MAX Inactivation in Small Cell Lung Cancer Disrupts MYC ...€¦ · Small cell lung cancer (SCLC)...

RESEARCH ARTICLE

MAX Inactivation in Small Cell Lung Cancer Disrupts MYC–SWI/SNF Programs and Is Synthetic Lethal with BRG1 Octavio A. Romero 1 , Manuel Torres-Diz 1 , Eva Pros 1 , Suvi Savola 6 , Antonio Gomez 1 , Sebastian Moran 1 , Carmen Saez 3 , 4 , Reika Iwakawa 7 , Alberto Villanueva 2 , Luis M. Montuenga 5 , Takashi Kohno 7 , Jun Yokota 7 , and Montse Sanchez-Cespedes 1

on January 6, 2021. © 2014 American Association for Cancer Research. cancerdiscovery.aacrjournals.org Downloaded from

Published OnlineFirst December 20, 2013; DOI: 10.1158/2159-8290.CD-13-0799

http://cancerdiscovery.aacrjournals.org/

MARCH 2014�CANCER DISCOVERY | 293

ABSTRACT Our knowledge of small cell lung cancer (SCLC) genetics is still very limited, ampli-fi cation of L-MYC , N-MYC , and C-MYC being some of the well-established gene

alterations. Here, we report our discovery of tumor-specifi c inactivation of the MYC-associated factor X gene, MAX , in SCLC. MAX inactivation is mutually exclusive with alterations of MYC and BRG1 , the latter coding for an ATPase of the switch/sucrose nonfermentable (SWI/SNF) complex. We demonstrate that BRG1 regulates the expression of MAX through direct recruitment to the MAX promoter, and that depletion of BRG1 strongly hinders cell growth, specifi cally in MAX-defi cient cells, heralding a synthetic lethal interaction. Furthermore, MAX requires BRG1 to activate neuroendocrine transcriptional pro-grams and to upregulate MYC targets, such as glycolysis-related genes. Finally, inactivation of the MAX dimerization protein, MGA, was also observed in both non–small cell lung cancer and SCLC. Our results provide evidence that an aberrant SWI/SNF–MYC network is essential for lung cancer development.

SIGNIFICANCE: We discovered that the MYC-associated factor X gene, MAX , is inactivated in SCLCs. Furthermore, we revealed a preferential toxicity of the inactivation of the chromatin remodeler BRG1 in MAX-defi cient lung cancer cells, which opens novel therapeutic possibilities for the treatment of patients with SCLC with MAX-defi cient tumors. Cancer Discov; 4(3); 292–303. ©2013 AACR.

See related commentary by Rudin and Poirier, p. 273.

Authors’ Affi liations: 1 Genes and Cancer Group, Cancer Epigenetics and Biology Program (PEBC); 2 Translational Research Laboratory, Cata-lan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona; 3 Instituto de Biomedicina de Sevilla (IBiS), 4 Department of Pathology, Hospital Universitario Virgen del Rocío, Consejo Superior de Investigaciones Cientifi cas (CSIC), Univer-sidad de Sevilla, Seville; 5 Division of Oncology, Centro para la Investigación Medica Aplicada (CIMA), University of Navarre, Pamplona, Spain; 6 MRC-Holland, Amsterdam, the Netherlands; and 7 Division of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan Note: Supplementary data for this article are available at Cancer Discovery Online (http://cancerdiscovery.aacrjournals.org/). O.A. Romero and M. Torres-Diz contributed equally to this work. Corresponding Author: Montse Sanchez-Cespedes, Genes and Cancer Group, Cancer Epigenetics and Biology Program (PEBC), Bellvitge Bio-medical Research Institute (IDIBELL), 08908, Hospitalet de Llobregat, Barcelona 08907, Spain. Phone: 34-93-260-71-32; Fax: 34-93-260-72-19; E-mail: [email protected] doi: 10.1158/2159-8290.CD-13-0799© 2013 American Association for Cancer Research.

