Infiltrating gliomas with FGFR alterations: Histologic features,genetic alterations,and potential clinical implications

Abstract

BACKGROUND:

Fibroblast growth factor receptors (FGFRs) are frequently altered in cancers and present a potential therapeutic avenue. However, the type and prevalence of FGFR alterations in infiltrating gliomas (IGs) needs further investigation.

OBJECTIVE:

To understand the prevalence/type of FGFR alterations in IGs.

METHODS:

We reviewed clinicopathologic and genomic alterations of FGFR-mutant gliomas in a cohort of 387 patients. Tumors were examined by DNA next-generation sequencing for somatic mutations with a panel interrogating 205-genes. For comparison, cBioPortal databases were queried to identify FGFR-altered IGs.

RESULTS:

Fourteen patients (3.6%) with FGFR-mutant tumors were identified including 11 glioblastomas, Isocitrate dehydrogenase (IDH) – wildtype (GBM-IDH-WT), 2 oligodendrogliomas, and 1 astrocytoma IDH-mutant. FGFR-altered IGs showed endocrinoid capillaries, microvascular proliferation, necrosis, oligodendroglioma-like cells, fibrin thrombi, microcalcifications, and nodular growth. FGFR3 was the most commonly altered FGFR gene (64.3%). The most common additional mutations in FGFR-altered IGs were TERTp, CDKN2A/B, PTEN, CDK4, MDM2, and TP53. FGFR3 alterations were only observed in GBM-IDH-WT. EGFR alterations were rarely identified in FGFR3-altered gliomas.

CONCLUSIONS:

Histologic features correlate with FGFR alterations in IGs. FGFR3-TACC3 fusion and FGFR3 amplification are the most common FGFR alterations in IGs. FGFR alterations are a rare, but potentially viable, therapeutic target in asubset of IGs.

Keywords

Infiltrating glioma FGFR1 FGFR2 FGFR3 glioblastoma oligodendroglioma FGFR3-TACC3 targeted therapy

1. Introduction

Approximately 100,000 individuals are diagnosed with infiltrating gliomas (IGs) annually [1] and, while this number only amounts to $<$ 1% of all newly diagnosed cancers, IGs remain a significant contributor to overall mortality and morbidity [2]. Historically, these tumors have been classified solely based on their histologic characteristics [3]. However, studies over the past decade reveal valuable insight into the distinct molecular profiles of these tumors [4, 5, 6, 7, 8, 9, 10, 11]. These findings ultimately led to a reclassification of IG integrating histology and genetic alterations. IGs are classified by the presence or absence of mutations in IDH1, IDH2 and H3-3A. Furthermore, IDH-mutant IGs are classified as oligodendrogliomas if there is 1p/19q codeletion, or astrocytomas in the presence of ATRX loss and/or TP53 mutations [12]. Recently, the WHO has recognized that other genetic alterations beyond IDH1/IDH2 influence the survival of patients with IDH-mutant gliomas (i.e., CDKN2A/B.) Moreover, diffuse low-grade glioma, Mitogen-activated protein kinase (MAPK) – altered (which includes gliomas with FGFR alterations) is a new diagnostic category in the 5 ${}^{\text{th}}$ edition of the WHO classification for CNS tumors published in 2021 [13]. Therefore, understanding the range of FGFR alterations in gliomas is critical for diagnosis. Beyond the impact of genetic alterations in tumor classification, expanding our understanding of molecular characteristics of IGs has impact in the utilization of new targeted therapies.

The fibroblast growth factor family of receptors (FGFRs) are frequently altered in different human cancers (bladder, esophageal carcinomas, lung adenocarcinoma, among others) [14] and have been garnering attention with regards to their role in IGs. Four FGFR genes have been identified: FGFR1-4, which encode for transmembrane receptor tyrosine kinases (TK) that are involved in a myriad of critical cellular processes including cell proliferation, angiogenesis, cell survival, migration, and differentiation [14]. In glioblastoma (GBM), multiple genetic alterations in FGFR genes have been identified, including fusions between FGFR1, -2, and -3 with TACC1 and TACC3[15]. The potential therapeutic value of FGFR inhibitors is supported by an ongoing phase 1 clinical trial evaluating the pan-FGFR inhibitor Erdafitinib (JNJ-42756493) for the treatment of solid tumors (Clinical Trial NCT02365596). Evidence of clinical benefit in patients with recurrent GBMs harboring the FGFR3-TACC3 fusion has been reported [16, 17, 18]. Moreover, several clinical trials evaluating FGFR inhibitors as therapy for gliomas are in progress or have been recently completed (clinicaltirals.gov; NCT02824133, NCT01975701, NCT04004975, NCT02840409). Taken together, these data emphasize the value of further characterization of FGFR alterations in IGs. In this study, we describe the clinical, histological, and genetic characteristics of adult IGs harboring FGFR alterations.

2. Material and methods

2.1 Patients and tumor samples

We performed a retrospective review of an institutional database of 387 patients diagnosed with IGs between 2010 to 2019. Patients were included in the study if they had 1) histologic diagnosis of IG; 2) analysis by next-generation sequencing; 3) alteration in an FGFR gene. This study was approved by the institutional review board of the University of Texas Health Science Center at Houston (UTHealth), protocol HSC-MS-17-0917. Clinical data were collected from the electronic medical record and compiled using a REDCap database [19]. These included age, gender, histologic diagnosis, imaging studies, recurrence, and survival. Histologic diagnosis was performed following the 2016 WHO Classification of CNS Tumors by a board-certified neuropathologist. A group of 210 patients diagnosed with GBM with wildtype (WT) IDH1, IDH2, and FGFR1-4 genes from our database were used for comparison of clinical, demographic, and genomic characteristics. Patients diagnosed with diffuse astrocytic gliomas, IDH-WT, with molecular features of GBM, WHO grade IV were considered as GBM-IDH-WT for further analysis (Supplementary Fig. 1) [20].

2.2 Histologic features

All slides prepared as part of routine initial diagnostic workup [Hematoxylin & Eosin-stain, GFAP (Agilent-GA524-Polyclonal), IDH1-R132H (Dianova-DIA H09-H09), and p53 (Agilent-M7001-DO7)] were reviewed by microscopic examination by a board-certified neuropathologist (LYB).

2.3 Targeted sequencing

Tumor samples were analyzed for genetic alterations by a targeted next-generation sequencing assay (NGS) DNA-based assay interrogating 205 genes for somatic mutations and 26 genes for rearrangements, as well as genomic signatures including microsatellite instability and tumor mutational burden (FoundationOne, Foundation Medicine Inc., Cambridge, MA, USA). The details of the FoundationOne assay have been described elsewhere [21, 22, 23].

2.4 cBioPortal cohort

We searched for FGFR-altered IG analyzed for single-nucleotide variant (SNV) and copy-number alterations (CNA) in cBioPortal (https://www.cbioportal. org/) (data accessed in February 2021) [24, 25]. We included cases from the following cBioPortal datasets: Brain Tumor PDXs (Mayo Clinic, 2019), Brain Lower Grade Glioma (TCGA, PanCancer Atlas), Glioblastoma Multiforme (TCGA, PanCancer Atlas), Memorial-Sloan Kettering Cancer Center (MSKCC, 2019), LGG University of California San Francisco (UCSF 2014), and GBM Columbia (Columbia, 2019) [26, 27, 28, 29]. Cases with SNV curated as a variant of unknown significance by the OncoKB Precision Oncology Knowledge Base were excluded from this study [30].

2.5 Statistical analyses

The clinical and demographic characteristics and genomic alterations between FGFR-altered and FGFR-WT IGs were evaluated by Fisher’s exact test or Mann-Whitney $U$ test for categorical or continuous variables, respectively. Overall survival (OS) was calculated from the date of diagnosis to the date of death or the last available follow-up. The Kaplan-Meier method was used to plot the estimated OS with 95% confidence intervals, which was examined by the univariable Log-rank test. All $p$ -value were two-sided and considered statistically significant if $p<$ 0.05. The false discovery rate controlled by the Benjamini-Hochberg procedure was performed to account for multiple comparisons. Statistical analyses were performed in EZR (1.40) [31] and GraphPad Prism (version 9.0.1), La Jolla, California, USA. The cBioPortal Oncoprint tool was utilized to analyze the cBioPortal datasets and generate the oncoplots [24, 25].

3. Results

3.1 Clinical and demographic characteristics

There were 387 patients with IGs in the institutional database with a median age of 57 years (range 13–87 years). There were 231 males (59.7%) and 156 (40.3%) females. Ethnicities included 275 Caucasians (71.1%), 52 Hispanics (13.4%), 37 African Americans (9.6%), 17 Asians (4.4%), and 6 of other ethnic backgrounds (1.5%). The most common histologic diagnoses were GBM-IDH-WT (276, 71.3%), followed by GBM-IDH-mutant (IDH-Mut) (26, 6.7%), oligodendroglioma IDH-mutant and 1p/19q co-deleted (OD) (23, 6.0%), anaplastic astrocytoma (AA) IDH-Mut (16, 4.1%), diffuse astrocytoma (DA) IDH-Mut (16, 4.1%), anaplastic oligodendroglioma IDH-mutant and 1p/19q co-deleted (AO) (15, 3.9%), AA IDH-WT (9, 2.4%), DA IDH-WT (6, 1.5%).

Alterations in FGFR genes (FGFR1, FGFR2, FGFR3, and FGFR4) were identified in 14/387 (3.6%) patients: 11/276 (4%) GBM-IDH-WT, 1/23 (4.3%) OD, 1/16 (6.3%) DA IDH-Mut, and 1/15 (6.7%) AO. The clinical characteristics of these 14 patients are depicted in Table 1. Eight patients were females, and the median age of FGFR-mutant patients was 56 years (range 15–75 years). Within the group of FGFR-mutant gliomas, patients with GBM-IDH-WT had a median age of 58.5 years (range 32–70 years). There were no statistically significant differences in clinical characteristics between patients with GBM-IDH-WT, FGFR-altered ( $n=$ 11) and GBM-IDH-WT, FGFR-WT ( $n=$ 210) tumors (Table 2).

