Introduction
Neuroblastic tumours (NTs) are the most common extracranial solid tumours of children, with diverse clinical outcomes ranging from spontaneous regression to progression [1,2]. The Children's Oncology Group (COG) and International Neuroblastoma Risk Group (INRG) stratify NTs into low-risk (LR), intermediate-risk (IR), and high-risk (HR) groups [3,4]. The overall survival rate for LR or IR patients is over 90%, while the long-term survival rate for children with HR tumours is below 50% [4]. Accurate tumour risk classification is crucial for NT therapy [5]. Clinical and molecular features of age, stage, histological type, MYCN status, tumour cell ploidy, and chromosomal abnormalities are widely accepted in most risk stratification schemes [3,6,7]; however, international consensus is still lacking for some patients. Identifying additional biomarkers is important to guide risk stratification.
It is generally accepted that HR NTs have MYCN amplification, ALK aberrations, or ATRX deletions [3,8–10], but the genomic alterations in some NTs remain unclear, necessitating the development of new genetic markers. In 2015, researchers from different groups showed that telomerase reverse transcriptase (TERT) rearrangement (20%) was the second most common genetic defect in HR neuroblastoma (NB), mutually exclusive with ATRX and MYCN amplification [11,12]. The prognosis for this group was extremely poor. Furthermore, the revised 2021 COG risk classification system recommended that TERT rearrangements be considered as future research criteria [7]. There is an urgent need to determine the prognostic significance of TERT rearrangements in NTs.
NTs are histologically classified as NB, ganglioneuroblastoma nodular (GNBn), ganglioneuroblastoma intermixed (GNBi), and ganglioneuroma (GN) [13]. Despite reports of TERT rearrangements in NB [11,12], it is unclear whether these rearrangements also occur in other pathological types of NT. TERT rearrangements result from chromosome breakage and recombination. Previously, they were mainly examined using high-throughput methods, such as whole-genome sequencing (WGS) and GeneChip assays [11,12,14], which are not suitable for routine clinical practice. Nevertheless, this large-scale structural alteration makes fluorescence in situ hybridisation (FISH) an excellent method for TERT aberration detection. In this study, we validate the detection of TERT rearrangements by FISH in 633 Chinese NTs of all histological types and summarise their clinical, histological, and genetic characteristics.
Materials and
Clinical specimens and information
The patients were diagnosed clinically and histopathologically at Beijing Children's Hospital from June 2016 to December 2019. The International Neuroblastoma Staging System (INSS) and COG Risk Classification System were used for clinical staging and grading by clinicians. This study was approved by the Institution's Research Ethics Board of Beijing Children's Hospital (2017-k-41). Clinical information such as patient age, sex, tumour site, histological type, stage and grade, treatment, recurrence or metastasis, and survival time was collected. MYCN, 1p, and 11q status were routinely detected using FISH [15]. The cohort was divided into MYCN−TERT−, MYCN+TERT−, and TERT+ groups according to MYCN and TERT status (Figure 1). As not all the patient data are complete, the staging, grading, and histological types are presented in percentages to make the differences more readily apparent. The MYCN gene status was classified into normal, gain, or amplification according to the International Consensus for Neuroblastoma Molecular Diagnostics [15]. The DNA and RNA were extracted from slices that contained at least 50% tumour cells.
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A dual-colour break-up probe set was developed to detect TERT rearrangements. According to TERT promoter rearrangement sites reported previously [11,12], bacterial artificial chromosome (BAC) clones of RP11-325I22, RP11-768M3 (the centromeric region), and RP11-260H6, RP11-1107M2 (the telomeric region) were selected using the UCSC Genome Browser Database (). All the BAC clones were purchased from Invitrogen (Carlsbad, CA, USA) and purified using a Qiagen Plasmid Maxi Kit (Qiagen, Hilden, Germany). By nick translation, the extracted DNA was further fluorescently labelled with either Spectrum Orange- or Spectrum Green-dUTP (Abbott Molecular, Des Plaines, IL, USA), respectively. The labelled DNA probes were then mixed with Human Cot-1 DNA, hybridisation buffer, and purified water. Before hybridisation, correct mapping and optimal signal strength were confirmed in peripheral blood.
