Small-cell lung cancer (SCLC) is a highly malignant pulmonary neuroendocrine tumor representing 15% of all lung carcinomas and is strongly associated with cigarette smoking.1,2 Patients with SCLC are classified as having either limited disease or extensive disease depending on whether the cancer has metastasized beyond one hemithorax. Given that more than 70% of all SCLC patients present with widely extensive disease, chemotherapy is the only treatment option. Unfortunately, all patients will relapse and the effectiveness of second-line therapies is limited. No significant improvement in SCLC treatment has emerged over the past 30 years.3 Molecular targeting approaches that have been successful against non–small-cell lung cancer (NSCLC), such as erlotinib and crizotinib, have been unsuccessful against SCLC.4,5 These failures suggest that fundamental biological differences exist between these two subtypes of lung cancer. Although SCLC is not included in The Cancer Genome Atlas, there is a growing interest in defining the somatic mutations associated with SCLC, as evidenced by two recent publications featuring comprehensive genomic analyses of SCLC tumors.6,7 A major limitation of these studies, however, is that mostly primary tumors were analyzed, likely obtained from a rare subgroup of patients with SCLC that have undergone surgical resection for very early stage disease and most likely represents a distinct biological behavior that may not be representative of the majority of patients.
We maintain a clinical/pathological database of all SCLC patients presenting at our medical center. We used this database to quantitate the distribution of diagnostic specimens available for genomic analysis. Furthermore, we initially selected six tumors for oncogene analysis and identified an activating somatic RET M918T mutation in a metastatic tumor. The downstream effects of stable overexpression of this RET mutant and wild-type RET in cultured SCLC cells were examined. Our results demonstrate that RET may represent a new target for tyrosine kinase inhibition in a subset of SCLC.
MATERIALS AND METHODS
Our study was approved by our local Institutional Review Board. All SCLC patients presenting between 2000 and 2012 for whom pathological diagnosis was obtained at our institution were eligible for this database. All obtained diagnostic specimens were recorded. Those which were obtained in the initial diagnostic process were considered as the first or primary diagnostic samples. A total of 422 patients are included in our database, of which 412 had diagnostic pathology samples. The mean age of the cohort was 66.2 ± 10.6 (SD) years, and the median overall survival of patients was 10.9 months. Further descriptive statistics for the SCLC cohort are given in Supplemental Table 1 (Supplemental Digital Content 1, http://links.lww.com/JTO/A675).
DNA from tumors of six different patients was prepared using two to three slides of formalin-fixed paraffin-embedded tissue, using a QIAmp DNA formalin-fixed paraffin-embedded kit (Qiagen, Valencia, CA). All specimens were at least 75% tumor. The primary tumors (no. 12, 16, 18) were peripheral in location and surgically resected. The SCLC metastatic tumors were from the brain (no. 22), pancreas (no. 182), and adrenal gland (no. 162). Additional descriptive features for the six patients are given in Supplemental Table 1 (Supplemental Digital Content 1, http://links.lww.com/JTO/A675). The tumor DNA was analyzed by SEQUENOM (San Diego, CA) using their platform technology called OncoCarta, which consists of multiplexed polymerase chain reaction (PCR) assays that are run on each sample and analyzed by subsequent matrix-assisted laser desorption ionization–time-of-flight (MALDI-TOF) mass spectroscopy. The OncoCarta panel of reagents assays for 238 somatic mutations across 19 common oncogenes (ABL-1, AKT-1 & 2, BRAF, CDK-4, EGFR, ERBB2, FGFR-1 & 3, FLT-3, JAK-2, KIT, MET, PDGFRα, PIK3CA, H-, K-, and N-RAS, and RET) and detects single base mutations, insertions, and deletions. The output of this assay reports the relative frequency of the mutated and expected wild-type sequences (see Supplemental Figure 1, Supplemental Digital Content 2, http://links.lww.com/JTO/A675).
RET mutations were verified by Sanger sequencing. The forward primer was 5′-actgaaagctcagggataggg-3′ and the reverse primer was 5′-catttgcctcacgaacacatc-3′ for amplification of RET exon 16 containing the mutation. A 357-bp product was generated containing the 71-bp exon, using an annealing temperature of 60°C and 30 cycles of PCR. We also performed targeted exon sequencing of exons 11 to 19 of RET in DNA isolated from 46 SCLC cell lines, 20 primary and 8 metastatic SCLC tumors. The exon sequencing results were not validated. The potential structural and functional effects of amino acid mutations in RET were predicted using PolyPhen-2 ( http://genetics.bwh.harvard.edu/pph2/) and SIFT Human Protein DB ( http://sift.jcvi.org/) using the longer RET-51 isoform.
