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. Author manuscript; available in PMC: 2018 Oct 1.
Published in final edited form as: Am J Med Genet A. 2017 Jul 25;173(10):2605–2613. doi: 10.1002/ajmg.a.38350

Whole exome sequencing identified genetic variations in Chinese hemangioblastoma patients

Dexuan Ma 1,#, Jingyun Yang 2,3,4,#, Ying Wang 1, Xiang Huang 1, Guhong Du 1, Liangfu Zhou 1,*
PMCID: PMC5603408  NIHMSID: NIHMS896413  PMID: 28742274

Abstract

Hemangioblastomas (HBs) are uncommon tumors characterized by the presence of inactivating alterations in the von Hippel-Lindau (VHL) gene in inherited cases and by infrequent somatic mutation in sporadic entities. We performed whole exome sequencing on 11 HB patients to further elucidate the genetics of HBs. A total of 270 somatic variations in 219 genes, of which there were 86 mutations in 67 genes, were found in sporadic HBs, and 184 mutations were found in 154 genes in familial HBs. C: G>T: A and T: A>C: G mutations are relatively common in most HB patients. Genes harboring the most significant mutations include PCDH9, KLHL12, DCAF4L1, and VHL in sporadic HBs, and ZNF814, DLG2, RIMS1, PNN, and MUC7 in familial HBs. The frequency of CNV varied considerably within sporadic HBs but was relatively similar within familial HBs. Five genes, including OTOGL, PLCB4, SCEL, THSD4 and WWOX, have CNVs in the six patients with sporadic HBs, and 3 genes, including ABCA6, CWC27 and LAMA2, have CNVs in the five patients with familial HBs. We found new genetic mutations and CNVs that might be involved in HBs; these findings highlight the complexity of the tumorigenesis of HBs and pinpoint potential therapeutic targets for the treatment of HBs.

Keywords: Hemangioblastomas, von Hippel-Lindau gene, whole exome sequencing, copy number variation, single nucleotide variant

Introduction

Hemangioblastomas (HBs) are highly vascularized neoplasms; they account for only 1–2.5% of all tumors in the central nervous system (CNS) [Conway and others 2001; Hussein 2007; Lonser and others 2003]. They often reside in a strikingly limited subset of CNS locations, including the cerebellum, brainstem, retina, and spinal cord. Due to their unique location and the existence of rich vascular networks in these areas, HBs can cause bleeding and rupture, or they can become symptomatic with/without an associated cyst. Therefore, CNS-HBs are a major cause of morbidity and mortality [Shehata and others 2008].

HBs are benign tumors with characteristic and well-described histopathological features, including rapid proliferation of vascular and stromal cells, which are regarded as the underlying neoplastic cells [Hussein 2007]. However, the ontogenesis of HBs remains a mystery for nearly a century since the discovery of HBs. Consequently, the World Health Organization has not classified HBs as neoplasms [Louis and others 2007]. Accordingly, exploration of the oncogenesis of HB will not only shed light on its etiology, pathology, and diagnosis, it will also provide useful insight into treating it.

HBs occur sporadically or in von Hippel-Lindau (VHL) disease. Although there are vast differences between the two subtypes of HBs in terms of genetics, age of onset, clinic recurrence, and other involved organs, they share identical histopathology. Germline mutations or aberrations in the VHL gene have been identified as the root cause of VHL disease. It has been estimated that only approximately 4% of VHL gene carriers are asymptomatic [Beitner and others 2011; Catapano and others 2005], with CNS-HBs occurring in up to 60–80% of VHL patients [Maher and others 1990; Richard and others 2000; Wanebo and others 2003]. It is also thought that there were 4–25% of seemingly sporadic HBs are VHL somatic mutations [Fukino and others 2000; Hes and others 2000; Neumann and others 1989]. These observations indicate that a dysfunctional or absent VHL protein (pVHL) could be involved in the tumorigenesis of HB, but it alone might not be enough to induce the lesions [Ma and others 2011; Nordstrom-O’Brien and others 2010]. Additional genetic variations that may contribute to the tumorigenesis of HB have not yet been identified [Nordstrom-O’Brien and others 2010; Sims 2001].