FISH was performed as previously described [16]. In brief, formalin-fixed paraffin-embedded (FFPE) tissue slices were cut at 4 μm. After dewaxing, heat retrieval, and digestion, the slices and probe were co-denatured at 85 °C for 5 min and hybridised overnight at 37 °C. Slices were then incubated, washed, and mounted with DAPI. A total of 200 intact nuclei were counted under a fluorescence microscope (Zeiss, Oberkochen, Germany). The sample was interpreted as positive when at least 15% of the nuclei showed a separate red and green signal pattern. Non-tumour cells in the tissue were used as internal controls to exclude false positives.
Whole-genome sequencing
A DNA FFPE kit (Tiangen Biotech, Beijing, PR China) was utilised to extract DNA from 10 to 20 slices of FFPE blocks with at least 50% tumour content. A total amount of 500 ng DNA was used for library preparation. The genomic library was generated using the Truseq Nano DNA HT Sample Prep Kit (Illumina, San Diego, CA, USA) according to the manufacturer's instructions. In brief, genomic DNA was fragmented to an average size of about 350 bps. After the PCR products were amplified and purified, the libraries were analysed for size distribution by an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA) and quantified by real-time PCR. Then the final DNA libraries were sequenced on an Illumina Hiseq platform and 150-bp paired-end reads were generated with about 90 Gb data per sample.
Raw sequencing data were aligned to the human genome (GRCh37/hg19) using Burrows-Wheeler Aligner (BWA) software. SAMtools-0.1.18 was used for sorting, removing duplicates, and building indexes for the bam files [17]. The LUMPY pipeline was applied to detect genomic structural variations (SVs) [18]. The Control-FREEC software was applied to generate copy number variation (CNV) and B allele frequency information based on single nucleotide polymorphism (SNP) data [19]. A circos plot representing the sequencing data was drawn by OmicStudio () [20]. The SVs were filtered according to the following criteria: events annotated as artefacts, footprints smaller than 100 bases, less than 15 run-reads or 5 discordant mate pairs, and under-represented repeats. All filtered SVs underwent manual rechecks using IGV software. Chromothripsis was defined as the formation of tens to hundreds of locally clustered rearrangements interspersed with oscillations between two copy number states [21].
Specific primers were designed to span breakpoints. Then junction fragments were amplified using the pre-designed primers and further sequenced by the 3500 Genetic Analyzer (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA).
Standard PCR was performed to amplify a 146-bp fragment of the TERT promoter region, covering all common mutations (C228T, CC229TT, CC242TT, and C250T, corresponding to nucleotide positions −124, −125, −138, and −145 from the ATG translational start site), with forward primer 5′-TTCCAGCTCCGCCTCCT-3′ and reverse primer 5′-AGCGCTGCCTGAAACTCG-3′. Subsequently, PCR products were used as templates for direct sequencing using the ABI 3500 Genetic Analyzer (Applied Biosystems).
Total RNA from 10 slices of FFPE tissues was extracted using the RNAprep Pure FFPE kit (Tiangen Biotech) following the manufacturer's protocol. RNA concentration was determined using Nano 8000. cDNA was then synthesised using PrimeScript RT Master Mix (Takara Bio, Shiga, Japan). RT-qPCR was conducted with iQ SYBR Green Supermix (Bio-Rad, Hercules, CA, USA) with TERT and ACTB primers. The primers were as follows: TERT, forward 5′-TCACGGAGACCACGTTTCAAA-3′, reverse 5′-TTCAAGTGCTGTCTGATTCCAAT-3′; ACTB, forward 5′-CATGTACGTTGCTATCCAGGC-3′, reverse 5′-CTCCTTAATGTCACGCACGAT-3′. Relative TERT expression was normalised to ACTB using the 2-∆Ct method. Separation of the amplified products was accomplished using 3% agarose gels.
Immunohistochemistry staining
Two TERT antibodies (1:50 dilution for ab32020 and 1:100 dilution for ab183105, Abcam, Cambridge, UK) were used to stain the FFPE slides. A Bond Refine polymer staining kit (Leica Biosystems, Wetzlar, Germany) was used with an automated staining system. After antigen retrieval with E1 retrieval solution (pH 6.0) for 20 min, slides were rinsed, dehydrated, and covered. Each slice was evaluated for the percentage and intensity (0 – none to 3 – intense) of staining. Tonsillar tissue was used as a positive control.
