BRG1/SMARCA4 Inactivation Promotes Non–Small Cell Lung Cancer Aggressiveness by Altering Chromatin Organization

Studies of the molecular mechanisms of non–small cell lung cancer (NSCLC) development have identified alterations in oncogene expression and inactivation of tumor suppressor genes, including ALK, KRAS, EGFR, RB, p16^INK4A, and p53 (1, 2). Recently, loss of BRG1 expression through mutations or other mechanisms has been observed in 10% of NSCLCs (3–7). The BRG1 gene, also known as SMARCA4, encodes one of the two mutually exclusive ATPase subunits of the SWI/SNF chromatin remodeling complex. The SWI/SNF complex, first discovered in saccharomyces cerevisiae, acts as a positive regulator of the HO endonuclease and Suc2 genes (8–10). The complexes contain approximately 10 to 12 components that show strong conservation of protein structure and function from yeast to Drosophila to mammals (11, 12). Mutations in members of the complex have been found in human cancers, including NSCLC, malignant rhabdoid tumors, ovarian carcinomas, and renal cell carcinomas, suggesting that loss of chromatin maintenance through active nucleosome positioning is associated with cancer development (3–7, 13, 14). How BRG1 inactivation contributes to the development of NSCLC remains unresolved.

In a previous study, we demonstrated that induction of BRG1 in BRG1-deficient tumor cell lines leads to reexpression of genes epigenetically silenced during NSCLC development (15, 16). Intriguingly, the genes reactivated after BRG1 reexpression did not seem to undergo changes in promoter methylation (15). These results suggested that BRG1 loss may provide an alternative mechanism for silencing of genes detrimental to the initiation and/or progression of NSCLC. In this current study, we examined the biologic, transcriptional, and chromatin effects of knockdown of BRG1 in NSCLC cell lines. We observed a significant increase in tumorigenic potential upon loss of BRG1 expression in NSCLC cells. We also identified a set of genes with reduced expression upon inactivation of BRG1 by RNAi. We further showed that several of these genes, previously implicated in the etiology of NSCLC, display reduced expression in BRG1-deficient primary NSCLC samples. Finally, we showed that BRG1 loss results in widespread changes in chromatin organization at regions including transcriptional start sites of these target genes. These results suggest that BRG1 mutations/deletions found in primary NSCLCs can provide an alternative mechanism to alter the expression of cancer-associated genes.

The H358, H441, SK-MES, H2170, H727, SW900, H2228, H520 and H1395, H1703, H522, A427, H23, H1299, and A549 human NSCLC carcinoma cell lines were used in this study. All cell lines were obtained from the ATCC and always used from frozen stocks within 3 months of acquisition. All cell lines were cultured at 37°C/5%CO2 in RPMI-1640 supplemented with 10% FBS (Gibco; standard growth medium). H358 and H441 cell lines containing stable BRG1 knockdowns, Brg1i.1, Brg1i.2, and Brg1i.3, were maintained in standard growth medium supplemented with 1 μg/mL puromycin or 0.4 mg/mL neomycin.

We used two methods to establish stable knockdown cell lines, lentiviral infection (H358 Brg1i.2 and Brg1i.3) and DNA transfection (H358 Brg1i.1). Lentivirus targeting BRG1 with shRNA was purified from 293FT cells (17). 293FT cells were transfected with one of the MISSION shRNA lentiviral transduction particles [TRCN0000015548 (Brg1i.3) or TRCN0000015549 (Brg1i.2)] using Lipofectamine 2000 (Invitrogen) to generate infectious viral particles. The H358 cell line was then infected in the presence of polybrene for 30 minutes. Twenty-four hours after infection, cells were selected with puromycin at 1 μg/mL. Stably infected clones were harvested, expanded, and screened for BRG1 expression by Western blotting. Clones with the most complete BRG1 silencing were combined to generate pooled cell lines for each respective BRG1 knockdown. Similarly treated control cell lines were also generated (Supplementary Fig. S1A).

The H358 Brg1i.1 and the H358 control cell line, designated Control, were generated using PHTP RNAi expression vectors that target BRG1, or the PHTP empty vector, respectively (18, 19). The H358 cell line was transfected with each vector using FuGene (Roche). After 24 hours, stable clones were selected in puromycin at 1 μg/mL. Over 30 Brg1i.1 and 20 Control puromycin-resistant clones were expanded and isolated for further characterization. Clones were screened for reduced BRG1 expression by Western blotting.

