Recurrent mutations of chromatin remodeling genes and kinase receptors in pheochromocytomas and paragangliomas

Abstract

Purpose

Pheochromocytomas and paragangliomas (PPGLs) are genetically heterogeneous tumors of neural crest origin, but the molecular basis of most PPGLs is unknown.

Experimental Design

We performed exome or transcriptome sequencing of 43 samples from 41 patients. A validation set of 136 PPGLs was used for amplicon-specific resequencing. In addition, a subset of these tumors was used for microarray-based transcription, protein expression and histone methylation analysis by western blot or immunohistochemistry. In vitro analysis of mutants was performed in cell lines.

Results

We detected mutations in chromatin remodeling genes, including histone-methyltransferases, histone-demethylases and histones in 11 samples from 8 patients (20%). In particular, we characterized a new cancer syndrome involving PPGLs and giant cell tumors of bone (GCT) caused by a postzygotic G34W mutation of the histone 3.3 gene, H3F3A. Furthermore, mutations in kinase genes were detected in samples from 15 patients (37%). Among those, a novel germline kinase domain mutation of MERTK detected in a patient with PPGL and medullary thyroid carcinoma was found to activate signaling downstream of this receptor. Recurrent germline and somatic mutations were also detected in MET, including a familial case and sporadic PPGLs. Importantly, in each of these three genes mutations were also detected in the validation group. Additionally, a somatic oncogenic hotspot FGFR1 mutation was found in a sporadic tumor.

Conclusions

This study implicates chromatin-remodeling and kinase variants as frequent genetic events in PPGLs, many of which have no other known germline driver mutation. MERTK, MET, and H3F3A emerge as novel PPGL susceptibility genes.

Introduction

Pheochromocytomas and paragangliomas (PPGLs) are catecholamine-secreting tumors of neural crest origin that arise from the sympathetic lineage cells of the adrenal medulla and paraganglia, respectively. Over 40% of these tumors are caused by a dominant driver mutation in one of various susceptibility genes involving a broad range of pathways (1). Remarkably, in more than one-third of patients the mutation is found in the germline and is transmitted in an autosomal dominant manner (1, 2).

To explore new genetic events underlying familial and sporadic cases we sequenced the exomes or transcriptomes of 43 PPGL samples from 41 individuals (Suppl. Table1, Fig. 1). Sequences were generated from 26 tumors, 13 germline samples and 4 tumor-germline pairs. Three separate tumors were from the same patient. Germline samples were selected from individuals at high-risk for hereditary PPGL, i.e. family history of PPGLs, disease onset before 30 years of age and/or multiple tumors (Suppl. Table1). Seven patients (17%) had a history of metastatic PPGLs. Here we report novel variants in genes coding for tyrosine kinases and chromatin-remodeling proteins in these samples.

Fig.1.

Overview of the pheochromocytoma and paraganglioma (PPGL) cohort including new genetic variants identified in chromatin-related and kinase genes, and mutations in known PPGL driver genes, along with their respective frequencies. Number of mutations per tumor is shown at the bottom of the diagram. Samples were sorted by inheritability likelihood. Samples with high inheritability carried one or more of the following features: young age at onset, familial history, multicentric tumors and/or co-occurrence of tumors associated with PPGLs), relative to the remaining samples (considered ‘likely sporadic”). Tumor location, malignancy status and type of sequencing (whole exome or transcriptome) are also indicated. Legends to the various mutation categories are shown below the image.

Materials and Methods

Patient Samples

One-hundred seventy-seven PPGLs, obtained after written informed consent or in an anonymized fashion after deidentification, were collected through a tumor repository approved by the University of Texas Health Science Center at San Antonio (UTHSCSA) Institutional Review Board (IRB). A summary of the main clinical features of this cohort are shown in Suppl. Table1. Forty three samples from 41 individuals were used for whole exome (n=40) or transcriptome sequencing (n=3). A separate cohort of 136 pheochromocytoma or paraganglioma tumor only samples was used for verification of some of the detected mutations (Suppl. Table2). Clinical features of one patient with associated PPGL and GCT has been reported elsewhere (3). Additional details of the samples used in the study are available in Suppl. Data.