Statistical analysis
GraphPad Prism (version 6.05, GraphPad Software, San Diego, CA, USA) was used for statistical analysis and data presentation. Overall survival was calculated based on the time between diagnosis and death or the last follow-up if the patient survived. Progression-free survival was calculated from diagnosis to the time of tumour progression, relapse, death from disease, or the last follow-up if no event had occurred. A Kaplan–Meier survival curve was estimated and compared with a log-rank test (R survival package version 2.15.0). Univariate and multivariate Cox regression analyses were applied to evaluate independent survival-related factors. Data analysis was conducted using JMP software, version 14.0.0 (SAS Institute Inc., Cary, NC, USA), and p values <0.05 were considered statistically significant.
Results
Demographic and clinical characteristics
A total of 633 NTs were recruited (Figure 1). The clinical–pathological characteristics are summarised in Table 1. The cohort comprised 330 boys and 303 girls, one-third of whom were under 18 months. Three hundred and forty-four (54.3%) of the primary tumours were located in the adrenal region, 118 (18.6%) in the chest, and 147 (23.2%) in other regions. The remaining 24 cases (3.8%) were metastases or relapses. In total, 308 specimens were surgically obtained from untreated individuals, and the remainder were treated with chemotherapy before surgery. As for the histological subtypes of untreated NTs, there were 233 (75.7%) NB and 75 (24.3%) GNBn, with 232 (75.3%) being undifferentiated/poorly differentiated and 76 (24.7%) being differentiated. Low, intermediate, and high mitosis karyorrhexis index (MKI) was found in 108 (38.0%), 137 (47.2%), and 39 (13.7%) cases, respectively. Eighty-five patients (26.6%) were diagnosed with stage 1, 2, or 4s tumours, while 235 (73.4%) were Stage 3 or 4. Based on the COG system, 160 patients (61.8%) were classified as HR and 99 as LR/IR. According to the genomic status of MYCN and TERT, this cohort was further divided into three different groups: the MYCN non-amplification with TERT non-rearrangement group (MYCN−TERT−, 505/633), the MYCN amplification with TERT non-rearrangement group (MYCN+TERT−, 90/633), and the TERT rearrangement group (TERT+, 38/633).
Table 1 Demographic and clinicopathological characteristics of all patients with NTs
| Factors | Total | MYCN−TERT− | MYCN+TERT− | TERT+ | p value |
| Sex, n (%) | |||||
| Male | 330 (52.13) | 252 (49.90) | 58 (64.44) | 20 (52.63) | 0.039 |
| Female | 303 (47.87) | 253 (50.10) | 32 (35.56) | 18 (47.37) | |
| Age at diagnosis (months) | |||||
| <18, n (%) | 204 (32.23) | 186 (36.83) | 17 (18.89) | 1 (2.63) | <0.001 |
| ≥18, n (%) | 429 (67.77) | 319 (63.17) | 73 (81.11) | 37 (97.37) | |
| Sites, n (%) | |||||
| Adrenal primary | 344 (54.34) | 246 (48.71) | 71 (78.89) | 27 (71.05) | <0.001 |
| Thoracic primary | 118 (18.64) | 111 (21.98) | 3 (3.33) | 4 (10.53) | |
| Others* | 147 (23.22) | 130 (25.74) | 12 (13.33) | 5 (13.16) | |
| Metastasis/relapse | 24 (3.79) | 18 (3.56) | 4 (4.44) | 2 (5.26) | |
| Diagnostic category (pre-chemotherapy), n (%) | |||||
| NB | 233 (75.65) | 189 (71.86) | 37 (100.00) | 7 (87.50) | 0.001 |
| GNBn | 75 (24.35) | 74 (28.14) | 0 (0.00) | 1 (12.50) | |
| Grade of differentiation (pre-chemotherapy), n (%) | |||||
| Undifferentiated/ poorly differentiated† | 232 (75.32) | 189 (71.86) | 37 (100.00) | 6 (75.00) | 0.001 |
| Differentiating | 76 (24.68) | 74 (28.14) | 0 (0.00) | 2 (25.00) | |
| MKI index (pre-chemotherapy)‡, n (%) | |||||
| Low (<2%) | 108 (38.03) | 103 (42.21) | 3 (9.09) | 2 (28.57) | <0.001 |
| Intermediate (2–4%) | 137 (48.24) | 117 (47.95) | 15 (45.45) | 5 (71.43) | |
| High (>4%) | 39 (13.73) | 24 (9.84) | 15 (45.45) | 0 (0.00) | |
| 1p status, n (%) | |||||
| Normal | 270 (70.87) | 245 (78.78) | 13 (26.00) | 12 (60.00) | <0.001 |
| Abnormal§ | 111 (29.13) | 66 (21.22) | 37 (74.00) | 8 (40.00) | |
| 11q status, n (%) | |||||
