Segmental chromosome aberrations as a prognostic factor of neuroblastoma: a meta-analysis and systematic review

Introduction

Neuroblastoma is a developing tissue disease, in which the cells originate from precursor cells incompletely developed from neuro crest tissues (1). Arising in the sympathetic nervous system, usually in the adrenal medulla (40%) or other abdominal site (25%), it can also occur in the pelvis (5%), neck (15%), and bone cavity (5%) as mass lesion (2-4). As expected with an embryonal tumor, it is one of the most common pediatric tumors in children, with a median age of diagnosis of 17 months and 37% of cases are diagnosed during infancy (5,6). Neuroblastoma accounts for 8–10% of all childhood malignancies (8.7 cases per million for all; 10.2 cases per million for children under 15 years old) and 15% of childhood tumor deaths (2,7,8). The etiology of neuroblastoma is still unconfirmed but several preconceptual or gestational factors have been suggested to play a significant role, including gestational diabetes, exposure to toxins, viruses, or drugs, and deficiency of folic acid (9-12).

The clinical and phenotypic variability of neuroblastoma is remarkable, ranging from asymptomatic masses with a favorable outcome to aggressive malignant tumors with local invasion or/and widespread dissemination, which is known as high-risk neuroblastoma (2,13). The diversity in the clinical behaviors of this tumor is associated with numerous clinical [such as age and International Neuroblastoma Staging System (INSS)], biological (such as tumor dormancy), and genetic features (such as MYCN gene amplification and ferroptosis-related gene signature), which are used to stratify patients into three risk subgroups with low, intermediate, and high risks of death (with high, intermediate, and low expected survival rates, respectively) (13-16). The International Society of Pediatric Oncology Europe Neuroblastoma Group uses age at diagnosis, MYCN gene amplification, and surgical factors by imaging for risk group assignment (17). The Children’s Oncology Group uses postsurgical tumor stage, histology by Shimada method, and DNA ploidy except for common age and MYCN gene amplification for risk group assignment (18). Furthermore, the International Neuroblastoma Risk Group (INRG) has identified grade of tumor differentiation and chromosome 11q (long arm of chromosome 11) status as new predictors for risk assessment (13).

Since last century, segmental chromosome aberrations have been demonstrated to be associated with poor survival outcome of neuroblastoma. A segmental chromosome aberration is defined as either presence of aberrations in the corresponding chromosomal arms identified by fluorescent in situ hybridization (FISH) method, or deletion or imbalance determined by loss of heterozygosity (LOH) analysis (13,19). The aberrations can be in whole short/long arm (p/q), or a specific part of arms. Loss of 1p, 3p, 4p, and 11q is associated with poor prognosis of neuroblastoma, whereas gain of 1q, 2p, 12q, and 17q is related to poor outcomes (20-25). Recent studies have shown that instead of whole chromosome arm loss or gain, the loss or gain of specific parts of chromosomes is of higher prognostic value (26). Loss of 1p36, 1p22, 6q27, and 11q23 predicts poor overall survival (OS) and event-free survival (EFS) of patients with neuroblastoma, as does gain of 1q22, 2p22, and 12q24 (21,27-29).

There has been controversy associated with the prognostic significance of segmental chromosome aberrations. Some studies could not find any prognostic significance of 1p deletion, 11q deletion, and 17q gain for neuroblastoma (30-32). The reason for this controversy is still unclear. Lim et al. speculated that the chemotherapy for patients with segmental chromosome aberrations varied among studies, which likely caused a difference in survival outcomes (30). To solve the controversy, a meta-analysis is needed to quantitatively analyze the effect of segmental chromosome aberrations on predicting survival of patients with neuroblastoma, which has not been performed before.

The objective of this meta-analysis is to analyze the hazard ratios (HRs) of different whole or segmental chromosome aberrations for OS or EFS rate of patients with neuroblastoma, and further provide useful evidence for clinical decision and recommendation. We present this article in accordance with the PRISMA reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-24-200/rc).

Methods

Inclusion criteria

Population: patients diagnosed with neuroblastoma for the first time regardless of stages, tumor sites, MYCN gene amplification, and other clinical behaviors.

Prognostic factors: segmental chromosome aberrations, defined as loss or gain of whole arms or specific parts of autosomes and sex autosomes. Studies focusing on numerical chromosome aberrations or other genetic factors are excluded.

Outcomes: long term (>3 years) EFS (including relapse-free survival and progression-free survival) and OS.

