Abstract
PURPOSE
To evaluate the relative diagnostic yield of clinical germline genomic tests in a diverse pediatric cancer population.
PATIENTS AND METHODS
The KidsCanSeq study enrolled pediatric cancer patients across six sites in Texas. Germline analysis included both exome sequencing and a therapy-focused pediatric cancer gene panel. Results were categorized by patient demographics, the presence of pathogenic or likely pathogenic (P/LP) variants and variants of uncertain significance (VUS) in cancer predisposition genes (CPGs). Pediatric actionable CPGs were defined as those with cancer surveillance recommendations during childhood.
RESULTS
Cancer P/LP variants were reported by at least one platform in 103 of 578 (17.8%) cases of which 76 cases were dominant cancer genes (13.1%) with no significant differences by self-described race or Hispanic ethnicity. However, the proportion of cases with VUS was greater in Asian and African-American patients (p=0.0029). Diagnostic yield was 16.6% for exome versus 8.5% for panel (p<0.001) with 42 cases with concordant germline results. Exome-only results included P/LP variants in 30 different CPGs in 54 cases, whereas panel-only results included 7 cases with a copy number or structural P/LP variants in CPGs. There was no significant difference in diagnostic yield limited to pediatric actionable CPGs (p= 0.6171).
CONCLUSION
Approximately 18% of a diverse pediatric cancer population had germline diagnostic findings with 50% of P/LP variants reported by only one platform due to CPGs not on the targeted panel and CNVs/rearrangements not reported by exome. Although diagnostic yields were similar in this diverse population, increases in VUS results were seen for Asian and African-American populations. Given the clinical significance of CNVs/rearrangements in this cohort, detection is critical to optimize germline analysis of pediatric cancer populations.
Context Summary
Key Objective:
What is the diagnostic yield of germline exome versus panel test platforms in a diverse pediatric cancer population and how do these results impact clinical actionability and counseling?
Knowledge Generated:
Combined, we found 17.8% of this pediatric cancer cohort had, cancer pathogenic/likely pathogenic (P/LP) variants which did not differ by race/ethnicity, although rate of VUS was higher in self-reported Asian and African American participants. Exome identified twice the cancer P/LP variants than panel, but when restricted to pediatric actionable findings the diagnostic yield between platforms was not significantly different due to CNVs/rearrangements detected by panel-only.
Relevance:
Diagnostic approaches to cancer predisposition in pediatric patients that includes both comprehensive gene coverage and CNVs/rearrangements is critical for identifying actionable alternations in the pediatric oncology population. Further work is needed to reduce uncertain variants in many populations.
INTRODUCTION
Genomic sequencing technologies have been developed in parallel for both tumor and normal (germline) analysis including next generation sequencing (NGS) panels, exome (ES) and genome (GS) sequencing1, 2. Tumor NGS panels are designed to optimize detection of targetable alterations and include many but not all relevant cancer predisposition genes (CPGs). Conversely, in 2021, the American College of Medical Genetics and Genomics (ACMG) issued an evidence-based guideline for consideration of ES as first- or second-line testing for individuals with intellectual disability and/or congenital anomalies given the increased diagnostic yield, however, cancer was not considered a frontline indication for ES3.
The Texas KidsCanSeq (KCS) study, a National Institutes of Health Clinical Sequencing Evidence-Generating Research (CSER) Consortium4 project, was designed to investigate implementation of genome-scale testing for pediatric cancer patients in the diverse population of Texas. A primary goal of KCS was to compare diagnostic yield of clinical germline NGS panel testing versus ES and the influence of patient race and ethnicity on testing results. The study was powered to measure: (1) whether ES would have a higher diagnostic yield than panel testing due to gene coverage, with the number of genes differentially reported by exome small enough to be easily added to future NGS capture platforms; (2) panel testing would have a higher sensitivity than ES to detect mosaic findings due to potentially higher-depth targeted coverage of CPGs on the panel.