To generate stable knockdown H441 cell lines, we infected cells with either pLKO.1, a nontargeting shRNA control vector (SHC002; Sigma), or the MISSION BRG1 shRNA lentiviral transduction particle (TRCN0000015549) and selected with 1 mg/mL puromycin, as described above for the H358 cells. We designated the BRG1 knockdown cell lines as H441 Brg1i.2 (TRCN0000015549) and the control nontargeting shRNA cell line as H441 Control.

Cells (5 × 10⁷) for each cell line were harvested by trypsinization, rinsed with PBS, and resuspended one-to-one in ice-cold Matrigel (BD Biosciences). Six-week-old Nu/Nu female mice were inoculated into the left lung with 40 μL (5 × 10⁶ cells/lung) of cell/Matrigel suspension. Mice were monitored daily for signs of distress and were sacrificed when they exhibited weight loss or difficulty in breathing.

Western blotting was performed as previously described (20). Protein expression was analyzed with the following antibodies: anti-BRG1 G7 (sc-17796; Santa Cruz Biotechnology) and anti–β-actin (A2066; Sigma). Secondary mouse IgG and rabbit IgG antibodies (GE Healthcare) were detected with enhanced chemiluminescence (GE Healthcare).

RNA expression was examined by the qRT-PCR analysis as previously described (20). All genes were normalized to β-actin and quantified using the 2^−ΔΔCt statistical method (21). The TaqMan primer and probes sets obtained from Applied Biosystems included BRG1 (Hs00946396_m1), SEM3B (Hs00190328_m1), EHF (Hs00171917_m1), DUSP6 (Hs04329643_s1), IL8 (Hs99999034_m1), SYK (Hs00895377_ m1), IFI16 (Hs00194261_m1), BATF (Hs00232390_m1), and β-ACTIN (Hs00357333_g1).

Total RNA was extracted from H358 (parental), H358 Control (empty vector), and H358 Brg1i.2 and H358 Brg1i.1 (BRG1 shRNA knockdown) cell lines and submitted to the UNC Lineberger Genomics Core for Agilent microarray analysis. RNA was labeled with Cy5 (experimental H358 Control, H358 Brg1i.1, and H358 Brg1i.2) and Cy3 (control H358) and hybridized to 4 × 44 whole human genome microarrays (Agilent Technologies). The normexp background correction and loess normalization procedures were applied to the probe-level data (22). Expression measurements for each gene were calculated by computing the mean of the normalized intensity values for all probes mapping to that gene, as specified in a gene annotation database. This produced expression values for 19,749 genes. These data are available at GEO (http://www.ncbi.nlm.nih.gov/geo/), under accession number GSE58542.

The SAMR package was used to detect differentially expressed genes by comparing the expression values in each of the two BRG1-deficient cell lines with the expression values in the Control cell line (23). Gene expression values were first standardized within each array. Differential expression was then assessed by finding the smallest value of the tuning parameter delta that produced a median FDR smaller than 0.001. A total of 1,000 permutations were used in each analysis.

Nine NSCLC cell lines with wild-type BRG1 (wtBRG1) expression (H358, SK-MES, H2170, H441, H727, SW900, H2228, H520, and H1395) and 6 cell lines with BRG1 nonsense/truncating mutations (mtBRG1; H1703, H522, A427, H23, H1299, and A549) were grown in standard growth medium. Isolated RNA samples were prepared and libraries created using TruSeq RNA Sample Preparation Kit v2 (Illumina), which included a poly A selection step. Libraries were pooled at 2 nmol/L concentration, and the samples were then subjected to cBot cluster generation using the TruSeq Rapid PE Cluster Kit (Illumina). The amplified libraries were sequenced using the TruSeq Rapid SBS Kit on the HiSeq 2500 (Illumina). mRNA-seq data were aligned with Mapsplice (24) and genes were quantified with RSEM (25). Gene expression estimates were upper quartile normalized (26). For comparison of target gene expression in wtBRG1 versus mtBRG1, gene expression measurements were computed by replacing all RSEM values identically equal to zero with the smallest nonzero RSEM value and then applying a log₂ transformation. The SAMR package was used to detect genes that were differentially expressed when the BRG1-mutant cell lines were compared with the BRG1 wild-type cell lines (23). Using an FDR threshold of 0.025, a total of 135 genes were downregulated in the BRG1-mutant cell lines (Supplementary Table S2).