Whole exome and transcriptome sequencing and variant detection

Whole-exome sequencing was performed in 40 and RNA sequencing was performed in 3 PPGL samples (Suppl. Table1). Of the 43, 26 were tumors, 13 were germline samples from blood, and four were matched tumor-germline pairs. Three of the tumors were from the same patient. The four paired samples and two tumors from the same patient were previously reported (4). For the remaining samples, libraries were prepared using Agilent SureSelect XT2 Target Enrichment System for Illumina Multiplexed Sequencing, version C.2, and exomes enriched using Agilent Sure Select 44Mbp or NimbleGen 44Mb SeqCap EZ Exome Kit v2 (at the Beijing Genomics Institute) or Agilent Sure Select XT2 Human All Exon V5 capture (at University of Texas at Austin Genomic Core facilities) and sequenced on Illumina HiSeq2000. Sequences were aligned and annotated as detailed in Suppl Methods. Distinct filtering thresholds were applied to germline and tumor samples and consensus variants were considered for further analysis. To prioritize significant germline or somatic missense variants we used separate tools of the Cancer-Related Analysis of Variants Toolkit (CRAVAT; Suppl. Methods)(5, 6). The somatic nature of selected variants was verified in the four paired cases and in an additional 11 samples for which matched germline or tumor DNA was available. RNAseq data was processed for sequence variant detection only.

Targeted next-generation sequencing

DNA from fresh-frozen or formalin-fixed paraffin-embedded (FFPE) sections from the various tumor and nontumor tissues from two cases carrying a H3F3A c.103 G>T, p.G34W mutation, as well as three unrelated PPGLs, and four sporadic GCTs were used to quantify variant allele representation. A similar approach was used to detect the MET c.2416G>A; p.V806M variant in samples from three individuals with familial pheochromocytoma without a known driver mutation, including germline DNA from two affected siblings and FFPE from a nonpheochromocytoma tissue section from their affected father, along with unrelated samples. Primers spanning the two variants contained adaptors to allow for detection of the variant allele at ultra-deep sequencing using Illumina TruSeq Custom Amplicon with slight modification, as detailed in Suppl Methods. The sequenced traces were annotated using VarScan2 (7) and the specific variants of interest were detected at an average read depth of 67700x (±47969SD). Samples with variant read counts below the threshold of quality detection (below 1%) were considered negative.

Sanger sequencing

Exons spanning the MERTK kinase domain, MET semaphorin, transcription factor immunoglobin (TIG), juxtamembrane and kinase domains, H3F3A and H3F3B exon 2 were sequenced in the relevant samples from the exome/transcriptome cohort and in the validation cohort of 136 PPGLs by Sanger sequencing (primers and PCR conditions available upon request). Sequencing was processed at Beckman Genomics and analyzed with Mutation Surveyor (Softgenetics, PA), as previously reported (4). The Mutation Quantifier tool of Mutation Surveyor was used to measure frequency of the H3F3A c.103 G>T, p.G34W mutation, expressed as % of the mutant allele in the tumor samples, and calculated as described in Suppl. Methods.

Differential gene expression analysis of PPGLs

Gene expression data generated using the Affymetrix U1332.0 platform were previously reported (GEO accessions GSE2841 and GSE19987)(8). Normalized data from the three tumors with H3F3A G34W mutation and from 36 tumors without this mutation were used for gene set enrichment analysis (GSEA), as detailed in Suppl. Methods. DAVID Bioinformatics Resources 6.7 NIAID/NIH toolset was used for further annotation of the GSEA-differentially expressed genes onto gene ontology terms, protein-protein interactions and protein functional domains(9). Results were expressed as an enrichment score and associated p value.

Structure Modeling

Structural predictions of histone 3.3 variants were performed using the I-TASSER server(10). I-TASSER selected the nucleosome PDB structure 1KX5, determined by X-ray crystallography at 1.9Å resolution, as the highest significance template for predicting the final models. We used the full length amino acid sequence for human histone H3F3A (ENST00000366813) and computationally modeled the wild-type (WT) and the G34W mutant. The C-scores (confidence score, range -5 to 2), TM-scores (template modelling) and RMSD values are shown in Figure S2a for all the structural models provided by I-TASSER. Additional details of model selection, 3D structure visualization and calculations of electrostatic surface potential and hydrophobicity are described in Suppl. Methods.

Cell lines, Cloning and Transfections

HEK293 and Kelly neuroblastoma cell lines were cultured at 37C in 5% CO₂ in Dulbecco's modified Eagle media (DMEM; CellGro) with 10% fetal bovine serum (Thermofisher, Life Technologies). HEK293 cell line was preexistent in our group and was obtained earlier from ATCC. The Kelly cell line was obtained from Dr. Gail Tomlinson (Dept. Pediatrics, UTHSCSA). The Kelly cell line was not formally authenticated but its identity was verified by this cell's characteristic amplification of MYCN at RNA and protein levels by quantitative real time PCR and Western blotting, respectively. Both cell lines were tested and cleared of Mycoplasma contamination before the start of the project. Transfection was performed as described (11). A construct containing wild-type MERTK was obtained from (Addgene, #23900), subcloned into pHM6 and the relevant mutations introduced using site-directed mutagenesis using primers containing the mutation (Sigma) and Phusion Taq polymerase (Thermofisher). Recombinant MERTK ligand Gas6 was purchased from R&D Systems and applied to culture media or HBSS (400nM) for 10 min before harvesting.