| Normal | 243 (63.78) | 196 (62.82) | 41 (83.67) | 6 (30.00) | 0.001 |
| Abnormal§ | 138 (36.22) | 116 (37.18) | 8 (16.33) | 14 (70.00) | |
| INSS stage, n (%) | |||||
| 1/2/4s | 85 (26.56) | 79 (32.24) | 3 (7.69) | 3 (8.33) | <0.001 |
| 3/4 | 235 (73.44) | 166 (67.76) | 36 (92.31) | 33 (91.67) | |
| COG risk group, n (%) | |||||
| LR | 51 (14.61) | 49 (22.07) | 0 (0%) | 2 (5.41) | 0.010¶ |
| IR | 48 (13.75) | 44 (19.82) | 0 (0%) | 4 (10.81) | |
| HR | 250 (71.63) | 129 (58.11) | 90 (100%) | 31 (83.78) |
A FISH-based probe set was developed to identify TERT rearrangements (Figure 2A). A total of 38 rearrangement-positive samples were identified. TERT rearrangement-positive samples exhibited fused yellow signals with split red and green signals, split green signals, split red signals, or additional red and green weak dots (Figure 2B). In addition, two cases (T65 and T97, Figure 2B) showed focal amplification of red or green signals. A commercial TERT gene counting probe (LBP Technology, Guangzhou, PR China) was used to verify that the TERT gene was present together with the translocation signal (data not shown).
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To validate TERT rearrangements, 20 FISH-positive samples with tumour content over 50% were selected for WGS. The precise breakpoint positions and fusion partners of 11 of the 20 sequenced tumours were determined, whereas the other nine cases with complex rearrangements or translocation partners were not determined. The breakpoints were further validated by PCR and Sanger sequencing (supplementary material, Figure S1). A circos plot (Figure 2C) displays all intra- and inter-chromosomal rearrangements from the TERT locus, as well as the breakpoint positions, mate chromosomes, and copies associated with the breakpoints (Figure 2D). Nine of the 11 cases had a breakpoint within 140-kb upstream of the TERT locus, while 4 had a breakpoint within 100-kb downstream (2 cases had two breakpoints, Figure 2D and supplementary material, Figure S1). Translocated chromosome regions were found on chromosome 5 (six cases) and other chromosomes (five cases). Various alteration patterns were observed, including balanced rearrangements, translocations associated with single-copy number gains or deletions, and focal amplifications (Figure 2D), all consistent with the corresponding FISH signals. Moreover, one rearrangement case was associated with chromothripsis of chromosome 5 (supplementary material, Figure S2). The rearrangements consistently clustered around the TERT locus without directly affecting the gene or its core promoter (Figure 2D). No mutations were observed in the TERT gene or its core promoter (data not shown).
As part of a further investigation of the incidence of TERT hot-spot mutations in NTs, 85 additional samples with a neoplastic cell content over 50% were randomly chosen for PCR amplification and Sanger sequencing. When the previous 20 WGS cases were included, the cohort was composed of 61 boys and 44 girls between the ages of 1 and 152 months, spanning all clinical stages and grades. With the exception of one 9-year-old girl who acquired a 228 C>T mutation, all members of the study had a wild type TERT promoter.
A total of 30 age, stage, and grade matched samples were selected to determine whether TERT rearrangements might affect mRNA expression (10 samples each for the MYCN−TERT−, MYCN+TERT−, and TERT+ groups). According to the quantitative RT-PCR results (Figure 3A), TERT mRNA expression was significantly higher in the TERT+ group than in other groups, suggesting that TERT rearrangements could increase TERT mRNA expression. MYCN-amplified cases also had elevated TERT mRNA levels, whereas HR NTs with neither TERT nor MYCN changes had low TERT mRNA levels. A further immunohistochemical analysis was conducted using two antibodies (ab32020 and ab183105) to determine the expression of the TERT protein. There was, however, only a trend towards increased TERT protein (Figure 3B), which did not reach statistical significance.
