Family with sequence similarity 83, member B is a predictor of poor prognosis and a potential therapeutic target for lung adenocarcinoma expressing wild‑type epidermal growth factor receptor
- Authors:
- Published online on: December 5, 2017 https://doi.org/10.3892/ol.2017.7517
- Pages: 1549-1558
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Copyright: © Yamaura et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 4.0].
Abstract
Introduction
Cancers are among the leading causes of mortality worldwide, with 8.2 million cancer-related deaths in 2014. Among different cancers, lung cancer has the highest mortality rate with 1.59 million deaths; this is more than twice the number of hepatocellular carcinoma deaths, which is the second most fatal form of cancer (1). Lung cancer patients have poor prognosis and at initial hospital visit are often diagnosed at an advanced stage, beyond the possibility of surgical intervention (2).
Cytotoxic chemotherapeutic agents are usually administered for advanced lung cancer therapy and are chosen according to histological subtype. Recently, molecular targeted agents and immune checkpoint inhibitors have been developed and have been in clinical use since the 2000s (3). In non-small cell lung cancer, including adenocarcinoma (ADC), which represents 40% of all lung cancers, several types of driver gene mutation that promote oncogenic transformation and tumor growth by aberrant activation of proliferation signaling pathways have been identified (4). These driver genes are proposed as novel candidates for molecular targeted therapy. Epidermal growth factor receptor (EGFR) activating mutations lead to auto-phosphorylation and promote EGFR/KRAS/MEK/ERK signaling (5). Aberrant anaplastic lymphoma kinase (ALK) protein, produced by an ALK fusion gene, drives MEK/ERK and PI3K/Akt pathways (6). EGFR-tyrosine kinase inhibitor (TKI) and an ALK inhibitor against the above two aberrant signals prevent tumor progression with a high response rate of 56.0–70.0%, while cytotoxic chemotherapy or immune checkpoint inhibition are successful only in 19.0–34.1% of cases (7–11). Thus, these precision medicines based on genetic or molecular features of lung ADC can provide therapy with a high response rate and fewer adverse effects (7–11). However, 29.2–40.0% of lung ADC patients have no targetable genetic features (4,12,13). There is an urgent need to discover novel biomarkers and therapeutic targets, and studies are ongoing to establish targeted therapy for rare driver gene mutations of malignancy (4).
We have identified and reported family with sequence similarity 83, member B (FAM83B) as a novel diagnostic and prognostic marker for lung squamous cell cancer (SqCC) (14). Comprehensive gene expression analysis using cDNA microarray analysis and immunohistochemistry showed lung SqCC expressed higher levels of FAM83B compared with lung ADC or adjacent normal lung tissue, and correlated with patient prognosis (14). FAM83B is also overexpressed in several other types of cancer, such as breast, ovary, bladder, and lung, and is associated with tumor proliferation (15). Additionally, induction of FAM83B in human mammary epithelial cells resulted in neoplastic growth by increasing mitogen-activated protein kinase (MAPK) signaling, while induction in human breast cancer cell lines resulted in TKI resistance (15). Aberrant EGFR signals and downstream signaling play an important role in targeted therapy for lung ADC; therefore, we assumed that FAM83B also correlates with tumor oncogenesis and growth in lung ADC. Here, we show an association between FAM83B expression in lung ADC and demographics and clinicopathological features.
Materials and methods
Ethics statement
This study was conducted with approval of the Ethics Committee of Fukushima Medical University (approval no. 2775). The participants' human rights and welfare were defended in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants.