Western Blots

Whole cell lysates from tumors (12) or cell lines were prepared as previously described (11) and detailed in Suppl. Methods. Proteins were detected with the following antibodies: H3K27me3, H3K36me3, Histone H3, MYCN, MERTK, phospho ERK (all from Cell Signaling Technology) or β-actin (Sigma-Aldrich, #A2228).

Immunohistochemistry

Immunohistochemical staining was performed using the standard 3-step staining ImmunoCruz TM LSAB Staining System (Santa Cruz Biotech) with histone H3 trimethyl-K36 antibody (Epigentek #A-4042) and H3 tri-methyl K27 (Cell Signaling C36B11) both at 1:200 dilution. In negative controls the primary antibody was replaced by normal rabbit IgG. Slides were counterstained with hematoxylin. Nuclear staining was evaluated based on intensity and percentage of positive cells. Five fields were analyzed from each slide.

Results

The mean depth of coverage of the 40 exomes was 107× and the average read number of the RNAseq samples was 140Mbp. The number of variants per tumor was small across the entire group: the median somatic mutation frequency was 0.8 per Mb in paired exomes (range 0.3-1.3), comparable to the rate recently described in other series (13-16). The overall mutation frequency was 9.7 mutations per Mb (range 1-26) in nonpaired samples, including both somatic and germline variants. Germline and somatic mutations in known PPGL genes were detected in 16 samples (41%, including two somatic NF1 mutations in the same tumor, Suppl. Table2). Some variants had low allelic fraction (Table 1, Suppl. Table 2), suggesting that they may represent subclonal mutant populations within the tumor.

Table 1. Variants in chromatin-related and tyrosine kinase genes list identified by exome or transcriptome sequencing of 43 tumors from 41 individuals.

Group	Sample ID	Gene	Chrom.	Mutation (nucleotide)	Mutation (amino acid)	Variant allele frequency	COSMIC	Mutation Taster	Mutation origin	PPGL driver mutation
CHR	128	ATRX	X	c.6253G>GT	R2085S	7	COSM4767393	1	somatic
CHR	1081	EZH2	7	c.545_547delCAT	D187del	37	N.R.		germline	somatic NF1
CHR	196*	H3F3A	1	c.103G>GT	G35W	20	COSM1732355	1	postzygotic
CHR	197*	H3F3A	1	c.103G>GT	G35W	26	COSM1732356	1	postzygotic
CHR	369*	H3F3A	1	c.103G>GT	G35W	46	COSM1732357	1	postzygotic
CHR	175	HIST1H1T	6	c.426C>CG	K142N	64	N.R.	1	unknown	**likely somatic NF1
CHR	444	HIST4H4	6	c.167C>CT	R56Q	45	N.R.	1	unknown
CHR	444	JMJD1C	10	c.808C>CT	V270I	32	COSM919524	0.998	unknown
CHR	92	KDM2B	12	c.3308G>AG	T1103I	50	N.R.	1	somatic	germline SDHB
CHR	257	KMT2B	19	c.5207G>AG	R1736H	49	N.R.		germline
CHR	203	SETD2	3	c.4219delT	R1407fs	5	COSM3069036		somatic
TK	235	EPHA5	7	c.2669C>T	A890V	54	COSM1056605	1	unknown
TK	472	FGFR1	8	c.1638C>A	N546K	30	COSM302229; COSM19176	1	somatic
TK	1081	FLT1	13	c.3154G>A	D1052N	52	COSM1718896	1	somatic	somatic NF1
TK	9	IGF1	12	c.373C>T	R125C	59	COSM199791	1	germline	somatic EPAS1
TK	84	INSRR	1	c.419G>A	R140H	54	COSM3771479	1	germline
TK	85	JAK1	1	c.2215C>T	D739N	41	N.R.	1	germline
TK	552	JAK3	19	c.2503T>A	S835C	43	COSM4154097	1	germline	germline FH
TK	54	MERTK	2	c.2273G>A	R758H	76	COSM1398803	1	germline
TK	105	MET	7	c.967A>G	S323G	35	N.R.	1	unknown
TK	370	MET	7	c.607T>A	S203T	52	COSM97089	1	unknown	germline RET
TK	493	MET	7	c.2416G>A	V806M	43	N.R.	1	germline
TK	203	MET	7	c.967A>G	S323G	12	N.R.	1	somatic
TK	1081	PDK1	2	c.1028G>A	R343H	79	COSM4456935	1	germline	somatic NF1
TK	1069	PIK3C2G	12	c.1039C>G	H347D	54	COSM3764401	0.964	unknown	**likely somatic SDHA
TK	381	PIK3CB	3	c.1193G>A	A398V	45	N.R.	1	unknown	VHL
TK	257	PIK3CG	7	c.1173A>T	Q391H	56	N.R.	1	germline