3.2 Histologic features of FGFR-altered gliomas

Microvascular proliferation was observed in 10/11 (91%) and pseudopalisading necrosis in 8/11 (72.7%) GBM-IDH-WT tumors, respectively. These histologic findings are well-known features associated with high-grade gliomas. Interestingly, other histologic features were observed in the FGFR-altered tumors independent of their WHO grade.

Oligodendroglia-like features (honeycomb-like arrangement of evenly spaced tumor cells with uniformly rounded nuclei and clear haloes imparting a “fried egg” appearance) were observed in 71% of cases; interestingly, this finding was observed in 67% of non-oligodendroglial tumors. 50% of all FGFR-altered patients exhibited evidence of vascular fibrin thrombi, all of which were GBM-IDH-WT. Additionally, an endocrinoid capillary network was identified in 57.1% of the 14 patients. Extensive microcalcifications were present in 35.7% of patients (all of them GBM-IDH-WT). Finally, a nodular growth pattern was identified in 14.3% of FGFR-altered patients (both were GBM-IDH-WT). Representative cases of these histopathologic features are seen in Fig. 1. The histopathologic features of FGFR-altered IG are summarized in Fig. 2.

Table 1
Demographic, clinical characteristics, and mutations in FGFR-altered gliomas

Pt’s ID	Sex	Age	Race	Dx	WHO grade	FGFR mutation	Site of tumor	Treatment	PFS ${}^{{\ddagger}}$	OS ${}^{{\ddagger}}$	Mutations	VUS
1	F	61	W	GBM	IV	FGFR3-TACC3 fusion	Frontal	TMZ and XRT Rec: TMZ, BCZ, CPT-11 TTF, and GK	3.1	14.7	CDKN2A/B, MTAP, PIK3CA, PIK3R1, TERTp	DIS3, FLT1, TEK, TYRO3
2	F	66	W	GBM	IV	FGFR3-TACC3 fusion	Parietal	TMZ and XRT	3.4	7.6	CDK4, MTOR, PTEN, MDM2, FRS2, TERTp	ERRFI1
3	M	70	H	GBM	IV	FGFR3-TACC3 fusion	Parietal, occipital,	TMZ and XRT Rec: BCZ	3.0	10.2	CBL, TERTp	BRAF, FGFR4, PREX2, RET, KDM5A, MYST3, PIK3CB
4	F	75	W	AA	III	FGFR3-TACC3 fusion	Temporal, basal ganglia	TMZ and XRT	4.1 ${}^{*}$	4.2	TERTp	CHD4, ERBB3, GRIN2A, LZTR1, SMARCA4, TSHR
5	M	32	W	GBM	IV	FGFR3-TACC3 fusion and FGFR3 Amp.	Parietal	TMZ and XRT Rec: BCZ	8.2	50.0	PTEN	ABL1, TSC1, ATM, CHEK1, FANCD2
6	M	53	W	GBM	IV	FGFR3 Amp.	Frontal	TMZ and XRT Rec: 2 ${}^{\text{nd}}$ Sx, TMZ, BCZ, CPT-11, and XRT	10.9	24.7	MDM2, CDKN2A, RB1	DNMT3A, GNAQ, EPHA3, NCOR1, FANCC, PRDM1
7	F	57	W	AA	III	FGFR3 Amp.	Frontal, insular, multifocal.	TMZ and XRT Rec:BCZ,	5.5	45.0 ${}^{{\dagger}}$	CDK4, PTEN, QKI, TERTp, TP53	ABL2, MAP3K1, MLL2, NTRK1
8	M	49	W	GBM	IV	FGFR3 p.K650E	Temporal, occipital, Intraventricular	TMZ and XRT Rec: BCZ, TPI-287 ${}^{\P}$ , XRT, and GK	6.7	23.8	CDK4, PIK3CA, PTEN, MDM2, FRS2, GLI1, TERT	ARID2, NOTCH2, GLI1, SPEN, HSP90AA, TSC1, IKBKE, ZNF217, MLL, MLL2
9	F	56	H	GBM	IV	FGFR2 p.K659E	Temporal	None	3.4	6.1	CDKN2A/B, TERTp	IRS2, KEL, MYST3, SNCAIP, NOTCH2, RAD50
10	F	68	W	GBM	IV	FGFR1 p.T141R	Frontal	TMZ, TTF, and XRT	9.6	10.5 ${}^{{\dagger}}$	EGFR, MDM4, CDKN2A/B, LRP1B, PIK3C2B, SPTA1, TERTp	ARID2, GNAS, MED12, MLL2
11	F	15	W	OD	II	FGFR1 p.K656E	Temporal	Observation	38.7 ${}^{*}$	38.7 ${}^{{\dagger}}$	ALK, IDH1, TP53	FBXW7, GATA2, PDCD1LG2
12	F	56	H	AO	III	FGFR1 p.N546K	Frontal	XRT	33.9 ${}^{*}$	33.9 ${}^{{\dagger}}$	IDH2,CIC, TERTp	ALK, MLL3, APC, PLCG2, BRCA2, POLE, FAT1, SMO, JAK1, SOCS1, TSC1
13	M	61	W	GBM	IV	FGFR4 p.R80W	Frontal	TMZ and XRT Rec: 2 ${}^{\text{nd}}$ Sx, TMZ, and GK	10.2	20.7	EGFR, CDKN2A/B, IKZF1, MSH6, NOTCH1, TERT	AXIN1, FLT1, PARK2 P437L
14	M	34	W	DA	II	FGFR4 H359fs*5	Temporal	XRT	74.1 ${}^{*}$	74.1 ${}^{{\dagger}}$	IDH1, TP53, ATRX	C11orf30, FANCE, KEAP1, PDGFRB

Abbreviation: WHO: World Health Organization; PFS: progression-free survival; OS: overall survival; VUS: variants of unknown significance; GBM: glioblastoma; AA: Anaplastic Astrocytoma; DA: Diffuse Astrocytoma; OD: Oligodendroglioma IDH mutant 1p/19q Co-deleted; AO: Anaplastic Oligodendroglioma IDH mutant 1p/19q Co-deleted; Amp: amplification; TMZ: Temozolomide; XRT: Radiotherapy; Rec: At Recurrence; BCZ: Bevacizumab; CPT-11: Irinotecan; GK: Gamma Knife. ${}^{*}$ The patient didn’t have a recurrence. ${}^{\ddagger}$ PFS and OS are represented in months ${}^{\dagger}$ Patient is alive at the moment of the report and the date of follow up was used to calculate OS and/or PFS. ${}^{\P}$ TP-287 treatment as part of a clinical trial.

Figure 1.

Microscopic characteristics of FGFR-altered gliomas are diverse. (A) Tumor cells with perinuclear clearing (indicated by arrows) are present in this oligodendroglioma, IDH-mutant, 1p/19q-codeleted with an FGFR1 mutation (case #11). (B–D) Tumor cells with perinuclear clearing, nodular growth pattern, and vacuolated appearance of the neuropil (indicated by arrows) are evident in this case with FGFR2 mutation (case #9). (E) Tumor cells with perinuclear clearing (horizontal arrow) and microcalcifications (vertical arrows), (F) nuclear palisading, and nodular growth (indicated by arrows) (G) are present in this case with the FGFR3-TACC3 fusion. (H) This other case with an FGFR3-TACC3 fusion shows characteristic features of glioblastoma including vascular proliferation (arrow) and pseudopalisading necrosis (star) (case #2). (I) FGFR4 altered case (#13) with palisading necrosis (stars). (J) Case #14 showed characteristic features of diffuse astrocytoma, IDH-mutant, including an increased number of mildly atypical glial cells. Bar $=$ 50 um for A–C, E, F, H and J, 100 um for D and I, 500 um for G.

Figure 2.

Histological and molecular features of diffuse gliomas with FGFR alterations in the study cohort. All TERT mutations were promoter mutations; PTEN, IDH1/IDH2, TP53, PIK3CA, CIC, and ATRX alterations were point mutations; CDKN2A/B were loss of the gene; and CDK4, MDM2, and EGFR were amplifications of the gene. ${}^{*}$ Anaplastic Astrocytoma IDH-Wildtype with molecular features of glioblastoma.

Table 2

Demographic, clinical, and genomic characteristics of GBM IDH-WT by FGFR alterations

Characteristic	All GBM IDH-WT $N=$ 221	GBM IDH/FGFR WT $N=$ 210	GBM IDH WT, FGFR Mut $N=$ 11	Unadjusted $p$ -value
Age at diagnosis, median [IQR]	61 [53–69]	61 [53–69]	61 [54.5–67]	0.770
Male, %	59.7	60.5	45.5	0.357
Non-Hispanic White, %	68.8	68.1	81.8	0.509
Karnofsky Performance Status (KPS), median [IQR]	70 [60–80]	70 [60–80]	80 [70–80]	0.019
Location (Lobe)
Frontal	38.9	38.6	45.5	0.754
Parietal	31.2	31.4	27.3	1.00
Temporal	42.5	43.3	27.3	0.361
Occipital	10.9	10.5	18.2	0.340
Multifocal	15.4	15.7	9.1	1.00
Stupp Protocol, %	92.3	91.9	90.1	1.00
Gross Total Resection in 1 ${}^{\text{st}}$ Surgery, %	33.0	33.3	18.2	0.510
Salvage Therapy ${}^{*}$ , %
Re-Operation	36.1	37.3	18.2	0.330
Temozolomide	41.0	47.8	30	0.527
Bevacizumab	59.7	59.0	60	1.00
Radiotherapy	21.5	21.6	20	1.00
Genetic Alterations
CDKN2A/B	70.1	70.9	45.5	0.093
EGFR	42.9	44.3	18.2	0.121
PIK3C	12.2	11.4	18.2	0.623
PTEN	49.3	50.0	36.4	0.539
TERTp ${}^{**}$	79.6	79.5	100	0.211
TP53	31.2	30.9	9.1	0.180
MDM2	6.8	5.7	27.3	0.030

GBM: glioblastoma; WT: wildtype; Mut: mutant. ${}^{*}$ A total of 144 GBM IDH-WT have record of Recurrence (10 FGFR Mutant and 134 FGFR WT patients).