Case selection
We identified 216 patients who underwent lung resection at Fukushima Medical University between January 2008 and June 2015 and who were pathologically diagnosed as primary lung ADC. FAM83B mRNA levels were determined in matched lung tumor and adjacent normal lung tissue and compared with clinical features and prognosis. The data collected were; age at surgery, sex, smoking history, presence of activating EGFR mutation in the tumor, histological ADC subtype, tumor size, lymph node metastasis, distant metastasis, pleural invasion, lymphovascular invasion, vascular invasion, date of surgery, date of recurrence, last confirmed survival date, and date of death. Disease-free survival (DFS) was defined as the time from surgery to the first recurrence or death. Overall survival (OS) was defined as the time from surgery to death. To ensure a sufficient observation period, prognostic analyses were performed for patients who underwent complete resection up to December 2013, and who were followed up for 5 years. Patients who had an additional advanced malignant history within 5 years before lung resection, died of postoperative complications, or who were followed up for less than 12 months were excluded. In total, 126 patients were analyzed.
Comprehensive gene expression analysis
Matched tumor and adjacent normal lung tissue samples, 7 mm3 in size, were excised from surgical specimens and frozen in liquid nitrogen. Frozen samples were processed for total RNA extraction using ISOGEN (Nippon Gene, Tokyo, Japan). As a control, common reference RNA was prepared by mixing equal amounts of total RNA extracted from 22 human cell lines to reduce cell type-specific expression bias (16). Synthetic 80mer polynucleotide probes representing 14,400 human transcripts (MicroDiagnostic, Tokyo, Japan) were arrayed using a custom arrayer. Labeled cDNA was synthesized from 5 µg of sample RNA using SuperScript II (Thermo Fisher Scientific, Inc., Waltham, MA, USA) and Cyanine 5-dUTP (PerkinElmer, Inc., Waltham, MA, USA), while Cyanine 3-dUTP (PerkinElmer, Inc.)-labeled cDNA was synthesized from 5 µg of human common reference RNA. Hybridization was performed using a Labeling and Hybridization kit (Microdiagnostic). Signals were measured using a GenePix 4000B Scanner (Axon Instruments; Molecular Devices, LLC, Sunnyvale, CA, USA), and then processed into primary expression ratios (ratio of Cyanine-5 intensity of each sample to the Cyanine-3 intensity of human common reference RNA). Each ratio was normalized by multiplication with normalization factors using GenePix Pro 3.0 software (Axon Instruments; Molecular Devices, LLC). The primary expression ratios were converted into log2 fold changes (designated log ratios). An expression ratio of 1 (i.e., log ratio of 0) was assigned to spots that exhibited fluorescence intensities under detection limits, and we included these in the calculation of signal averages. Data were processed using Microsoft Excel software (Microsoft Corporation, Redmond, WA, USA) and the MDI gene expression analysis software package (MicroDiagnostic, Inc., Tokyo, Japan). mRNA expression data related to FAM83B were extracted for this study.
Preparation of cell lines
HLC-1 cells were purchased from Riken Cell Bank (Saitama, Japan). NCI-H2347, NCI-H1975 and MCF-7 cells were purchased from American Type Culture Collection (Manassas, VA, USA). HLC-1 cells were grown in Ham's F12 medium (087–08335; Wako Pure Chemical Industries, Ltd., Osaka, Japan). NCI-H2347 and NCI-H1975 cells were grown in RPMI-1640 medium (R8758; Sigma-Aldrich; Merck KGaA, Darmstadt, Germany), MCF-7 cells were grown in DMEM medium (Wako Pure Chemical Industries, Ltd.). All media contained 10% fetal bovine serum (Nichirei Biosciences, Tokyo, Japan) and 1% penicillin-streptomycin (Sigma-Aldrich; Merck KGaA, Darmstadt, Germany). Cells were cultured at 37°C in a humidified atmosphere of 5% CO2.
siRNA preparation
siRNAs against FAM83B were purchased (Hs_FAM83B_8 and Hs_FAM83B_9 FlexiTube siRNA; Qiagen GmbH,, Hilden, Germany). Sequences of siRNAs were: Hs_FAM83B_8 (siRNA-8): 5′-CAGGAACGAGTTTCAGACTTT-3′, and Hs_FAM83B_9 (siRNA-9): 5′-TCCCGTTATTTGACAACTCAA-3′.