To identify an expression matched but unregulated gene set for comparison for each cell line, the mean expression of all 275 downregulated genes was calculated. We then used ranked values of the Pearson correlation coefficient to identify a set of 300 genes that had expression patterns most similar to mean expression values across all cell lines. This set of 300 genes was chosen from among those genes that did not belong to the set of 591 differentially expressed genes. Using a similar procedure, for each of the 275 downregulated genes, we identified a set of 100 nondifferentially expressed genes that had expression patterns most similar to each downregulated gene of interest across all cell lines. This produced a list of 1,484 unique genes that contained all of the 300 genes described above. For sampling purposes, RefSeq genes were selected from this group.

To determine whether reduced BRG1 protein levels correlated with lower mRNA expression in NSCLC, we obtained RNA-seq–based gene expression data from The Cancer Genome Atlas (TCGA) lung adenocarcinoma project. RNA-seq data were analyzed by first replacing all RSEM values identically equal to zero with the smallest nonzero RSEM value, and then a log₂ transformation was applied (25). Samples with BRG1 mutations were identified, and the expression values from samples with nonsense or frame shift mutations were used to identify samples that have reduced BRG1 expression. The threshold for reduced BRG1 expression was defined to be the highest BRG1 expression value observed in any of the samples with BRG1 nonsense or frameshift mutations. The one-sided Wilcoxon rank sum test was applied to assess the statistical significance of differences in the expression values for specific BRG1 target genes, where the null hypothesis corresponds to no difference in expression and the alternative hypothesis is that expression is lower in samples that have reduced BRG1 expression, as defined above.

We initially determined the optimal conditions of MNase digestion to generate a distribution of approximately 35% mononucleosomes for the parental H358 cell line. We then confirmed a similar distribution of nucleosomes after MNase digestion of chromatin for each cell line to preferentially analyze nucleosomes with similar sensitivity to MNase and avoid overdigestion (27). H358 Control, Brg1i.2, and Brg1i.1 pooled cell lines were harvested at 60% to 80% confluence. Cells were then removed by treatment with trypsin-ethylenediaminetetraacetic acid (EDTA) and resuspended in 1 mL reticulocyte-specific buffer [10 mmol/L Tris-HCl (pH 7.4), 10 mmol/L NaCl, 3 mmol/L MgCl₂] and placed on ice for 10 minutes, followed by addition of 0.1 mL 10% NP-40 detergent for 30 minutes. After two washes with reticulocyte-specific buffer, nuclei were stored at −80°C. For MNase digestion, extracts were resuspended in 0.2 mL 1× MNase reaction buffer [10 mmol/L Tris-HCl (pH 7.5), 5 mmol/L MgCl₂, 5 mmol/L CaCl₂, 0.1 mmol/L phenylmethylsulfonylfluoride, 0.5 mmol/L dithiothreitol), aliquoted into 0.5 mL samples with an OD₂₆₀ of 0.2 and treated with 10 U of MNase (Affymetrix) for 10 minutes. MNase was inactivated with the addition of 10 mmol/L EDTA and ethylene glycol-bis(2-aminoethylether)-N,N,N′,N′-tetraacetic acid (EGTA). All samples were then treated with RNase A and Proteinase K followed by DNA isolation by phenol–chloroform extraction and ethanol precipitation. DNA was resuspended in 10 μL 0.1×TE and run on a 2% agarose gel to separate nucleosomes. The mononucleosome band was cut from the gel and purified with the Qiagen Gel Extraction Kit (Qiagen). The manufacturer's protocol was followed with the exception that six volumes of QG (Qiagen, catalog no. 19063) were used to dissolve the gel, two gel volumes of isopropanol were used, and DNA was eluted with 30 μL elution buffer.

Libraries were created following the manufacturer's specifications (Illumina). Library preparation included blunt ending of DNA, addition of a polyA-overhang, adapter ligation (Illumina), two times SPRI beads clean up, PCR amplification with PfuUltra II Fusion HS DNA Polymerase (Stratagene), and size selection from a 2% agarose gel. After library generation, paired-end sequencing was performed (Illumina HiSeq2000; UNC Chapel Hill High Throughput Sequencing Facility).