PATIENTS AND METHODS
2.1. Study Subjects and Data Collection
KidsCanSeq was approved by the Baylor College of Medicine Institutional Review Board (BCM IRB) and at non-BCM sites using the SMART IRB (https://smartirb.org/). Pediatric cancer patients (<18 years) with central nervous system (CNS) and non-CNS solid tumors, lymphomas and histiocytic disorders were offered enrollment at one of six recruitment sites across Texas (Table 1). Due to challenges obtaining germline sample without tumor contamination (e.g., potential need for skin biopsy), patients with leukemia were ineligible for enrollment. Similar to the prior BASIC3 study5, parent(s) and/or legal guardian(s) were also consented with required enrollment of at least one English and/or Spanish-preferring parent or guardian. Completion of a baseline survey within 7 days of enrollment was required for continued participation in the study. Survey measures, including self-described race and ethnicity, are described6.
Table 1.
Demographic and clinical characteristics of subjects with complete germline analysis (n=578).
| Descriptor | Enrollment (n=578) | Summary % |
|---|---|---|
|
| ||
| Parent response to combined race/ethnicity survey question | ||
| Hispanic /Latino | 279 | 48.3% |
| White or European American | 169 | 29.2% |
| Black or African American | 54 | 9.3% |
| Asian | 15 | 2.6% |
| Middle Eastern or North African / Mediterranean | 4 | 0.7% |
| American Indian, Native American, or Alaska Native | 2 | 0.3% |
| Native Hawaiian / Pacific Islander | 1 | 0.2% |
| More than one category excluding Hispanic/Latino(a) | 33 | 5.7% |
| Prefer not to answer | 9 | 1.6% |
| Unknown / none of these fully describe me | 4 | 0.7% |
| Not Reported | 8 | 1.4% |
| Clinical Site | ||
| Texas Children’s Hospital | 377 | 65.2% |
| Cook Children’s Hospital | 106 | 18.3% |
| Children’s Hospital of San Antonio | 29 | 5.0% |
| University of Texas Health Science Center San Antonio | 27 | 4.7% |
| Vannie Cook Children’s Clinic | 26 | 4.5% |
| MD Anderson Cancer Center | 13 | 2.2% |
| Age at Enrollment (median = 8; range 0.3–17) | ||
| <5 years | 177 | 30.6% |
| 5–9 years | 129 | 22.3% |
| 10–14 years | 152 | 26.3% |
| >=15 years | 120 | 20.8% |
| Sex | ||
| Female | 286 | 49.5% |
| Male | 292 | 50.5% |
| Tumor Category | ||
| CNS Tumors | 210 | 36.3% |
| Lymphoma or Histiocytosis | 43 | 7.4% |
| Non-CNS Solid Tumors | 325 | 56.2% |
| Cohort | ||
| Germline Only | 224 | 38.8% |
| Germline + Tumor | 354 | 61.2% |
All patients had germline analysis. In addition, patients with treatment-refractory tumors or those considered diagnostically challenging, rare and without well-defined treatment options, or high-risk (estimated long term survival of <70%) were also eligible for tumor profiling via panel, exome, transcriptome, and copy number array. Tumor results were analyzed and reported independently of germline analysis and will be described separately. The availability of tumor data was variable and therefore not used to influence germline reporting.
2.2. Germline Testing Procedures
Samples of peripheral blood and/or saliva were obtained from probands for germline testing. Saliva samples were requested from parents. Tumor histopathologic diagnosis was provided to the germline labs. Other non-cancer phenotypes abstracted from the medical record by study staff were provided on the ES requisition form.
2.3. Genomic Analysis
Panel sequencing of germline genomic DNA was conducted in the Texas Children’s Hospital (TCH) Cancer Genomics laboratory using the same Solid Tumor Mutation Panel backbone (initially 124 genes, expanded to 169 genes in 2021) used for tumor sequencing (Supplementary Figure 1; Supplementary Table 1)7. Germline reporting from the panel was restricted to Pathogenic or Likely Pathogenic (P/LP) variants per ACMG/Association for Molecular Pathology (AMP) guidelines8 in a subset of 35 CPGs increasing to 57 CPGs when the panel expanded in June 2021 (Supplementary Table 1). ES was used as orthogonal confirmation for variants detected by panel. VUS reporting was not completed due to workflow. In September 2020, the test was separately updated to include reporting of copy number variants (CNVs) and structural rearrangements7 (Supplementary Figure 1). Average read depth for the panel was 206x and variant allele fractions of 0.15 to 0.30 were reported as mosaic.
