Seven of 13 OS cases (54%) with available clinical information experienced disease relapse, suggesting that SMARCAL1-associated cases may be more aggressive. Nevertheless, longitudinal studies are needed to assess the penetrance and clinical features of OS associated with germline SMARCAL1 variation. Somatic SMARCAL1 deficiency in glioblastoma causes ALT-mediated telomere
synthesis.28,35 Similarly, ALT appeared active in four tu- mors, three of them with biallelic SMARCAL1 alterations. A fifth tumor harbored an inactivating ATRX mutation, which may contribute to ALT.36 Altogether, these data suggest that SMARCAL1 is a tumor suppressor, whereby loss of SMARCAL1 protein function impairs DNA replication and repair, leading to acquisition of an ALT phenotype or so- matic mutations in ALT-permissive genes, and ultimately resulting in OS formation (Fig 3D).
The following limitations should be considered when interpreting the results of this study. We were unable to validate the three additional novel gene:cancer associations identified in this study across each of our replication cohorts. This finding may be due to the low sample sizes for specific cancer types in the replication cohorts. To achieve adequate statistical power, we combined high-risk primary cancers with presumably lower-risk cancers from adult survivors of childhood cancer, which may have diluted genetic signals and added survival bias (Data Supplement, Figs S7 and S8). The variant filtering criteria were rigorous, and it is possible that additional clinically relevant germline variants with less stringent in silico scores remain undescribed. To evaluate this possibility for SMARCAL1 in OS, we relaxed the missense filtering threshold to REVEL >0.5 across the discovery and replication cohorts and identified two additional germline SMARCAL1 variants (p.D424V and p.K27E) in three unrelated cases with relapsed OS from the INFORM cohort (data not shown). Matched tumor data from two of three cases with D424V revealed SMARCAL1 LOH; however, we have not in- cluded these cases in the current study to maintain con- sistency across our discovery and replication analyses. Given the sparse tumor data available, expanded tumor sequencing is needed to validate SMARCAL1 biallelic inactivation patterns observed herein. Finally, we could not establish the mode of inheritance or cosegregation with other cancers for many of the identified variants because of lack of familial testing. Future efforts examining the relatives of germline SMAR- CAL1 PV carriers are needed as this information may serve to strengthen existing evidence. Ultimately, the role of germline SMARCAL1 variation in OS tumorigenesis requires further investigation.
In summary, we demonstrate the importance of DDR pathway perturbations in predisposition to childhood cancer by validating known and discovering novel DDR gene:cancer
associations. Our finding that germline damaging variants in SMARCAL1 predispose to OS serves as a foundation for future studies aimed at developing novel therapies for this aggressive cancer, one for which there have been little
advances in treatment over the past four decades.37 Similarly, genetic testing for germline SMARCAL1 PV will enable pro- spective surveillance of germline carriers to detect and treat incipient OS tumors at their earliest and most curable stages.
AFFILIATIONS
1Department of Oncology, St Jude Children’s Research Hospital, Memphis, TN
2Center for Applied Bioinformatics, St Jude Children’s Research Hospital, Memphis, TN
3Division of Computational Biology, Mayo Clinic, Rochester, MN
4Hopp Children’s Cancer Center Heidelberg (KiTZ), Heidelberg, Germany 5Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
6German Cancer Consortium (DKTK), Heidelberg, Germany
7Department of Pediatric Oncology, Hematology and Immunology, Heidelberg University Hospital, Heidelberg, Germany
8Department of Human Genetics, Institute of Human Genetics, Heidelberg University Hospital, Heidelberg, Germany
9Pediatric Hematology and Oncology, Hannover Medical School, Hannover, Germany
10Department of Human Genetics, Hannover Medical School, Hannover, Germany
11Division of Pediatric Glioma Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
12National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
13CCU Pediatric Oncol, German Cancer Research Center (DKFZ), Heidelberg, Germany
14Pediatrics III, West German Cancer Center University Hospital Essen, Essen, Germany
15German Cancer Consortium (DKTK) Site Essen, Essen, Germany
16National Center for Tumor Diseases (NCT) Site Essen, Essen, Germany
17Department of Biostatistics, St Jude Children’s Research Hospital, Memphis, TN
18Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, TN
19Department of Computational Biology, St Jude Children’s Research Hospital, Memphis, TN
20Department of Pathology, St Jude Children’s Research Hospital, Memphis, TN
21 Department of Hematology, St Jude Children’s Research Hospital, Memphis, TN
22Department of Pediatric Hematology Oncology and Blood and Marrow Transplantation, Cleveland Clinic Children’s, Cleaveland, OH
PREPRINT VERSION
This study was posted on medRxiv preprint server on May 13, 2025 (https://www.medrxiv.org/content/10.1101/2025.05.12.25325832v2).