^*these three tumors are from the same patient;

^**low allele frequency of known PPGL variants, shown in Table S2, suggests subclonal somatic mutation; COSMIC= catalog of somatic mutations in cancer; Mutation Taster=variant pathogenicity prediction algorithm, highest score= 1; CHR= chromatin-related; TK= tyrosine kinase; N.R.=not reported; PPGL=pheochromocytoma and paraganglioma.

We next explored genes that had not been implicated in PPGL tumorigenesis, specifically searching for variants belonging to the same functional or structural class and found two gene categories that were recurrently mutated in our series (Fig.1, Table 1): 11 high-scoring variants (11/43, 25.6%) were found in chromatin remodeling genes, including histone (H3F3A), histone chaperone ATRX, methyltransferases (KMT2B, EZH2 and SETD2), demethylases (JMJD1C, KDM2B), of 8 patients. The second category encompassed kinase receptor-encoding genes, in which we identified 16 mutations (16/43, 35%) in 15 distinct individuals. These 27 variants were found somatically and in the germline, had few overlaps between the two groups (only 3 tumors had variants in both gene groups), and predominantly targeted PPGLs without a recognizable germline mutation (Fig. 1, Suppl. Fig.1a, 1b, Table 1).

Postzygotic H3F3A mutation in a new paraganglioma syndrome

Within the first group, we detected a mutation of the histone 3.3 encoding gene, H3F3A, which was shared by the exome of three tumors from the same patient, suggesting that the mutation was inherited as a driver event in these tumors (Fig.2a). The patient was a 31-year old female who had bilateral pheochromocytomas and later bladder and periaortic paragangliomas, but without a family history of PPGLs. The H3F3A mutation (c.103 G>T, p.G34W, COSM1732355) was identical to that reported recently as the main oncogenic driver of sporadic giant cell tumor of bone (GCTs) (17, 18). Upon reviewing the patient's records we identified a previous history of recurrent tibial GCT. These bone tumors occur mainly in young adults, preferentially affect epiphyseal sites and have the potential to metastasize(19). The same glycine is also mutated in about 15% of pediatric gliomas, although distinct amino acid changes (either G34R or G34V) are seen in these tumors(20, 21), suggesting a tight association between histological type and the mutated amino acid(18). To expand on this initial finding, we obtained samples from an unrelated 20-year old male patient who was previously reported with an aggressive retroperitoneal paraganglioma with liver metastasis and recurrent, metastatic GCTs(3), and found the same H3F3A mutation (Table 2, Suppl. Fig.2). In both patients, the G34W mutation was detected in all tumors and their metastasis, but was either absent (first case, C1), or detected at a low fraction (7.8%, second case, C2) in adjacent, histologically tumor-free tissue by ultra-deep targeted sequencing (Table 2). This mutation pattern excluded a germline event and suggested instead that the mutation might have occurred postzygotically. This differs from H3F3A mutations in bone and brain cancers, which have been detected exclusively at the somatic level (18, 20, 21). No other mutations of H3F3A, or its homolog H3F3B, were found in an independent set of 136 PPGLs not associated with GCT (Suppl. Table3).

Fig.2.