Furthermore, identified mutations span the entire VHL gene and occur in nearly every codon [Nordstrom-O’Brien and others 2010]. Dysfunctional or absent pVHL has organ-specific expression and age-dependent penetrance. Moreover, different types of VHL mutations could also influence tumorigenesis. For example, VHL deletions and protein truncating mutations appear to confer a higher risk of CNS-HBs than missense mutations [Cybulski and others 2002; Franke and others 2009; Maher and others 1996; Maranchie and others 2004]. Previous studies have indicated the importance of different pathways in the development of HB neoplasms as well as the existence of additional unknown genetic alterations that might drive disease progression [Dulaimi and others 2004]. In this study, we performed a whole exome sequencing to explore the possible genetic variations that may contribute to the tumorigenesis of HBs.

Materials and Methods

Study Participants

Eleven HB samples and the corresponding peripheral blood samples (including six sporadic HBs and five familial HBs, respectively) were selected randomly from the sample bank in the Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University. These patients underwent resection of CNS-HBs between November 2008 and June 2015 at our hospital. All the specimens were ultimately diagnosed by experienced neuropathologists. The five patients with familial HBs were from three families. All of the familial HB patients had a family history of HBs, and VHL mutations were identified in genetic testing. All the sporadic HB patients had no family history of HB, showed no clinical signs of VHL HBs, and did not show any VHL mutation. This research was approved by the institutional review board of Huashan Hospital (KY2009-313). Informed consent was obtained from all patients.

Extraction of DNA

In this study, the sample detection included concentration, sample integrity and purification of the extracted DNA. Concentration was detected using a fluorometer or a Microplate Reader (Qubit Fluorometer, Invitrogen, Carlsbad, CA, USA). Sample integrity and purification were detected by Agarose Gel Electrophoresis (concentration of agarose gel: 1%, voltage: 150 V, electrophoresis time: 40 min). Library construction followed the standard commercial guidelines. Briefly, 1 μg–2μg of genomic DNA was randomly fragmented using Covaris AFA process to an average size of 250–300 bp. Fragments were end repaired, and an extra A base was added to the 3′ end. Illumina adaptors were ligated to the fragments, and proper cycles of polymerase chain reaction (PCR) amplification were applied to each sample after ligation. DNA was quantified using either Agilent 2100 Bioanalyzer or the Qubit fluorometer (Invitrogen, Carlsbad, CA, USA). We used the required amount of pre-capture library for each capture reaction. Agilent SureSelect, NimbleGen SeqCap EZ Hybridization and Wash kits (Roche, Basel, Switzerland) were used for whole-exome capture following the standard manufacturer’s protocol.

Exome Capture and Sequencing and Bioinformatics Analysis

Genomic DNA was extracted from the tumor and blood of each of the 11 patients, and then it was fragmented randomly. After electrophoresis, DNA fragments of the desired length were gel purified. Adapter ligation and DNA cluster preparation were performed and the samples were subjected to Solexa sequencing [Mardis 2008; Wang and others 2008; Wheeler and others 2008]. WES was performed using the Complete Genomics (CG) platform, which utilizes two proprietary technologies, DNA nanoball (DNB) sequencing and combinatorial probe-anchor ligation (cPAL). The results showed a high concordance with the Illumina platform and a high sensitivity [Lam and others 2012; Porreca 2010]. To minimize the likelihood of systematic bias in the sampling, two paired-end libraries with an insertion size of 500 bp were prepared for all the samples and then they subjected to whole exome sequencing. This resulted in at least 30-fold haploid coverage for each sample. Raw image files were processed using the Illumina pipeline for base calling with default parameters, and the whole exome sequences of each individual patient were generated as 90-bp-paired-end reads.

We used the Burrows-Wheeler Aligner program [Li and Durbin 2009] to map the raw sequencing data for each individual to the human reference genome (build hg19). We then used Picard to sort and mark duplicated reads. Gene mutations or alterations in peripheral blood were considered to be nonspecific genetic variations and were excluded from the final analyses. The SNVs were detected by VarScan [Koboldt and others 2009]. P-values were calculated by Fisher’s exact test on the read counts, using reference and variant allele [Koboldt and others 2009]. The CNVs of the normal samples and the tumor samples were detected by in-house pipeline CNV-Detection (BGI-Tech, Shenzhen, Guangdong, China) based on the Broad Institute’s Segseq algorithm [Chiang and others 2009]. Segseq can detect breakpoints at any read position. The segments were iteratively joined by eliminating the breakpoints. Statistical significance was calculated based on the number of reads in the tumor and normal samples in the entire segment. This enables a more accurate estimation of statistical significance because of the increased number of aligned reads [Chiang and others 2009]. We then used ANNOVAR to annotate the variant results [Wang and others 2010], based on which subsequent advanced analysis could be conducted. Quality control (QC) was performed at each stage of the analysis pipeline.