CORRESPONDING AUTHOR
Richa Sharma, MD; e-mail: sharmar19@ccf.org.
EQUAL CONTRIBUTION
R.J.A, K.E.N., and R.S contributed equally to this work.
SUPPORT
Supported by the American Lebanese Syrian associated charities and by the following National Cancer Institute grants, R01CA283333 (Zhaoming Wang and Kim E. Nichols), The St. Jude Lifetime Cohort (SJLIFE) (CA195547, M.M. Hudson, K.K. Ness), and The Childhood Cancer Survivor Study (CCSS) (CA55727, G.T. Armstrong). This study was also supported in part by Deutsche Kinderkrebsstiftung DKS 2021.02 (Christian P. Kratz). Funding for this study was provided by the American Lebanese Syrian Associated Charities. This study was supported by the following National Cancer Institute grants: R01CA283333 (Z.W. and K.E.N.), The St Jude Lifetime Cohort (SJLIFE; CA195547, M.M.H., K.K.N.), and The Childhood Cancer Survivor Study (CCSS; CA55727, G.T.A.). This study was also supported by Deutsche Kinderkrebsstiftung DKS 2021.02 (C.K.). The INFORM program is financially supported by the German Cancer Research Center (DKFZ), several German health insurance companies, the German Cancer Consortium (DKTK), the German Federal Ministry of Education and Research (BMBF), the German Federal Ministry of Health (BMG), the Ministry of Science, Research, and the Arts of the State of Baden- Württemberg (MWK BW); the German Cancer Aid (DKH), the German Childhood Cancer Foundation (DKS), RTL television, the aid organization BILD hilft e.V. (Ein Herz für Kinder), and the generous private donation of the Scheu family. The authors would like to express their sincere thanks to Carsten Maus, Erjia Wang (Next Generation Sequencing Core Facility, DKFZ), Lena Weiser and Gregor Warsow (Omics IT and Data Management Core Facility, DKFZ) for their highly dedicated support in data management and processing, and Rolf Kabbe (Division of Pediatric Neurooncology, DKFZ) for his sincere and dedicated contribution to the bioinformatics analyses. Biostatistics support is provided by the Biostatistics Shared Resource (BSR) of the St Jude Children’s Research Hospital and St Jude Comprehensive Cancer Center (NIH P30CA021765).
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
Disclosures provided by the authors are available with this article at DOI https://doi.org/10.1200/JCO-25-01114.
DATA SHARING STATEMENT
A data sharing statement provided by the authors is available with this article at DOI https://doi.org/10.1200/JCO-25-01114.
The processed genomic data generated in this study are provided in the Supplementary Tables. Controlled-access raw genomic data can be requested via St Jude Cloud at https://platform.stjude.cloud/. The Childhood Cancer Survivor Study is a US National Cancer Institute- funded resource (U24 CA55727) to promote and facilitate research among long-term survivors of cancer diagnosed during childhood and adolescence. CCSS data are publicly available on the St Jude Survivorship Portal within the St Jude Cloud at https://
survivorship.stjude.cloud/. In addition, use of the CCSS data that leverage the expertise of CCSS Statistical and Survivorship research and resources will be considered on a case-by case basis. For this use, a research Application of Intent followed by an Analysis Concept Proposal must be submitted for evaluation by the CCSS Publications Committee. Users interested in accessing this resource are encouraged
SMARCAL1 Germline Variation and Pediatric Osteosarcoma
to visit http://ccss.stjude.org. Full analytical data sets associated with CCSS publications since January 2023 are available on the St Jude Survivorship Portal at https://viz.stjude.cloud/community/cancer- survivorship-community~4/publications. Any additional data are available upon request from the corresponding author.
