Targeting FGFR in non-small cell lung cancer: implications from the landscape of clinically actionable aberrations of FGFR kinases

Patients

A total of 15,150 consecutive clinical lung cancer patients were analyzed using comprehensive genomic profiling targeting 400+ cancer-relevant genes, including all the exons of FGFR genes (FGFR1-4), as well as flanking intronic regions, and other introns selected by a Clinical Laboratory Improvement Amendments-certified, and College of American Pathologists-accredited laboratory (Nanjing Geneseeq Technology, Jiangsu, China), as previously described¹⁴. We identified patients with FGFR alterations using a natural language search tool in the laboratory information management system database. Relevant demographic and clinical data were extracted from the database, including age, gender, date of diagnosis, histology, pathological stage, and evaluation of treatment response based on reports by clinical investigators.

For tumor tissue samples, the pathological diagnosis and tumor content of each case was confirmed by pathologists. Peripheral blood (8–10 mL) was collected in EDTA-coated tubes (BD Biosciences, San Jose, CA, USA) and centrifuged at 1,800 × g for 10 min within 2 h of collection to isolate the plasma for circulating tumor DNA (ctDNA) extraction, and white blood cells for genomic DNA extraction as the germline control.

DNA extraction and targeted enrichment

The ctDNA from plasma was purified using a Circulating Nucleic Acid Kit (Qiagen, Hilden, Germany) following the manufacturer’s protocol. Genomic DNA from white blood cells was extracted using the DNeasy Blood and Tissue Kit (Qiagen), while genomic DNA from formalin-fixed paraffin-embedded (FFPE) samples was purified using the QIAamp DNA FFPE Tissue Kit (Qiagen). All DNA was quantified using the dsDNA HS Assay Kit using a Qubit Fluorometer (Life Technologies, Carlsbad, CA, USA). Sequencing libraries were prepared using the KAPA Hyper Prep Kit (Roche, Basel, Switzerland), as described previously¹⁴. Indexed DNA libraries were pooled for probe-based hybridization capture of the targeted gene regions covering over 400 cancer-related genes for all solid tumors; all of which contained all exons of FGFR genes and selected introns for the detection of FGFR fusions.

Sequencing data processing

Sequencing was performed using the Illumina HiSeq4000 platform (Illumina, San Diego, CA, USA), followed by data analysis as previously described¹⁵. In brief, sequencing data were analyzed by Trimmomatic¹⁶ to remove low quality (quality < 15) or n bases, and were then mapped to the human reference genome, hg19, using the Burrows-Wheeler Aligner (https://github.com/lh3/bwa/tree/master/bwakit). PCR duplicates were removed by Picard (https://broadinstitute.github.io/picard/). The Genome Analysis Toolkit (GATK) (https://software.broadinstitute.org/gatk/) was used to perform local realignments around indels and for base quality reassurance. Single nucleotide polymorphisms (SNPs) and indels were analyzed by VarScan2¹⁷ and HaplotypeCaller/UnifiedGenotyper in GATK, with the mutant allele frequency cutoff at 0.5% for tissue samples, 0.1% for cfDNA samples, and a minimum of three unique mutant reads. Common SNPs were excluded if they were present in > 1% population frequency in the 1,000 Genomes Project or the Exome Aggregation Consortium (ExAC) 65,000 exome database. The resulting mutation list was further filtered using an in-house list of recurrent artifacts based on a normal pool of whole blood samples. Gene fusions were identified by FACTERA¹⁸.

Ethical approval

The study was approved by the Ethics Committee of Guangdong General Hospital, China (Approval No. GDREC2016262H). Shanghai Chest Hospital served as one of the hospitals participating in the research project. The study was conducted in accordance with the tenets of the Declaration of Helsinki, and written informed consent was collected from each patient prior to sample collection.