As a negative control, AllStars negative control siRNA (Qiagen GmbH,) was used. As a positive control, AllStars Hs Cell Death siRNA (Qiagen GmbH,) was used.
siRNA transfection efficiency assay
For 96-well siRNA transfections, 0.3 µl of Lipofectamine RNAiMAX (Thermo Fisher Scientific, Inc.) in 10 µl of serum-free Opti-MEM (Thermo Fisher scientific, Inc.) was added to preplated siRNAs in each well and incubated for 5 min at room temperature. MCF7, HLC-1, H2347, or H1975 cells were added at 1.0×104 to each well. After incubation for 72 h, 10 µl of Cell Counting Kit-8 (Dojindo Laboratories, Kumamoto, Japan) was added and absorbance at 450 nm measured 4 h later using a Multiskan GO (Thermo Fisher scientific, Inc.). Each test was replicated three times.
RNA interference and cell proliferation assay
According to a transfection efficiency test, RNA interference experiments (RNAi) were performed using siRNA-9. siRNA-9 (final concentration of 2.5 nM) and 7.5-µl Lipofectamine RNAiMAX were mixed in 100 µl of serum-free Opti-MEM in a microcentrifuge tube, then added within 20 min to cells in 6-well plates. RNAi was performed using 1×105 cells/well for HLC-1, and 5×104 cells/well for H1975 and replicated three times. To determine the silencing effects of siRNA against FAM83B, cell numbers were counted after transfection using Clone select imager (Molecular devices Japan, Tokyo, Japan).
Reverse transcription-quantitative polymerase chain reaction (RT-qPCR)
Total RNA was isolated from cell lines using TRIzol reagent (Thermo Fisher Scientific, Inc.) and a PureLink RNA Mini Kit (Thermo Fisher Scientific, Inc.) according to the manufacturers' instructions. RNA quantity was assessed using a Nanodrop UV-Vis Spectrophotometer (Thermo Fisher Scientific, Inc.), and samples with a 260/280 nm absorbance ratio of 1.8 or larger were adopted as eligible for RT-PCR. Relative mRNA expression was determined by RT-PCR. One-step RT-qPCR using a Taqman RNA-to-CT 1-Step kit (Thermo Fisher Scientific, Inc.) was performed according to the manufacturer's instructions. To detect FAM83B mRNA, Taqman gene expression assays (Hs00289694_m1; Thermo Fisher Scientific, Inc.) were used. As an endogenous control, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, Hs02758991_g1; Thermo Fisher Scientific, Inc.) was used. Forty cycles of amplification were performed for each triplicated sample. The ΔΔCq method was applied for quantitative evaluation (17). Cycle quantification (Cq) values were calculated by Step One Plus software version 2.3 (Thermo Fisher Scientific, Inc.). ΔCq was defined as the difference between FAM83B Cq and GAPDH Cq, and ΔΔCq was defined as the ratio to the endogenous control sample. Signals undetected after 40 cycles were considered to have an expression of zero.
SDS-page
Cell lysates were prepared by homogenization of cells in RIPA lysis buffer (SC-24948; Santa Cruz Biotechnology, Inc., Dallas, TX, USA), using a Polytron homogenizer (Sonifier SFX250; Emerson Electric Co., St. Louis, MO, USA) at 4°C. After centrifugation at 10,000 × g for five min at 4°C, supernatants were mixed with an equal volume of Sample buffer (2X Laemmli Sample Buffer; Bio-Rad Laboratories, Inc., Hercules, CA, USA). 2-mercaptoethanol (Bio-Rad; 200:1) was then added and samples heated for three min at 100°C. Five micrograms of each sample were then loaded on a polyacrylamide gel (Supersep ace 5–20%; Wako Pure Chemical Industries, Ltd.) and electrophoresis was performed to separate proteins (18).