Germline ES was conducted at the BCM Human Genome Sequencing Center – Clinical Laboratory with reports generated by board-certified Baylor Genetics laboratory geneticists9. Average read depth for KCS ES was 156x and variant allele fractions of 0.1 to 0.3 were reported as mosaic. In addition to P/LP variants, ES reporting included variants of uncertain significance (VUS) in any CPG (regardless of concordance with the patient’s specific tumor histology) and variants in genes related to any non-cancer phenotypes provided. ES reports included P/LP variants from the non-cancer genes on the “ACMG SF v2.0” gene list10 and carrier status in 10 genes recommended by ACMG and the American College of Obstetrics and Gynecology11 (Supplementary Table 2). Parental DNA was assessed by Sanger sequencing for variants selected for reporting on the proband’s exome report.
The targeted panel and ES tests were performed asynchronously and reported separately. However, there was a weekly meeting where the teams reviewed results and harmonized variant nomenclature. The resulting panel and exome reports were returned separately to each study site for placement in the medical record.
2.4. Analysis of Study Results
Reports with one or more P/LP variants were classified as having significant findings (SF(s)), which were further categorized by gene and associated syndrome(s). The remaining reports, including those with VUS only, were considered non-significant (NSF). Concordance of SF(s) with the subject’s tumor was determined based on reported gene-phenotype associations in the AACR pediatric oncology series12 and/or GeneReviews13. CSER harmonized diagnostic determinations14 were assigned as definitive/probable positive for concordant gene-phenotypes (e.g., APC-colon cancer) and inconclusive for discordant pairs (e.g., BRCA1-germinoma). For subjects with non-cancer phenotypes, CSER-defined phenotype categories14, e.g., cardiovascular, were assigned and additional diagnostic determinations were made for each phenotype category. For this study we also used the phenotype categories to categorize the gene-tumor relationship. Separately, cancer genes with P/LP variants (Supplementary Table 3) were defined as pediatric actionable by the KidsCanSeq genetics team as those with surveillance measures recommended before 18 years of age, e.g. guidelines published in the AACR Pediatric Oncology Series12. Germline results were returned to participants via mailed letter for NSF reports and in person or by telemedicine per parent preference for SF reports15. Suckiel et al provides an overview of CSER disclosures as well as an example KCS disclosure16.
2.5. Statistical Analysis
Fisher’s exact tests were used to assess associations between self-described demographic or clinical features and significant germline cancer or VUS findings. Paired panel and exome data for detecting probands with (1) germline cancer P/LP findings and (2) a subset of “pediatric actionable” cancer findings was analyzed using McNemar’s test. Analyses were performed using SAS 9.4. All p-values are two-sided and p<0.05 were considered statistically significant.
RESULTS
3.1. Patient Characteristics and Samples
Study enrollment was offered to 847 families across six sites between June 2018 and July 2021, of whom 626 (73.9%) consented to participation and 578 (92.3%) completed all required steps for enrollment with adequate subject samples (blood n=546; saliva n=32) for completion of both germline tests. Parental samples available for reporting inheritance in exome analysis were, 261 probands (both parents), 276 probands (single parent) and 41 proband-only. Self-described demographic information (from baseline survey) and clinical information from the electronic medical record are summarized in Table 1. The 578 subjects with complete germline analysis ranged from 0–17 years of age at enrollment (median 9 years) with approximately equal male:female ratio. By parent report, approximately half of subjects (48.3%) identified as Hispanic, 9.3% identified as Black or African American only and 2.6% identified as Asian. Overall, 61.2% met clinical criteria for the high-risk study arm which included tumor analysis. The two largest enrollment sites were TCH (65.2%) and Cook Children’s Hospital (18.3%), with 16.4% from the four remaining study sites.