The incidence of FGFR aberrations in NSCLC patients

From December 2016 to February 2019, a total of 15,150 individual clinical lung cancers were successfully evaluated by comprehensive genomic profiling using hybrid capture-based NGS. This work was based on the validated dataset for a total of 10,966 patients in our database system. Lung cancer tumor samples and liquid biopsies, if applicable, were compared to matched normal whole blood controls. A total of 87% of NSCLC samples examined were lung adenocarcinomas [lung adenocarcinoma (LUAC), n = 9,596], 9% were lung squamous cell carcinoma (LUSC, n = 954), and the remainder (4%) were of either mixed adenocarcinomas and squamous cell carcinomas or were missing sub-histological information in the database. Approximately 40% of the entire study population had only liquid biopsy specimens for genetic testing. A total of 210 patients (1.9%, 210/10,966) were identified with somatic aberrations of FGFRs (FGFR1–4), including mutations, gene rearrangements, and gene amplifications (Figure 1A). Fifty-one patients (roughly 24%) had liquid biopsy samples including only plasma and pleural effusion samples. The median age of the cohort was 62 years of age (range: 34–84 years of age). Approximately 72% (152/210) of the patients were male. Approximately 61% of FGFR-positive patients were LUAC (n = 128), 31% were LUSC (n = 65), and the remaining 7 cases were of either mixed or unknown histology. Thus, FGFR alterations were more frequent in LUSC patients (6.8%, 65/954) than in LUAC patients (1.3%, 128/9,596). The majority of the FGFR aberrations were gene mutations (75%) with gene amplification and gene rearrangements being observed in similar frequencies (10% and 15%, respectively) (Figure 1A). FGFR1 alterations were slightly more abundant than alterations in FGFR2-4 (Figure 1B). Notably, we observed more amplification events in FGFR1s than in other FGFRs, and over 90% of FGFR4 alterations were mutations (Figure 1C).

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Figure 1

Distribution of FGFR aberrations in a large population of Chinese patients with non-small cell lung cancer. (A) The frequency of FGFR aberrations among all cases and (B) the relative proportion of FGFR aberrations of FGFR genes among all cases, with the breakdown of FGFR alterations (C). (D) Co-mutation plot showing patients who carried FGFR oncogenic mutations, fusions, and gene amplifications, as well as concomitant aberrations of genes, including EGFR, RAS, and components of the PI3K pathway. An additional 9 patients with FGF19 amplifications were also plotted. The asterisk indicates mutations or fusions in FGFRs other than FGFR3. The triangle indicates non-FGFR1 amplifications.

Enrichment of the activated PI3K pathway in the FGFR mutant cohort

We identified a total of 187 patients with somatic point mutations and indels in FGFRs. The most frequent amino acid replacements across all FGFRs were FGFR3 S249C and R248C (Supplementary Figure S1). In particular, 19 patients representing ∼0.17% (19/10,966) of the NSCLC population were identified with FGFR1-4 oncogenic or likely oncogenic mutations according to the OncoKB database¹⁹ (Figure 1D, Table 1, and Supplementary Table S1). The majority of these patients (68%, 13/19) had lung squamous cell carcinoma, and two-thirds were male. Intriguingly, more than half of the 19 patients (58%, 11/19) had co-occurring PIK3CA aberrations, including PIK3CA E545K (n = 3), E453K (n = 1), H1049R (n = 1), A1035T (n = 1), PIK3CA amplifications (n = 4), and PIK3R2 G373R (n = 1) mutations. One patient had a concurrent activating EGFR ex19del, 4 patients had KRAS G12D/V or Q61L mutations, and the remaining 6 patients had no other known driver mutations (Table 1). A majority of the 19 patients with FGFR1-4 oncogenic mutations (68%, 13/19) were systemic treatment-naïve, with the exception that 1 patient progressed on multiple lines of EGFR tyrosine kinase inhibitors 9TKIs0, including gefitinib, osimertinib, and afatinib, and 5 patients either received multiple lines of chemotherapy or chemotherapy in combination with radiotherapy or VEGFR antibody therapy (Table 1). Notably, the patient (P2) who received multiple EGFR TKIs likely acquired FGFR3 R248C and/or G380R to overcome the anti-tumor activity of TKIs, including osimertinib and afatinib, although pretreatment samples were unfortunately not available (Table 1).

The identification of novel FGFR fusions in NSCLC patients

FGFR fusions retaining the intact kinase domain were identified in 0.11% (12/10,966) of NSCLC patients examined (Figure 1D and Table 2). A majority of these patients (75%, 9/12) were positive for FGFR3-transforming acidic coiled-coil containing protein 3 gene (TACC3) fusions (FGFR3-TACC3), which were mostly reported in solid tumors²⁰. Four of the 9 (45%) patients with FGFR3-TACC3 fusions had 5′ breakpoints in FGFR3 exon 17 and the remaining 55% were in exon 18, while TACC3 exons 10 and 11 were the most common 3′ breakpoint locations (Figure 2A). We observed 1 case of FGFR3 exon 17 fused to TACC3 exon 14 that may have resulted in a fusion protein with compromised dimerization capacity due to a truncated coiled-coil domain (Figure 2A).