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To evaluate the clinical relevance of TERT defects on patient survival, follow-up information was collected from 236 cases. According to Kaplan–Meier analysis, the progression-free survival rates and the overall survival rates of the TERT+ group were significantly lower than those of the MYCN−TERT− group, and close to those of the MYCN+TERT− group (Figure 3C,D). Univariate Cox regression analysis revealed that age, MYCN, and TERT alterations were significantly related to progression-free survival and overall survival (Figure 3E). Based on the multivariate Cox regression analysis, both MYCN amplification and TERT rearrangements were associated with poor prognosis (Figure 3F). The most significant variable was MYCN amplification, followed by TERT rearrangement. These results suggest that TERT rearrangement is an independent prognostic factor for NTs.
Characteristics of
Thirty-eight of the 633 specimens tested were positive for TERT rearrangements (Tables 1 and 2). The positive rate was 6.0% in all NTs (38/633) and 12.4% in HR NTs (31/250). The TERT+ group included 20 boys and 18 girls with a median age of 44 months at diagnosis (range 10–93 months, mean 47 months). When compared with the groups negative for TERT rearrangement (MYCN−TERT− and MYCN+TERT−), this TERT+ group had a greater prevalence of older children over 18 months (except for a 10-month-old baby). The majority of tumours originated from the adrenal gland, mimicking the MYCN+TERT− group. Furthermore, the TERT+ group consisted primarily of Stage 3/4 (33 of 36) and HR (31 of 37) NTs, and the percentage of TERT rearrangements in Stage 3/4 and HR NTs was greater than that in stage 1/2/4s and LR/IR NTs.
Table 2 Clinicopathological characteristics of NTs with
| Cases | Age (mo.)/sex | Origin | Preoperative chemotherapy | Diagnostic category | Tumour differentiation | INSS stage | COG risk | TERT amp. | MYCN status | 1p status | 11q status | Outcome |
| T2 | 57/M | Adrenal | Yes | NB | Differentiating | 4 | HR | No | Normal | – | – | NA |
| T12 | 37/F | Adrenal | Yes | GNBn | Poorly differentiated | 4 | HR | No | Gain | – | – | DOD (16) |
| T17 | 22/F | Retroperitoneal | No | NB | Differentiating | 4 | HR | No | Normal | – | – | NED |
| T28 | 44/M | Adrenal | Yes | GNBn | – | 4 | HR | No | Normal | – | – | AWD (53) |
| T29 | 52/M | Adrenal | Yes | NB | Poorly differentiated | 4 | HR | No | Normal | – | – | DOD (13) |
| T65 | 47/F | Adrenal | Yes | NB | Differentiating | 4 | HR | Yes | Amp. | – | – | NED |
| T78 | 90/M | Adrenal | Yes | GNBn | Differentiating | 4 | HR | No | Gain | – | – | AWD (59) |
| T82 | 10/M | Mediastinal | No | NB | Poorly differentiated | 2 | LR | No | Normal | – | – | NED |
| T97 | 48/F | Retroperitoneal | No | NB | Poorly differentiated | 3 | IR | Yes | Gain | – | – | DOD (47) |
| T125 | 31/F | Bone marrow | No | – | – | 4 | HR | No | Normal | – | – | DOD (30) |
| T144 | 52/M | Adrenal | Yes | GNBn | Poorly differentiated | 4 | HR | No | Normal | – | – | NA |
| T145 | 37/M | Adrenal | Yes | GNBn | Differentiating | 4 | HR | No | Normal | – | – | NA |
| T151 | 93/M | Mediastinal | Yes | NB | Differentiating | 4 | HR | No | Gain | – | – | NED |
| T170 | 62/M | Adrenal | Yes | NB | Poorly differentiated | 4 | HR | No | Gain | – | – | NED |
| T174 | 36/M | Adrenal | Yes | GNBn | Poorly differentiated | 4 | HR | No | Normal | – | – | AWD (36) |
| T181 | 76/M | Mediastinal | Yes | GNBn | Poorly differentiated | 4 | HR | No | Gain | – | – | DOD (24) |
