Neuroblastoma is a solid tumor that can develop from immature nerve cells in several areas of the body. It most commonly affects children and rarely occurs in adults 1. In this study, we analyzed both WXS and RNA-seq data from neuroblastoma patients to identify somatic mutations and their allele-specific expression. Because the majority of somatic mutations are identified from DNA-seq techniques such as whole exome sequencing, the allelic expression of those mutations is often not known. Proteins, the functional units of a live cell, are made from mRNA, so a somatic mutation may have very different effects on cellular function that vary with its allelic expression profile. In our study, we confirmed multiple known neuroblastoma mutations and also identified ZNF44 (zinc finger protein 44) as a potentially actionable somatic mutation.
Our study explored two cohorts of neuroblastoma patients with either WXS or WTS data available. The overlapping rates of the two cohorts were high, 38.8% (85/219) of WXS group and 66.9% (85/127) of WTS group. It has been reported that, using WXS identification, mutation frequencies of somatic genes including ALK (9.2% of cases), PTPN11 (2.9%), ATRX (2.5%), MYCN (1.7%), and NRAS (0.83%) are significant in neuroblastoma 18. As expected, WXS revealed mutations in some of these genes, including ALK, MYCN and PTPN11. The MYCN mutation rate (1.4%, 3/219) was similar to a previous report. However, ALK (3.2%, 7/219) and PTPN11 (1%, 2/219) mutation rates were lower than previously reported 19. Notably, in our study, RUSC2 presented the second highest mutation frequency (3.7%, 8/219) in analysis of WXS, and was identified by WTS as well. RUSC2 is a protein-coding gene which has mutations associated with mental retardation and microcephaly. CNGB1 and ZNF44 variants were revealed by both WXS and WTS as well. Although CNGB1 and ZNF44 are not commonly associated with neuroblastoma, they both presented similar mutation frequencies (1%, 2/219) to that of MYCN in the WXS analyzed in this study. ZNF44 encodes a zinc finger protein also known as gonadotropin-inducible transcription factor (GIOT-2). ZNF44 is expressed in human organs and tissues at various levels (Suppl Fig. 1). Mutations in ZNF44 have been detected cancers of the uterus, stomach, ovaries, and more (Suppl Fig. 2). However, mutations of this gene have not been reported in neuroendocrine tumors before; to the best of our knowledge, it is the first report of ZNF44 mutation in neuroblastoma (Suppl Fig. 3). ZNF44 is reported to be involved in epilepsy susceptibility, and binds a factor which is abundant in developing nervous tissue 20. Thus, ZNF44 may play an as-yet-undetected role in neuroendocrine tumors like neuroblastoma. In our study, ZNF44 mutations were discovered in neuroblastoma by both WXS and RNA-sEq. Specifically in the analyzed RNA-seq data, the prevalence of ZNF44 variant chr19: 12,273,632/ C > CA, was 6.3%. Given that the average tumor and stroma percentages in samples were highly consistent at 80%/20%, respectively, the ZNF44 normal allele was expressed an average of 3.0 fold higher than the mutated allele, suggesting the ZNF44 variant might be a potential disease-related site.
As expected, there were some differences between WTS and WXS analysis. WXS identified a gene RIMS4 (Regulating Synaptic Membrane Exocytosis 4) with a high mutation frequency (8.7%, 19/219), but this was not detected by WTS. Notably, more variants in known disease-related genes ALK (Suppl Fig. 4) and MYCN (Suppl Fig. 5) were detected in the WTS group, but far fewer were found by WXS, suggesting WTS provided more information on gene variation. It can be understood that WXS and WTS are both useful bio-technological methods with their own advantages. WXS is considered the gold standard method and is routinely used in oncology 4. However, it cannot reflect gene expression levels. WTS has been hailed as a promising approach that presents distinct advantages, especially for determining transcriptome characteristics 21. However, WTS is not suitable for discovery of DNA mutations. Thus, the combination of WXS and WTS can provide complementary perspectives on gene mutations. In our study, an interesting finding from RNA-seq analysis was that, in one patient sample harboring two different RUSC2 variants, the allelic expression levels of the normal vs. mutated SNVs were quite different. Although the samples were from the same patient, the results were completely opposite, suggesting that the allelic expression levels of the two SNVs were not due to different ratios of normal and tumor cells in the sample, but due to allele-specific expression. Proteins play their bio-functional roles via both biological structure and expression levels. Therefore, both the mutation locations and their allelic expression levels may be related to response to targeted therapy. However, the limitations of our study include the small sample size, limited clinical information, lack of original raw FASTQ files to confirm indel alignment errors, and lack of original samples for clinical validation. A further, well-designed study with a larger number of samples and clinical details is planned for the future.
In summary, to date few studies have explored gene mutations in neuroblastoma using both WXS and WTS. Our study revealed that these two methods present different perspectives and meaningful results. Specifically, we found that allele-specific expression assessed by RNA-seq can be quite different even for the same gene mutations, which underscores the importance of WTS in cancer research. Furthermore, we identified gene mutations through both methods, validating some well-known NB genes like MYCN and ALK, but also discovering novel candidate genes such as ZNF44. Importantly, mutations identified in this study in genes such as ZNF44, which have not previously been reported in neuroblastoma, may provide new opportunities for diagnosis and treatment that are worthy of further investigation.