RET Receptor Stable Cell Culture and Treatment
Human small-cell lung carcinoma cell lines NCI H1048 and SW1271 were purchased from American Type Culture Collection (Manassas, VA). Cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM)/Ham’s F-12, 1:1 supplemented with 10% (v/v) fetal bovine serum (Hyclone, South Logan, UT) in a 5% carbon dioxide humidified incubator at 37°C. Cells were seeded for transfection at 1 × 105 cells per well in 6-well plates. TransIT-2020 (Mirus, Madison, WI) was used as the transfection reagent with 1 μg of either pcDNA-RET wild type or pcDNA-RET M918T in DMEM/F12 media without serum. Both constructs contained the shorter, RET-9 isoform. After 5 hours of incubation, media was replaced with DMEM/F12 media containing fetal bovine serum (10%). Stable transfectants were isolated by selection for 2 weeks in 1 mg/ml G418 (Sigma, St. Louis, MO). Clones were collectively trypsinized to form a pool of stable cells.
In ERK phosphorylation experiments, 2 × 105 cells were initially seeded into 6-well plates. After an overnight incubation in complete medium, cells were switched to serum-free medium for 24 hours. Cells were then stimulated with 5 or 50 ng/ml GDNF (Gibco/Life Technologies, Grand Island, NY) for 10 minutes, then protein lysates were prepared.
Quantitative Real-Time PCR
Cells were harvested under exponential growth conditions. RNA was extracted using the RNeasy Mini Kit (Qiagen), digested with DNase I (Promega, Madison, WI), and reverse transcription was performed using a Superscript III First Strand synthesis kit for real-time PCR (Invitrogen, Carlsbad, CA). Real-time PCR was performed using TaqMan Fast Universal Master Mix and the TaqMan probe for human RET (Hs01120030) on an Applied Biosystems 7500 Fast Sequence Detection System according to the manufacturer’s instructions (Applied Biosystems, Foster City, CA). Samples were run in triplicate and standardized against endogenous β-actin (Human ACTB Endogenous Control, Applied Biosystems). The resulting relative RET mRNA amounts in each sample (ΔCT = RET CT − ACTB CT) were normalized to control values (ΔΔCT) to yield fold changes.
Immunoblotting and Antibodies
Cells were washed with cold phosphate-buffered saline (PBS), resuspended in radioimmunoprecipitation assay (RIPA) lysis buffer, and centrifuged at 12,000g for 4 minutes. The supernatant was collected and stored at −80°C. Protein concentrations were estimated using Bradford reagent (Bio-Rad, Hercules, CA). Equal amounts of protein were loaded for immunoblotting. After SDS-PAGE, resolved proteins were electroblotted onto immobilon polyvinylidene difluoride (PVDF) membrane. The membrane was blocked overnight in PBS containing 0.1% Tween-20 (PBST) and 5% bovine serum albumin. The membrane was then probed with primary antibody in PBST/5% milk for 2 hours at room temperature or overnight at 4°C, followed by three 10-minute PBST washes at room temperature. Secondary antibody in PBST/5% milk was incubated for 1 hour, followed by three 10-minute PBST washes before chemiluminescence detection using ECL Plus substrate (Amersham, GE Healthcare, Piscataway, NJ). Antibodies used for western blots were total Ret (sc-13104), total Erk (sc-94), and p-Erk (sc-7383) from Santa Cruz Biotechnology (Santa Cruz, CA), c-Myc from Abcam (Cambridge, MA), and β-actin (A5441) from Sigma.
Cell Proliferation Assays
Cell proliferation was assayed as percent confluence using an IncuCyte ZOOM (ESSEN Bioscience, Ann Arbor, MI) in 24-well dishes. Briefly, 5 × 104 parental or RET-receptor stable cells were seeded per well. After overnight incubation in complete medium, cells were switched to serum-free conditions for the rest of the experiment. The percent confluence was measured every 2 hours for 8 days. Results show the average of triplicate wells.