3.3 Genetic alterations

NGS analysis identified 134 alterations involving 93 genes, approximately half (70/134; 52.2%) were reported as variance of unknown significance. There were 64 alterations in 30 genes that were classified as mutations (SNV, fusions, and CNA). The median number of genetic alterations per patient was 3 (range 1–7). The genetic alterations observed in FGFR-altered cases are described in Table 1. FGFR1-4 alterations were mutually exclusive between FGFR genes but can occur within the same gene (e.g., FGFR3-TACC3 fusion and FGFR3 amplification), as previously described [32]. As demonstrated in Fig. 2, 5/14 (35.7%) tumors had the FGFR3-TACC3 fusion, while 3/14 (21.4%) showed FGFR3 amplification, and one patient had a tumor with an FGFR3 p.K650E SNV. One patient showed both FGFR3-TACC3 fusion and FGFR3 amplification. The remaining FGFR alterations were SNVs, each was observed in a single patient and included FGFR1 (p.T141R, p.N546K, p. K656E), FGFR2 (p.K659), and FGFR4 (p.R80W, H359fs*5).

In addition to FGFR alterations, FGFR-altered gliomas frequently showed alterations in telomerase reverse transcriptase promoter (TERTp) 10/11, 90.1%. CDKN2A/B was altered in 5/14 (35.7%), PTEN in 4/14 (28.6%) $,$ and CDK4, MDM2, TP53, and IDH1/IDH2 in 3/14 (21.4%) of patients. Interestingly, PTEN, CDK4, and MDM2 alterations were present only in FGFR3-altered gliomas. EGFR alterations were identified in 2/14 (14.3%) cases with FGFR1 and FGFR4 SNVs. PIK3CA was mutated in 2 FGFR3-altered patients.

The Fischer-exact test was used to compare the most common genetic alterations between GBM-IDH-WT, FGFR-altered ( $n=$ 11) and GBM-IDH-WT, FGFR-WT ( $n=$ 210). There was an increased frequency of MDM2 amplification in the FGFR-altered group in the unadjusted analysis (27.3% vs 5.7%, $p=$ 0.03). After adjustment for multiple comparisons, no significant differences were identified between GBM-IDH-WT, FGFR-altered and GBM-IDH-WT, FGFR-WT. However, there was a lower percentage of CDKN2A/B loss (45.5% vs 70.9%), EGFR alterations (18.2% vs 44.3%), PTEN mutations (36.4% vs 50%), and TP53 mutations (9.1% vs 30.9%) in the FGFR-altered group (Table 2 and Supplementary Table 1).

3.4 FGFR-altered infiltrating gliomas in cBioPortal

In cBioPortal, 104/1884 (5.5%) IG with FGFR alterations were identified. Fifty-eight of these 104 patients were included in the study (3.1% of the cohort), as some patients were incompletely characterized, had an unclear histologic diagnosis, or had FGFR variants of unknown significance. Most FGFR alterations 44/58 (76%) involved the FGFR3 gene. The FGFR3 alterations included 24 cases with amplification (10 co-occurred with an FGFR3 fusion), 19 FGFR3-TACC3 fusion, 4 p.K650E SNV, 1 p.R248H SNV, and 6 other FGFR3 fusions that occurred in one case each (FGFR3-ELAVL3, FGFR3-FBXO28, FGFR3-AMBRA1, FGFR3-ST7L, FGFR-PTBP1, FGFR-NBR1). Most cases were IDH-WT infiltrating gliomas (43/44, 97.7%), except for one AA-IDH-mutant that showed FGFR3 amplification. The 5 cases with FGFR1 alterations showed amplification of the gene. Of the 5 patients with FGFR1-amplified tumors, 3 were GBM-IDH-WT, while 2 were DA-IDH-mutant. Five patients harbored alterations in the FGFR2 gene, including 2 amplifications, 1 FGFR2-SPRNP1 fusion, 1 p.R203H SNV, and 1 p.E731K SNV. FGFR2 altered patients included 2 GBM-IDH-WT, and 3 astrocytomas-IDH-mutant (grade 2–4). Finally, FGFR4 alterations in this cohort included 3 amplifications and 1 p.Y367C SNV. Two GBM-IDH-WT, 1 DA IDH-mutant, and 1 OD harbored FGFR4 alterations. Additionally, the evaluation of other genetic alterations of FGFR-altered IG revealed that FGFR3 alterations were mutually exclusive with ATRX ( $q<$ 0.001), IDH1 ( $q=$ 0.004), and TP53 ( $q=$ 0.037) mutations (Supplementary Fig. 2). CDKN2A/B loss (16/38, 42%), EGFR amplification (3/38, 7.9%), and PTEN alterations (15/38, 39.5%) were less frequent in GBM-IDH-WT, FGFR-altered compared to the reported percentage of alterations in these genes in GBM-IDH-WT tumors [24, 25].

3.5 Prognosis and survival

There was no significant difference in the overall survival of patients with GBM-IDH-WT, FGFR-altered ( $n=$ 11) and those with GBM-IDH-WT, FGFR-WT ( $n=$ 210) (20.7 months vs 17.6 months, $p=$ 0.90) (Fig. 3).

4. Discussion

The improvement of molecular diagnostic assays has contributed to elucidating a diversity of genomic alterations in IGs. This has improved the classification of gliomas and has also uncovered several potential therapeutic targets including FGFR genes [33]. In this study, we identified 14 IGs with FGFR alterations (out of 387 cases) and reviewed their histologic features and additional genetic alterations.

We identified 3 cases with FGFR1 alterations, p.T141R, p.K656E, and p.N546K. FGFR1 p.T141R was previously described in lung squamous cell carcinoma (lung SCC) [33]. FGFR1 p.K656E and p.N546K are known to occur in GBM [33], however, both SNVs were identified in oligodendrogliomas (with IDH-mutation and 1p/19q codeletion) in our cohort. The same two SNVs have also been identified in pilocytic astrocytomas and rosette-forming glioneuronal tumors [34]. Both FGFR1 p.K656E and p.N546K affect the $\alpha$ isoform, which is the most prevalent isoform in low-grade gliomas [35, 36]. No FGFR1 tyrosine kinase SNVs were observed in the cBioPortal dataset. In the cBioPortal dataset FGFR1 amplification was identified in a subset of astrocytomas-IDH-mutant and GBM-IDH-WT, but not in OD.

Figure 3.

Overall Survival of GBM-IDH-WT with and without FGFR alterations. No difference in OS between GBM-IDH-WT, FGFR-Altered ( $n=$ 11) and GBM-IDH-WT, FGFR-WT ( $n=$ 210) was observed (20.7-months vs 17.6-months, $p=$ 0.90).

FGFR2 is critical for astrocytes and its overexpression has been previously reported to be associated with lower tumor grade and better survival in gliomas [37]. However, we identified the FGFR2 p.K659E missense SNV, affecting the intracellular tyrosine kinase domain, in one patient with GBM-IDH-WT. This SNV has been described in multiple neoplasms including GBM, pilocytic astrocytoma, lung SCC, endometrial carcinoma, medulloblastoma, and spermatocytic seminoma [33]. The cBioPortal dataset showed 2 cases with FGFR2 amplification, one case with FGFR2-SPRNP1 fusion, and two cases with FGFR2 SNV (p.R203H and p.E731K). The p.R203H SNV has been previously described in colon and endometrium carcinomas, meanwhile, the p.E731K SNV involves the tyrosine kinase domain. Various FGFR2 fusions have been associated with OD in the pediatric population [38]. However, in cBioPortal, FGFR2-mutant tumors were astrocytoma-IDH-mutant or GBM-IDH-WT. In addition, FGFR2 and FGFR3 alterations have recently been described in the Polymorphous low-grade neuroepithelial tumor of the young (PLNTY) [39]. PLNTY is characterized by mutually exclusive genetic alterations involving either BRAF or FGFR2/FGFR3 genes; both pathways are involved in MAPK signaling activation [39].

Table 3

Summary findings if FGFR-altered infiltrating gliomas

Histology
• Frequent morphologic features that should prompt FGFR alteration evaluations are: oligodendroglia-like appearance (in non-oligodendroglioma tumors), endocrinoid network, extensive micro-calcifications, nodular growth pattern, and vascular fibrin thrombi.
Genetics
• FGFR1-4 alterations occur in $\sim$ 3% of infiltrating gliomas. • FGFR3 alterations are mutually exclusive with IDH mutant tumors, except for rare cases of FGFR3 amplifications in IDH mutant infiltrating gliomas. • FGFR3-TACC3 fusion and FGFR3 amplification are the most common FGFR alterations in adult IDH-WT infiltrating gliomas. • FGFR3 altered tumors infrequently harbor EGFR alterations. • FGFR3 p.K650E SNV, which affects the kinase domain, is the most common FGFR hotspot in IDH-WT astrocytoma.
Prognosis
• In this study, no significant overall survival differences were observed among FGFR-altered and non-altered glioblastoma IDH-WT. • Anecdotally, FGFR3 amplified cases had longer overall survival. • Prior studies have shown that FGFR3-TACC3 fused glioblastomas have improved survival. • Future investigations should evaluate if pan-FGFR inhibitors improve the survival of FGFR-altered patients.