Western blotting
Proteins were transferred to a polyvinylidene difluoride membrane (Immobilon; Merck KGaA) in Towbin transfer buffer (25 mM Tris base, 192 mM glycine, 0.1% SDS, 20% methanol) (19). The membranes were then blocked with 5% skimmed milk in PBS (0.137 M NaCl, 2.6 mM KCl, 1.8 mM KH2PO4, 8.1 mM Na2HPO4/12H2O) and incubated overnight in primary antibody solution at 4°C. Anti-FAM83B antibodies (1:1,000; PA5-28548; ThermoFisher scientific, or 1:2,000; HPA031464; Atlas Antibodies AB, Stockholm, Sweden) or an anti-GAPDH antibody (1:2,500; no. 2118; Cell Signaling Technology, Inc., Danvers, MA, USA) were used as primary antibodies. Membranes were then incubated with secondary antibody (anti-rabbit IgG, Horseradish Peroxidase-Linked species-specific whole antibody (1:20,000; GE Healthcare UK Ltd., Amersham, UK). The chemiluminescent signals were captured with the ImageQuant LAS 4000 system (GE Healthcare UK Ltd.) using ECL select Western Blotting Detection Reagent (GE Healthcare UK Ltd.) according to the manufacturer's instructions.
Statistical analysis
Statistical analyses were performed using SPSS 21.0 (IBM Corp., Armonk, NY, USA). The patient cohort was divided into two subgroups according to high or low FAM83B expression with the log ratio of zero as the boundary. Patients were divided into two groups according to median age. Tumor (T), Nodes (N), and Metastasis (M) (TNM) factors of lung cancer were classified according to the Union for International Cancer Control 7th edition (20). T factor was not adopted but tumor size and pleural invasion were. Continuous variables were compared by two-tailed t-tests or one-way ANOVA, and categorical variables were compared by the Chi-square test or Fisher's exact test, as appropriate. Multivariate analyses using a binary logistic regression model were performed to evaluate independent predictors of FAM83B expression. DFS and OS were estimated using the Kaplan-Meier method, and survival curves were compared using log-rank tests. Variables that were suitable for a Cox proportional hazards univariate model with significance were analyzed by a multivariate model to adjust for potential confounders. P<0.05 was considered to indicate a statistically significant difference.
Results
FAM83B is highly expressed in ADC with wild type-EGFR
This study included 119 male and 97 female patients, with a mean age of 68.5 years (range 26–87 years). Up to 111 (51.4%) were current or former smokers, and 118 (54.6%) had wild-type EGFR ADC. FAM83B tended to be expressed at higher levels in solid subtypes while lower FAM83B expression was observed in lepidic pattern tumors that were less aggressive. Mean tumor size was 2.9 cm (range 0.8–14.0). The clinicopathological characteristics of patients according to FAM83B expression in tumor tissue are summarized in Table I. Univariate analysis showed that higher FAM83B expression correlates with males (P=0.007), smoking history (P=0.007), and wild-type EGFR tumors (P<0.001). Multivariate analysis showed wild-type EGFR tumors correlate with FAM83B expression (P<0.001) (Table II).
Table I.Clinicopathological and genetic features of lung adenocarcinoma patients according to fam83b expression in tumor tissue. |
Table II.Associations between clinicopathological characteristics of lung adenocarcinoma patients and FAM83B expression in tumors. |
Correlation between FAM83B expression obtained from cDNA microarray analysis and EGFR mutation in lung ADC
The mean FAM83B expression in adjacent normal lung tissue (n=98), wild-type EGFR tumors (n=118) and mutant EGFR tumors (n=98) was −0.190, standard deviation (SD) of 0.365, 0.877, SD of 0.689, and −0.231, SD of 0.425, respectively. Multiple comparison of these three groups showed that FAM83B expression in wild-type EGFR tumors was higher than in adjacent normal lung tissue (P<0.001) or mutant EGFR tumors (P<0.001), while there was no significant difference between mutant EGFR tumors and adjacent normal lung tissue (P=0.852) (Fig. 1).