Results

Basic Characteristics of the Study Participants

The basic characteristics of the 11 study participants are presented in Table 1. Six of the participants had sporadic HB, and five had familial HB. Of the participants with familial HB, patient 21 and 23 came from the same family while patient 24 and 25 were from a different family. Four of the patients were female (three had sporadic HB and one had familial HB), and the HBs appeared in different locations.

Table 1.

Basic characteristics of the HB patients.

Patient ID Age Sex Type of HB Features of HB (location and VHL-related presentation) Family history of HB
11 60 F Sporadic Left cerebellum HB No
12 26 F Sporadic Fourth veutficula HB No
13 56 M Sporadic Cerebellum HB No
14 56 M Sporadic Left CPA HB No
15 59 M Sporadic Right cerebellum HB No
16 47 F Sporadic Left cerebellum HB No
21 47 F Familial HB Posterior cranial fossa HBs (bilateral renal cell carcinoma) Yes, mother
22 32 M Familial HB T6–7 HB (5 yrs after cerebellum HB operation, multiple cysts in the left kidney and pancreas) Yes, father and sister
23 25 M Familial HB Multiple HBs in medulla oblongata and cerebellum sample from the cerebellum Yes, mother
24 39 M Familial HB Cerebellum HB Yes, mother and sister
25 25 M Familial HB Multiple cranial HBs in sample from the cerebellum Yes, mother and cousin
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CPA, ; VHL, ; F, female; M, Male; HB, hemangioblastoma

Single Nucleotide Variation

We identified a total of 270 somatic single nucleotide variation (SNV) mutations in the 11 tumors, of which 67 (26.8%) might affect protein coding (61 missense, five nonsense and one splice site; Table 2). These 270 somatic mutations are in 219 genes, with four genes (MAP4K3, NBPF20, PGM5, and ZNF814) having two mutations and 47 mutations located in intergenic regions. We found that, for most of the patients in this study, C: G>T: A transitions were the most common mutation in individual HB samples; however, the T: A>C: G mutation were also very common in many HB patients (Fig. 1A). Some patients, such as patient 12 and patient 21, have more mutations in the coding regions (Fig. 1B). An examination based on HB type indicated that there were 86 mutations in the patients with sporadic HBs (mean 14.3), of which 51 represent novel mutations, and 184 mutations in the patients with familial HBs (mean 36.8), of which 139 represent novel mutations (Table 2). The 86 mutations in the sporadic HBs are in 67 genes with 19 mutations in the intergenic regions (Supplementary Fig. 1). The 184 mutations in the familial HBs are in 154 genes with two genes (MAP4K3 and ZNF814) having two mutations each and 28 mutations in the intergenic regions (Supplementary Fig. 2).

Table 2.

Somatic single nucleotide variants in patients with HBs.

Patients Missense Nonsense Splice site Other Total mutation Novel mutation
11 0 0 0 9 9 1
12 11 2 1 19 33 29
13 4 0 0 10 14 9
14 1 0 0 10 11 10
15 0 0 0 6 6 0
16 0 0 0 13 13 2
Total 16 2 1 67 86 51
21 27 2 0 65 94 81
22 2 0 0 13 15 5
23 8 1 0 23 32 29
24 7 0 0 9 16 12
25 1 0 0 26 27 12
Total 45 3 0 136 184 139
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Patients 11–16 were those with sporadic HBs, and patient 21–25 were those with familial HBs.

HB, hemangioblastomas.

Fig. 1. Distribution of single nucleotide variants in patients with HBs.

Fig. 1

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A: Distribution of all single nucleotide variants.

B: Distribution of single nucleotide variants in coding regions.

Patients 11–16 were those with sporadic HBs, and patient 21–25 were those with familial HBs.