Five patients had a fusion between FGFR3 and the transforming acidic coiled-coil containing 3 (FGFR3-TACC3 fusion). This fusion has been recently discovered in GBM, bladder cancer, lung cancer, head, and neck SCC, and gallbladder cancer [40]. In addition to the FGFR3-TACC3 fusion, we identified two patients with FGFR3 amplification, which has been identified as the most common FGFR3 alteration in human cancers ( $\sim$ 30% of FGFR3 alterations) [41]. FGFR3 amplification has been described in ovarian carcinoma, urothelial carcinoma, gallbladder carcinoma, and carcinoma of unknown origin [41]. Also, the FGFR3 p.K650E SNV, which affects the kinase domain, has been previously associated with neonatal lethal syndrome TDII, multiple myeloma, and bladder cancer [33]. FGFR3 SNVs were found to be associated with a good prognosis in patients with bladder cancer, however, not much is known about the prognostic impact of these SNVs in IGs. All 5 FGFR3-TACC3 positive cases in the cohort were GBM-IDH-WT. In the cBioPortal dataset, the most common FGFR3 alteration was amplification. FGFR3 amplification often co-occurred with FGFR-TACC3 and other FGFR3 fusions. Five FGFR3-mutant cases showed SNV, 4 of which corresponded with the p.K650E SNV, highlighting this as a hotspot for FGFR3 alterations in astrocytomas-IDH-WT. While the p.K650E SNV was the most common FGFR3 SNV identified in our study, of the 3 FGFR3 hotspots according to Catalogue of Somatic Mutations in Cancer (COSMIC), lysine 650 is the least commonly mutated codon [42]. In our study, the FGFR3-TACC3 fusion was not detected in low-grade infiltrating astrocytomas or oligodendrogliomas. Interestingly, we found that the only IDH-mutant IGs harboring an FGFR3 alteration was an amplification, which is congruent with prior studies, in which only 3 IDH-mutant tumors had FGFR3 alteration, all of which were amplifications of the gene [43]. Moreover, our study suggests that FGFR3 alterations are more frequent in IDH-WT tumors and EGFR alterations are uncommon in FGFR-altered gliomas, findings that have been identified by previous large FGFR-TAC3 fusion studies [44, 45].

We identified 2 cases with FGFR4 alterations (p.R80W and p.H359fs*5). FGFR4 p.R80W has been rarely detected in cancer [32] and the functional consequences of this mutation remain unknown. The p.H359fs*5 mutation is a truncating mutation that has not been reported in COSMIC or TCGA, we predict that it leads to FGFR4 inactivation. Therefore, we interpret these FGFR4 mutations as likely incidental findings (or passenger mutations). The cBioPortal dataset showed 3 cases of FGFR4 amplification and one case with a p.Y367C SNV, which has been suggested to drive tumor growth in a breast cancer cell line [46]. However, FGFR4 alterations are rare events in IG and their significance needs to be further studied.

Previous studies have focused on gliomas with FGFR3-TACC3 fusion [47]. Bielle et al. reported recurrent histologic features including monomorphous ovoid nuclei, nuclear palisading, thin parallel cytoplasmic processes, an endocrinoid network of thin capillaries associated with frequent microcalcifications and desmoplasia in patients harboring the FGFR3-TACC3 fusion [47]. Our findings confirm histologic features that are associated with FGFR-TACC3 fusion including microcalcifications, oligodendroglia-like cells, endocrinoid capillary network, and a nodular growth pattern of tumor cells. We recognize that these features are not specific to FGFR-altered gliomas, however, the presence of some of these features in an IGs could alert the pathologist to the possibility of an FGFR alteration.

The overall survival of the patients harboring the FGFR3-TACC3 fusion ranged from 4.2 to 14.7 months. Interestingly, 1 of the 5 FGFR3-TACC3 positive cases also had coexisting FGFR3 amplification. The overall survival for this case was 50 months, longer than the other FGFR3-TACC3 positive cases. Moreover, 2 additional cases with FGFR3 amplification (#6 and #7) showed OS longer than the average for GBM, IDH-WT, namely 24.7 and 45 months, respectively. These findings raise the question of whether GBM, IDH-WT with FGFR3 amplifications have a better OS. Even though small case series have anecdotally associated FGFR alterations with an aggressive phenotype [48], recent large studies evaluating FGFR3-TACC3 fusions in GBM have identified that patients harboring this fusion had improved survival compared to FGFR3-TACC3 WT patients [44, 45]. The survival benefit on FGFR3-TACC3 fused patients might not be exclusive from this fusion but rather a common feature among patients with FGFR3 alterations that increase the tyrosine domain activity (amplification and SNV). Further studies with a larger number of FGFR3 alterations other than FGFR3-TACC3 fusion are needed to elucidate this question.

This manuscript has the inherent limitations of retrospective cohorts, as well as a cohort with a relatively small sample size. However, the rare frequency of FGFR alterations ( $\sim$ 3% of IGs) and the scope of the manuscript – exploring FGFR alterations beyond FGFR3-TACC3 fusions, in which most published data focus, made this manuscript valuable for the neuro-oncology community. Future studies should evaluate survival differences of FGFR-altered compared to FGFR-WT IGs, as well as the potential therapeutic value of pan-FGFR inhibitors in FGFR-altered IGs, as prior reports have shown clinical benefit in FGFR3-TACC3 fused recurrent GBMs [16, 17, 18]. The performance of these future studies will require multi-institutional collaborations given the low percentage of IGs that harbored FGFR alterations, but it might provide a better understanding and therapeutic avenue for this subtype of IDH-WT GBM.

5. Conclusions

In summary (Table 3), there are characteristic histologic features that can alert the pathologist about the possibility of FGFR alterations in IGs. Alterations in FGFR1-4 are a rare event in adult IGs and frequently co-occur with TERTp mutations in GBM-IDH-WT. FGFR3-TACC3 fusion and FGFR3 amplification are the most common FGFR alterations in adult IDH-WT-IGs. In addition, FGFR3 p.K650E is the most common FGFR3 SNV in IDH-WT astrocytomas. EGFR amplification is infrequent in FGFR3-altered GBM-IDH-WT. No significant difference in OS was observed between FGFR-altered and FGFR-WT GBM-IDH-WT. It is important to identify FGFR alterations in IGs, given the potential implications for diagnosis and targeted therapies.

Funding

Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number K08CA241651 (LYB). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author contributions

Antonio Dono M.D.: Interpretation and analysis of data, preparation of the manuscript.

Hanadi El Achi M.D.: Preparation of the manuscript.

Bethany E. Bundrant B.A.: Interpretation and analysis of data, preparation of the manuscript.

Puneetha S. Goli: Interpretation and analysis of data, preparation of the manuscript.

Ping Zhu M.D., MMed., Ph.D.: Interpretation and analysis of data.

Hanim Istem Ozkizilkaya M.D.: Preparation of the manuscript.

Yoshua Esquenazi M.D.: Conception, interpretation and analysis of data and preparation of the manuscript.

Leomar Y. Ballester M.D., Ph.D.: Conception, interpretation and analysis of data and preparation of the manuscript.

Supplementary data

The supplementary files are available to download from https://dx-doi-org.web.bisu.edu.cn/10.3233/CBM-220041.

Footnotes

Acknowledgments

We would like to thank Kimberly Fontenot for her assistance with this project.

Conflict of interest

The authors declared no conflict of interest.

References

Bray

Ferlay

Soerjomataram

Siegel

R.L.

Torre

L.A.

and Jemal

, Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries, Ca Cancer J Clin 68 (2018), 394–424.

Ferlay

Colombet

Soerjomataram

Mathers

Parkin

D.M.

Piñeros

Znaor

and Bray

, Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods, Int J Cancer 144 (2019), 1941–1953.

Louis

D.N.

Ohgaki

Wiestler

O.D.

Cavenee

W.K.

Burger

P.C.

Jouvet

Scheithauer

B.W.

and Kleihues

, The 2007 WHO Classification of Tumours of the Central Nervous System, Acta Neuropathol 114 (2007), 97–109.

McLendon

Friedman

Bigner

Meir

E.G.V.

Brat

D.J.

Mastrogianakis

G.M.

Olson

J.J.

Mikkelsen

Lehman

Aldape

Yung

W.K.A.

Bogler

VandenBerg

Berger

Prados

Muzny

Morgan

Scherer

Sabo

Nazareth

Lewis

Hall

Zhu

Ren

Alvi

Yao

Hawes

Jhangiani

Fowler

Lucas

A.S.

Kovar

Cree

Dinh

Santibanez

Joshi

Gonzalez-Garay

M.L.

Miller

C.A.

Milosavljevic

Donehower

Wheeler

D.A.

Gibbs

R.A.

Cibulskis

Sougnez

Fennell

Mahan

Wilkinson

Ziaugra

Onofrio

Bloom

Nicol

Ardlie

Baldwin

Gabriel

Lander

E.S.

Ding

Fulton

R.S.

McLellan

M.D.

Wallis

Larson

D.E.

Shi

Abbott

Fulton

Chen

Koboldt

D.C.

Wendl

M.C.

Meyer

Tang

Lin

Osborne

J.R.

Dunford-Shore

B.H.

Miner

T.L.

Delehaunty

Markovic

Swift

Courtney

Pohl

Abbott

Hawkins

Leong

Haipek

Schmidt

Wiechert

Vickery

Scott

Dooling

D.J.

Chinwalla

Weinstock

G.M.

Mardis

E.R.

Wilson

R.K.

Getz

Winckler

Verhaak

R.G.W.

Lawrence

M.S.

O’Kelly

Robinson

Alexe

Beroukhim

Carter

Chiang

Gould

Gupta

Korn

Mermel

Mesirov

Monti

Nguyen

Parkin

Reich

Stransky

Weir

B.A.

Garraway

Golub

Meyerson

Chin

Protopopov

Zhang

Perna

Aronson

Sathiamoorthy

Ren

Yao

Wiedemeyer

W.R.

Kim

Kong

S.W.

Xiao

Kohane

I.S.

Seidman

Park

P.J.

Kucherlapati

Laird

P.W.

Cope

Herman

J.G.

Weisenberger

D.J.

Pan

Berg

D.V.D.

Neste

L.V.

J.M.

Schuebel

K.E.

Baylin

S.B.

Absher

D.M.

J.Z.

Southwick

Brady

Aggarwal

Chung

Sherlock

Brooks

J.D.

Myers

R.M.

Spellman

P.T.

Purdom

Jakkula

L.R.

Lapuk

A.V.

Marr

Dorton

Choi

Y.G.

Han

Ray

Wang

Durinck

Robinson

Wang

N.J.

Vranizan

Peng

Name

E.V.

Fontenay

G.V.

Ngai

Conboy

J.G.

Parvin

Feiler

H.S.

Speed

T.P.

Gray

J.W.

Brennan

Socci

N.D.