a) Sanger sequencing traces of two pheochromocytomas and one paraganglioma from the same patient displaying a H3F3A gene mutation (c.103G>T; p. G34W) alongside sequence of DNA isolated from formalin-fixed paraffin embedded (FFPE) tissue sections from normal tissue (gallbladder) and giant cell tumor (GCT) of the tibia, displaying variant (T) allele % representation quantified by Mutation Surveyor (Suppl.Methods). b) Structural impact of histone H3 G34W mutation on lysine 27 and 36 side-chain position. Predicted structures of the WT (blue) and the G34W (magenta) histones H3F3A were aligned and visualized as cartoons. Close up view depicts the side-chains of lysine (K) residues K27, K36 and the point mutation G34W. The angular change of the methylated nitrogen atom of both lysine residues was calculated using Pymol comparing the WT to the G34W mutant. c) Immunohistochemical staining of trimethylated H3 lysine 36 (H3K36me3) in samples from case 1: (pheo=pheochromocytoma, PGL-bladder= retroperitoneal, paraganglioma adjacent to the bladder; PGL-periaortic=periaortic paraganglioma; GCT=giant cell tumor of bone. Scale bars are 50 μm. d) Western blot of pheochromocytomas and paraganglioma lysates using an antibody that recognizes trimethylated forms of lysine 36 (H3K36me3) and 27 (H3K27me3) of histone 3. Total H3 was used as a loading control. Shown are lysates from two different regions of the retroperitoneal paraganglioma and the left pheochromocytoma with the H3F3A G34W mutation (H3F3A); unrelated pheochromocytomas/paragangliomas with wild-type H3F3A sequence and mutations in other susceptibility genes (SDHB VHL, HRAS mutation) or sporadic tumors. e) Western blot of pheochromocytoma lysates containing the indicated mutations, including two independent regions of the paraganglioma and the left pheochromocytoma from the same patient with a G34W-mutation (H3F3A), along with three tumors with intact H3F3A sequence (WT): one with a MAX mutation (arrow), one sporadic and one with a RET mutation, probed with an MYCN antibody. The neuroblastoma cell line Kelly, which has amplification of MYCN, was included as a positive control and loaded as 5% input lysate. Loading was verified with beta-actin.

Table 2. Targeted, amplicon-based next-generation sequencing and variant allele quantification at the H3.3 G34W site in multiple samples from two patients with paraganglioma and giant cell tumor of bone (GCT).

Sample ID	Total Read Counts	Variant Allele Read Counts	% Variant Allele Frequency (VAF)
C1-NL_gb	70190	365	neg.
C1-RPHEO	252093	119371	47.4
C1-LPHEO	67490	29646	43.9
C1-PGL	63990	27863	43.5
C1-GCT	34433	1833	5.3
C2-NL_liv	63419	5162	8.1
C2-PGL	57328	23947	41.8
C2-PGLmetliv	55178	13753	24.9
C2-GCTtib	44968	4314	9.6
C2-GCTfem	62907	16193	25.7
C2-GCTlun	62297	11680	18.8
Sp-GCT1	69707	14839	21.3
Sp-GCT2	64334	18146	28.2
Sp-GCT3	18707	3719	19.9
Sp-GCT4	48655	9525	19.6
WT-PPGL 1	51386	262	neg.
WT-PPGL 2	73058	455	neg.
WT-PPGL 3	59571	383	neg.

C1 and C2= index case and second patient with pheochromocytoma (PHEO) and/or paraganglioma (PGL) and (GCT) syndrome, as described in the text. The target sequence spans the H3F3A exon 2 gene and nucleotide 103. Number of reads containing the variant “T” allele is shown. Three unrelated pheochromocytomas/paragangliomas (PPGLs) with wild-type (WT) H3F3A gene sequence are shown as negative controls (neg), and four unrelated, sporadic GCTs containing the same mutation (G>T), are included as positive controls. Total read count, total variant (T) allele number and frequency of variant allele. NL_gb=normal gallbladder; NL_liv=normal liver; tib=tibia; metliv=metastatic liver; fem=femur; lun=lung(metastatic)

We next performed computational modeling to infer the tridimensional structure of the G34W mutant and found that this variant is predicted to change the electrostatic potential (Suppl. Fig.3a,b) and surface hydrophobicity of H3.3 (Suppl. Fig.3c,d). These alterations are expected to promote a marked shift on the side chains of K27 and K36 (Fig.2b, Suppl. Fig.3e), two key post-translationally regulated residues relevant for modulating DNA accessibility, thus impacting on gene transcription (17). To determine whether the G34W mutation modulated the levels of methylation of these two histone residues, we examined tumor sections from the two H3F3A-mutant patients by immunohistochemistry (IHC). Both tri-methylated K36 (Fig.2c, Suppl.Fig.4a), and K27 (Suppl. Fig.4b) were detectable in the majority of paraganglioma nuclei, and in a significant proportion of GCT cells. These IHC findings were confirmed by western blots of lysates from the pheochromocytomas and paraganglioma from one of the patients (Fig.2d). These observations suggest that the mutation does not cause overt changes in K36 or K27 methylation, although it is not possible to unequivocally determine in these experiments that the mutant allele binds to the methylation-specific antibodies with the same affinity as wild-type H3.3. Nonetheless, these results are similar to the findings in G34-mutant brain tumors (22-24). However, it should be noted that the amino acid changes in gliomas, G34V or G34R, are distinct from the specific variant detected in our samples, G34W, thus structural and functional differences may exist among these variants and lead to unique phenotypes.