AUTHOR CONTRIBUTIONS
Conception and design: Ninad Oak, Wenan Chen, Gang Wu, Kim E. Nichols, Richa Sharma
Financial support: Kim E. Nichols, Zhaoming Wang, Kirsten K. Ness, Greg T. Armstrong, Melissa M. Hudson, Stefan M. Pfister
Administrative support: Ninad Oak, Lynn Harrison, Gang Wu, Kim E. Nichols, Richa Sharma
Provision of study materials or patients: Ninad Oak, Kendra Maass, Judith Penkert, Kristian W. Pajtler, Olaf Witt, Uta Dirksen, Stefan M. Pfister, Greg T. Armstrong, Melissa M. Hudson, Kim E. Nichols Collection and assembly of data: Ninad Oak, Wenan Chen, Alise Blake, Lynn Harrison, Martha O’Brien, Kendra Maass, Steffen Hirsch, Judith
Penkert, Barbara C. Jones, Michaela Nathrath, Kristian W. Pajtler, David T.W. Jones, Olaf Witt, Uta Dirksen, Stefan M. Pfister, Christian Kratz, Zhaoming Wang, Greg T. Armstrong, Melissa M. Hudson, Gang Wu, Robert J. Autry, Kim E. Nichols, Richa Sharma
Data analysis and interpretation: Ninad Oak, Wenan Chen, Alise Blake, Martha O’Brien, Christopher Previti, Gnanaprakash Balasubramanian, Steffen Hirsch, Kathrin Schramm, Olaf Witt, Jiaming Li, Yadav Sapkota, Kirsten K. Ness, Lillian M. Guenther, Zhaoming Wang, Greg T. Armstrong, Melissa M. Hudson, Gang Wu, Robert J. Autry, Kim E. Nichols, Richa Sharma
Manuscript writing: All authors
Final approval of manuscript: All authors
Accountable for all aspects of the work: All authors
ACKNOWLEDGMENT
The authors thank the patients and families included in this study and the members of the St Jude Clinical Genomics Laboratory, without whom this work would not have been possible.
REFERENCES
1. Zhang J, Walsh MF, Wu G, et al: Germline mutations in predisposition genes in pediatric cancer. N Engl J Med 373:2336-2346, 2015
2. Gröbner SN, Worst BC, Weischenfeldt J, et al: The landscape of genomic alterations across childhood cancers. Nature 555:321-327, 2018
3. Newman S, Nakitandwe J, Kesserwan CA, et al: Genomes for kids: The scope of pathogenic mutations in pediatric cancer revealed by comprehensive DNA and RNA sequencing. Cancer Discov 11: 3008-3027, 2021
4. Fiala EM, Jayakumaran G, Mauguen A, et al: Prospective pan-cancer germline testing using MSK-IMPACT informs clinical translation in 751 patients with pediatric solid tumors. Nat Cancer 2: 357-365, 2021
5. Wagener R, Taeubner J, Walter C, et al: Comprehensive germline-genomic and clinical profiling in 160 unselected children and adolescents with cancer. Eur J Hum Genet 29:1301-1311, 2021
6. Ripperger T, Bielack SS, Borkhardt A, et al: Childhood cancer predisposition syndromes-A concise review and recommendations by the Cancer Predisposition Working Group of the Society for Pediatric Oncology and Hematology. Am J Med Genet A 173:1017-1037, 2017
7. Blake A, Perrino MR, Morin CE, et al: Performance of tumor surveillance for children with cancer predisposition. JAMA Oncol 10:1060-1067, 2024
8. Sharma R, Lewis S, Wlodarski MW: DNA repair syndromes and cancer: Insights into genetics and phenotype patterns. Front Pediatr 8:570084, 2020
9. Qin N, Wang Z, Liu Q, et al: Pathogenic germline mutations in DNA repair genes in combination with cancer treatment exposures and risk of subsequent neoplasms among long-term survivors of childhood cancer. J Clin Oncol 38:2728-2740, 2020
10. Downing JR, Wilson RK, Zhang J, et al: The pediatric cancer genome project. Nat Genet 44:619-622, 2012
11. Ma X, Liu Y, Liu Y, et al: Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours. Nature 555:371-376, 2018
12. Hudson MM, Ness KK, Nolan VG, et al: Prospective medical assessment of adults surviving childhood cancer: Study design, cohort characteristics, and feasibility of the St. Jude Lifetime Cohort Study. Pediatr Blood Cancer 56:825-836, 2011
13. 1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491:56-65, 2012
14. Raghavan NS, Brickman AM, Andrews H, et al: Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer’s disease. Ann Clin Transl Neurol 5:832-842, 2018
15. Robison LL, Armstrong GT, Boice JD, et al: The Childhood Cancer Survivor Study: A National Cancer Institute-supported resource for outcome and intervention research. J Clin Oncol 27:2308-2318, 2009