Olshen

Taylor

B.S.

Lash

Schultz

Reva

Antipin

Stukalov

Gross

Cerami

Wang

W.Q.

Qin

L.-X.

Seshan

V.E.

Villafania

Cavatore

Borsu

Viale

Gerald

Sander

Ladanyi

Perou

C.M.

Hayes

D.N.

Topal

M.D.

Hoadley

K.A.

Balu

Shi

Penny

Bittner

Shelton

Lenkiewicz

Morris

Beasley

Sanders

Kahn

Sfeir

Chen

Nassau

Feng

Hickey

Zhang

Weinstein

J.N.

Barker

Gerhard

D.S.

Vockley

Compton

Vaught

Fielding

Ferguson

M.L.

Schaefer

Madhavan

Buetow

K.H.

Collins

Good

Guyer

Ozenberger

Peterson

and Thomson

, Comprehensive genomiccharacterization defines human glioblastoma genes and core pathways, Nature 455 (2008), 1061–1068.

Killela

P.J.

Reitman

Z.J.

Jiao

Bettegowda

Agrawal

Diaz

L.A.

Friedman

A.H.

Friedman

Gallia

G.L.

Giovanella

B.C.

Grollman

A.P.

T.-C.

Hruban

R.H.

Jallo

G.I.

Mandahl

Meeker

A.K.

Mertens

Netto

G.J.

Rasheed

B.A.

Riggins

G.J.

Rosenquist

T.A.

Schiffman

Shih

I.-M.

Theodorescu

Torbenson

M.S.

Velculescu

V.E.

Wang

T.-L.

Wentzensen

Wood

L.D.

Zhang

McLendon

R.E.

Bigner

D.D.

Kinzler

K.W.

Vogelstein

Papadopoulos

and Yan

, TERT promotermutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal, Proc National Acad Sci 110 (2013), 6021–6026.

Yan

Parsons

D.W.

Jin

McLendon

Rasheed

B.A.

Yuan

Kos

Batinic-Haberle

Jones

Riggins

G.J.

Friedman

Reardon

Herndon

Kinzler

K.W.

Velculescu

V.E.

Vogelstein

and Bigner

D.D.

, IDH1 and IDH2 Mutations in Gliomas, New Engl J Med 360 (2009), 765–773.

Sturm

Witt

Hovestadt

Khuong-Quang

D.-A.

Jones

D.T.W.

Konermann

Pfaff

Tönjes

Sill

Bender

Kool

Zapatka

Becker

Zucknick

Hielscher

Liu

X.-Y.

Fontebasso

A.M.

Ryzhova

Albrecht

Jacob

Wolter

Ebinger

Schuhmann

M.U.

van Meter

Frühwald

M.C.

Hauch

Pekrun

Radlwimmer

Niehues

von Komorowski

Dürken

Kulozik

A.E.

Madden

Donson

Foreman

N.K.

Drissi

Fouladi

Scheurlen

von Deimling

Monoranu

Roggendorf

Herold-Mende

Unterberg

Kramm

C.M.

Felsberg

Hartmann

Wiestler

Wick

Milde

Witt

Lindroth

A.M.

Schwartzentruber

Faury

Fleming

Zakrzewska

Liberski

P.P.

Zakrzewski

Hauser

Garami

Klekner

Bognar

Morrissy

Cavalli

Taylor

M.D.

van Sluis

Koster

Versteeg

Volckmann

Mikkelsen

Aldape

Reifenberger

Collins

V.P.

Majewski

Korshunov

Lichter

Plass

Jabado

and Pfister

S.M.

, Hotspot Mutations in H3F3A and IDH1 Define Distinct Epigenetic and Biological Subgroups of Glioblastoma, Cancer Cell 22 (2012), 425–437.

The Somatic Genomic Landscape of Glioblastoma, Cell 155 (2013), 462–477.

Noushmehr

Weisenberger

D.J.

Diefes

Phillips

H.S.

Pujara

Berman

B.P.

Pan

Pelloski

C.E.

Sulman

E.P.

Bhat

K.P.

Verhaak

R.G.W.

Hoadley

K.A.

Hayes

D.N.

Perou

C.M.

Schmidt

H.K.

Ding

Wilson

R.K.

Berg

D.V.D.

Shen

Bengtsson

Neuvial

Cope

L.M.

Buckley

Herman

J.G.

Baylin

S.B.

Laird

P.W.

Aldape

and the Cancer Genome Atlas Research Network, Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma, Cancer Cell 17 (2010), 510–522.

10.

Cancer Genome Atlas Research Network Brat

D.J.

Verhaak

R.G.W.

Aldape

K.D.

Yung

W.K.A.

Salama

S.R.

Cooper

L.A.D.

Rheinbay

Miller

C.R.

Vitucci

Morozova

Robertson

A.G.

Noushmehr

Laird

P.W.

Cherniack

A.D.

Akbani

Huse

J.T.

Ciriello

Poisson

L.M.

Barnholtz-Sloan

J.S.

Berger

M.S.

Brennan

Colen

R.R.

Colman

Flanders

A.E.

Giannini

Grifford

Iavarone

Jain

Joseph

Kim

Kasaian

Mikkelsen

Murray

B.A.

O’Neill

B.P.

Pachter

Parsons

D.W.

Sougnez

Sulman

E.P.

Vandenberg

S.R.

Meir

E.G.V.

von Deimling

Zhang

Crain

Lau

Mallery

Morris

Paulauskis

Penny

Shelton

Sherman

Yena

Black

Bowen

Dicostanzo

Gastier-Foster

Leraas

K.M.

Lichtenberg

T.M.

Pierson

C.R.

Ramirez

N.C.

Taylor

Weaver

Wise

Zmuda

Davidsen

Demchok

J.A.

Eley

Ferguson

M.L.

Hutter

C.M.

Shaw

K.R.M.

Ozenberger

B.A.

Sheth

Sofia

H.J.

Tarnuzzer

Wang

Yang

Zenklusen

J.C.

Ayala

Baboud

Chudamani

Jensen

M.A.

Liu

Pihl

Raman

Wan

Ally

Auman

J.T.

Balasundaram

Balu

Baylin

S.B.

Beroukhim

Bootwalla

M.S.

Bowlby

Bristow

C.A.

Brooks

Butterfield

Carlsen

Carter

Chin

Chu

Chuah

Cibulskis

Clarke

Coetzee

S.G.

Dhalla

Fennell

Fisher

Gabriel

Getz

Gibbs

Guin

Hadjipanayis

Hayes

D.N.

Hinoue

Hoadley

Holt

R.A.

Hoyle

A.P.

Jefferys

S.R.

Jones

C.D.

Kucherlapati

Lai

P.H.

Lander

Lee

Lichtenstein

Maglinte

D.T.

Mahadeshwar

H.S.

Marra

M.A.

Mayo

Meng

Meyerson

M.L.

Mieczkowski

P.A.

Moore

R.A.

Mose

L.E.

Mungall

A.J.

Pantazi

Parfenov

Park

P.J.

Parker

J.S.

Perou

C.M.

Protopopov

Ren

Roach

Sabedot

T.S.

Schein

Schumacher

S.E.

Seidman

J.G.

Seth

Shen

Simons

J.V.

Sipahimalani

Soloway

M.G.

Song

Sun

Tabak

Tam

Tan

Tang

Thiessen

Triche

Berg

D.J.V.D.

Veluvolu

Waring

Weisenberger

D.J.

Wilkerson

M.D.

Wong

A.W.

Yang

Zack

T.I.

Zhang

Aksoy

B.A.

Arachchi

Benz

Bernard

Carlin

Cho

DiCara

Frazer

Fuller

G.N.

Gao

Gehlenborg

Haussler

Heiman

D.I.

Iype

Jacobsen

Katzman

Kim

Knijnenburg

Kreisberg

R.B.

Lawrence

M.S.

Lee

Leinonen

Lin

Ling

Liu

Mills

Noble

M.S.

Paull

Rao

Reynolds

Saksena

Sanborn

Sander

Schultz

Senbabaoglu

Shen

Shmulevich

Sinha

Stuart

Sumer

S.O.

Sun

Tasman

Taylor

B.S.

Voet

Weinhold

Weinstein

J.N.

Yang

Yoshihara

Zheng

Zhang

Zou

Abel

Sadeghi

Cohen

M.L.

Eschbacher

Hattab

E.M.

Raghunathan

Schniederjan

M.J.

Aziz

Barnett

Barrett

Bigner

D.D.

Boice

Brewer

Calatozzolo

Campos

Carlotti

C.G.

Chan

T.A.

Cuppini

Curley

Cuzzubbo

Devine

DiMeco

Duell

Elder

J.B.

Fehrenbach

Finocchiaro

Friedman

Fulop

Gardner

Hermes

Herold-Mende

Jungk

Kendler

Lehman

N.L.

Lipp

Liu

Mandt

McGraw

McLendon

McPherson

Neder

Nguyen

Noss

Nunziata

Ostrom

Q.T.

Palmer

Perin

Pollo

Potapov

Potapova

Rathmell

W.K.

Rotin

Scarpace

Schilero

Senecal

Shimmel

Shurkhay

Sifri

Singh

Sloan

A.E.

Smolenski

Staugaitis

S.M.

Steele

Thorne

Tirapelli

D.P.C.

Unterberg

Vallurupalli

Wang

Warnick

Williams

Wolinsky

Bell

Rosenberg

Stewart

Huang

Grimsby

J.L.

Radenbaugh

A.J.

and Zhang

, Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas, New Engl J Medicine 372 (2015), 2481–2498.

11.

Eckel-Passow

J.E.

Lachance

D.H.

Molinaro

A.M.

Walsh

K.M.

Decker

P.A.

Sicotte

Pekmezci

Rice

Kosel

M.L.

Smirnov

I.V.

Sarkar

Caron

A.A.

Kollmeyer

T.M.

Praska

C.E.

Chada

A.R.

Halder

Hansen

H.M.

McCoy

L.S.

Bracci

P.M.

Marshall

Zheng

Reis

G.F.

Pico

A.R.

O’Neill

B.P.

Buckner

J.C.