We also examined the global gene transcription profile of the three G34-mutant PPGLs from the first patient (8). These mutants clustered with tumors carrying mutations in RET, NF1, or TMEM127 genes, known as cluster 2 PPGLs (8) (Suppl. Fig.5a). Gene set-enrichment analysis (GSEA) and gene ontology assessment revealed significant association with ontologies related to neurogenesis and neural differentiation in the three G34W-mutant PPGLs (Suppl. Fig.5b, Suppl. Fig.5c, Suppl. Table4), which mirrors the profile found in G34-mutant pediatric gliomas(25, 26). We next investigated whether MYCN, which is overexpressed in G34-mutant gliomas(25), could also be deregulated in PPGLs with H3F3A mutation. Using western blot of primary tumors, we demonstrated that the MYCN protein is upregulated in mutant G34W-PPGLs when compared to tumors with intact H3F3A sequence (Fig.2e). Future studies will be required to establish a causative connection between the G34W histone mutation and MYCN upregulation, but our current results suggest that MYCN may be overexpressed in paragangliomas with this mutation, and may contribute to the pathogenesis of PPGLs.

Other chromatin remodeling gene mutations

Besides the H3.3 mutation, variants were also identified in other genes involved in chromatin-mediated gene regulation. Among the methyltransferases, we identified a truncating mutation in SETD2 in an otherwise mutation-free, sporadic PPGL (Table 1, Suppl. Table1). SETD2 is a K36 methyltransferase frequently mutated in renal cancers and leukemias (27, 28) suggesting that this variant is pathogenically relevant. An in-frame, single amino acid germline deletion of the K27 methyltransferase EZH2 was found in another sporadic pheochromocytoma (Table 1, Suppl. Table1). Activating and inactivating EZH2 mutations are involved in, respectively, lymphomas (29) and myeloid malignancies (30). In addition, KMT2B, a member of the K4 methyltransferase 2 (KMT2) family formerly known as MLL, was mutated in germline DNA of a patient with multiple paraganglioma recurrences since age 14 (Table 1). KMT2 mutations occur in various cancers(31) and both germline and somatic variants of the KMT2D isoform were recently described in pheochromocytomas (16) supporting the likely pathogenetic relevance of the KMT2B variant that we identified. Two demethylases, JMJD1C and the KDM2B, members of the Jumonji C (JmjC)-domain containing demethylase family were mutated, respectively, in a benign, sporadic and in a malignant PPGL carrying a mutation in the PPGL susceptibility gene, SDHB (Table 1). Finally, ATRX, a histone 3.3 chaperone, was mutated in one sporadic tumor (Table 1). Somatic ATRX mutations, including the same variant detected in one of our samples, were recently reported in PPGLs (13-15) and found to associate with malignant forms of these tumors (15). Together, these data suggest a broad role of chromatin remodeling genes in PPGLs.

MERTK mutations associated with MEN2-like phenotype

A second group of recurrently mutated genes comprised tyrosine kinase receptors (Table 1), a class of proteins often disrupted in cancers (32). We evaluated three of these variant kinase-encoding genes in detail. A germline mutation was detected in a residue within the tyrosine kinase domain of the MERTK gene (c.2273G>A, p.R758H, COSM1398803, Fig.3a) in a 32-year old patient diagnosed with pheochromocytoma, recurrent and metastatic paragangliomas and medullary thyroid carcinoma (MTC). The association of pheochromocytoma and MTC is reminiscent of multiple endocrine neoplasia type 2 (MEN 2), but no mutations were detected in the MEN2 susceptibility gene, RET, in this patient. MERTK is one of the three components of the TAM kinase receptor family (TYRO3, AXL, MERTK), which is overexpressed in cancers (33). We sequenced the MERTK kinase domain in a separate cohort of 136 PPGLs and identified a germline mutation targeting the same residue, R758C, in a 36-year old female with a sporadic pheochromocytoma (Fig.3a). Ectopic expression of both 758R- and 758C-mutant MERTK in HEK293 cells led to sustained phosphorylation of downstream signaling effector ERK after stimulation with the MERTK ligand GAS6, compared to cells expressing an empty vector (EV), WT construct or a dominant negative MERTK mutant Y754F (Fig.3b). Importantly, ERK phosphorylation was maintained in these mutants after nutrient starvation (Fig.3c), suggesting that kinase domain changes may lead to constitutive activation of the receptor. Further, somatic MERTK mutations were identified in two pheochromocytomas of the TCGA dataset [preliminary release at (34) (35, 36)]. These results are consistent with MERTK mutations playing a role in PPGL pathogenesis.