Paired-end reads were aligned to the reference human genome (hg19) using Bowtie v1.0.0 (28), and samtools v0.1.19 (29) was used for necessary file conversions. DANPOS (30) was used to predict size and positions of nucleosomes. DANPOS default parameters were used with the exceptions of 50 base pair smoothing, single base pair resolution, and a minimum nucleosome size of 146 base pairs. DANPOS was also used to predict nucleosomes and calculate positional conservation scores. BEDTools v2.17.0 (31) and R v2.15.1 were used to extract genomic regions and for subsequent analyses using default parameters. Local trends in MNase signal were removed using the kernel smoothing function in R with a bandwidth of 250 bp. Heatmaps were generated using MATLAB v2012b. UCSC genome browser (32) was used to visualize gene and signal tracks. Transcriptional starts sites (TSS) used were defined by RefSeq, whereas CCCTC-Binding Factor (Zinc Finger Protein) (CTCF) sites were predicted by MotifMap (33).

To determine the effects of BRG1 loss on NSCLC development, we generated BRG1 knockdown clonal cell lines derived from the human NSCLC H358 cell line (hereafter referred to as “NSCLC cells”) that expresses a wild-type BRG1 protein (5). We used two different shRNAs (Brg1i.1 and Brg1i.2) to control for possible off-target effects. In general, the Brg1i.2 shRNA proved more efficient at reducing BRG1 mRNA and protein levels than the Brg1i.1 shRNA. Therefore, to control for clonal variation, we generated pools of at least four clonally derived cell lines from each BRG1 shRNA or the vector control, referred to as “Control” (Supplementary Fig. S1). Cells with reduced BRG1 expression exhibited a consistent change in cellular morphology from a tightly packed and cuboidal appearance to an elongated morphology with distinct cellular borders (Fig. 1A).

We next examined whether BRG1 loss altered the tumorigenic potential of NSCLC cells in vivo. Parental, Control, and Brg1i.1 cell lines were orthotopically inoculated into the lungs of athymic nude mice. Reduced expression of BRG1 led to decreased survival (mean survival = 37.5 days) compared with either the parental cell line (mean survival = 110 days, P < 0.05) or the control (mean survival = 100 days, P < 0.018; Fig. 1B). The reduced survival correlated with the appearance of larger tumors within the lung and mediastinum in mice with the Brg1i.1 cells compared with small tumors limited to the lungs of the animals with Control cells (Fig. 1C). Therefore, knockdown of BRG1 expression resulted in dramatic changes in the tumorigenic potential of NSCLC cells.

We next asked how BRG1 loss might lead to the observed in vitro and in vivo changes. Because of the SWI/SNF complex's role in regulating gene transcription, we determined the effects of reduced BRG1 protein levels on gene expression. We identified genes that were differentially expressed between either the Brg1i.1 or Brg1i.2 cell lines relative to parental cells (median FDR < 0.001; Supplementary Table S1—genes altered by BRG1 KD). Consistent with more efficient BRG1 silencing, a greater number of genes demonstrated differential expression in the Brg1i.2 cells when compared with the parental cells (2,050 downregulated and 2,251 upregulated) than the H358 Brg1i.1 cells (363 downregulated and 454 upregulated).

We identified 591 genes that were differentially expressed in both BRG1 knockdown cell lines—275 downregulated genes (Table 1) and 316 upregulated genes (Supplementary Table S1—consensus genes). Hierarchical clustering showed highly concordant gene expression patterns among the replicates as well as consistent alterations in gene expression between the each of the two BRG1 knockdown cell lines relative to control cells (Fig. 2). Our previous study had correlated BRG1 loss with reduced expression of genes frequently downregulated during NSCLC development (15), therefore we focused on downregulated genes after BRG1 knockdown in this current study.

We examined the 275 genes that showed decreased expression in both BRG1 knockdown cell lines for candidates previously associated with cancer development (Table 1). These putative targets included many genes in signaling pathways associated with tumor development, including inflammation (IL1B, IL23A, IFI16, and FAS), cell invasion (ICAM1, ICAM2, and MMP7) and cell proliferation (AREG, BATF, and SYK). We additionally identified three genes with reduced expression that had been previously associated with the development of lung and other cancers: DUSP6, EHF, and SEMA3B. DUSP6 (MKP3) is a dual-specificity phosphatase that regulates MAPK signaling through inactivation of ERK2 (34, 35), and recent studies have demonstrated decreased DUSP6 expression in adenocarcinomas of the lung (36, 37). EHF (ESE-3) is a member of the ETS transcription factor family that has been implicated as a tumor suppressor for prostate cancer as well as a regulator of inflammation in airway epithelium (38, 39). SEMA3B codes for a secreted member of the semaphorin/collapsin family (40). The protein plays a critical role in the guidance of growth cones during neuronal development and has been implicated as a tumor-suppressor gene for NSCLC (40–42).