INTRODUCTION

Small cell lung cancer (SCLC) accounts for about 20% of lung cancer diagnoses and is a highly aggressive malignancy. However, the genetics underlying its development are still largely unknown. The genes most widely known to be fre-quently altered in SCLC are TP53 , RB1 , and those of the MYC family ( 1 ). PTEN , PIK3CA , and BRG1 (also called SMARCA4 ) are less frequently altered ( 1, 2 ). Novel high-throughput sequencing screening approaches, such as exome sequenc-ing, have been performed on SCLCs, revealing alterations at other genes, including the chromatin modifi ers CREBBP and EP300 ( 2 ).

Amplifi cations of L-MYC , N-MYC , and C-MYC are some of the best established gene alterations in lung cancer; L-MYC and N-MYC are more commonly amplifi ed in SCLC than in non–small cell lung cancer (NSCLC; ref. 1 ). In fact, the

pattern of gene alterations in SCLC is rather specifi c to this tumor type, probably refl ecting the different cell of origin of the distinct classes of lung cancers. For this reason, it has been suspected for some time that some SCLC subtype arises from neuroendocrine cells in the lung, which are com-monly found in clusters known as neuroendocrine bodies ( 3 ). Recent observations, using mouse models for targeted Trp53 and Rb1 inactivation in distinct cell types of the adult lung, support the explanation of the neuroendocrine origin of at least some SCLCs ( 4 ). Either because of its possible neuroendocrine origin or because of a specifi c neural tumor differentiation, SCLCs are enriched in transcripts that are related to neural tissues ( 5, 6 ). The neural origin of some SCLCs may serve to explain why some of the genes mutated in this type of lung cancer are also altered in other neural-related tumors. Such is the case of N-MYC and RB1 , which are commonly altered in neuroblastomas and retinoblastomas, respectively ( 7, 8 ).

Recently, germline-inactivating mutations at MAX , the MYC-associated factor X gene, were found to be responsible for hereditary pheochromocytoma, a tumor with neuroen-docrine features ( 9 ). Homozygous inactivation of MAX in rat adrenal pheochromocytoma PC12 cells had previously been reported ( 10 ). Inasmuch as the genes of the MYC family are commonly activated in SCLC and that, similar to pheochro-mocytomas, SCLCs have neuroendocrinal features ( 11 ), we decided to test for MAX inactivation in lung cancer.

RESULTS

The MYC-Associated Factor X Gene, MAX , Is Recurrently Inactivated in SCLC

We sequenced the entire coding region and the intron–exon boundaries of MAX in lung cancer cell lines (Supple-mentary Table S1) and found MAX intragenic homozygous deletions, which caused the complete loss of MAX protein,




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Romero et al.RESEARCH ARTICLE

in H1417, Lu134, Lu165, and COR-L95 cells, all of which are of the SCLC type ( Fig. 1A and B ). We also sequenced MAX in primary SCLCs and performed multiplex ligation-dependent probe amplifi cation (MLPA; ref. 12 ) to test for intragenic deletions ( Fig. 1C and D ). We tested the tumor xenograft directly derived from the same primary tumor as the Lu134 cells and confi rmed the presence of an identical MAX alteration, which ruled out the possibility that the observation was a cell culture artifact (Supplementary Fig. S1). Overall, we found homozygous and tumor-specifi c MAX -inactivating alterations in about 6% of the 98 SCLCs tested ( Table 1 ), a prevalence similar to that of the recently identifi ed CREBBP and EP300 tumor-suppressor genes ( 2 ). All of the tumor specimens were surgically resected before treatment, so that the possibility can be ruled out that alterations of MAX are secondary alterations due to chemo-therapy or radiotherapy.

The MAX protein contains a basic helix–loop–helix zipper domain, which is required to form heterodimers

with MYC, and which binds to hexameric E-box motifs (CACGTG) in the DNA to activate transcription. The MYC–MAX heterodimers also indirectly repress the expression of other genes ( 13, 14 ). In keeping with the current view that proteins acting in a common biologic pathway are not simultaneously altered in the same tumor specimen ( 1 ), we found that the alterations in MAX and amplifi cation of the MYC genes were mutually exclusive. Moreover, none of the MAX -mutant cells carried concomitant mutations of BRG1 (Supplementary Table S1), which are also known to be mutually exclusive with amplifi cation of the MYC genes in lung cancer ( 15 ).