3.2. Overall Variant and Participant-Level Germline Results
Significant findings (SFs) were reported in 137 of 578 (23.7%) subjects (Supplementary Table 4) including 14 subjects with a P/LP variant in more than one gene (Supplementary Table 5). None of the patients with more than one variant had dual diagnoses that clearly contributed to their phenotype(s). Focusing on cancer-related findings, 110 P/LP CPG variants were reported in 103 (17.8%) KCS subjects (Figure 1A). P/LP variants were most frequent in TP53 (n=11), CHEK2 (n=7) and MUTYH (n=6). Biallelic variants was found only once (MUTYH, n=1); however single variants in CPGs only associated with recessive disorders were reported in 26 subjects (4.5%) (Figure 1B). Heterozygous variants in CPGs associated with dominant disorders were reported in 76 participants (13.1%), of which 43 were considered definitive/probable positive for the cancer phenotype because the gene identified was concordant with tumor pathology. Five subjects (0.9%) had P/LP variants in genes only related to non-cancer phenotypes (e.g., PKD1). Of all SFs, only 3 variants (2-RB1 and 1-TP53) were reported as mosaic by both exome and panel. The remaining 441 subjects (76.3%) had NSF, of these, 130 subjects (22.5%) had negative germline exome and panel reports, and 311 subjects (53.8%) had ES reports containing only VUS (Figure 1A). In total, 405 reports had VUS including 94 ES with P/LP variant(s)s.
Figure 1.
(A) Case-level classification of germline results with (B) additional subcategorization of cancer P/LP variants by inheritance pattern and actionability.
There was no difference in overall diagnostic yield (CPG P/LP variants) by demographic factors including parent-reported proband race and/or ethnicity, sex, tumor category and cohort, except when limited to the two largest enrollment sites, TCH (15.9%) and Cook Children’s (25.5%) (p=0.0313) (Table 2).
Table 2.
Case-level diagnostic rate comparisons by demographic and clinical factors.
| Patient Characteristic | Patients with Cancer P/LP variants (n=103) | % Cancer P/LP variants | p-value* |
|---|---|---|---|
|
| |||
| Ethnicity (parent-reported) | 0.2246 | ||
| Hispanic/Latino | 56 | 20.1 | |
| Non-Hispanic | 44 | 15.8 | |
|
| |||
| Parent response to combined race/ethnicity survey question | 0.2811$ | ||
| Hispanic/Latino | 56 | 20.1 | |
| White or European American | 27 | 16 | |
| Black or African American | 9 | 16.7 | |
| Asian | 0 | 0 | |
| Middle Eastern or North African/Mediterranean | 1 | 25 | |
| American Indian, Native American, or Alaska Native | 0 | 0 | |
| Native Hawaiian or Pacific Islander | 0 | 0 | |
| More than one category | 7 | 21.2 | |
| Prefer not to answer | 1 | 11.1 | |
| Unknown/none of these fully describe my child | 0 | 0 | |
| Not Reported | 2 | 25 | |
|
| |||
| Clinical Site | 0.1322 | ||
| Texas Children’s Hospital | 60 | 15.9 | |
| Cook Children’s Hospital | 27 | 25.5 | |
| Children’s Hospital of San Antonio | 3 | 10.3 | |
| University of Texas Health Science Center San Antonio | 7 | 25.9 | |
| Vannie Cook Children’s Clinic | 3 | 11.5 | |
| MD Anderson Cancer Center | 3 | 23.1 | |
|
| |||
| Among 2 Largest Sites | 0.0313 | ||
| Texas Children’s Hospital | 60 | 15.9 | |
| Cook Children’s Hospital | 27 | 25.5 | |
|
| |||
| Age at Consent | 0.1105 | ||
| <5 years | 40 | 22.6 | |
| 5–9 years | 19 | 14.7 | |
| 10–14 years | 29 | 19.1 | |
| >=15 years | 15 | 12.5 | |
| Median (range) | 8 (0.3,17) | ||
| Gender | 0.6654 | ||
| Female | 53 | 18.5 | |
| Male | 50 | 17.1 | |
|
| |||
| Tumor Category | 0.1174 | ||
| CNS Tumors | 45 | 21.4 | |
| Lymphoma or Histiocytosis | 4 | 9.3 | |
| Non-CNS Solid Tumors | 54 | 16.6 | |
|
| |||
| Cohort | 1 | ||
| Germline Only | 40 | 17.9 | |
| Germline + Tumor | 63 | 17.8 | |
p-values were calculated using Fisher’s exact tests to compare pts with vs without cancer P/LP
comparison was made among Hispanic/White/Black/Asian/more than one race. Groups. Groups with small n’s were excluded.