FAM83B is a predictor of poor lung ADC prognosis, especially for ADC with wild-type EGFR
The FAM83B high expression group showed significantly shorter survival times both in DFS (P=0.011) and OS (P=0.001). Subgroup analysis showed that the FAM83B high expression group had shorter DFS and OS with wild-type EGFR tumors (P=0.017, P=0.008, Fig. 2), while no significant difference was found in patients with mutant EGFR tumors (P=0.746, P=0.588). Survival analysis using a Cox regression hazard model was then conducted. For DFS, univariate analysis showed that high levels of FAM83B expression, male sex, lymph node metastasis, pleural invasion, lymphovascular invasion, and vascular invasion were involved in poor prognosis. Multivariate analysis identified high levels of FAM83B expression and lymph node metastasis as independent poor prognostic factors (Table III). In OS, univariate analysis showed high levels of FAM83B expression, male sex, wild-type EGFR tumors, lymph node metastasis, pleural invasion, lymphovascular invasion, and vascular invasion as poor prognostic factors. Multivariable analysis showed high levels of FAM83B expression, pleural invasion, and vascular invasion were independent predictors of poor prognosis (Table III).
Involvement of FAM83B in cell proliferation in several types of lung cancer cell line
Cell lines derived from lung ADC, including HLC-1, H2347 (both wild-type for EGFR) and H1975 (mutant EGFR), and a positive control breast cancer cell line, MCF7 (15) were prepared. RT-qPCR showed high levels of FAM83B expression in HLC-1 and H2347 cells but scarcely detectable levels in H1975 cells (Fig. 3A). Immunoblot analysis showed levels of FAM83B that were consistent with the HLC-1, MCF7, and H1975 RT-qPCR results (Fig. 3B). In MCF7 cells, FAM83B knockdown with siRNA-8 or siRNA-9 caused inhibition of cell proliferation (siRNA-8; P=0.393, siRNA-9; P=0.061 at 6 days after knockdown), with siRNA-9 having the stronger anti-proliferative effect (Fig. 4E-G); therefore, we performed subsequent knockdown experiments using siRNA-9. siRNA transfection efficacy assays (Fig. 4A-D) indicated FAM83B RNAi should be performed in HLC-1 and H1975 cells. Depletion of FAM83B expression and suppression of cell proliferation were confirmed in HLC-1 and even in H1975 cells, which expressed low levels of FAM83B (Fig. 3C-H).
Discussion
In this study, we focused on comprehensive gene expression analysis of tumors from resected lungs of Japanese ADC patients, and we showed that FAM83B expression was higher in tumors with wild-type EGFR compared with tumors with mutant EGFR, and that FAM83B expression was associated with proliferation in cell lines. Furthermore, FAM83B expression was identified as a biomarker of poor prognosis from patient clinical outcomes.