| T225 | 92/F | Bone marrow | No | – | – | 4 | HR | No | Amp. | – | – | DOD (18) |
| T248 | 23/F | Adrenal | No | NB | Undifferentiated | 4 | HR | No | Normal | Normal | LOH | NED |
| T254 | 20/M | Adrenal | No | NB | Poorly differentiated | 4 | HR | No | Gain | LOH | Normal | DOD (6) |
| T258 | 18/M | Retroperitoneal | Yes | GNBn | Poorly differentiated | 4 | HR | No | Normal | Imbalance | LOH | NA |
| T259 | 47/F | Adrenal | No | GNBn | Poorly differentiated | 3 | IR | No | Normal | Normal | LOH | NED |
| T333 | 37/M | Adrenal | Yes | NB | Differentiating | 4 | HR | No | Gain | Normal | LOH | AWD (33) |
| T346 | 62/M | Adrenal | Yes | NB | Poorly differentiated | 4 | HR | No | Gain | LOH | LOH | NED |
| T377 | 70/M | Adrenal | No | NB | Differentiating | 4 | HR | No | Normal | Normal | LOH | NED |
| T392 | 59/F | Mediastinal | Yes | GNBn | Differentiating | 4 | HR | No | Gain | Imbalance | Normal | NED |
| T454 | 36/F | Adrenal | Yes | GNBn | Differentiating | 4 | HR | No | Normal | Normal | Imbalance | NED |
| T463 | 50/F | Adrenal | Yes | GNBn | Differentiating | 4 | HR | No | Normal | Normal | LOH | NED |
| T488 | 32/M | Adrenal | Yes | NB | Poorly differentiated | 4 | HR | No | Amp. | Imbalance | Imbalance | NED |
| T504 | 32/F | Adrenal | Yes | GNBn | Poorly differentiated | 4 | HR | No | Normal | Normal | LOH | NED |
| T522 | 43/M | Adrenal | Yes | NB | Differentiating | 4 | HR | No | Gain | Normal | Normal | NED |
| T574 | 41/F | Adrenal | Yes | NB | Poorly differentiated | 4 | HR | No | Normal | Imbalance | Imbalance | AWD (18) |
| T579 | 37/F | Adrenal | Yes | NB | Poorly differentiated | 4 | HR | No | Normal | Normal | LOH | NED |
| T601 | 36/F | Adrenal | Yes | NB | Poorly differentiated | 2 | IR | No | Normal | Normal | LOH | NED |
| T607 | 81/M | Retroperitoneal | Yes | GNBn | Differentiating | 2 | LR | No | Normal | Normal | Normal | NED |
| T609 | 51/F | Adrenal | Yes | NB | Poorly differentiated | – | HR | No | Normal | – | – | DOD (44) |
| T699 | 66/F | Adrenal | Yes | NB | Poorly differentiated | – | – | No | – | LOH | Normal | NA |
| T703 | 28/F | Retroperitoneal | No | NB | Poorly differentiated | 4 | HR | No | – | Normal | LOH | NED |
| T720 | 37/M | Adrenal | Yes | NB | Poorly differentiated | 3 | IR | No | Normal | Imbalance | Normal | AWD (20) |
Pre-chemotherapy samples were analysed to investigate the histopathological features of TERT rearrangement cases. The TERT+ group was composed of either NB or GNBn (Table 1, Figure 4A–D), whereas the MYCN+TERT− group was exclusively composed of NB.
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To explore if TERT rearrangement was associated with tumour differentiation grade, 308 pre-chemotherapy specimens were analysed (Table 1). All the MYCN amplification cases were undifferentiated/poorly differentiated NBs, but not the TERT-rearranged tumours, which could occur in all three histological subtypes. There was no statistical difference between histological subtypes and TERT rearrangement.
Post-chemotherapy specimens showed TERT rearrangement in NB and GNB types with all differentiation subtypes and MKI indices. The mild histological appearance after chemotherapy might be misleading. One post-chemotherapy specimen displayed a rearrangement-negative GN-like appearance in the primary site (Figure 4E1), but a rearrangement-positive NB component in the invaded distal lymph node (Figure 4E2). To investigate whether TERT rearrangements exist in histologically benign NT types, an additional cohort of 87 GNBi and GN specimens was tested; no positive results were observed (data not shown).