HB, hemangioblastoma; SNV, single nucleotide variant

Genes with the Most Significant Mutations

For sporadic HBs, the most significant mutation (c.2639C>G; p=3.22×10−11) is found in the PCDH9 gene. Other genes harboring strongly significant mutations for familial HBs include KLHL12, DCAF4L1, and VHL (all p<5×10−8). For familial HBs, the most significant mutation (c.1010C>T; p=6.18×10−40) is found in the ZNF814 gene, which also harbors a synonymous mutation (p=1.01×10−22). Other genes harboring strongly significant mutations for familial HBs include DLG2, RIMS1, PNN and MUC7 (all p<5×10−19; for the complete list of significant mutations, please see online Supplementary Table 1 and Supplementary Table 2).

Supplementary Figs. 3 and 4 schematically illustrate two identified somatic mutation networks for sporadic HBs and familial HBs, respectively. In sporadic HBs, we identified several statistically significant networks that are involved in different functions, such as the spliceosomal complex (P=3.77×10−5) and RNA splicing (P=1.66×10−4). In the VHL HBs, we did not identify any network that was found to be statistically significant after correction for multiple comparisons using the false discovery rate.

Copy Number Variations

We detected a large number of copy number variations (CNVs) in all the HB samples across the chromosomes. Specifically, we identified a total of 26,072 CNVs in patients with sporadic HB (Supplementary Fig. 5) and 8,000 CNVs in patients with familial HBs (Supplementary Fig. 6). The frequency of CNVs varied considerably among patients with sporadic HBs: one patient (patient 13) had 13,310 CNVs and one patient (patient 15) had 4,167 CNVs, while patient 16 only had 707 CNVs across the genome. In contrast, the frequency of CNVs was generally lower and relatively similar among patients with familial HB: on average, there were 1,600 CNVs per patient; patient 21 had the smallest number of CNVs (1358) and patient 22 had the largest number of CNVs (1,901).

We identified five genes, OTOGL, PLCB4, SCEL, THSD4, and WWOX, which has CNVs in the six patients with sporadic HB (Table 3). We identified three genes, ABCA6, CWC27, and LAMA2, with CNVs in the five patients with familial HBs (Table 4).

Table 3.

The five genes having CNV in all of the six patients with sporadic HBs.

Gene Chr Start End Copy Ratio Type Patient
OTOGL 12 80707425 80714079 1.70 amplification 11
OTOGL 12 80764407 80765658 1.99 amplification 11
OTOGL 12 80661063 80665359 0.66 deletion 12
OTOGL 12 80730572 80732809 0.53 deletion 12
OTOGL 12 80496991 80605596 1.71 amplification 13
OTOGL 12 80660659 80663966 1.26 amplification 13
OTOGL 12 80750095 80831570 1.26 amplification 14
OTOGL 12 80672958 80703998 0.60 deletion 15
OTOGL 12 80707447 80714034 0.63 deletion 15
OTOGL 12 80714535 80717256 0.45 deletion 15
OTOGL 12 80752478 80761196 0.59 deletion 15
OTOGL 12 80762203 80770863 0.71 deletion 15
OTOGL 12 80722584 80726771 1.31 amplification 16
PLCB4 20 9255315 9317733 1.38 amplification 11
PLCB4 20 9353750 9364815 1.45 amplification 11
PLCB4 20 9215047 9317649 0.69 deletion 12
PLCB4 20 9449377 9453533 0.61 deletion 12
PLCB4 20 8862743 9287807 1.89 amplification 13
PLCB4 20 9287952 9364795 1.28 amplification 13
PLCB4 20 9382481 9388309 1.48 amplification 13
PLCB4 20 9343176 9351983 1.36 amplification 14
PLCB4 20 9346283 9364729 0.74 deletion 15
PLCB4 20 9299560 9318813 1.32 amplification 16
SCEL 13 78137954 78143397 1.35 amplification 11
SCEL 13 78201874 78210222 0.45 deletion 12
SCEL 13 77904169 78124018 2.00 amplification 13
SCEL 13 78133951 78142864 1.28 amplification 13
SCEL 13 78130942 78133692 0.60 deletion 14
SCEL 13 78178371 78217054 1.32 amplification 14
SCEL 13 78176890 78191481 0.73 deletion 15
SCEL 13 78196903 78208368 0.50 deletion 15
SCEL 13 78042366 78125039 1.38 amplification 16
THSD4 15 71548883 71581017 0.69 deletion 11
THSD4 15 71704021 71731836 0.67 deletion 11
THSD4 15 71903510 71939503 0.55 deletion 12
THSD4 15 71411565 71446614 1.68 amplification 13
THSD4 15 71550735 71630571 1.57 amplification 13
THSD4 15 71634234 71700371 1.58 amplification 13
THSD4 15 71704946 71834240 1.90 amplification 13
THSD4 15 71834244 71950228 1.35 amplification 13
THSD4 15 71953052 72020695 1.68 amplification 13
THSD4 15 72037749 72041318 0.68 deletion 14
THSD4 15 71603850 71633595 0.66 deletion 15
THSD4 15 72039196 72050246 0.73 deletion 16
WWOX 16 78285500 78323808 1.40 amplification 11
WWOX 16 78267224 78289780 0.56 deletion 12
WWOX 16 78083567 78142310 1.40 amplification 13
WWOX 16 78151058 78387973 1.54 amplification 13
WWOX 16 78466792 78789897 1.64 amplification 13
WWOX 16 78792488 78859135 1.68 amplification 13
WWOX 16 78867130 79245296 1.65 amplification 13
WWOX 16 79246081 79340769 1.76 amplification 13
WWOX 16 78128470 78136040 0.48 deletion 14
WWOX 16 78466467 78482962 1.27 amplification 15
WWOX 16 78642591 78714289 1.41 amplification 16
WWOX 16 78873601 79034196 1.26 amplification 16
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CNV, copy number variation