BRG1, an ATPase of the SWI/SNF Chromatin Remodeling Complex, Directly Regulates the Expression Levels of MAX

The functional relationship of MYC with both MAX and BRG1 is well established ( 13, 14 , 16 ). Here, we aimed to elu-cidate the mechanistic interaction between MAX and BRG1

Figure 1. MAX is genetically inactivated in SCLC. A, PCR products of indicated exons show absence of amplifi cation, indicating the presence of deletions at some exons (E) of the MAX gene in the indicated lung cancer cell lines (underlined). Appropriate positive controls from cells without MAX deletions are also included. B, Western blot analysis of endogenous MAX in the indicated lung cancer cell lines implying the lack of MAX protein in the MAX- mutant cells (underlined). C, top, schematic representation of the structure of MAX , with all its corresponding exons and with the different probes used in the multiplex ligation-dependent probe amplifi cation (MLPA) assay. Probes 6 and 8 are located within alternative exons. Ratio charts of the MLPA depicting the intragenic deletions of various exons in the indicated lung cancer cell lines and in the lung primary tumor PT2. Appropriate controls from normal cells are also included. The black square indicates the location of the probes for the MAX gene. D, chromatogram depicting the indicated nucle-otide substitution in a lung primary SCLC. The normal matched DNA is also included.

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MAX Inactivation in Small Cell Lung Cancer RESEARCH ARTICLE

Table 1. List of the MAX alterations found among the 98 SCLCs (53 cell lines and 45 primary tumors) tested

Sample Nucleotide change Exon/intron Protein change LOH Tumor specifi c Other gene mutations

H1417 c.(?_-170)_171+?del E1-3 No protein Yes NA CDKN2A , RB1 , TP53

Lu134 c.172-?_(*1349_?)del E4-5 No protein Yes NA PTEN , RB1 , TP53

Lu165 c.(?_-170)_(*1349_?)del E1-5 No protein Yes NA RB1 , TP53

COR-L95 c.(?_-170)_(*1349_?)del E1-5 No protein Yes NA RB1 , TP53

PT-1 c.296-1G>A I4 Unknown Yes Yes TP53 a

PT-2 c.64-?_295+?del E3-4 No protein Yes Yes TP53 a

NOTE: The presence of LOH indicates the homozygous nature of the alterations at MAX . The presence of alterations at other genes is also indicated ( 39 ). Abbreviations: NA, not analyzable; PT, primary tumor. a Only TP53 , MYC , MYCN , and MYCL have been tested in these samples.

and to explore the role of MAX inactivation in cancer. To this end, we took advantage of three lung cancer cell lines lack-ing MAX and studied the effects of restoring MAX activity and depleting BRG1 in these cells ( Fig. 2A ). Reconstitution of MAX signifi cantly reduced cell growth in the three cancer cell lines ( Fig. 2B and Supplementary Fig. S2A), which is consistent with a previous observation in PC12 cells ( 10 ) and provides evidence of the tumor-suppressor function of MAX. Likewise, depletion of BRG1 gave rise to a highly signifi cant reduction in cell viability.

We observed that the 5′-untranslated region (5′-UTR) of MAX contains putative glucocorticoid response elements. Glucocorticoids are critical in normal lung differentiation, and BRG1 is required to mediate the transcriptional activi-ties of the glucocorticoid receptor ( 3 , 16 ). Therefore, we examined whether MAX was responsive to, or involved in, mediating the response to treatment with glucocorticoids. For this purpose, we cloned MAX with the 5′-UTR (hence-forth 5′-UTR–MAX; Fig. 2C ). Ectopic levels of MAX were low in cells infected with 5′-UTR–MAX, in a hormone-free environment, and became upregulated after treatment with glucocorticoids. In contrast, cells carrying MAX devoid of the 5′-UTR exhibited high basal levels of MAX, which increased moderately upon treatment with glucocorticoids ( Fig. 2D ). This indicates that the 5′-UTR contains regula-tory elements that modulate the expression of MAX in response to glucocorticoids.