Genetically, MYCN status is positively associated with chromosome 1p aberration, but negatively with chromosome 11q aberration, whereas TERT-rearranged individuals have abnormal 11q but not 1p (Table 1, Figure 3A). An array of comparative genomic hybridisation-like CNV profiles was created based on WGS coverage data to examine the cytogenetic features of TERT-rearranged NTs. A detailed overview of all imbalances exceeding 1 Mb, as well as smaller (>100 kb) homozygous deletions and imbalances affecting TERT or MYCN, is presented in supplementary material, Table S1 and visualised in Figure 5. All 11 samples validated by WGS showed multiple imbalances (mean 123, range 42–517). Most imbalances were segmental chromosomal abnormalities. The following changes were recurrent: gain of several regions on 17q, 7q, 1q, or 2p in 11, 9, 6, or 6 cases respectively, as well as loss of heterozygosity (LOH) on 5p12-q11.1, 11q, 12p11.1-q11, or 19p11-q11 in 6, 5, 5, or 5 cases respectively.
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Discussion
The TERT gene is the core component of human telomerase and TERT activation correlates with advanced tumour stage and poor prognosis in various tumours [22,23]. Rearrangement of the TERT promoter region was recently reported to be the second most frequent gene alteration and defined as a separate group of NBs [11,12], making it a promising molecular biomarker for NT risk stratification. In this study, we developed a fast and convenient FISH probe to detect TERT rearrangements in a large cohort of 633 NT specimens of all pathological types. Both WGS and Sanger sequencing validated this probe's reliability. Clinical and histological characteristics of TERT-rearranged NTs were further addressed.
TERT rearrangements occur both upstream and downstream of the TERT locus and are often accompanied by CNVs [12], which are commonly examined using WGS or GeneChip SNP arrays [11,14]. However, their high cost, high-tech nature, and specimen type-dependence limit their clinical use. An easy and reliable method of detecting large-scale SVs in almost any sample type is FISH. This prompted us to develop a FISH-based probe to detect TERT rearrangements. Peifer et al examined 161 primary NB by FISH and targeted sequencing and found 16 TERT-rearranged cases [11]. Here, we further analysed the reliability and utility of the FISH method in detecting TERT rearrangements in a large sample of 633 NT patients. Various types of balanced and unbalanced translocation signal patterns were observed, including TERT locus amplification, which had substantial practical value.
Previous reports of TERT rearrangements were within 50 kb upstream and 6–40 kb downstream of the TERT locus [11,12]. This region was expanded to 140 kb upstream and 100 kb downstream as part of our study. Additionally, we also found that one case had acquired two breakpoints, due to chromothripsis or other reasons (Figure 2D). To ensure that the breakpoints were limited to the TERT promoter region, we manually screened all the 600-kb regions up and downstream of this locus, which covers all the FISH probe loci. No further breakpoints other than those previously mentioned were found. In summary, as a potential assay recommended to detect TERT maintenance mechanisms [24], FISH is an applicable method for TERT alteration detection.
Telomerase activity is crucial for cancer initiation and immortalisation, which correlates with advanced tumour stages and poor outcomes [22,23]. TERT hot-spot mutations and rearrangements are two mechanisms resulting in high TERT expression and telomerase activation [22,25]. In most HR NTs, TERT is overexpressed [11,12,26]. Studies using a large cohort of NTs indicated that TERT mutations were not common mechanisms of TERT overexpression [27,28]. In our study, a total of 105 samples were tested for TERT promoter mutation. All members of the cohort had a wild type TERT, except for one 9-year-old girl who acquired a 228 C>T mutation, suggesting TERT promoter mutations are not a frequent mechanism of TERT overexpression in NTs. However, TERT rearrangements were associated with transcriptional upregulation of TERT mRNA regardless of MYCN status. TERT rearrangement was often accompanied by CNVs. Peifer et al reported that TERT rearrangement itself, rather than copy number gain, was the major cause of mRNA upregulation [11]. Additionally, MYCN activates TERT expression [25]. The TERT mRNA expression level was also elevated in the MYCN+TERT− group. Therefore, both TERT rearrangement and MYCN amplification contribute to HR NTs through telomerase activation.