The proportion of participants with any VUS was greater in subjects identifying as Asian (100%, 15 of 15) or Black/African American (83.3%, 45 of 54) compared to those identifying as Hispanic (68.1%, 190 of 279) or White/European American (64.5%, 109 of 169) (p=0.0029) (Table 3). Similarly, median number of VUS differed for Black/African American subjects at 3 (Range 1–7), Asian or Hispanic/Latino subjects at 2 (Range: 1–6), and White/European American subjects at 1(Range: 1–8) (p=0.0012). These differences persisted when considering participants with VUS-only reports.
Table 3.
Analysis of VUS and cancer P/LP variants by race and ethnicity.
| Parent-reported race/ethnicity | Total | VUS (+/− P/LP) | Cancer P/LP | |||||
|---|---|---|---|---|---|---|---|---|
|
| ||||||||
| n=578 | *p=0.0029$ | #p=0.0012 | p=0.2811$ | |||||
|
| ||||||||
| n | n | % | mean | median | range | n | % | |
|
| ||||||||
| Hispanic/Latino | 279 | 190 | 68.1 | 1.98 | 2 | 1–6 | 56 | 20.1 |
| White or European American | 169 | 109 | 64.5 | 1.73 | 1 | 1–8 | 27 | 16 |
| Black or African American | 54 | 45 | 83.3 | 2.71 | 3 | 1–7 | 9 | 16.7 |
| Asian | 15 | 15 | 100 | 2.33 | 2 | 1–6 | 0 | 0 |
| More than one category | 33 | 25 | 75.8 | 1.96 | 2 | 1–4 | 7 | 21.2 |
p-values were calculated using Fisher’s exact tests to compare pts with VUS vs not
comparison was made among Hispanic/White/Black/Asian/more than one race.
p-values were calculated using Kruskal-Wallis tests comparing # of VUS among patients with VUS.
3.3. Exome Versus Panel Testing Platform Comparison
Exome reports included 29 (5.0%) patients with non-cancer carrier status variant(s) reported and 5 (0.9%) with findings related to a non-cancer phenotype not included on panel testing. However, given that KidsCanSeq is a pediatric cancer cohort, we focused platform comparative analysis on the 103 subjects with a total of 110 P/LP CPG variants reported. Of those, only 42 subjects (40.8%) had all cancer variant(s) identified by both platforms (Figure 2A), with 54 subjects on ES-only (Table 4) and 7 on panel-only. Of 578 subjects, cancer P/LP variants were reported by exome in 96 subjects (16.6%) compared to 49 subjects (8.5%) reported by panel (McNemar’s test p<0.0001) (Figure 2B).
Figure 2.
Case-level comparison of exome and panel reporting of cancer P/LP variants. For all subjects with cancer predisposition gene (CPG) P/LP variants (n=103), (A) visualizes case-level reporting by platform and (B) diagnostic yield for each test. When restricting to subjects with pediatric actionable CPG P/LP variants (n=53), (C) shows case-level reporting by platform and (D) diagnostic yield by test.
Table 4.