Unexpectedly, we found a severe reduction in the levels of ectopic MAX after depleting BRG1 in the glucocorticoid-treated 5′-UTR–MAX cells, implying that the regulation of MAX expression through its 5′-UTR is strongly dependent on BRG1 ( Fig. 2E ). The requirement of BRG1 for transac-tivation of endogenous MAX was verified in several lung cancer cell lines and in neuroblastoma-derived SHSY-5Y cells. These exhibited a strong reduction of MAX follow-ing depletion of BRG1 ( Fig. 2F and Supplementary Fig. S2B). In addition, the findings were reproduced in cells derived from the H1299 lung cancer cells, which are BRG1 deficient. These were the isogenic cells H1299tr-BRG1wt and H1299tr-BRG1mut, which express the wild-type and a mutant version of BRG1, respectively ( 16 ). The level of

expression of ectopic MAX from the 5′-UTR-MAX was very low in the BRG1 -mutant cells, in a hormone-free environ-ment, and increased slightly upon the addition of gluco-corticoids. In contrast, neither the status of BRG1 nor the presence of glucocorticoids impinged on the levels of MAXfrom the construct lacking the 5′-UTR (Supplementary Fig. S2C).

We then examined whether BRG1 is recruited to the MAX promoter. Chromatin from the H1299tr-BRG1wt and H1299tr-BRG1mut cells was precipitated [chromatin immunoprecipitation (ChIP)] using a BRG1 antibody. DNA enrichment was measured by quantitative PCR (qPCR) using primer sets fl anking a region of about 3,000 bp. We observed enrichment of BRG1 in a region of about 700 bp within the 5′-UTR of MAX ( Fig. 2G ). These fi ndings demonstrate, for the fi rst time, a direct functional connection between these two tumor suppressors, in virtue of which BRG1, as part of the switch/sucrose nonfermentable (SWI/SNF) complex, facilitates the access of the glucocorticoid receptor to the MAX promoter, thereby activating its expression.

Depletion of BRG1 Is Preferentially Toxic in MAX -Defi cient Cells

Depletion of BRG1 dramatically impaired (by >95%) cell viability in the MAX -deficient cells ( Fig. 2B and Sup-plementary Fig. S2A). To test whether this behavior also took place in cancer cells with wild-type MAX , we depleted BRG1 in a panel of six lung cancer cell lines with amplifi-cation of either MYC , MYCL , or MYCN . Only a moderate decrease (<25%) in cell growth was found in some cells, implying that the depletion of BRG1 was preferentially toxic in MAX- deficient cells ( Fig. 3A ). It is of particular note that the MAX–sh BRG1 cells, from parental Lu134 and Lu165 cells, were more viable than either the MAX-reconstituted or sh BRG1 cells ( Fig. 3B and Fig. 2B ). This suggests that MAX restores, to some extent, the cell viabil-ity that is undermined by sh BRG1 , or vice versa . Taken together, these results imply the existence of a synthetic lethal type of interaction between MAX and BRG1, and raise the possibility of developing a therapeutic strategy for patients with MAX -deficient tumors.






MAX Requires BRG1 to Activate Neuroendocrine Transcriptional Programs and to Upregulate MYC Targets Such as Glycolysis-Related Genes

To elucidate the functional relationship between MAX and BRG1, we performed global gene expression analysis in the ectopic MAX and sh BRG1 cell models. On the basis of their Gene Ontology (GO) function, reconstitution of MAX showed a signifi cant enrichment of transcripts related to neural differentiation and to glycolysis/carbohydrate metab-olism (Supplementary Fig. S3). Some of these transcripts are well-established targets of MYC ( Fig. 4A ; refs. 17, 18 ). Because SCLCs have neuroendocrine features ( 6 , 11 ), the upregulation of neural-related genes upon MAX reconstitution possibly

refl ects the activation of prodifferentiation programs. Recon-stitution of MAX also upregulated genes encoding glycolysis enzymes (e.g., LDHA , HK2 , PDK1 , PKM2 , and PGK1 ), which are targets of MYC. Conversely, the levels of these glycolysis-related genes were lower in the sh BRG1 cells than in the con-trol cells ( Fig. 4A ), whereas the MAX–sh BRG1 cells showed a reversion in the expression of glycolysis- and neural-related genes toward the profi le of the control cells ( Fig. 4B ).