Another mechanism associated with telomere abnormality in NB is alternative lengthening of telomeres (ALT). The ALT phenotypes are mostly seen in tumours with ATRX or DAXX aberration [29,30]. The lack of ALT data limited our understanding of the clinicopathological characteristics of other telomere abnormal cases. More efforts are needed to solve this issue.
Evidence has shown that high TERT expression is associated with poor prognosis [11,12,26,31], which was also supported by our study. Telomerase represents a promising therapeutic target in NTs, and telomerase-interacting compounds have been developed [32]. Recently, BET bromodomain inhibitor OTX015 and carfilzomib (an approved oncology drug) have shown strong synergistic effects to block TERT overexpression and suppressed tumour progression [33], encouraging the potential use of targeted therapy in patients with TERT-rearranged NTs.
Which types of
While MYCN is amplified in 20–30% of NB [9,34], the ratio of TERT rearrangements in NTs has not been fully explored. Previously, TERT rearrangements were reported in 11–13% in NB [14,35], whereas the ratio ranged from 23% to 31% in HR patients [11,12]. According to our study, the positive rate in all types of NT was approximately 6%, while it was 12.4% in HR NTs. Different histological types and patient risk grades, as well as regional differences, might explain these differences in ratios. In our previous study that summarised the characteristics of 1041 NTs, MYCN amplification was prevalent in 11% of Chinese patients [36], supporting the regional/ethnic differences with regard to risk categories.
Further, not all TERT-rearranged NTs were Stage 3/4 or HR (Figure 1A), which is different from previous studies [11,12]. Moreover, all cases with TERT rearrangements had onset ages over 18 months, with the exception of one 10-month-old infant. Aside from two cases, the genomic pattern of TERT rearrangements in our study was generally mutually exclusive with MYCN amplification, as reported in existing studies [11,12]. They were usually coupled with other structural abnormalities such as 11q LOH and 17q gain, which are molecular markers for adverse prognosis [3,7]. Therefore, detection of TERT rearrangements is especially important in patients over 18 months without MYCN amplification.
Histologically, NTs are highly heterogeneous, making it difficult to determine which types of NT require determination of TERT status. According to our results, TERT rearrangements were present in all histological subtypes of NB and GNBn, and metastatic lesions tended to have a greater chance of being positive than primary tumours (data not shown). No TERT rearrangements were found in GNBi or GN. Intra-tumoural heterogeneity was common, with better and poorly differentiated areas showing heterogeneity in TERT rearrangements in post-chemotherapy specimens.
Conclusions
In summary, our study confirmed that TERT rearrangements in NTs could be reliably detected by FISH with various signal patterns. TERT defects elevated TERT expression, which acted as an independent prognostic factor and defined a subtype of NT with poor outcomes. Histopathologically, TERT rearrangements occurred in all histological subtypes of NB and GNBn lesions but not in GNBi or GN. This should help with risk management of NT patients.
Acknowledgements
We would like to thank all patients and guardians for their cooperation. This work was supported by the Beijing Hospitals Authority Clinical Medicine Development of special funding support (No. XMLX202121), the National Natural Science Foundation of China (No. 82172849), the Beijing-Tianjin-Hebei Integration Project (No. J200004), and Beijing Hospitals Authority Innovation Studio of Young Staff Funding Support (No. 202126).
Author contributions statement
YY and MZ carried out most of the experiments, data analysis and visualisation, drafting of the manuscript. XY, XG and CJ carried out some experiments and data curation. PC and RZ performed statistical analyses. YY and YJ provided critical technical assistance. HW and XN provided patient sample resources and clinical information. LH and YG provided conceptualisation, funding, project administration and wrote and edited the manuscript. All authors gave feedback and agreed on the final version of the manuscript.
Data availability statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. All data generated or analysed during this study are included in this published article.
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1 Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health (NCCH), Beijing, PR China
2 Department of Pathology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health (NCCH), Beijing, PR China
3 Department of Surgical Oncology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health (NCCH), Beijing, PR China
4 Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health (NCCH), Beijing, PR China, Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health (NCCH), Beijing, PR China, Biobank for Clinical Data and Samples in Pediatrics, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health (NCCH), Beijing, PR China