Giannini

Huse

J.T.

Perry

TIHAN

Berger

M.S.

Chang

S.M.

Prados

M.D.

Wiemels

Wiencke

J.K.

Wrensch

M.R.

and Jenkins

R.B.

, Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors, New Engl J Medicine 372 (2015), 2499–2508.

12.

The 2016 World Health Organization Classification of Tumors of theCentral Nervous System: a summary, Acta Neuropathol 131 (2016), 803–820.

13.

Louis

D.N.

Perry

Wesseling

Brat

D.J.

Cree

I.A.

Figarella-Branger

Hawkins

H.K.

Pfister

S.M.

Reifenberger

Soffietti

von Deimling

and Ellison

D.W.

, The 2021 WHO Classification of Tumors of the Central Nervous System: a summary, Neuro-Oncology 23 (2021), 1231–1251.

14.

Touat

Ileana

Postel-Vinay

André

and Soria

J.-C.

, Targeting FGFR Signaling in Cancer, Clin Cancer Res 21 (2015), 2684–2694.

15.

Singh

Chan

J.M.

Zoppoli

Niola

Sullivan

Castano

Liu

E.M.

Reichel

Porrati

Pellegatta

Qiu

Gao

Ceccarelli

Riccardi

Brat

D.J.

Guha

Aldape

Golfinos

J.G.

Zagzag

Mikkelsen

Finocchiaro

Lasorella

Rabadan

and Iavarone

, Transforming fusions of FGFR and TACC genes in humanglioblastoma, Science 337 (2012), 1231–1235.

16.

Stefano

A.-L.D.

Fucci

Frattini

Labussière

Mokhtari

Zoppoli

Marie

Bruno

Boisselier

Giry

Savatovsky

Touat

Belaid

Kamoun

Idbaih

Houillier

Luo

F.R.

Soria

J.-C.

Tabernero

Eoli

Paterra

Yip

Petrecca

Chan

J.A.

Finocchiaro

Lasorella

Sanson

and Iavarone

, Detection, Characterization, and Inhibition of FGFR-TACC Fusions in IDH Wild-type Glioma, Clin Cancer Res 21 (2015), 3307–3317.

17.

Bahleda

Italiano

Hierro

Mita

Cervantes

Chan

Awad

Calvo

Moreno

Govindan

Spira

Gonzalez

Zhong

Santiago-Walker

Poggesi

Parekh

Xie

Infante

and Tabernero

, Multicenter Phase I Study of Erdafitinib (JNJ-42756493), Oral Pan-Fibroblast Growth Factor Receptor Inhibitor, in Patients with Advanced or Refractory Solid Tumors, Clin Cancer Res 25 (2019), 4888–4897.

18.

Wang

Liang

Chen

Fan

Gao

Tao

and Zhang

, Targeted Therapy with Anlotinib for a Patient with an Oncogenic FGFR3-TACC3 Fusion and Recurrent Glioblastoma, Oncol 26 (2021), 173–177.

19.

Harris

P.A.

Taylor

Minor

B.L.

Elliott

Fernandez

O’Neal

McLeod

Delacqua

Kirby

Duda

S.N.

and on behalf of the Redc. Consortium, The REDCap Consortium: Building an International Community of Software Platform Partners, J Biomed Inform 95 (2019), 103208.

20.

Brat

D.J.

Aldape

Colman

Holland

E.C.

Louis

D.N.

Jenkins

R.B.

Kleinschmidt-DeMasters

B.K.

Perry

Reifenberger

Stupp

von Deimling

and Weller

, cIMPACT-NOW update 3: recommended diagnosticcriteria for “Diffuse astrocytic glioma, IDH-wildtype, with molecularfeatures of glioblastoma, WHO grade IV”, Acta Neuropathol 136 (2018), 805–810.

21.

Dono

Anapolsky

Hines

Takayasu

Yan

Tandon

Zhu

J.-J.

Bhattacharjee

M.B.

Esquenazi

and Ballester

L.Y.

, Additional genetic alterations in BRAF-mutant gliomas correlate with histologic diagnoses, J Neuro-Oncol 149 (2020), 463–472.

22.

Schwaederle

Krishnamurthy

Daniels

G.A.

Piccioni

D.E.

Kesari

Fanta

P.T.

Schwab

R.B.

Patel

S.P.

Parker

B.A.

and Kurzrock

, Telomerase reverse transcriptase promoter alterations across cancer types asdetected by next-generation sequencing: A clinical and molecular analysis of 423 patients, Cancer 124 (2018), 1288–1296.

23.

Frampton

G.M.

Fichtenholtz

Otto

G.A.

Wang

Downing

S.R.

Schnall-Levin

White

Sanford

E.M.

Sun

Juhn

Brennan

Iwanik

Maillet

Buell

White

Zhao

Balasubramanian

Terzic

Richards

Banning

Garcia

Mahoney

Zwirko

Donahue

Beltran

Mosquera

J.M.

Rubin

M.A.

Dogan

Hedvat

C.V.

Berger

M.F.

Pusztai

Lechner

Boshoff

Jarosz

Vietz

Parker

Miller

V.A.

Ross

J.S.

Curran

Cronin

M.T.

Stephens

P.J.

Lipson

and Yelensky

, Development and validation of aclinical cancer genomic profiling test based on massively parallel DNA sequencing, Nat Biotechnol 31 (2013), 1023–1031.

24.

Gao

Aksoy

B.A.

Dogrusoz

Dresdner

Gross

Sumer

S.O.

Sun

Jacobsen

Sinha

Larsson

Cerami

Sander

and Schultz

, Integrative analysis of complex cancer genomics and clinical profiles usingthe cBioPortal, Sci Signal 6 (2013), pl1 pl1.

25.

Cerami

Gao

Dogrusoz

Gross

B.E.

Sumer

S.O.

Aksoy

B.A.

Jacobsen

Byrne

C.J.

Heuer

M.L.

Larsson

Antipin

Reva

Goldberg

A.P.

Sander

and Schultz

, The cBio cancer genomics portal: an openplatform for exploring multidimensional cancer genomics data, Cancer Discov 2 (2012), 401–404.

26.

Liu

Lichtenberg

Hoadley

K.A.

Poisson

L.M.

Lazar

A.J.

Cherniack

A.D.

Kovatich

A.J.

Benz

C.C.

Levine

D.A.

Lee

A.V.

Omberg

Wolf

D.M.

Shriver

C.D.

Thorsson

, the Cancer Genome Atlas Research Network Caesar-Johnson

S.J.

Demchok

J.A.

Felau

Kasapi

Ferguson

M.L.

Hutter

C.M.

Sofia

H.J.

Tarnuzzer

Wang

Yang

Zenklusen

J.C.

Zhang

Chudamani

Liu

Lolla

Naresh

Pihl

Sun

Wan

Cho

DeFreitas

Frazer

Gehlenborg

Getz

Heiman

D.I.

Kim

Lawrence

M.S.

Lin

Meier

Noble

M.S.

Saksena

Voet

Zhang

Bernard

Chambwe

Dhankani

Knijnenburg

Kramer

Leinonen

Liu

Miller

Reynolds

Shmulevich

Thorsson

Zhang

Akbani

Broom

B.M.

Hegde

A.M.

Kanchi

R.S.

Korkut

Liang

Ling

Liu

Mills

G.B.

K.-S.

Rao

Ryan

Wang

Weinstein

J.N.

Zhang

Abeshouse

Armenia

Chakravarty

Chatila

W.K.

de Bruijn

Gao

Gross

B.E.

Heins

Z.J.

Kundra

Ladanyi

Luna

Nissan

M.G.

Ochoa

Phillips

S.M.

Reznik

Sanchez-Vega

Sander

Schultz

Sheridan

Sumer

S.O.

Sun

Taylor

B.S.

Wang

Zhang

Anur

Peto

Spellman

Benz

Stuart

J.M.

Wong

C.K.

Yau

Hayes

D.N.

Parker

J.S.

Wilkerson

M.D.

Ally

Balasundaram

Bowlby

Brooks

Carlsen

Chuah

Dhalla

Holt

Jones

S.J.M.

Kasaian

Lee

Marra

M.A.

Mayo

Moore

R.A.

Mungall

A.J.

Mungall

Robertson

A.G.

Sadeghi

Schein

J.E.

Sipahimalani

Tam

Thiessen

Tse

Wong

Berger

A.C.

Beroukhim

Cherniack

A.D.

Cibulskis

Gabriel

S.B.

Gao

G.F.

Meyerson

Schumacher

S.E.

Shih

Kucherlapati

M.H.

Kucherlapati

R.S.

Baylin

Cope

Danilova

Bootwalla

M.S.

Lai

P.H.

Maglinte

D.T.

Berg

D.J.V.D.

Weisenberger

D.J.

Auman

J.T.

Balu

Bodenheimer

Fan

Hoadley

K.A.

Hoyle

A.P.

Jefferys

S.R.

Jones

C.D.

Meng

Mieczkowski

P.A.

Mose

L.E.

Perou

A.H.

Perou

C.M.

Roach

Shi

Simons

J.V.

Skelly

Soloway

M.G.

Tan

Veluvolu

Fan

Hinoue

Laird

P.W.

Shen

Zhou

Bellair

Chang

Covington

Creighton

C.J.

Dinh

Doddapaneni

Donehower

L.A.

Drummond

Gibbs

R.A.

Glenn

Hale

Han

Korchina

Lee

Lewis

Liu

Morgan

Morton

Muzny

Santibanez

Sheth

Shinbro

Wang

Wheeler

D.A.

Zhao

Hess

Appelbaum

E.L.

Bailey

Cordes

M.G.

Ding

Fronick

C.C.

Fulton

L.A.

Fulton

R.S.

Kandoth

Mardis

E.R.

McLellan

M.D.

Miller

C.A.

Schmidt

H.K.

Wilson

R.K.

Crain

Curley

Gardner

Lau

Mallery

Morris

Paulauskis

Penny

Shelton

Sherman

Thompson

Yena

Bowen

Gastier-Foster

J.M.

Gerken

Leraas

K.M.

Lichtenberg

T.M.