Most of the MYC targets that were upregulated by MAX were inversely associated with the gene expression profi le of sh BRG1 cells ( Fig. 4C ). The MAX signature was also negatively correlated with that of embryonic lungs from mice overexpressing Nmyc and Cmyc , whereas there was a direct

Figure 2. Effects of MAX reconstitution and of BRG1 depletion in lung cancer cells. A, top, schematic depiction of the experimental design using dif-ferent lentiviral constructs expressing human MAX , and the shRNA targeting BRG1 (sh BRG1 ). Control (∅) and scramble RNAs are also shown. The sh BRG1 used were validated in our previous study ( 16 ). Bottom, Western blot analyses, from total lysates, depicting MAX and BRG1 in the indicated cells. Tubulin is shown as a loading control. B, left, cell proliferation measured using MTT assays. Lines, the number of viable cells relative to the total number of cells at 0 hours. Error bars, SD. ***, P < 0.0005. Right, images of the MTT assays. C, schematic representation of the 5′-UTR–MAX construct. The putative glucocorticoid receptor–binding region is highlighted in green. D, Western blot analysis, from total lysates, depicting the ectopic expression of MAX from the 5′-UTR–MAX construct and from that lacking the 5′-UTR (MAX) in cells cultured in hormone-free (HF) medium or at the indicated glucocorticoid (GC) concentrations. E, Western blot analysis, from total lysates, showing the levels of ectopic expression of MAX and coexpression of MAX–sh BRG1 and 5′-UTR–MAX/sh BRG1 in the indicated cell lines. F, reduction of levels of endogenous MAX, after depletion of BRG1, in one MYC -amplifi ed lung cancer cell line (H460) and in the neuroblastoma-derived SHSY-5Y cells, treated with 2 μmol/L of glucocorticoid. In the latter, two sh BRG1 s (#1 and #4) have been used. G, ChIP of BRG1 in the indicated cells after inducing BRG1 expression with doxycycline, followed by qPCR to determine DNA enrichment in the MAX promoter, relative to the input. The bars represent the data for the BRG1 ChIP in H1299tr-BRG1wt and the H1299tr-BRG1mt cells, as indicated. Error bars, SDs of three replicates. Under the graph there is a schematic representation of the region screened and the position (in bp) of each amplicon (vertical lines) relative to the ATG (+1). TSS, transcription start site. The bottom corresponds to the 2% agarose gel of the qPCR of the top, shown for comparison.

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Figure 3. Effects of BRG1 depletion in the proliferation of lung cancer cells with amplifi cation at the MYC family of genes and in MAX -defi cient cells, after reconstitution of MAX. A, MTT assay to determine viability, after depleting BRG1 and in the scramble (scr) control, of cells carrying amplifi cation of MYC (H446, H460, and H82), MYCN (H69), or MYCL (HCC33 and H1963). Lines, the number of viable cells relative to the total number of cells at 0 hours. Error bars, SD. NS, not signifi cant; *, P < 0.05; **, P < 0.005. B, left, MTT assays of MAX-defi cient cells carrying the indicated constructs. Right, images of the MTT assay of Lu134 cells.

association with the expression profi le after BRG1 reconstitu-tion in lung cancer cells ( Fig. 4C ; ref. 16 ). These observations imply that BRG1, MAX, and MYC orchestrate the transcrip-tional regulation of a common set of genes, and suggest that MYC represses cell differentiation–related transcripts in a MAX-independent manner.

Genetic Inactivation of the MAX Dimerization Protein, MGA , in Lung Cancers with Wild-Type Components of the SWI/SNF or MYC Pathways

MAX interacts not only with MYC, but also with other BHLHZ-containing proteins (i.e., MXD1, MXI1, MXD3, MXD4, MNT, and MGA), which antagonize the transcriptional






Figure 4. Gene expression profi les of 5′-UTR–MAX and of sh BRG1 -expressing cells. A, circos plot of the heatmap of the approximately 2,030 transcripts that constitute the MAX- and sh BRG1 -gene expression signatures (Supplementary Tables S2 and S3). The GO categories for those genes associated with neural development, glucose metabolism, targets of MYC, and apoptosis are indicated in orange, light blue, pink, and gray, respectively. Selected genes from these GO categories are highlighted in blue in the outer part of the circle. B, expression heatmap for genes in the indicated GO categories (from Supplementary Table S2). Gene expression of Lu134-derived cells. Controls (∅), 5′-UTR–MAX, sh BRG1 , and 5′-UTR–MAX/sh BRG1 . C , graph of the ranked gene lists derived from the comparison (using gene set enrichment analysis) of the indicated datasets and gene lists. Probabilities and FDRs are indicated. NES, normalized enrichment score.