Fig.3.

a) Schematic of MERTK protein structure and functional domains (I-set=immunoglobulin set domain, Ig-2=immunoglobulin-like, FN3-fibronectin typeIII, TM=transmembrane; TK=tyrosine kinase; TAM=tyro3, axl, mertk domain). The two R758 mutations are indicated by the ‘lollipop—shaped marks. The magnified region displays the TAM KWIAIES kinase domain, which is conserved within TAM kinases but is highly homologous with other tyrosine kinase receptors and is here aligned to the corresponding region within the RET receptor. The R758 residue of MERTK and corresponding RET R921 are highlighted in red and orange, respectively. The RET M918 residue mutated in cancers is colored in blue. b) HEK293 cells expressing an empty vector (EV) or MERTK wild-type (WT) or mutants R758H, R758C, Y754F. The R758H/C variants were found in patients with pheochromocytoma, and Y754F is a dominant negative MERTK form used as a control. Cells were starved of nutrients for 3h and then exposed to MERKT ligand Gas6 for 10min. The Western blot shows expression of multiple MERTK isoforms [long (l.e.) and short (s.e.) exposures] and phosphorylation of the downstream kinase ERK (p-ERK);. c) HEK293 cells expressing the same constructs shown in b after nutrient starvation (3h); lysates were prepared and probed with MERTK and p-ERK. Beta-actin was used for loading in both b and c blots. d) Pedigree drawing of three generations of a family with pheochromocytoma (males indicated by squares and females, by circles). Affected individuals are represented by filled symbols. Genotype for the V806M MET mutation is indicated as mutant (MUT) or wild-type (WT). e) MET mutations identified in this study displayed along the protein structure. Length of vertical lines reflects the number of events. The V806M variant was found in a patient with familial pheochromocytoma and segregates with the phenotype in the family. The remaining variants were detected in tumor DNA. Plot was designed using the Mutation Mapper tool of the cBioPortal of Cancer Genomics(35, 36).

MET mutation in familial and sporadic PPGL

We also identified a novel germline mutation of the MET kinase receptor in the exome of the index case of a three-generation family with pheochromocytomas but without a known driver mutation. MET is somatically mutated in multiple cancers and germline activating mutations cause familial papillary renal carcinoma(37). The germline c.2416G>A; p.V806M mutation found in this patient resides within the transcription factor immunoglobin (TIG) juxtamembrane domain, and segregates with the disease in this family: it is present in the affected sibling and father, but absent in the unaffected mother, when tested by Sanger and targeted next-generation sequencing (Fig.3d, Suppl. Fig.5a,b). There is no report of renal cancer in this family but one of the affected individuals had bladder cancer diagnosed after 70 years of age. Additional MET variants were identified within the semaphorin domain, a hotspot region for cancer mutations(38), in the exome of three sporadic PPGLs (Table 1). We next sequenced 118 unrelated PPGLs for exons spanning these domains and identified 11 other variants present in COSMIC, TCGA, and/or predicted to be pathogenic, or present in reference databases with a minor allele frequency <0.05 (Fig.3e, TableS5). Three of the variants occurred in more than one tumor, while a variant of controversial pathogenicity was seen in five tumors(39). Overall, we identified 15 different samples carrying MET variants, both somatic and germline (Fig.3e), suggesting that this gene may be more commonly mutated in PPGLs. In support of our findings, somatic MET mutations were recently reported in an independent series of PPGLs(14).

Hotspot FGFR1 mutated in PPGL

A somatic mutation in the main hotspot residue of the FGFR1 receptor (c.1638C>A; p.N546K COSM19176/302229), known to constitutively activate the receptor in glioblastomas (40) and other cancers(41), was detected in one patient with a sporadic pheochromocytoma without an identifiable PPGL susceptibility gene mutation (Table 1). No additional N546K mutations were found in our validation group of 136 samples, but this variant was detected in a sample of the PPGL TCGA dataset (35, 36), suggesting that FGFR1 mutation is a rare but recurrent event in PPGLs.

Mutations in PPGLs have been considered mutually exclusive (1). Only three samples in our series carried mutations in both chromatin-related and kinase genes (3/23 separate tumors from 20 individuals, Fig. 1, Table 1). We also verified whether novel mutations (of either class) coexisted with those of well-known PPGL genes. These variants tended to occur predominantly in tumors with no mutation of an established PPGL gene (13/23, log odds ratio -1.28; p=0.06, Table1), suggesting that they might play a dominant role in tumor development.