Table 4.

The three genes having CNV in all of the five patients with familial HBs.

Gene Chr Start End Copy Ratio Type Sample
ABCA6 17 67091701 67101720 1.32 amplification 21
ABCA6 17 67087558 67101675 1.28 amplification 22
ABCA6 17 67110783 67124511 1.30 amplification 22
ABCA6 17 67060848 67077218 0.72 deletion 23
ABCA6 17 67114246 67120997 1.28 amplification 24
ABCA6 17 67098740 67101581 0.60 deletion 25
CWC27 5 64081466 64084760 1.63 amplification 21
CWC27 5 64079888 64110852 1.38 amplification 22
CWC27 5 64064936 64070739 0.65 deletion 23
CWC27 5 64291614 64313873 0.63 deletion 24
CWC27 5 64096124 64100055 0.71 deletion 25
LAMA2 6 129419549 129467874 1.44 amplification 21
LAMA2 6 129475563 129478619 1.61 amplification 21
LAMA2 6 129591600 129601349 1.53 amplification 22
LAMA2 6 129774271 129777347 1.68 amplification 22
LAMA2 6 129475586 129478619 0.62 deletion 23
LAMA2 6 129794354 129799655 1.47 amplification 24
LAMA2 6 129377950 129389401 0.67 deletion 25
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CNV, copy number variation

Discussion

In this study, we performed whole exome sequencing (WES) on six patients with sporadic HBs and five patients with familial HBs to explore the potential genetic variations that may contribute to the tumorigenesis of HBs. We identified many mutations, the majority of which represent novel mutations, in both sporadic HBs and familial HBs. We found a large number of CNVs in many patients with sporadic HBs, but fewer CNVs in patients with familial HBs. To the best of our knowledge, this is the first WES study to examine potential genetic variations for HBs.

Nowadays, WES has become a very powerful strategy in the discovery of rare causal variants of inherited diseases and in the identification of additional somatic genetic variations that may account for unexplained heritability [Cirulli and Goldstein 2010]. In this study, we screened and identified a number of potential new mutations in patients with HBs. For example, in patients with familial HBs, we found mutations in ZNF814, DLG2, RIMS1, PNN, and MUC7. Further studies are needed to examine whether andhow these additional genetic mutations contribute to HB tumorigenesis and if they are associated with age-dependent penetrance of HBs with synergetic inactivation of VHL. In sporadic HBs, we found the most significant mutations in PCDH9, KLHL12, and DCAF4L1 but not in VHL. The exact roles of these genetic mutations need to be elucidated. Taken together, our findings provide additional insights into the genetic basis of HBs, and they enhance our understanding of the complexity of the clinical phenotypes of HBs.