16. Worst BC, van Tilburg CM, Balasubramanian GP, et al: Next-generation personalised medicine for high-risk paediatric cancer patients-The INFORM pilot study. Eur J Cancer 65:91-101, 2016
17. Karczewski KJ, Francioli LC, Tiao G, et al: The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581:434-443, 2020
18. Richards S, Aziz N, Bale S, et al: Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17:405-424, 2015
19. Li Q, Wang K: InterVar: Clinical interpretation of genetic variants by the 2015 ACMG-AMP guidelines. Am J Hum Genet 100:267-280, 2017
20. Pinto EM, Chen X, Easton J, et al: Genomic landscape of paediatric adrenocortical tumours. Nat Commun 6:6302, 2015
21. Ercan AB, Aronson M, Fernandez NR, et al: Clinical and biological landscape of constitutional mismatch-repair deficiency syndrome: An International Replication Repair Deficiency Consortium cohort study. Lancet Oncol 25:668-682, 2024
22. Negm L, Chung J, Nobre L, et al: The landscape of primary mismatch repair deficient gliomas in children, adolescents, and young adults: A multi-cohort study. Lancet Oncol 26:123-135, 2025 23. Kim J, Vaksman Z, Egolf LE, et al: Germline pathogenic variants in neuroblastoma patients are enriched in BARD1 and predict worse survival. J Natl Cancer Inst 116:149-159, 2024
24. Brady SW, Liu Y, Ma X, et al: Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations. Nat Commun 11:5183, 2020
25. Wang Z, Wilson CL, Armstrong GT, et al: Association of germline BRCA2 mutations with the risk of pediatric or adolescent non-hodgkin lymphoma. JAMA Oncol 5:1362-1364, 2019 26. Grange LJ, Reynolds JJ, Ullah F, et al: Pathogenic variants in SLF2 and SMC5 cause segmented chromosomes and mosaic variegated hyperploidy. Nat Commun 13:6664, 2022
27. Singh VK, Rastogi A, Hu X, et al: Mutational signature SBS8 predominantly arises due to late replication errors in cancer. Commun Biol 3:421, 2020
28. Liu H, Xu C, Diplas BH, et al: Cancer-associated SMARCAL1 loss-of-function mutations promote alternative lengthening of telomeres and tumorigenesis in telomerase-negative glioblastoma cells. Neuro Oncol 25:1563-1575, 2023
29. Chen C, Qin N, Wang M, et al: Cancer germline predisposing variants and late mortality from subsequent malignant neoplasms among long-term childhood cancer survivors: A report from the St Jude Lifetime Cohort and the Childhood Cancer Survivor Study. Lancet Oncol 24:1147-1156, 2023
30. Feuerbach L, Sieverling L, Deeg KI, et al: TelomereHunter - In silico estimation of telomere content and composition from cancer genomes. BMC Bioinformatics 20:272, 2019
31. Ballinger ML, Pattnaik S, Mundra PA, et al: Heritable defects in telomere and mitotic function selectively predispose to sarcomas. Science 379:253-260, 2023
32. Akhavanfard S, Padmanabhan R, Yehia L, et al: Comprehensive germline genomic profiles of children, adolescents and young adults with solid tumors. Nat Commun 11:2206, 2020
33. Lippner ELT, Lücke T, Salgado C, et al: Schimke immunoosseous dysplasia, in Adam MPFJ, Feldman J, Mirzaa GM, et al (eds): GeneReviews. Seattle, WA, University of Washington, 2023 34. Mirabello L, Zhu B, Koster R, et al: Frequency of pathogenic germline variants in cancer-susceptibility genes in patients with osteosarcoma. JAMA Oncol 6:724-734, 2020
35. Brosnan-Cashman JA, Davis CM, Diplas BH, et al: SMARCAL1 loss and alternative lengthening of telomeres (ALT) are enriched in giant cell glioblastoma. Mod Pathol 34:1810-1819, 2021
36. O’Sullivan RJ, Greenberg RA: Mechanisms of alternative lengthening of telomeres. Cold Spring Harbor Perspect Biol 17:a041690, 2025
37. Cole S, Gianferante DM, Zhu B, et al: Osteosarcoma: A Surveillance, Epidemiology, and End Results program-based analysis from 1975 to 2017. Cancer 128:2107-2118, 2022
38. Rafati M, Guenther LM, Egolf LE, et al: SMARCAL1 is a new osteosarcoma predisposition gene. J Natl Cancer Inst 310.1093/jnci/djaf278 [epub ahead of print on September 25, 2025]
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
Investigation of DNA Damage Response Genes Validates the Role of DNA Repair in Pediatric Cancer Risk and Identifies SMARCAL1 as a Novel Osteosarcoma Predisposition Gene
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center.