FAM83B was first reported by Cipriano and colleagues (15) to be correlated with anchorage-independent growth in breast cancer cell lines using a validation-based insertion mutagenesis method. FAM83B is a member of the FAM83 family, which includes eight members (FAM83A to H) characterized by a domain of unknown function 1669 (DUF1669), which contains an N terminal phospholipase D-like motif. DUF1669 is considered to be involved in tumor proliferation and oncogenesis (15). FAM83B expression is elevated relative to normal associated tissues in several types of cancer, such as breast, ovary, cervical, testis, thyroid, bladder, lymphoid and lung (15). In lung cancer, analysis of FAM83B expression confirmed that FAM83B expression was significantly elevated in tumor specimens relative to normal tissues (15). It was also reported that FAM83B mRNA levels were significantly higher in SqCC than in normal lung or ADC (14). It is a novel finding that FAM83B is more highly expressed in lung ADCs containing wild-type EGFR compared with ADCs carrying mutant EGFR. Interestingly, in breast cancer, FAM83B is expressed at higher levels in tumors without estrogen and progesterone receptors or human EGFR-2, compared with receptor-positive tumors (21). Furthermore, FAM83H, the paralog of FAM83B, is overexpressed in androgen independent-prostate cancer (22). These findings could indicate that FAM83B has an oncogenic role without aberrant signals from driver gene mutations or overexpressed hormone receptors. The function of FAM83B remains unclear; however, a bifunctional interaction mechanism with responses to EGF was proposed. EGF signals to multiple growth and survival pathways, including the RAS/RAF/MEK/ERK and the PI3K/AKT pathways. FAM83B may interfere with the binding of 14-3-3 protein to CRAF, thereby promoting membrane localization of CRAF, and promoting downstream signals to MAPK (15,23,24). Furthermore, FAM83B may also bind to p85 and p110 subunits of PI3K to promote PI3K/AKT signaling (25), which promotes oncogenic transformation through phospholipase D activation (26), and shows resistance against EGFR-TKI (15,24,27). Our knockdown study of FAM83B showed that its expression was associated with tumor proliferation in cell lines expressing high levels of FAM83B; however, H1975 cells showed that knockdown of low levels of FAM83B also inhibited proliferation. Of all the FAM83 members, only FAM83H knockout mice, which live for only 2 weeks, have been reported, and FAM83H is proposed to play a role in the maintenance of cell homeostasis (22,28). Other FAM83 family members, including FAM83B, may also be required at certain levels, even in normal cells.
FAM83 family members are usually associated with poor cancer prognosis (21). Our study of lung ADC also showed that FAM83B correlates with poor prognosis; however, our previous study reported high FAM83B expression to be a biomarker for good DFS prognosis in lung SqCC (14). Snijders et al conducted a meta-analysis of several databases (29–31) and suggested that lung ADC expresses relatively high levels of FAM83A, D, E, F, and H, but FAM83A, B, D, and F correlate with prognosis. In lung SqCC, all FAM83 members except FAM83E are highly expressed, but only FAM83A correlates with poor prognosis (21). These findings indicate FAM83B has separate roles among cancers or tumor subtypes.
FAM83 family members, including FAM83B, are more highly expressed in lung cancer than in normal lung tissue, and their expression is reflected in the T factor of TNM classification (20,29,32). Our study did not show a correlation between tumor size and FAM83B expression. This contradiction was caused by the fact that the T factor includes not only tumor size but pleural invasion. Both tumor size and pleural invasion had no significant effect on FAM83B expression.
FAM83B RNAi suppressed proliferation of human lung cancer cell lines. This result indicates that FAM83B could be a potential therapeutic target against EGFR-WT malignancies, which account for 47–88.7% of lung ADC (4,29) and which are rarely indicated for molecular targeted therapies. Limitations of this study include lack of evaluation of advanced or recurrent cancer cohorts because the patient cohort was derived from operable lung ADC cases biased to early stages. Moreover, this study did not examine other driver mutations of lung ADC, such as KRAS, ALK fusions. Subdivision based on other genomic or molecular features could further explain the function of FAM83B in lung ADC. Further investigation is required.
Acknowledgements
This study was partially supported by a grant for translational research programs of Fukushima Prefecture. H. Suzuki received research support from Bristol Myers Squibb, AstraZeneca, and Tsumura, outside the submitted study. T. Yamaura received research support from AstraZeneca, outside the submitted study. S. Muto had been employed by AstraZeneca, outside the submitted study. Y. Yanagisawa had been employed by Nippon Gene Co., Ltd., outside the submitted study. R. Honma is employed by Nippon Gene Co., Ltd., outside the submitted study. The authors thank H I, M Otsuki, E Otomo, and Y Kikuta for their technical supports.
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