Ramirez

N.C.

Wise

Zmuda

Corcoran

Costello

Hovens

Carvalho

A.L.

de Carvalho

A.C.

Fregnani

J.H.

Longatto-Filho

Reis

R.M.

Scapulatempo-Neto

Silveira

H.C.S.

Vidal

D.O.

Burnette

Eschbacher

Hermes

Noss

Singh

Anderson

M.L.

Castro

P.D.

Ittmann

Huntsman

Kohl

Thorp

Andry

Duffy

E.R.

Lyadov

Paklina

Setdikova

Shabunin

Tavobilov

McPherson

Warnick

Berkowitz

Cramer

Feltmate

Horowitz

Kibel

Muto

Raut

C.P.

Malykh

Barnholtz-Sloan

J.S.

Barrett

Devine

Fulop

Ostrom

Q.T.

Shimmel

Wolinsky

Sloan

A.E.

Rose

A.D.

Giuliante

Goodman

Karlan

B.Y.

Hagedorn

C.H.

Eckman

Harr

Myers

Tucker

Zach

L.A.

Deyarmin

Kvecher

Larson

Mural

R.J.

Somiari

Vicha

Zelinka

Bennett

Iacocca

Rabeno

Swanson

Latour

Lacombe

Têtu

Bergeron

McGraw

Staugaitis

S.M.

Chabot

Hibshoosh

Sepulveda

Wang

Potapova

Voronina

Desjardins

Mariani

Roman-Roman

Sastre

Stern

M.-H.

Cheng

Signoretti

Berchuck

Bigner

Lipp

Marks

McCall

McLendon

Secord

Sharp

Behera

Brat

D.J.

Chen

Delman

Force

Khuri

Magliocca

Maithel

Olson

J.J.

Owonikoko

Pickens

Ramalingam

Shin

D.M.

Sica

Meir

E.G.V.

Zhang

Eijckenboom

Gillis

Korpershoek

Looijenga

Oosterhuis

Stoop

van Kessel

K.E.

Zwarthoff

E.C.

Calatozzolo

Cuppini

Cuzzubbo

DiMeco

Finocchiaro

Mattei

Perin

Pollo

Chen

Houck

Lohavanichbutr

Hartmann

Stoehr

Taubert

Wach

Wullich

Kycler

Murawa

Wiznerowicz

Chung

Edenfield

W.J.

Martin

Baudin

Bubley

Bueno

Rienzo

A.D.

Richards

W.G.

Kalkanis

Mikkelsen

Noushmehr

Scarpace

Girard

Aymerich

Campo

Giné

Guillermo

A.L.

Bang

N.V.

Hanh

P.T.

Phu

B.D.

Tang

Colman

Evason

Dottino

P.R.

Martignetti

J.A.

Gabra

Juhl

Akeredolu

Stepa

Hoon

Ahn

Kang

K.J.

Beuschlein

Breggia

Birrer

Bell

Borad

Bryce

A.H.

Castle

Chandan

Cheville

Copland

J.A.

Farnell

Flotte

Giama

Kendrick

Kocher

J.-P.

Kopp

Moser

Nagorney

O’Brien

O’Neill

B.P.

Patel

Petersen

Que

Rivera

Roberts

Smallridge

Smyrk

Stanton

Thompson

R.H.

Torbenson

Yang

J.D.

Zhang

Brimo

Ajani

J.A.

Gonzalez

A.M.A.

Behrens

Bondaruk

Broaddus

Czerniak

Esmaeli

Fujimoto

Gershenwald

Guo

Lazar

A.J.

Logothetis

Meric-Bernstam

Moran

Ramondetta

Rice

Sood

Tamboli

Thompson

Troncoso

Tsao

Wistuba

Carter

Haydu

Hersey

Jakrot

Kakavand

Kefford

Lee

Long

Mann

Quinn

Saw

Scolyer

Shannon

Spillane

Stretch

Synott

Thompson

Wilmott

Al-Ahmadie

Chan

T.A.

Ghossein

Gopalan

Levine

D.A.

Reuter

Singer

Singh

Tien

N.V.

Broudy

Mirsaidi

Nair

Drwiega

Miller

Smith

Zaren

Park

J.-W.

Hung

N.P.

Kebebew

Linehan

W.M.

Metwalli

A.R.

Pacak

Pinto

P.A.

Schiffman

Schmidt

L.S.

Vocke

C.D.

Wentzensen

Worrell

Yang

Moncrieff

Goparaju

Melamed

Pass

Botnariuc

Caraman

Cernat

Chemencedji

Clipca

Doruc

Gorincioi

Mura

Pirtac

Stancul

Tcaciuc

Albert

Alexopoulou

Arnaout

Bartlett

Engel

Gilbert

Parfitt

Sekhon

Thomas

Rassl

D.M.

Rintoul

R.C.

Bifulco

Tamakawa

Urba

Hayward

Timmers

Antenucci

Facciolo

Grazi

Marino

Merola

de Krijger

Gimenez-Roqueplo

A.-P.

Piché

Chevalier

McKercher

Birsoy

Barnett

Brewer

Farver

Naska

Pennell

N.A.

Raymond

Schilero

Smolenski

Williams

Morrison

Borgia

J.A.

Liptay

M.J.

Pool

Seder

C.W.

Junker

Omberg

Dinkin

Manikhas

Alvaro

Bragazzi

M.C.

Cardinale

Carpino

Gaudio

Chesla

Cottingham

Dubina

Moiseenko

Dhanasekaran

Becker

K.-F.

Janssen

K.-P.

Slotta-Huspenina

Abdel-Rahman

M.H.

Aziz

Bell

Cebulla

C.M.

Davis

Duell

Elder

J.B.

Hilty

Kumar

Lang

Lehman

N.L.

Mandt

Nguyen

Pilarski

Rai

Schoenfield

Senecal

Wakely

Hansen

Lechan

Powers

Tischler

Grizzle

W.E.

Sexton

K.C.

Kastl

Henderson

Porten

Waldmann

Fassnacht

Asa

S.L.

Schadendorf

Couce

Graefen

Huland

Sauter

Schlomm

Simon

Tennstedt

Olabode

Nelson

Bathe

Carroll

P.R.

Chan

J.M.

Disaia

Glenn

Kelley

R.K.

Landen

C.N.

Phillips

Prados

Simko

Smith-McCune

VandenBerg

Roggin

Fehrenbach

Kendler

Sifri

Steele

Jimeno

Carey

Forgie

Mannelli

Carney

Hernandez

Campos

Herold-Mende

Jungk

Unterberg

vonDeimling

Bossler

Galbraith

Jacobus

Knudson

Knutson

Milhem

Sigmund

Godwin

A.K.

Madan

Rosenthal

H.G.

Adebamowo

S.N.

Boussioutas

Beer

Giordano

Mes-Masson

A.-M.

Saad

Bocklage

Landrum

Mannel

Moore

Moxley

Postier

Walker

Zuna

Feldman

Valdivieso

Dhir

Luketich

Pinero

E.M.M.

Quintero-Aguilo

C.G.C.

Santos

J.S.D.

Kemp

Sankarankuty

Tirapelli

Catto

Agnew

Swisher

Creaney

Robinson

Shelley

C.S.

Godwin

E.M.

Kendall

Shipman

Bradford

Carey

Haddad

Moyer

Peterson

Prince

Rozek

Wolf

Bowman

Fong

K.M.

Yang

Korst

Rathmell

W.K.

Fantacone-Campbell

J.L.

Hooke

J.A.

Kovatich

A.J.

Shriver

C.D.

DiPersio

Drake

Govindan

Heath

Ley

Tine

B.V.

Westervelt

Rubin

M.A.

Lee

J.I.

Aredes

N.D.

Mariamidze

and Hu

, An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics, Cell 173 (2018), 400–416.

27.

Jonsson

Lin

A.L.

Young

R.J.

DiStefano

N.M.

Hyman

D.M.

B.T.

Berger

M.F.

Zehir

Ladanyi

Solit

D.B.

Arnold

A.G.

Stadler

Z.K.

Mandelker

Goldberg

M.E.

Chmielecki

Pourmaleki

Ogilvie

S.Q.

Chavan

S.S.

McKeown

A.T.

Manne

Hyde

Beal

Yang

T.J.

Nolan

C.P.

Pentsova

Omuro

Gavrilovic

I.T.

Kaley

T.J.

Diamond

E.L.

Stone

J.B.

Grommes

Boire

Daras

Piotrowski

A.F.

Miller

A.M.

Gutin

P.H.

Chan

T.A.

Tabar

V.S.

Brennan

C.W.

Rosenblum

DeAngelis

L.M.

Mellinghoff

I.K.

and Taylor

B.S.

, Genomic Correlates of Disease Progression and Treatment Response in Prospectively Characterized Gliomas, Clin Cancer Res 25 (2019), 5537–5547.

28.

Immune and genomic correlates of response to anti-PD-1 immunotherapy inglioblastoma, Nat Med 25 (2019), 1–23.

29.

Johnson

B.E.

Mazor

Hong

Barnes

Aihara

McLean

C.Y.

Fouse

S.D.

Yamamoto

Ueda

Tatsuno

Asthana

Jalbert

L.E.

Nelson

S.J.

Bollen

A.W.

Gustafson

W.C.

Charron

Weiss

W.A.

Smirnov

I.V.

Song

J.S.

Olshen

A.B.

Cha

Zhao

Moore

R.A.

Mungall

A.J.

Jones

S.J.M.

Hirst

Marra

M.A.

Saito

Aburatani

Mukasa

Berger

M.S.

Chang

S.M.

Taylor

B.S.

and Costello

J.F.

, Mutational Analysis Reveals the Origin and Therapy-Driven Evolution of Recurrent Glioma, Science 343 (2014), 189–193.

30.

Chakravarty

Gao

Phillips

Kundra

Zhang

Wang

Rudolph

J.E.

Yaeger

Soumerai

Nissan

M.H.

Chang

M.T.

Chandarlapaty

Traina

T.A.

Paik

P.K.

A.L.

Hantash

F.M.

Grupe

Baxi

S.S.