Cell proliferation was also determined by the MTT assay using a CellTiter 96 AQueous One Solution Cell Proliferation Assay Kit (Promega). Approximately 2 × 104 cells were added to each well of a 96-well plate in 100 μl of complete medium. After overnight incubation, cells were switched to serum-free conditions for the rest of the experiment. Four days later, 20 μl of CellTiter 96 AQueous One Solution was added to each well and the plates were further incubated for 2 hours at 37°C. Absorbance was measured at 490 nm with a 96-well plate reader. In some experiments, cells were continuously treated for the indicated times with various doses of either vandetanib or ponatinib (Selleckchem, Houston, TX). Drug was administered 1 day after the initial seeding and growth inhibition measured in complete medium. All experimental conditions were assayed in triplicate.
RET mRNA expression in SCLC cells was compared with that of NSCLC cells by multiple comparisons tests after one-way analysis of variance, using GraphPad PRISM software (La Jolla, CA).
The MaxArray Human Lung Cancer Tissue Microarray was obtained from InVitrogen (Camarillo, CA). Antibodies used in immunohistochemistry were total RET (HPA008356) from Sigma and p-MAPK (Erk 1/2) (no. 4376) from Cell Signaling Technology. Immunohistochemistry was scored by a thoracic pathologist on a scale of 0 (<5%), 1+ (5–25%), 2+ (25–50%), or 3+ (>50%), depending on the percentage of tumor cells staining positive for RET.
Distribution of SCLC Diagnostic Samples
The distribution of primary diagnostic samples, segregated by disease stage, in our SCLC cohort of patients is shown in Figure 1. Biopsy was the main procedure for initial diagnosis of both extensive (77%) and limited (71%) disease patients. Of particular note, however, surgical samples were the first diagnostic specimen in only 11 cases, all from limited disease patients, representing only 2.7% of all specimens.
RET Mutations in SCLC Tumors
We initially used our database to find six SCLC specimens, three primary and three metastatic, having sufficient tissue for genomic analysis. We detected only two high-confidence mutations by SEQUENOM analysis, a RET (rearranged during transfection, GDNF receptor) M918T mutation in a brain metastasis (no. 22) and a MET (met protooncogene, hepatocyte growth factor receptor) R970C mutation in a primary tumor (no. 18) (see Supplemental Figure 1, Supplemental Digital Content 2, http://links.lww.com/JTO/A675). Both were present at high allelic frequency (63% and 52%, respectively), indicating their potential as “driver” mutations. We selected the RET M918T mutation for further investigation because of its strong association with the MEN2B syndrome of medullary thyroid cancer (MTC),8,9 a disease that also has neuroendocrine features. The activating MET R970C mutation (also termed R988C) was previously reported in two SCLC cell lines but could not be found in a cohort of 33 SCLC tumors.10
We validated the RET M918T mutation in the tumor by Sanger sequencing, and its absence in a matched skin biopsy, establishing its somatic nature (see Supplemental Figure 2, Supplemental Digital Content 2, http://links.lww.com/JTO/A675). RET expression in the tumor was confirmed by immunohistochemistry (Fig. 2). We next performed our own targeted sequencing of exons 11 to 19 of RET, containing the tyrosine kinase domain, in an additional cohort of 20 primary and 8 metastatic SCLC tumors and 46 SCLC cell lines and found no RET mutations in the tumors but five cell lines harboring RET mutations (Table 1). We also looked for RET mutations in other reports of SCLC tumors6,7,11 and cell lines.12 Although we did not find any other occurrence of the RET M918T mutation, we did find four tumors and two cell lines with additional RET mutations, mainly within the tyrosine kinase domain (Table 1). Notably, several RET mutations were predicted to produce structural and/or functional effects using either the PolyPhen-2 or SIFT program.
RET Signaling and Inhibition in SCLC Cells
The mutant RET M918T receptor demonstrates high transforming activity relative to WT receptor in NIH3T3 cells.13 We, therefore, prepared stable pools of two SCLC cell lines, H1048 and SW1271, which overexpressed either WT or M918T RET receptors (Fig. 3A and B) and looked for differential effects on cell signaling and proliferation. Western blotting experiments demonstrated that downstream MYC expression and ERK signaling were activated more by mutant versus WT RET receptors, both in the absence and in the presence of added GDNF ligand (Fig. 3B and C). The greater downstream signaling by mutant M918T versus WT RET receptor in SW1271 cells compared with H1048 cells most likely reflects the different relative expression levels of the exogenous RET receptors observed in these cells (Fig. 3A and B). ERK activation in the original tumor specimen was also observed (Fig. 2). Greater cell proliferation could also be demonstrated in mutant compared with WT cells, measured by either confluence (Fig. 4A) or MTT (Fig. 4B) assays. Cells expressing either RET receptor grew more rapidly than the parental (control) cells. These data are consistent with RET M918T acting as an oncogene in SCLC.