We next validated the gene expression differences of six representative genes by qPCR in the BRG1-deficient cell lines as well as a third BRG1-silenced cell line (Brg1i.3; Fig. 3). Reduced levels of mRNA for these genes generally correlated with the degree of BRG1 loss (Fig. 3). We then determined if BRG1 knockdown in a second NSCLC cell line would cause similar changes. We generated a BRG1-deficient H441 cell line using the Brg1i.2 shRNA as well as a nontargeting shRNA Control cell line (Supplementary Fig. S1B). Similar to the H358 Brg1i cell lines, the H441 Brg1i.2 cells show a consistent change in cellular morphology (Supplementary Fig. S1C). A gene expression analysis of our six putative target genes showed reduced expression of three genes with no change or increased expression of the remaining genes (Supplementary Fig. S3). To further validate the remaining target genes, we compared RNA-seq expression data from nine NSCLC cell lines with wild-type BRG1 genes with six cell lines with documented BRG1 truncating/nonsense mutations (5). Using an FDR of 0.025, we confirmed that lower EHF, IFI16, and SYK expression correlated with BRG1 loss (Supplementary Table S2). Therefore, we identified three candidate genes whose expression decreases in the presence of reduced BRG1 expression.

We then asked whether these putative target genes demonstrate similar expression changes in primary human tumors based on BRG1 status. Using the recently released TCGA data for human adenocarcinomas of the lung, we assessed whether BRG1 gene expression correlated with BRG1 mutational status. BRG1 nonsense and frameshift mutations that should lead to truncated or absent protein showed reduced expression of BRG1 mRNA (Fig. 4A). In contrast, tumors with missense mutations in BRG1 did not exhibit an obvious change in mRNA expression compared with wild-type BRG1 tumors (Fig. 4A). On the basis of these observations, we divided the dataset into tumors with either high or low BRG1 expression. We then asked whether expression of our BRG1 target genes correlated with BRG1 expression. EHF, IFI16, and SYK showed a statistically significant association with BRG1 expression (P ≤ 0.01, one-sided Wilcoxon rank sum test, Fig. 4B–D). In contrast, we did not observe a statistically significant association for ACTB expression (P = 0.121, Fig. 4E). Therefore, for these putative downstream targets, expression changes resulting from BRG1 loss in cell lines were similar to those seen in primary tumors.

Given the role of SWI/SNF in active chromatin remodeling, we examined nucleosomal differences associated with BRG1 loss. By virtue of its ability to cleave internucleosomal linker DNA, MNase analyzed by high-throughput sequencing (MNase-seq) offers the ability to compare multiple features of nucleosomes. MNase-seq data from control cells and the two BRG1-silenced cell lines were processed to generate normalized signal tracks (DANPOS; ref. 30). Local peaks in MNase signal indicate the presence of nucleosomes and their position, whereas the signal magnitude indicates relative occupancy. Occupancy in this context refers to the fraction of chromatin that is nucleosomal at a specific position among the population of cells being assayed.

We first examined averaged signal around all TSSs. We observed a decrease in overall signal in the −1- to +1-kb region surrounding the TSS (Fig. 5A). This difference was associated with the degree of BRG1 knockdown and indicates that, in aggregate, fewer nucleosomes occupy these regions of chromatin. In all samples, we observed three well-positioned nucleosomes preceding and five nucleosomes following the TSS (designated as −3 to +5). BRG1 knockdown did not alter the position of nucleosomes around the TSS; rather it resulted in signal attenuation that correlated with BRG1 expression levels. An even broader region of well-defined nucleosomes was also observed around CTCF sites (Supplementary Fig. S2A). In contrast to the TSS, relative peak signal attenuation was not observed between samples, although overall signal was diminished, similar to the TSS. We then examined signal further from the TSS and noted that aggregate signal was greater within the gene body compared with upstream regions (Fig. 5B). This polarity was lost when BRG1 was knocked down (Fig. 5B). To correlate BRG1 chromatin interaction with variation in MNase signal after BRG1 knockdown, we overlaid differential MNase signal with publicly available BRG1 ChIP-seq signal around the TSS (43). BRG1 ChIP signal is greatest at the region of maximal MNase signal change (Supplementary Fig. S2B). Together, these data suggest that BRG1 plays an influential role in maintenance of nucleosomes at the TSS.