Genes with variants reported on exome but not panel testing. Numbers in the table represent counts of variants rather than subjects and therefore exceed the number of subjects (n=54) with variants reported by exome-only.
| Pediatric Actionable | NOT Pediatric Actionable | ||||
|---|---|---|---|---|---|
| Dominant | Dominant | Recessive | |||
|
| |||||
| 3 | LZTR1 | 7 | CHEK2 | 6 | MUTYH |
| 1 | CDKN1B | 3 | MSH6 * | 5 | SBDS |
| 1 | DDX41 | 3 | PALB2 | 3 | FANCA |
| 1 | FLNA | 1 | AXIN2 | 2 | DIS3L2 * |
| 1 | PTCH2 | 1 | RAD51C | 2 | SLX4 |
| 1 | SDHB * | 1 | TGFBR1 | 2 | RECQL4 |
| 1 | SDHD * | 1 | FLCN * | 2 | NTHL1 |
| 1 | MLH1 * | 2 | BUB1B | ||
| 1 | PMS2 * | 1 | ERCC2 | ||
| 1 | ERCC3 | ||||
| 1 | FANCE | ||||
| 1 | FANCM | ||||
| 1 | NBN | ||||
| 1 | SLC26A4 | ||||
Denotes genes added to the panel during expansion to the 57-gene list in June 2021.
Of 53 subjects (51.5% of cancer variants) with at least one pediatric actionable finding (see Methods) 37 subjects (69.8%) were reported by both modalities, 9 (17%) were exome-only and 7 (13.2%) were panel-only (Figure 2C). In total, pediatric actionable SFs were reported by exome in 46 subjects (8.0%) and panel in 44 subjects (7.6%)(Figure 2D), which was not significantly different (p=0.6171).
3.4. Assessment of Differential Reporting by Test Modality
The 54 exome-only reports contained cancer P/LP variants in 30 different genes not reported by panel (Table 4) including 7 genes associated with pediatric actionable dominant disorders (e.g., SDHB), 9 genes for “adult-onset” dominant conditions (e.g., CHEK2) and 14 genes with monoallelic variants associated with rare recessive conditions (e.g., FANCA). Seven of these genes were subsequently added to the panel in June 2021, which accounted for 10 of 54 exome-only reports. The 7 P/LP variants reported by panel-only were deletions (n=6) and one complex rearrangement including two each for SMARCB1 and WT1 and single reports for TP53, RB1 and NF1, all genes considered pediatric actionable.
ES also included inheritance reporting of CPG P/LP variants when parental samples were available. Of 35 kindreds with analysis of both parents for cancer variants in the proband, only 7 subjects had confirmed de novo status (20%) and the remaining 28 were inherited (80%).
DISCUSSION
In the KidsCanSeq cohort, cancer P/LP variants (regardless of inheritance pattern or penetrance) were reported in 17.8% of subjects, 13.1% when limited to autosomal dominant genes, similar to other reports in pediatric cancer populations1, 17. Another result consistent with multiple pediatric cancer studies is the small contribution of recessive diagnoses (biallelic variants in the same gene): we previously found only 1 of 278 patients in our BASIC3 study9, 1 of 1120 was reported in the St. Jude–Washington University Pediatric Cancer Genome Project17, and 1 of 578 was found in this Texas KidsCanSeq. This may increase in populations with higher rates of consanguinity18.
A key goal of CSER consortium studies was to investigate implementation of genomic testing in diverse populations including assessing the yield of diagnostic and uncertain results. The overall yield of P/LP variants in CPG (by panel and/or exome) did not reveal any statistical difference based on self-described Hispanic or non-Hispanic ethnicity, race or age at study entry (comparing infancy with school age and adolescent children). However, evaluation of exome results revealed that Asians and Black/African-Americans had a higher proportion of reports with VUS and Black/African-American subjects had a higher median number of VUS. Median VUS declined from 3 in our BASIC3 study8 (completed in the preceding 4 years) to 2 in KidsCanSeq. However, we also found a higher median VUS in Black/African-American subjects (median of 5; Supplementary Figure 2). Thus, overall improvement in variant classification and improved population databases have not diminished this health disparity with some families having a greater need for ongoing follow-up of VUS results. Other hereditary cancer studies in Asian populations have also suggested an increase in VUS rate19. Interestingly, the lack of difference in P/LP variants between these demographic groups suggests the additional VUS findings are not likely to be diagnostic but may result from lack of adequate population data to curate benign variants.