Study type: original articles focusing on prognosis analysis of patients. Reviews and meta-analyses were excluded. Studies focusing on neuroblastoma cells or other animals were also excluded. Only English-language articles were accepted.

Searching strategy

The databases of PubMed, Embase, and Web of Science were searched for eligible original studies published from inception to April 2023. The keywords searched were chromosome, neuroblastoma, predictor, prognosis, and survival (Appendix 1). All searched records were imported into Endnote 20 (Clarivate, Philadelphia, PN, USA), where duplicates were removed. Thereafter, records with irrelevant titles and abstracts were removed, and the full texts of the remaining articles were obtained and reviewed. Illegible records were removed after full text review and reasons for exclusion were recorded in a flow diagram of study selection. To improve comprehensiveness, the reference lists of the included full text records were further screened for additional eligible records.

Data extraction

Basic characteristics of included articles were extracted: first name of first author, publication year, country, total sample size, mean or median age of patients at first diagnosis and percentage of female patients. Both adjusted and unadjusted HRs of long term (>3 years) EFS and OS with 95% confidence intervals (CIs) were extracted for quantitative synthesis. If HRs were not provided, brief descriptions of results were also collected.

Quality evaluation

The risk of bias of the included articles was evaluated using the Quality In Prognosis Studies tool (33). This tool is composed of 6 bias domains:

• Study participation: assess the risk of selection bias by participation rate, source population statement, baseline sample description, recruitment details, sampling description, and selection criteria.
• Study attribution: assess the risk of attribution bias by response rate, attempt to collect information on patients who dropped out, description of loss to follow up, and outcome and prognostic factor information on patients who dropped out.
• Prognostic factor measurement: assess the risk of measurement bias related to prognostic factors by definition, measurement description, measurement consistency, blindness, continuity or cut-off of variables, and methods to deal with missing data.
• Outcome measurement: assess the risk of measurement bias related to outcomes by definition, measurement description, and consistency.
• Study confounding: assess the risk of confounding bias by inclusion of important confounding factors, definition, consistency of measurement, and appropriate accounting for confounding factors in study design and analysis.
• Statistical analysis and reporting: assess the risk of reporting bias by analytical strategy description, model appropriateness, model adequacy, and reporting of results.

All six domains above are rated as high, moderate, or low risk of bias. If all domains are rated as low or only 1 domain is rated as moderate with others rated as low, the article is rated as low risk of bias. If 1–2 domains are rated as high or 2–3 domains are rated as moderate, the article is rated as moderate risk of bias. If more than 2 domains are rated as high or more than 3 domains are rated as moderate, the article is rated as high risk of bias.

Statistical analysis

For articles that provided HRs of EFS or OS, a random effect model of DerSimonian-Laird was used to analyze the pooled effect (34). R language with Rstudio environment (R Foundation for Statistical Computing, Vienna, Austria) was used to perform meta-analysis and the main package was “metafor”. Tau² test and I² level were used to measure heterogeneity of included articles. Tau² represents the between-study variance whereas I² represents the proportion of total variation across studies truly due to heterogeneity rather than chance. When a P value of Tau² test was <0.1 and I² level was >50%, the level of heterogeneity among the included studies was considered high.

For articles lacking reporting of HRs of EFS and OS, narrative synthesis was used for summarization.

Results

Study selection

The database search yielded 844 records, with 290 from PubMed, 229 from Embase, and 325 from Web of Science (Figure 1). A total of 456 duplicates were removed and titles and abstracts of the remaining 388 records were screened. A further 347 records with irrelevant titles and abstracts are removed and the full texts of the remaining 41 records were obtained and reviewed. A total of seven records were removed: one for non-English written language, two for no available full text, and four for same group of patients. Additionally, five articles were found through screening reference lists of included records. A total of 34 records were included for further qualitive, narrative, and quantitative analysis.

Figure 1 Flow diagram of study selection.

Study characteristics and quality

The basic characteristics and results of risk assessment are summarized in Table 1. The 34 included articles were published from 1988 to 2022. A total of 21 studies were conducted in Europe, 5 were conducted in Asia, 1 was conducted in Africa, 5 were conducted in America, and 2 were conducted across multiple countries. In total, the 34 articles included 14,356 patients and the sample size ranged from 23 to 7,251. The mean or median age of patients at first diagnosis ranged from 12 to 34.8 months. The percentage of female patients ranged from 41.4% to 90%.