If RET overexpression was driving cell proliferation, then it should also sensitize these cells to tyrosine kinase inhibitors of RET. As shown in Figure 4C, ponatinib was a more potent inhibitor than vandetanib, and neither inhibitor produced similar growth inhibition in the parental cells, indicating that the stable cells were indeed sensitized to tyrosine kinase inhibitors. Interestingly, there was little difference in growth inhibition of WT versus M918T mutant stable cells.
Variable RET Expression in Lung Cancer
Although M918T mutant cells were significantly more proliferative compared with transfected WT cells, WT RET and M918T RET cells were similarly inhibited by RET inhibitors. Thus, we wondered whether changes in RET global expression might contribute to the SCLC phenotype. Initially, we compared RET mRNA expression in various cancer cell lines using data from the Cancer Cell Line Encyclopedia12 and found that SCLC cells express relatively high levels of RET mRNA transcripts compared with most cancer cells, including NSCLC cells (see Figure 3, Supplemental Digital Content 2, http://links.lww.com/JTO/A675). We then focused on the expression of RET transcripts in specific thoracic cancers, shown in Figure 5A, compared with neuroblastoma, which demonstrated the highest RET expression levels among all cancer cells. It was clear that although RET expression was generally much lower in SCLC compared with neuroblastoma cells, a subgroup of SCLC cells expressed RET at the same high levels seen in neuroblastoma cells. The variability in SCLC RET expression was not due to changes in copy number (data not shown). Compared with NSCLC cells, RET mRNA expression in SCLC cells was significantly greater than that observed in adenocarcinoma cells (p < 0.05) but was not significantly different from squamous- or large-cell carcinoma cells.
We initially validated the variable level of RET mRNA expression using gene array data from a recent study of 15 SCLC tumors.7 The results, shown in Figure 5B, demonstrate that RET expression, normalized to β-actin, varies 272-fold among SCLC tumors. This contrasts with the expression of phosphatase and tensin homolog (PTEN), also located on chromosome 10q and expressed at approximately equivalent levels to RET, which varies by only fourfold. Epidermal growth factor receptor (EGFR) expression differed by only 30-fold, further highlighting RET expression variability in SCLC. We then examined RET expression among multiple thoracic cancers by immunohistochemical staining of a tissue microarray (TMA), as shown in Figure 5C. Small-cell lung carcinoma demonstrated the highest percentage of strongly positive cores (80%), although only five such samples were present in the TMA, limiting any broad interpretation of these results. Squamous- and adenocarcinomas, which were represented by a greater number of samples in the TMA (25 and 21, respectively), each demonstrated a majority of strongly positive cores (60% and 50%, respectively). Large cell, carcinoid, and mesothelioma cores demonstrated low to medium positive staining but were represented by few samples. Examples of strong RET positivity are shown in Figure 5D. Taken together, our data indicate a wide variability in RET mRNA expression in both SCLC cells and tumors, although variable RET expression at a protein level in SCLC needs validation in a larger cohort. RET protein expression was variable, however, in NSCLC.
Our study is the first to identify an oncogenic somatic RET M918T mutation in SCLC. RET mutations underlie all forms of MTC, and the RET M918T mutation in particular is present in 95% of all MTC patients with hereditary MEN2B syndrome.8,9 The oncogenic potential of the RET M918T mutation in the setting of SCLC was shown by increased ERK activation, MYC expression, and cell proliferation in two cell lines with stable RET M918T receptor expression (Figs. 3 and 4). Our discovery of a RET mutation in SCLC is not an isolated event, although our finding of an M918T mutation is unique. Remarkably, most RET mutations were located in the tyrosine kinase domain, potentially affecting receptor signaling function (Table 1). When the SCLC RET mutations were compared with those annotated in the MEN2 mutation database hosted by the University of Utah ( http://www.arup.utah.edu/database. Accessed December 2013), which lists 159 RET variants, there were three amino acids mutated in both SCLC and MEN2: residues 791, 904, and 918. The Y791N SCLC mutation is an exact match to one found in the MEN2 database, whereas the S904T SCLC mutation is unique to SCLC. The RET A664D mutation, found by Futami et al.11 in two SCLC tumors, occurs in the extracellular domain (exon 11). RET mutations in exons 10 and 11, encoding the cysteine-rich domain of the receptor, are also frequently observed in thyroid cancers associated with MEN2A syndrome. Although many of the observed SCLC RET mutations listed in Table 1 have yet to be validated, the majority of them are predicted to have functional effects. Furthermore, their occurrence in MEN2 syndromes, along with their abundance in the tyrosine kinase domain, suggests a potential role in some cases of SCLC. Given that RET mutations are important in both thyroid medullary cancer and pheochromocytoma, both neuroendocrine in nature like SCLC,2 it is possible that RET mutations play a significant role in subgroups of neuroendocrine cancers.