Callahan

M.K.

Snyder

Chi

Danila

D.C.

Gounder

Harding

J.J.

Hellmann

M.D.

Iyer

Janjigian

Y.Y.

Kaley

Levine

D.A.

Lowery

Omuro

Postow

M.A.

Rathkopf

Shoushtari

A.N.

Shukla

Voss

M.H.

Paraiso

Zehir

Berger

M.F.

Taylor

B.S.

Saltz

L.B.

Riely

G.J.

Ladanyi

Hyman

D.M.

Baselga

Sabbatini

Solit

D.B.

and Schultz

, OncoKB: A Precision Oncology Knowledge Base, Jco Precis Oncol 2017 (2017), 1–16.

31.

Kanda

, Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics, Bone Marrow Transpl 48 (2013), 452–458.

32.

Ballester

L.Y.

Moghadamtousi

S.Z.

Leeds

N.E.

Huse

J.T.

and Fuller

G.N.

, Coexisting FGFR3 p.K650T mutation in two FGFR3-TACC3 fusion gliomacases, Acta Neuropathologica Commun 7 (2019), 63.

33.

Ding

Getz

Wheeler

D.A.

Mardis

E.R.

McLellan

M.D.

Cibulskis

Sougnez

Greulich

Muzny

D.M.

Morgan

M.B.

Fulton

R.S.

Zhang

Wendl

M.C.

Lawrence

M.S.

Larson

D.E.

Chen

Dooling

D.J.

Sabo

Hawes

A.C.

Shen

Jhangiani

S.N.

Lewis

L.R.

Hall

Zhu

Mathew

Ren

Yao

Scherer

S.E.

Clerc

Metcalf

G.A.

Milosavljevic

Gonzalez-Garay

M.L.

Osborne

J.R.

Meyer

Shi

Tang

Koboldt

D.C.

Lin

Abbott

Miner

T.L.

Pohl

Fewell

Haipek

Schmidt

Dunford-Shore

B.H.

Kraja

Crosby

S.D.

Sawyer

C.S.

Vickery

Sander

Robinson

Winckler

Baldwin

Chirieac

L.R.

Dutt

Fennell

Hanna

Johnson

B.E.

Onofrio

R.C.

Thomas

R.K.

Tonon

Weir

B.A.

Zhao

Ziaugra

Zody

M.C.

Giordano

Orringer

M.B.

Roth

J.A.

Spitz

M.R.

Wistuba

I.I.

Ozenberger

Good

P.J.

Chang

A.C.

Beer

D.G.

Watson

M.A.

Ladanyi

Broderick

Yoshizawa

Travis

W.D.

Pao

Province

M.A.

Weinstock

G.M.

Varmus

H.E.

Gabriel

S.B.

Lander

E.S.

Gibbs

R.A.

Meyerson

and Wilson

R.K.

, Somatic mutations affect key pathways in lung adenocarcinoma, Nature 455 (2008), 10691075.

34.

Gessi

Moneim

Y.A.

Hammes

Goschzik

Scholz

Denkhaus

Waha

and Pietsch

, FGFR1 mutations in Rosette-forming glioneuronal tumors of the fourth ventricle, J Neuropathology Exp Neurology 73 (2014), 580–584.

35.

Yamaguchi

Saya

Bruner

J.M.

and Morrison

R.S.

, Differential expression of two fibroblast growth factor-receptor genes is associated with malignant progression in human astrocytomas, Proc National Acad Sci 91 (1994), 484–488.

36.

Morrison

R.S.

Yamaguchi

Saya

Bruner

J.M.

Yahanda

A.M.

Donehower

L.A.

and Berger

, Basic fibroblast growth factor and fibroblast growth factor receptor I are implicated in the growth of human astrocytomas, J Neuro-Oncol 18 (1994), 207–216.

37.

Ohashi

Matsuda

Ishiwata

and Naito

, Downregulation of fibroblast growth factor receptor 2 and its isoforms correlates with a high proliferation rate and poor prognosis in high-grade glioma, Oncol Rep 32 (2014), 1163–1169.

38.

Ryall

Zapotocky

Fukuoka

Nobre

Stucklin

A.G.

Bennett

Siddaway

Pajovic

Arnoldo

Kowalski

P.E.

Johnson

Sheth

Lassaletta

Tatevossian

R.G.

Orisme

Qaddoumi

Surrey

L.F.

M.M.

Waanders

A.J.

Gilheeney

Rosenblum

Bale

Tsang

D.S.

Laperriere

Kulkarni

Ibrahim

G.M.

Drake

Dirks

Taylor

M.D.

Rutka

J.T.

Laughlin

Shroff

Shago

Hazrati

L.-N.

D’Arcy

Ramaswamy

Bartels

Huang

Bouffet

Karajannis

M.A.

Santi

Ellison

D.W.

Tabori

and Hawkins

, Integrated Molecular and Clinical Analysis of 1,000 Pediatric Low-Grade Gliomas, Cancer Cell 37 (2020), 569–583.

39.

Huse

J.T.

Snuderl

Jones

D.T.W.

Brathwaite

C.D.

Altman

Lavi

Saffery

Sexton-Oates

Blümcke

Capper

Karajannis

M.A.

Benayed

Chavez

Thomas

Serrano

Borsu

Ladanyi

and Rosenblum

M.K.

, Polymorphous low-grade neuroepithelial tumor ofthe young (PLNTY): an epileptogenic neoplasm with oligodendroglioma-like components, aberrant CD34 expression, and genetic alterations involving the MAP kinase pathway, Acta Neuropathol 133 (2016), 417–429.

40.

Costa

Carneiro

B.A.

Taxter

Tavora

F.A.

Kalyan

Pai

S.A.

Chae

Y.K.

and Giles

F.J.

, FGFR3-TACC3 fusion in solid tumors: mini review, Oncotarget 7 (2016), 55924–55938.

41.

Helsten

Elkin

Arthur

Tomson

B.N.

Carter

and Kurzrock

, The FGFR Landscape in Cancer: Analysis of 4,853 Tumors by Next-Generation Sequencing, Clin Cancer Res 22 (2016), 259–267.

42.

Tate

J.G.

Bamford

Jubb

H.C.

Sondka

Beare

D.M.

Bindal

Boutselakis

Cole

C.G.

Creatore

Dawson

Fish

Harsha

Hathaway

Jupe

S.C.

Kok

C.Y.

Noble

Ponting

Ramshaw

C.C.

Rye

C.E.

Speedy

H.E.

Stefancsik

Thompson

S.L.

Wang

Ward

Campbell

P.J.

and Forbes

S.A.

, COSMIC: the Catalogue Of Somatic Mutations In Cancer, Nucleic Acids Res 47 (2018), D941–D947.

43.

Ahrendsen

J.T.

Torre

Meredith

D.M.

Hornick

J.L.

Reardon

D.A.

Wen

P.Y.

Yeo

K.K.

Malinowski

Ligon

K.L.

Ramkissoon

and Alexandrescu

, IDH-mutant gliomas with additional class-defining molecular events, Modern Pathol 34 (2021), 1236–1244.

44.

Mata

D.A.

Benhamida

J.K.

Lin

A.L.

Vanderbilt

C.M.

Yang

S.-R.

Villafania

L.B.

Ferguson

D.C.

Jonsson

Miller

A.M.

Tabar

Brennan

C.W.

Moss

N.S.

Sill

Benayed

Mellinghoff

I.K.

Rosenblum

M.K.

Arcila

M.E.

Ladanyi

and Bale

T.A.

, Genetic and epigenetic landscape of IDH-wildtype glioblastomas with FGFR3-TACC3 fusions, Acta Neuropathologica Commun 8 (2020), 186.

45.

Stefano

A.L.D.

Picca

Saragoussi

Bielle

Ducray

Villa

Eoli

Paterra

Bellu

Mathon

Capelle

Bourg

Gloaguen

Philippe

Frouin

Schmitt

Lerond

Leclerc

Lasorella

Iavarone

Mokhtari

Savatovsky

Alentorn

Sanson

and TARGET study group, Clinical, molecular, and radiomic profile of gliomas with FGFR3-TACC3 fusions, Neuro-Oncology 22 (2020), 1614–1624.

46.

Ruhe

J.E.

Streit

Hart

Wong

C.-H.

Specht

Knyazev

Knyazeva

Tay

L.S.

Loo

H.L.

Foo

Wong

Pok

Lim

S.J.

Ong

Luo

H.K.

Peng

Lee

T.C.

Bezler

Mann

Gaertner

Hoefler

Iacobelli

Peter

Tay

Brenner

Venkatesh

and Ullrich

, Genetic Alterations in the Tyrosine Kinase Transcriptome of Human Cancer Cell Lines, Cancer Res 67 (2007), 11368–11376.

47.

Bielle

Stefano

A.D.

Meyronet

Picca

Villa

Bernier

Schmitt

Giry

Rousseau

Figarella-Branger

Maurage

Uro-Coste

Lasorella

Iavarone

Sanson

and Mokhtari

, Diffuse gliomas with FGFR3-TACC3 fusion have characteristic histopathological and molecular features, Brain Pathol 28 (2017), 674–683.

48.

Georgescu

M.-M.

Islam

M.Z.

Traylor

and Nanda

, Novel targetable FGFR2 and FGFR3 alterations in glioblastoma associate with aggressive phenotype and distinct gene expression programs, Acta Neuropathologica Commun 9 (2021), 69.

Infiltrating gliomas with FGFR alterations: Histologic features,genetic alterations,and potential clinical implications

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Material and methods

2.1 Patients and tumor samples

2.2 Histologic features

2.3 Targeted sequencing

2.4 cBioPortal cohort

2.5 Statistical analyses

3. Results

3.1 Clinical and demographic characteristics

3.2 Histologic features of FGFR-altered gliomas

Table 1 Demographic, clinical characteristics, and mutations in FGFR-altered gliomas

3.4 FGFR-altered infiltrating gliomas in cBioPortal

3.5 Prognosis and survival

4. Discussion

Funding

Author contributions

Supplementary data

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Demographic, clinical characteristics, and mutations in FGFR-altered gliomas