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Figure 2

Visualization of FGFR fusions, including fusion partners, using the Integrative Genomics Viewer Browser. (A) The frequency of FGFR3-TACC3 fusions in the cohort. (B-D) The IGV screenshots display the reads from next generation sequencing and reveal FGFR fusions of (B) FGFR2-INA (F17:I2), (C) FGFR4-RAPGEFL1 (F17:R4), and (D) SLC20A1-FGFR1.

We also observed 1 gene rearrangement event involving FGFR2 and an internexin neuronal intermediate filament protein α gene (INA) fusion (FGFR2 F17: INA I2) in a patient (P16) with stage IV lung adenocarcinoma (Figure 2B). The FGFR2-INA fusion was previously reported in low grade gliomas that drove oncogenesis via MAPK and PI3K/mTOR pathway activation²¹. Our observations represented the first case of a FGFR2-INA fusion in NSCLC, in particular, lung adenocarcinoma. Furthermore, 1 gene fusion event involving fibroblast growth factor receptor 4 (FGFR4) and the Rap guanine nucleotide exchange factor like 1 gene (RAPGEFL1) (FGFR4 F17: RAPGEFL1 R4) was detected in a lung adenocarcinoma patient (P26) (Figure 2C), which has not been previously documented, and therefore further validation of its function is necessary in future research. Notably, a concurrent activating EGFR ex19del mutation was also detected at an allele frequency of 21.71% in this patient. In addition, we observed 1 patient with a 5′-untranslated region of the Solute Carrier Family 20 Member 2 gene (SLC20A2) fused to FGFR1 exon 17 (Figure 2D).

Of note, concomitant EGFR mutations or EGFR amplifications were observed in 6 of the 12 FGFR fusion patients (Table 2), 4 of which were previously treated with EGFR TKIs, but the disease had progressed prior to NGS tests. Although half the patients (n = 2) did not have pretreatment samples, the remaining 2 patients (P16 and P17) likely acquired FGFR fusions as alternative mechanisms to combat the anti-tumor activity of EGFR TKIs (Table 2). Furthermore, a concurrent PIK3CA H1047R mutation was observed in 1 patient (P22) and may also have acted as a mechanism of acquired resistance to prior therapies including TKIs (Table 2). No other known dominant driver mutations were detected in the remaining 6 patients (Table 2).

Amplification of the FGF19 and FGFR genes in NSCLC patients

As previously mentioned, we observed more amplification events in FGFR1 than other FGFRs (Figure 1B). FGFR amplification was detected in a total of 24 patients, a majority of which (87.5%, 21/24) were FGFR1 amplifications (Figure 1D). Similarly, the majority of FGFR-amplified patients (67%) were LUSC and 92% were male (Table 3). Notably, 25 patients (12%, 25/210) had multiple alterations in FGFR genes, but oncogenic FGFR mutations, fusions, or gene amplifications were almost mutually exclusive events, with the exception that 4 FGFR3-mutant patients had concurrent FGFR1 amplifications (Figure 1D). Two patients had concurrent EGFR activating mutations and received prior EGFR-TKI treatments. However, no pretreatment samples were available for mutation profiling for these patients. The remaining patients (92%, 22/24) had no other dominant driver mutations and were either chemotherapy-refractory or treatment naïve (Table 3).

We also identified 9 patients (0.08%, 9/10,966) who had amplifications of FGF19 (Figure 1D), which encodes a unique, high affinity ligand that specifically binds to FGFR4 in a heparin-dependent manner. Our observations were consistent with previous studies reporting on the role of the FGF19-FGFR4 signaling axis in human cancers, including hepatocellular carcinoma²² and lung squamous cell carcinoma²³. Two patients had concomitant aberrations of the PI3K signaling pathway, including PIK3CA amplification and the PIK3R2 G373R missense mutation (Table 3). All patients were either chemotherapy-refractory or treatment naïve.