A unique aspect of KidsCanSeq was to directly evaluate benefits and limitations of different germline test platforms for use in pediatric cancer care. Overall, reporting of P/LP variants in CPGs in the KidsCanSeq pediatric cancer cohort was almost twice from ES (16.6%) versus panel (8.5%). Note, the panel used for KidsCanSeq germline reporting was designed for tumor analysis used for treatment decisions including many targetable oncogenes and therefore did not include all highly penetrant CPGs (e.g., SDHB), in contrast to hereditary cancer panels. Nevertheless, these findings are comparable to those of a similar analysis in a cohort of pediatric patients with non-cancer genetic conditions from the CSER NYCKidSeq study, which reported diagnostic rate of 16.5% and 8.1% for GS and panel respectively20. As described in Methods, although the germline exome and panel reporting teams evaluated results separately, the teams reviewed results weekly. If this practice had any effect on study findings, it would have been expected to minimize differences between reports rather than increasing discordance.
Pre-study, we hypothesized that ES would have greater diagnostic yield than panel testing; however, there were two related initial hypotheses that were not validated. The rate of mosaic results was low (less than 1%) and was not different between the platforms with similar coverage between the two platforms (exome 156X and panel 206X). Future comparisons of mosaic reporting from genome sequencing (GS) are indicated given much lower depth of coverage. Although pre-study we assumed increased yield from ES would be due to a few genes that could be added to the panel, this difference was driven by variants in 30 CPGs ranging from pediatric actionable conditions (e.g., SDHB), to single variants in recessive disorders (e.g., WRN), as well as adult-onset CPGs of varying penetrance (e.g., BRCA2, CHEK2) and not currently considered pediatric actionable. In adult hereditary cancer populations21, 22, comparison of panels vs. ES or GS has yielded very little difference in germline reporting, whereas our study highlighted differences in (1) gene-content likely due to the nature of design for pediatric tumor focused panel vs. adult populations and (2) CNV detection based on methodologies employed.
Many other ES and GS studies have reported enrichment of adult-onset CPS in children with cancer, e.g., Lynch syndrome diagnoses and BRCA2 in rhabdomyosarcoma, lymphoma and medulloblastoma patients1. However, absolute risk of pediatric cancer remains low in these children and cascade testing of healthy pediatric relatives (e.g. siblings) is not currently recommended23–25. Identification of adult-onset CPS in this setting is particularly important for parents who are often approaching or past the age at which surveillance recommendations begin.
Single variants in autosomal recessive CPGs accounted for a quarter of CPG P/LP variants in this cohort, which at present are not known to be associated with cancer risk in the absence of a P/LP variant on the other allele although will have reproductive implications for the subject and/or parents. There is emerging evidence, however, that single recessive variants may contribute to cancer risk for specific genes. For example, our previous BASIC3 report of a Wilms tumor patient with heterozygous DIS3L2 was recently validated in a Swedish Wilms Tumor study reporting enrichment of heterozygous DIS3L2 accompanied by tumor loss of heterozygosity in most cases 26. In addition, association of single recessive variants in DNA repair genes with increased second malignancy risk in long-term survivors of childhood cancer was reported27.
Thus, use of panel testing for hereditary cancer evaluation in children would require expansive gene content and flexibility for updating to be comparable to exome. For example, updates to the gene content occurred only once during the 4-year study period. To overcome these limitations in flexibility, current practices are transitioning to adoption of genome or exome-slice panels with in silico filtering for rapid panel design updates. Aside from gene content, each platform has unique benefits to consider. ES reports typically include inheritance by assessing parental samples, without the need for referral of parents for reflex testing. A prior CSER study of children with neurodevelopmental disorders reported a de novo rate of 76%28. In KidsCanSeq, de novo status was only confirmed in 20% of informative trios and 80% were confirmed to be inherited. The contrast between the two studies may represent differences in reproductive fitness for these different types of disorders. Utility for parental carriers included adult cancer surveillance recommendations and/or implications for family planning.