A total of 24 articles were rated as low risk of bias. The other 10 articles were rated as moderate risk of bias due to either insufficient description of study participants or insufficient consideration of confounding factors. No article was rated as high risk of bias, so all articles were included for further narrative and quantitative analysis.

Narrative and quantitative analysis

1p loss, 1p36 loss, and 1p22 loss

A total of 25 articles reported inconsistent results of 1p loss. As shown in Figure 2, the pooled effect of HR was 4.46 (95% CI: 1.88–10.59; six studies) for EFS with high heterogeneity (I²=85.34%) and 2.29 (95% CI: 1.26–4.15; eight studies) for OS with high heterogeneity (I²=81.90%). However, Lastowska et al., Ambros et al., Jeison et al., and Twist et al. reported non-significance of 1p loss for EFS, whereas Takeda et al. reported significance (25,32,37,45,53). Hesseling et al., Vandesompele et al., Burgues et al., Mosse et al., Jeison et al., Schleiermacher et al., Ambros et al., and Salim et al. reported non-significance of 1p loss for OS, whereas Christiansen et al., Caron et al., and Schleiermacher et al. reported significance (20-23,36,38,40,43,45,47,53,54).

Figure 2 Forest plots of 1p loss. EFS, event-free survival; CI, confidence interval; RE, random effects.

A total of 5 articles reported inconsistent results of 1p36 loss. For OS, Mora et al. and Maris et al. reported that it was not a significant predictor whereas Attiyeh et al. reported its HR of 2.92 with 95% CI of 1.48–5.76 in multivariate analysis (27,28,41). For EFS, Maris et al. reported its HR of 1.90 with 95% CI of 1.21–2.97 in multivariate analysis, whereas Pezzolo et al. and Yue et al. reported non-significance in multivariate analysis with significance in univariate analysis (28,44,55).

Mora et al. also reported that 1p22 loss was not a significant predictor for OS (27).

17q gain

A total of 15 articles reported inconsistent results of 17q gain. As shown in Figure 3, the pooled effect of HR was 4.81 (95% CI: 3.29–7.04; five studies) for EFS without heterogeneity (I²=0) and 3.98 (95% CI: 2.11–7.54; three studies) for OS without heterogeneity (I²=0). However, Jeison et al., Ambros et al., and Lim et al. reported non-significance of 17q gain for EFS, whereas Lastowska et al. reported significance (25,30,45,53). Mora et al., Mosse et al., Janoueix-Lerosey et al., Jeison et al., Schleiermacher et al., Lim et al., and Salim et al. all reported non-significance of 17q gain for OS, whereas Ambros et al. reported significance (21,26,27,30,45,47,53,54).

Figure 3 Forest plots of 17q gain. EFS, event-free survival; CI, confidence interval; RE, random effects.

11q loss, 11q23 loss, and 11q13-q14 gain

A total of 12 articles reported inconsistent results of 11q loss. As shown in Figure 4, the pooled effect of HR was 2.94 (95% CI: 2.32–3.73; four studies) for OS without heterogeneity (I²=0). However, Lim et al., Salim et al., Schleiermacher et al., and Mosse et al. all reported non-significance of 11q loss for OS, whereas Ambros et al. reported significance (21,30,47,53,54). For EFS, Caron et al., Takeda et al., Amros et al., and Lim et al. all reported non-significance of 11q loss for EFS, whereas Twist et al. reported significance (22,30,32,37,53).

Figure 4 Forest plots of 11q loss. OS, overall survival; CI, confidence interval; RE, random-effects.

A total of 4 studies reported inconsistent results of 11q23 loss. For OS, Mora et al. and Attiyeh et al. reported that it was not a significant predictor, whereas Mosse et al. reported it as a significant predictor with P<0.0001 (21,27,41). For EFS, Yue et al. reported that it was not a significant predictor for all patients, but it was a significant predictor for MYCN gene nonamplified patients with HR =1.774 (95% CI: 1.007–3.126) (55).

Mosse et al. also reported that 11q13-q14 gain was a significant predictor for EFS (21).

1q gain and 1q22 gain

A total of 3 studies reported inconsistent results of 1q gain. For OS, Ambros et al. reported it as a significant predictor with P=0.002, whereas Vandesompele et al. and Janoueix-Lerosey et al. reported that it was not significant in multivariate analysis (23,26,53). Ambros et al. also reported non-significance in multivariate analysis of EFS (53).