CNVs are considered to be a significant source of genetic diversity, and they can influence phenotypic variability, such as disease susceptibility[Diskin and others 2009]. Many of the genes harboring the identified genetic variations are also implemented in different tumor-related pathways. For example, we found CNVs in WW domain-containing oxidoreductase (WWOX) in the six patients with sporadic HBs. WWOX is located at 16q23.3–24.1, an area with a high frequency of gene deletions or chromosomal alterations. WWOX is a tumor suppressor gene that regulates multiple cancer-related pathways [Aqeilan and Croce 2007; Salah and others 2010]. It exerts its cancer-suppressing function by suppressing the carcinogenic effects of oncogenes [Gaudio and others 2006], and/or by inducing cell apoptosis via activation of other tumor suppressor genes[Aqeilan and others 2004]. WWOX loses its expression in various tumors [Lewandowska and others 2009]. Previous studies have reported that the CNVs in WWOX are associated with increased risk of lung cancer and gliomas in a Chinese population [Yang and others 2013; Yu and others 2014]. We found that there were five common CNVs in WWOX (http://dgv.tcag.ca/dgv/app/home?ref=GRCh37/hg19), none of which were among the list of CNVs that we identified in patients with sporadic HBs. Therefore, the CNVs we found in this study represent novel CNVs in WWOX that might be involved in the function of WWOX with respect to its role in cancer suppression and HB-tumorigenesis for sporadic HBs. Importantly, because the CNVs we identified in WWOX did not occur in the matched peripheral blood DNA, the occurrence of CNVs in WWOX within sporadic HBs might be due to acquired environment influences. Future studies are needed to explore the potential mechanism of the identified CNVs in influencing the function of WWOX.

A recent study identified a reverse relationship between CNVs and mutations in 12 types of cancer such as glioblastoma multiformae and head and neck squamous cell carcinoma, and it found that tumors can roughly be divided into two classes based on somatic genetic variations: the M class predominantly has mutations while the C class predominantly has CNVs [Ciriello and others 2013]. Overall all, we found a large number of CNVs (mean=4345) but a relatively smaller number of mutations (mean= 14) in patients with sporadic HBs; in contrast, we found significantly fewer CNVs (mean=1,600) but relatively more mutations (mean=37) in familial HBs. However, we did not observe this inverse relationship in some of the individual patients. For example, we identified a large number of CNVs in patient 13 who had sporadic HB (n=13,310), but he had an average number of SNVs (n=14). Another sporadic HB patient (patient 16) had the least number of CNVs (n=707), but an average number of SNVs (n=13). These results highlight the genetic heterogeneity underlying the tumorigenesis of HB.

We identified several mutations/CNVs in genes that are involved in angiogenesis, such as vascular endothelial growth factor A (VEGFA) and VEGFC. VEGFA, located at 6p12, is a member of the cysteine knot family of growth factors, and it is produced by most cells in the body[Ferrara 2004]. It is well known for its essential role in the growth of blood vessels and for its involvement in angiogenesis in brain tumors [Jain and others 2007]. A recent study also reported that VEGFA was over-expressed in HB tissues in comparison to normal surrounding tissues from the same patients [Kruizinga and others 2016]. We also observed many mutations/CNVs in the intergrin (ITG) gene family, such as ITGA8, ITGA1, ITGB5, and ITGB8. ITGB8, located on the cytogenetic band 7p21.1 of the human chromosome 1, can prevent neuronal apoptosis that is induced by deprivation of oxygen-glucose, and inhibition of ITGB8 leads to down regulation of VEGF [Zhang and others 2012]. ITGB8 is also involved in the management of neurovascular physiology. Its removal in perivascular cells leads to the inability to regulate the active phases of blood vessel growth, leading to problems with neurovascular homeostasis [Salajegheh 2016]. Suppression of ITGB8 can promote tumor growth and angiogenesis [Fang and others 2011]. Many of the other genes that we identified in the ITG family also play important functions regarding angiogenesis or the pathogenesis of various types of tumors [Salajegheh 2016]. These findings suggest potential pharmacological targets for the prevention and/or treatment of HBs.

Our study has some limitations. First, the sample size is rather limited. This prevented us from differentiating driver mutations from passenger mutations [Tokheim and others 2016]. More studies with larger sample sizes are needed to validate our findings. Second, the patients in this study were from a single hospital in China, and it is uncertain as to whether our findings can be generalized to patients of different races/ethnicities. Third, although we identified many genetic variations that might contribute to the tumorigenesis of HBs, in this exploratory analysis, we did not examine the underlying mechanisms. Future studies are also needed to investigate how multiple genetic variants interact with each other in the development of HBs. Finally, in this study, we used VarScan to detect the SNVs. Previous research indicated that this caller had a sensitivity >70% in whole-exome sequencing [Kroigard and others 2016], and had medium specificities [Cai and others 2016]. It exhibited advantages in comparison with other callers in the detection of somatic SNVs with high frequencies. However, because we did not perform analytical validation of the identified somatic variants, we cannot rule out the possibility of false positive findings. Various factors, such as sample preparation, exome enrichment laboratory procedure and random/systematic sequencing and alignment errors, can lead to false positive findings. We are conducting an ongoing study which aims at including more patients with HBs to validate the findings from this study.