Panel testing typically includes analyses of copy number and rearrangements and we found that 7 of 44 (15.9%) pediatric actionable P/LP variants reported by panel were of this class. Consistent with our study, a commercial laboratory reported 7.2% of structural variants (majority being CNVs) in a large series of pan-cancer germline tests 29. In KidsCanSeq, there was no difference between platforms for pediatric actionable findings as exome increased gene content was balanced by reporting of structural events. This highlights importance of using GS or methods to optimize CNV/rearrangement detection in ES. Another important difference between platforms, is the ability of the exome to make diagnoses for non-cancer indications, which occurred in approximately 1% of subjects (n=5). ES is preferred as a first-line test in patients with cancer and other complex medical history. Finally, 29 patients (5.0%) had non-cancer carrier status, which may provide important reproductive information for their parents or the child in the future.
Findings from these analyses highlight several issues. First is the importance of complex variant detection. As demonstrated by the clinical significance of these findings, detection of CNVs and complex rearrangements is critical for comprehensive germline analysis in this population. While exome analysis provided a much higher diagnostic rate, it often does not include rearrangement detection, and further research is needed to minimize VUS reporting in underrepresented populations and determine the utility of reporting single variants in recessive disease genes and adult-onset CPGs. As germline analysis expands in this population, utilizing methodologies that address these issues is critical to maximize diagnostic yield.
Supplementary Material
Supplementary Figure 1. Timeline of KCS germline panel updates.
Supplementary Figure 2. Analysis of VUS data in the BASIC3 cohort by (A) ethnicity and (B) race, which demonstrated increased VUS in African-American participants (median=5) relative to Hispanic and Non-Hispanic White participants (median=3).
Supplementary Table 1. Genes reported on the tumor and germline panels including genes both on the initial panel as well as the expanded panel gene list.
Supplementary Table 2. Genes reported on the ACMG SF v2.0 gene list and the carrier status reported by exome.
Supplementary Table 3. Genes reported on KCS exomes as pathogenic or likely pathogenic that were assigned to the “Cancer” or “Multiple Indications (including cancer)” phenotype categories. Those genes with active surveillance measures recommended before 18 years of age were defined as pediatric actionable.
Supplementary Table 4. List of all germline pathogenic/likely pathogenic (P/LP) variants reported in KCS by subject.
Supplementary Table 5. Pathogenic/likely pathogenic (P/LP) variants reported in subjects with more than one P/LP variant.
ACKNOWLEDGMENTS
The Texas KidsCanSeq study, part of the Clinical Sequencing Evidence-Generating Research (CSER) consortium, was funded by National Human Genome Research Institute (NHGRI) with co-funding from the National Cancer Institute (NCI) grant U01 HG006485 (Drs McGuire, Parsons and Plon). We thank KidsCanSeq participants and their families as well as CSER consortium collaborators for their important contributions to this work.
This study was supported by U01 HG006485 (NHGRI/NCI).
Footnotes
Previously Presented: Part of this analysis was presented at the American Society of Human Genetics and Genomics Annual Meeting, 10/27/22, Los Angeles, CA
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Associated Data
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Supplementary Materials
Supplementary Figure 1. Timeline of KCS germline panel updates.
Supplementary Figure 2. Analysis of VUS data in the BASIC3 cohort by (A) ethnicity and (B) race, which demonstrated increased VUS in African-American participants (median=5) relative to Hispanic and Non-Hispanic White participants (median=3).
Supplementary Table 1. Genes reported on the tumor and germline panels including genes both on the initial panel as well as the expanded panel gene list.
Supplementary Table 2. Genes reported on the ACMG SF v2.0 gene list and the carrier status reported by exome.
Supplementary Table 3. Genes reported on KCS exomes as pathogenic or likely pathogenic that were assigned to the “Cancer” or “Multiple Indications (including cancer)” phenotype categories. Those genes with active surveillance measures recommended before 18 years of age were defined as pediatric actionable.
Supplementary Table 4. List of all germline pathogenic/likely pathogenic (P/LP) variants reported in KCS by subject.
Supplementary Table 5. Pathogenic/likely pathogenic (P/LP) variants reported in subjects with more than one P/LP variant.