Discussion

Our study uncovered new candidate germline, postzygotic and somatic driver mutations in PPGLs. Overall, mutations in genes related to chromatin remodeling or kinase receptors were found in 20 of the 41 patients, and when cases with known PPGL gene mutations are combined, driver mutations could be assigned to 68% of the samples in this series.

Our data point to mutations in chromatin remodeling genes as a recurrent feature of PPGLs, implying that epigenetic modifications occur in these tumors. Indeed, epigenetic changes associated with enhanced DNA and histone methylation have been linked to loss-of-function mutants of the well-known PPGL susceptibility genes SDH and FH, engendered as a result of metabolic imbalances that decrease the activity of histone demethylases (42). Our data now suggest that the chromatin architecture of a sizeable proportion of PPGLs is disrupted by different mechanisms, involving direct mutations of chromatin regulators. At least in the case of histone 3.3 mutations, such misregulation occurs in a specific clinical and developmental context. Furthermore, the postzygotic H3.3 mutation pattern found in our cases, not previously reported in other H3.3-mutated tumors, may now instigate studies to revisit the cell of origin of sympathetic lineage and bone tumors, not hitherto thought to share common precursors(43), and may also have implications for measuring transmission risk of the mutation in affected patients. More broadly, identification of specific consequences of each individual and combinatorial variant on chromatin deposition throughout the PPGL genome may provide key insights into gene regulation and tumorigenesis.

Our findings also expand the role of kinase receptors in PPGLs. The RET kinase receptor, the oncogene mutated in MEN2 syndrome and the related syndrome familial MTC, is one of the earliest recognized PPGL susceptibility genes (44). The mutated MERTK R758, found in two patients of our study, is homologous to RET R912, previously detected in FMTC (45). R758 is adjacent to a conserved KWIAIES sequence within the kinase domain, known as the TAM domain(46), which is highly homologous to RET and encompasses a hotspot residue for mutation of this gene in human cancers (M918T, COSM965). Moreover, the phenotype of one of the affected patients in our cohort raises the intriguing possibility that MERTK may be related to rare RET-negative cases with MEN2-like clinical manifestations.

The relevance of mutations of the MET receptor found in our study is corroborated by recent findings of somatic mutations of this gene in PPGLs (14). We expand on these observations by also identifying MET as a susceptibility gene to familial pheochromocytoma. Somatic MET mutations occur in multiple cancer types, but germline MET mutations have only been previously reported in papillary renal cancers (37). Although the patients with MET mutations in our series had no history of renal tumors, there is increasing recognition of an overlap between genes that cause susceptibility to pheochromocytoma and renal cancers (47, 48). Taken together, these findings suggest that MET may also be involved in PPGL predisposition.

The identification of variants in either chromatin or kinase genes in patients without a known germline PPGL mutation, detection of additional mutations of these new candidate genes in our validation cohort and also in other, independent series (13-16) offer support for their role in PPGL pathogenesis. Definitive validation of these new candidates as susceptibility genes and their potential value for genetic risk assessment, prognosis, and surveillance awaits further analyses. Importantly, although these variants were not specifically enhanced in malignant tumors, the availability of clinical grade tyrosine kinase inhibitors, including those targeting MET and FGFR1, and agents directed at chromatin modifications may expand the number of experimental therapeutic options to malignant or inoperable PPGLs (32, 49).

Notably, the low mutation frequency and limited overlap between individual genes found in our and other PPGL series (13-16)suggests that the spectrum of genetic driver events in these rare tumors is not saturated, and that multiple cohorts will be required to complete the catalog of genetic variations implicated in PPGLs. The relevance of pursuing the full genetic repertoire of these tumors is even more compelling given their high rates of heritability, at present conservatively estimated at 40%, and the heightened transmission risk of affected alleles.

Statement of translational relevance.

Pheochromocytomas and paragangliomas are genetically heterogeneous neuroendocrine tumors caused by inherited mutations in 40% of the cases. Using exome or transcriptome sequencing we identified novel recurrent germline, mosaic or somatic mutations in genes encoding chromatin regulators, including histone and histone modifiers, as well as kinase receptors, among which were MERTK, MET and FGFR1. Some of these mutations, in histone 3.3, MERTK and MET, were associated with co-occurring tumors or familial disease, suggesting that they belong to previously unappreciated susceptibility syndromes. These new variants increase the proportion of pheochromocytomas and paragangliomas with a known genetic basis and broaden the spectrum of genes targeted in these tumors. Furthermore, our findings provide new markers for genetic risk assessment. Future studies should define the utility of these data in the development of targeted therapeutic strategies for malignant or inoperable paragangliomas.