Several recent reports have identified KIF5B-RET fusions in NSCLC patients that are considered new driver mutations because they segregate from other typical mutations such as EGFR, RAS, and ALK.14–17RET fusions are rare events, estimated to occur in only 1% to 2% of patients, typically with adenocarcinoma.18 Their discovery was tremendously aided, however, by the large cohorts of patients examined, which included 561, 936, and 1529 patients.15–17 By comparison, the two recent studies on comprehensive SCLC genomics included cohorts of only 406 and 677 patients and not all analyses (mutations, CNV, RNAseq) were completed on all samples. Thus, the role of oncogenic RET mutations in SCLC cannot be judged fairly until a larger number of tumors is studied, including metastatic tumors. It should be noted, however, that no other activating mutation was identified among the 19 oncogenes assayed in the tumor harboring the RET M918T mutation, potentially making RET M918T the responsible “driver” mutation in this tumor. Similarly, the majority of SCLC cell lines and tumors listed in Table 1 harbor only 0 to 1 mutations among these 19 oncogenes, although mutations of unknown significance in other consensus cancer genes were present (see Table 2, Supplemental Digital Content 1, http://links.lww.com/JTO/A675). These data reflect the high mutational burden associated with lung cancer.
Our finding that RET exhibits widely variable expression in SCLC and can increase proliferation of SCLC cell lines stably overexpressing WT RET provides further evidence that RET may play a role in the pathogenesis of this disease. Interestingly, RET expression in lung adenocarcinoma was recently shown to be associated with shorter overall survival, but only in tumors coexpressing ASCL1, a neuroendocrine marker.19 Because ASCL1 is expressed in essentially all SCLC tumors, this suggests that high RET expression in SCLC may have a similar negative effect on survival. Our studies also demonstrate that cells stably overexpressing WT RET are sensitive to growth inhibition by RET-targeted tyrosine kinase inhibitors such as vandetanib, which is Food and Drug Administration–approved for treating thyroid medullary carcinoma,20,21 and ponatinib, which is currently in clinical trials for NSCLC harboring RET fusion proteins. Thus, patients harboring lung carcinomas with elevated RET protein expression may benefit from treatment with RET kinase inhibitors. Although several randomized clinical trials of vandetinib in lung cancer were reported as negative, including SCLC,22–25 it is possible that these results could be improved by patient enrichment for high RET expression. Indeed, one study suggests that the development of a biomarker may improve vandetanib efficacy in NSCLC.26
Our analysis is the first to quantitatively outline the types and frequency of diagnostic specimens obtained from SCLC patients during routine treatment of their disease. The data in Figure 1 clearly show that although the majority of diagnostic specimens obtained from SCLC patients are biopsies (75%), only a very small minority of these biopsies (11% or 2.7%) are surgical resections. This is in stark contrast to the routine treatment of NSCLC, where more than 30% of patients undergo surgical resection. Moreover, all the resections in our SCLC cohort were from limited disease patients. Thus, our data support a view that the lack of progress in therapeutic innovation in SCLC can be traced back to a lack of sufficient tumor tissue required for thorough genomic and proteomic studies. Furthermore, genomic data of surgically resected SCLC primary tumors may not be representative of the disease, particularly when considering recent evidence that tumors evolve during metastasis.27 Thus, it is essential to capture more genomic data on metastatic SCLC tumors to obtain a full view of this disease.
RET plasmids and helpful suggestions were graciously provided by Dr. Lois Mulligan of Queens College, Toronto, Canada. We thank Karen McColl and Yanwen Chen for their assistance during the course of this study.
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