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Wenan Chen Stock and Other Ownership Interests: Illumina, 10X Genomics
Barbara C. Jones
Employment: Heidelberg Epignostix GmbH (I) Leadership: Heidelberg Epignostix GmbH (I)
Stock and Other Ownership Interests: Heidelberg Epignostix GmbH (I) Patents, Royalties, Other Intellectual Property: Patent WO 2013075237 A1, titled “Mutations of histone proteins associated with proliferative disorders” (I), Patent WO2016142533A1, titled “DNA methylation-based method for classifying tumor species” (I)
David T.W. Jones Employment: Heidelberg Epignostix
Stock and Other Ownership Interests: Heidelberg Epignostix Consulting or Advisory Role: Day One Biopharmaceuticals Patents, Royalties, Other Intellectual Property: Patent: “DNA methylation-based method for classifying tumor species”
Olaf Witt
Honoraria: Roche Pharma AG
Consulting or Advisory Role: Novartis, AstraZeneca, Janssen Research & Development (Inst), BMS, Roche, Day One Therapeutics, SK Life Sciences, Merck KGAA
Research Funding: Janssen Research & Development (Inst), PreComb Therapeutics (Inst), Bristol Myers Squibb/Ono Pharmaceutical (Inst), Roche Pharma AG (Inst), Novartis (Inst), Loxo/Bayer (Inst), Loxo (Inst), AstraZeneca (Inst), Lilly (Inst), Day One Therapeutics (Inst), GlaxoSmithKline (Inst), Blueprint Medicines (Inst), Bayer (Inst)
Uta Dirksen Consulting or Advisory Role: Lilly (Inst), Ipsen, Recordati
Jiaming Li
Employment: St Jude Children’s Research Hospital
Kirsten K. Ness Consulting or Advisory Role: City of Hope
Stefan M. Pfister
Leadership: PMC, University Hospital Essen Westdeutsches Tumorzentrum
Stock and Other Ownership Interests: Heidelberg Epignostix
Consulting or Advisory Role: BioSkryb Research Funding: Lilly (Inst), Bayer (Inst), Roche (Inst), PharmaMar (Inst), Pfizer (Inst), AstraZeneca (Inst), Janssen & Janssen (Inst), Servier (Inst), Sanofi (Inst), Amgen (Inst)
Patents, Royalties, Other Intellectual Property: Patent on using DNA methylation profiling for tumor classification, patent on using nanopore sequencing for rapid tumor diagnostics, Rapid comprehensive adaptive nanopore-sequencing of CNS tumors, a proof of concept study, Method for the detection of a premalignant lesion in a subject
Melissa M. Hudson
Employment: Methodist Hospital (I)
Consulting or Advisory Role: Princess Maxima Center, VIVA Foundation Singapore
Robert J. Autry
Patents, Royalties, Other Intellectual Property: Patent application filed in EU. EP 25 166 938.8 (5%) with DKFZ IP office for detection of premalignant lesions in newborns or young children
Kim E. Nichols Research Funding: Incyte (Inst)
No other potential conflicts of interest were reported.