Individual nucleosomes were then computationally predicted and assigned occupancy and positional ambiguity scores. These scores were then compared between the control and BRG1 knockdown cells. Occupancy scores for individual nucleosomes were diminished genome-wide when BRG1 was knocked down (Fig. 5C; Supplementary Fig. S2C). Variation in occupancy was also observed at TSS-proximal (± 3 kb) nucleosomes. As anticipated, nucleosomes near the TSS demonstrated higher occupancy scores compared with nucleosomes genome-wide. However, BRG1 silencing resulted in TSS-proximal nucleosomes with occupancy lower than nucleosomes genome-wide. These data indicate that nucleosomes with the highest occupancy scores demonstrate the greatest change in the absence of BRG1 with the TSS-proximal nucleosomes being most affected. We also scored nucleosomes based on predicted positional ambiguity. Ambiguity score measures signal characteristics indicative of variable positioning among the cell population. A higher score indicates increased ambiguity. The loss of BRG1 was associated with increased positional ambiguity overall (Fig. 5D and Supplementary Fig. S2B). However, in contrast to occupancy, TSS-proximal nucleosomes demonstrated less change in positional ambiguity when compared with nucleosomes genome-wide. These data suggest that relative to nucleosomes genome-wide, BRG1 plays a greater role in maintaining occupancy at the TSS but relatively less of a role in maintaining the positioning of these nucleosomes. This is consistent with the role of factors such as RNA polymerase in the maintenance of nucleosome positioning around the TSS (44).

We then examined MNase signal around the TSS of those genes differentially expressed after BRG1 knockdown. We also compared signals around the TSS for a set of genes that were expression-level matched to the downregulated genes but without altered expression after BRG1 knockdown (designated as unregulated genes; Supplementary Table S1). Because, as a group, RNA levels were higher for the downregulated gene set, expression-level matching was performed to control for the effect of gene expression on MNase signal. We observed decreased signal around TSS in BRG1-silenced cells (Fig. 6A, top and Supplementary Fig. S3). This difference was most clearly observed downstream of the TSS. To better characterize differences between samples, MNase signal was denoised to remove the effect of general signal depletion around the TSS (Fig. 6A, bottom and Supplementary Fig. S4). Signal peaks corresponding to nucleosomes were diminished, most notably around the downregulated genes, affecting the −2 to +2 nucleosomes. In the absence of BRG1, signal at the nucleosome depleted region (NDR) was increased. This effect was also evident, albeit to a lesser degree, when all genes were examined (Supplementary Fig. S4A). This effect was observed when we similarly analyzed a previously published dataset from BRG1 knockout murine embryonic fibroblasts (Supplementary Fig. S4B; ref. 45). Signal at the TSS of a subset of downregulated genes exemplifies this effect and suggests a correlation with the level of BRG1 expression (Fig. 6B and Supplementary Fig. S5).

To further explore this effect, we calculated the ratio of differences in MNase signal between the −1 nucleosome and the NDR for Control and Brg1i.2 samples at each gene in the downregulated and unregulated gene sets. This analysis was performed in the absence of kernel smoothing to eliminate potential effects associated with this correction technique. Loss of BRG1 resulted in a greater MNase signal change for the downregulated genes compared with the unregulated genes. The predominant difference for the downregulated genes (compared with the matched unregulated genes) reflected a decreased signal variation between the −1 nucleosome position and NDR (P < 0.01 based on permutation of a 1,300-gene class of matched unregulated genes; Fig. 6C). Together, these data support that loss of BRG1 is associated with increased relative nucleosome occupancy at the NDR, suggesting that BRG1 may cooperate with RNA Pol II in the eviction and maintenance of nucleosomes around the TSS.

Five to 20% of NSCLCs contain reduced or absent SWI/SNF complex activity through mutations in BRG1 and/or BRM (3, 6, 12), and 10% to 20% of NSCLCs have also been found to have mutations in multiple members of the SWI/SNF complex (3–7, 13, 46–49), such as ARID1A, ARID1B, and PBRM1. How loss of components of the SWI/SNF contributes to oncogenesis remains unclear. Here, we show that loss of BRG1 alters chromatin, especially around the TSS of genes. Our findings are consistent with previous studies showing that BRG1 loss affects nucleosome positioning during differentiation of hematopoietic stem cells and in mouse fibroblasts (45, 50). Moreover, our data indicate a critical role for BRG1 to maintain nucleosome positioning and occupancy around the TSS, particularly at the NDR and in gene bodies, and suggest a role for nucleosome positioning in gene expression.