In summary, we performed WES in six patients with sporadic HBs and five patients with familial HBs. We found many SNVs and CNVs, many of which were reported to play essential roles in angiogenesis or the pathogenesis of cancers. Our findings highlight the complexity of the pathogenesis of HBs, even in patients with familial HBs. Future studies exploring the underlying mechanisms will further illustrate how multiple genetic variations lead to the initiation and progression of HB, and they can help pinpoint therapeutic targets for the treatment of HBs.

Supplementary Material

Supp FigS1-6

Supplementary Fig. 1. Somatic mutations in the 6 patients with sporadic HBs.

The left column represents genes harboring somatic mutations. Each other column represents an individual patient with sporadic HBs.

HB, hemangioblastoma.

Supplementary Fig. 2. Somatic mutations in the 5 patients with familial HBs.

The left column represents genes harboring somatic mutations. Each other column represents an individual patient with familial HBs.

HB, hemangioblastoma.

Supplementary Fig. 3. An identified somatic mutation network for sporadic HBs.

Network was constructed using genes harboring significant somatic mutations in patients with sporadic HBs.

HB, hemangioblastoma.

Supplementary Fig. 4. An identified somatic mutation network for familial HBs.

Network was constructed using genes harboring significant somatic mutations in patients with familial HBs.

HB, hemangioblastoma.

Supplementary Fig. 5. Distribution of copy number variations (CNV) across chromosomes in patients with sporadic HBs.

Each row represents an individual patient, and the columns represent different chromosomes.

HB, hemangioblastoma.

Supplementary Fig. 6. Distribution of copy number variations (CNV) across chromosomes in patients with familial HBs.

Each row represents an individual patient, and the columns represent different chromosomes.

HB, hemangioblastoma.

Supp TableS1
Supp TableS2

Acknowledgments

Funding statement

This work was supported by grants from the Shanghai Committee of Science and Technology (15411951800, 15410723200) and the National Natural Science Foundation of China (81172392).

Dr. Jingyun Yang’s research was supported by NIH/NIA R01AG036042 and the Illinois Department of Public Health.

List of abbreviations

ANNOVAR

Annotate Variation

CNS

central nervous system

CNV

copy number variation

HB

hemangioblastoma

SNV

single nucleotide variant

WES

Whole exome sequencing

Footnotes

Competing interests

The authors have declared that no competing interests exist.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp FigS1-6

Supplementary Fig. 1. Somatic mutations in the 6 patients with sporadic HBs.

The left column represents genes harboring somatic mutations. Each other column represents an individual patient with sporadic HBs.

HB, hemangioblastoma.

Supplementary Fig. 2. Somatic mutations in the 5 patients with familial HBs.

The left column represents genes harboring somatic mutations. Each other column represents an individual patient with familial HBs.

HB, hemangioblastoma.

Supplementary Fig. 3. An identified somatic mutation network for sporadic HBs.

Network was constructed using genes harboring significant somatic mutations in patients with sporadic HBs.

HB, hemangioblastoma.

Supplementary Fig. 4. An identified somatic mutation network for familial HBs.

Network was constructed using genes harboring significant somatic mutations in patients with familial HBs.

HB, hemangioblastoma.

Supplementary Fig. 5. Distribution of copy number variations (CNV) across chromosomes in patients with sporadic HBs.

Each row represents an individual patient, and the columns represent different chromosomes.

HB, hemangioblastoma.

Supplementary Fig. 6. Distribution of copy number variations (CNV) across chromosomes in patients with familial HBs.

Each row represents an individual patient, and the columns represent different chromosomes.

HB, hemangioblastoma.

NIHMS896413-supplement-Supp_FigS1-6.pdf (7.2MB, pdf)
Supp TableS1
NIHMS896413-supplement-Supp_TableS1.docx (19.4KB, docx)
Supp TableS2
NIHMS896413-supplement-Supp_TableS2.docx (25.9KB, docx)

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