Pezzolo et al. reported that 1q22 gain was not a significant predictor for OS (44).

2p gain

A total of 3 studies reported inconsistent results of 2p gain. Janoueix-Lerosey et al. and Szewczyk et al. reported its non-significance for OS, whereas Ambros et al. reported that it was a significant predictor both for OS and EFS in univariate analysis (26,49,53).

3p loss, 4p loss, 14q loss, and 14q32 loss

The results for these segmental chromosome aberrations were consistent. Ambros et al., Vandesompele et al., and Janoueix-Lerosey et al. all reported non-significance of 3p loss for OS and Ambros et al. also reported non-significance of 3p loss for EFS (23,26,53). Janoueix-Lerosey et al. and Ambros et al. both reported non-significance of 4p loss for OS, and Ambros et al. and Caron et al. both reported non-significance of 4p loss for EFS (22,26,53). Caron et al. and Takeda et al. both reported non-significance of 14q loss for EFS and Mora et al. reported non-significance of 14q32 loss for OS (22,27,37).

Others

Mora et al. reported that both 19q13 loss and 9p21 loss were not significant predictors for OS (27). Mosse et al. reported that 3q gain, 6p gain, 10q gain, and 12q gain were all significant predictors for EFS in univariate analysis, whereas only 12q24 gain was a significant predictor for EFS in multivariate analysis (21). Pezzolo et al. reported significance of 7p11.2p22 gain for EFS (44). Parodi et al. reported non-significance of chromosome X for OS (50). Qin et al. reported significance of 11p14 gain for OS (52). Ognibene et al. reported that 6q27 was responsible for poor OS (29).

Discussion

A total of 34 articles were included for analysis and the pooled effects suggested that 1p loss, 11q loss, and 17q gain were significant independent predictors for long-term OS and EFS of patients with neuroblastoma. However, the evidence level of these results is still doubtful.

Although 25 articles reported 1p loss, the number of studies reporting HRs of OS and EFS was still less than 10, which means that test of publication bias and leave one out sensitive analysis were not applicable in this case. Moreover, quite a few of the included studies did not report HRs of 1p loss in multivariate analysis because of non-significance in univariate analysis, making this pooled effect biased. Besides, the heterogeneity of pooled effects was very high (>80%), making the credibility weaker. Similar to 1p loss but without heterogeneity, quite a few studies did not report HRs of 17q gain and 11q loss, making the results biased.

As for other segmental chromosome aberrations reported in at least 3 articles, only the results of 3p loss, 4p loss, 14q loss, and 14q32 loss were consistent with non-significance. The results of 1p36 loss, 11q23 loss, 1q gain, and 2q gain were inconsistent and more articles reported non-significance. With regard to the remaining chromosome aberrations reported only in 1 or 2 studies, more evidence is needed for synthesis.

The potential mechanism of action of segmental chromosome aberrations remained unknown, yet articles reporting on it indicated that it was not related to MYCN gene amplification (26,30). Stigliani et al. reported that neuroblastoma with segmental chromosome aberrations tend to accumulate additional genetic instability so the coexistence of several segmental chromosome aberrations should be considered (56). Besides, Szewczyk et al. speculated that 2p gain causes a partial trisomy of 2p, which contains several genes involved in carcinogenesis such as ADAM17, ALK, and BCL11A (49). Ognibene et al. also reported that SFT2D1, RPS6KA2, and FGFR1OP genes on 6q27 were responsible for poor prognosis of patients with high-risk neuroblastoma with 6q27 loss (29). Therefore, specific genes on altered chromosomes can act as surrogate markers for segmental chromosome aberrations and will confer an extra edge to the selection (57). Future studies should focus on the relationship between specific genes, segmental chromosome aberrations, and prognosis of patients with neuroblastoma to further research on the potential mechanism.

This meta-analysis has some limitations as mentioned before. First, the number of eligible articles for quantitative synthesis is too small to conduct test of publication bias and leave one out sensitive analysis. Second, quite a few studies reporting non-significance provided HRs, making the synthesized result biased. Third, all of the included studies were English-language and none of the non-English datasets were searched, leading to language bias. Therefore, the evidence level of these results was not that high.

Conclusions

In conclusion, 1p loss, 11q loss, and 17q gain were shown to be significant independent predictors for long-term OS and EFS of patients with neuroblastoma. Future studies should report comprehensive and detailed statistical results and focus on special genes on these chromosomes.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-24-200/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-24-200/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-24-200/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Jones)