We also find that silencing of BRM, the mutually exclusive SWI/SNF ATPase, in NSCLC cells does not result in reduced expression of the same set of genes as BRG1 (unpublished observation), suggesting BRG1- and BRM-containing SWI/SNF complexes act in a nonredundant fashion to regulate gene expression in NSCLC. Our identification of BRG1 downstream targets allows for a comparison of the role of other complex members in gene regulation and nucleosome positioning using techniques described in this report. We acknowledge that not all of the gene expression differences between the parental and BRG1-silenced cells reflect a direct effect of BRG1 loss. These genes may be indirectly regulated by other modes of epigenetic silencing, microRNAs, or aberrant RNA processing. Further studies including characterization of the chromatin structure surrounding the putative target genes will address this issue.

We have identified three BRG1 target genes (EHF, IFI16, and SYK) that show significantly reduced expression in human NSCLC tumors and cell lines that share low BRG1 expression. SYK has previously been identified as putative tumor-suppressor gene for NSCLC and suppresses invasive potential in the BRG1-deficient A549 NSCLC cell line (51, 52). IFI16 has also been reported to act as a tumor suppressor but its role in cancer development remains unclear (53–55). However, reduced expression of EHF has only been reported for prostate cancer (38, 56). Downregulation of EHF may account for some of the morphologic changes observed (Fig. 1A and Supplementary Fig. S1C) as EHF has been shown to contribute to differentiation and proliferation of epithelial cells (57), as well as regulating apoptotic signaling, EZH2 expression, and epithelial-to-mesenchymal transition in prostate cancer stem cells (26, 34, 36).

The current study offers insights that may reveal new strategies for the treatment of patients with BRG1-deficient cancers by revealing key target genes that fuel NSCLC development. Importantly, patients with BRG1-deficient NSCLC may respond differently to evolving chromatin-targeted treatments, as many of our identified target genes also undergo silencing through other mechanisms including promoter DNA methylation and histone deacetylation in BRG1-expressing cells (36, 38, 41, 42). Treatments such as DNA methylation inhibitors or histone deacetylase inhibitors may be ineffective in activating genes that are repressed due to BRG1 loss-associated chromatin changes. Treatments that target BRG1 loss need to be further investigated. The identification of genes differentially expressed due to BRG1 deficiency may also provide insights into clinical course or treatment response differences for NSCLC. Identifying pathways associated with genes that are silenced in BRG1-deficient tumors may lead to novel therapeutic approaches (2, 58, 59). Murine models for BRG1-induced tumor development may also provide a convenient avenue for testing new treatments (60, 61).

No potential conflicts of interest were disclosed.

Conception and design: A. Hepperla, I.J. Davis, B. Weissman

Development of methodology: T. Orvis, M.D. Wilkerson, D.N. Hayes, I.J. Davis

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): T. Orvis, S. Song, J. Simon, N. Desai, M.B. Major, D.N. Hayes, B. Weissman

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): T. Orvis, A. Hepperla, V. Walter, S. Song, J. Simon, J. Parker, M.D. Wilkerson, N. Desai, D.N. Hayes, I.J. Davis, B. Weissman

Writing, review, and/or revision of the manuscript: T. Orvis, A. Hepperla, V. Walter, S. Song, J. Simon, M.D. Wilkerson, N. Desai, D.N. Hayes, I.J. Davis, B. Weissman

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): T. Orvis, N. Desai, D.N. Hayes, B. Weissman

Study supervision: I.J. Davis, B. Weissman

The authors thank UNC LCCC Genomics Core Services, the UNC-LCCC Animal Studies Core Facility, and the UNC Chapel Hill High Throughput Sequencing Facility for outstanding experimental support. They also thank Tim Palpant, Fang Fang, Jason Lieb, and members of the Davis and Lieb laboratories for constructive input.

This study was supported in part by a UNC Lineberger Clinical/Translational Research Award and grants from NCI (CA138841 to B. Weissman; CA166447 to I.J. Davis; 1-DP2-OD007149-01 to M. Major; and P30 CA016086).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.