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‘na_pos’ (positively correlated) ‘na_pos’ (positively correlated) ‘na_pos’ (positively correlated)

‘na_pos’ (positively correlated)‘na_pos’ (positively correlated)‘na_pos’ (positively correlated)

shBRG1 downregulated vs. Lu134MAXexpression profile as reference dataset

shBRG1 downregulated vs. datasetGSE35168 from H1299tr-BRG1wt cells

MAX upregulated vs. dataset GSE10954from lungs of mice overexpressing cMyc

HK2PFKFB3PDK1PFKFB4LDHAPGK1ENO2ALDOAPGM1PKM2APOEHSPG2PCP4SPON2ADM2MAPTCSPG5MALFGF11CXCR4AHNAKLAMB2ODZ1NESISL1HEY1SLITRK6LHX2GAL3ST1SEMA3BEMX1DLX6DLG4CLDN1EPORUCN

5

-Lu1

34-∅

-Lu1

34 M

AX

Gly

colis

is-r

elat

edN

eura

l-rel

ated

-Lu1

34 s

hBR

G1

-Lu1

34-M

AX

/shB

RG

1






control of MYC, at the same E-box target DNA sequences ( 14 ). Some of these MAX-binding proteins promote differ-entiation in vivo , block cellular growth and MYC-induced transformation, and suppress the development of cancer ( 19 ). Furthermore, apart from BRG1 , genes coding for other components of the SWI/SNF complex are altered in cancers, including lung cancer ( 20, 21 ). We have exhaustively searched public databases for gene alterations in partners of MAX in all types of lung cancer and found inactivation of the MAX dimerization protein, MGA , in lung cancer cell lines ( Fig. 5A ) and in lung primary tumors ( http://www.cbioportal.org/ ) of both the NSCLC and SCLC type. We have tested a panel of these cell lines and confi rmed the alterations, most of which are homozygous and predictive of truncated proteins ( Fig. 5B ). Moreover, inactivation of MGA and alterations at different members of the SWI/SNF complex at MAX and MYC were mutually exclusive in lung cancer ( Fig. 5C ).

DISCUSSION

We report the discovery of the recurrent inactivation of MAX in SCLC. The alterations were tumor-specifi c and homozygous, leaving little doubt that MAX constitutes a bona fi de tumor-suppressor gene. MAX -inactivating altera-tions occurred in about 6% of the SCLCs, a prevalence similar to that of the recently identifi ed CREBBP and EP300 tumor-suppressor genes ( 2 ). Most alterations of MAX were intra-genic deletions, which may explain why inactivation of MAX has not been picked up in recent exome or whole-genome sequencing of SCLCs ( 2 , 22 ). Germline-inactivating muta-tions at MAX were found to be responsible for hereditary

pheochromocytoma, a tumor with neuroendocrine features ( 9 ). This is interesting because MAX inactivation was found only in SCLC and not in the NSCLC type, the latter com-prising about 80% of the lung cancers. Taking into account that, unlike NSCLCs, SCLCs have neuroendocrine features, it can be hypothesized that MAX is preferentially mutated in neuroendocrine-related malignancies.

None of the MAX -mutant cells carried concomitant ampli-fi cation at the MYC family of genes or mutations at BRG1 . In lung cancer, genetic inactivation of BRG1 is mutually exclusive with amplifi cation of MYC genes, which is consist-ent with the biologic connection between these two cancer proteins ( 15 ). BRG1 encodes one ATPase of the SWI/SNF chromatin remodeling complex and is involved in the tran-scriptional control of various cell processes, such as embry-onic development and cell differentiation ( 23, 24 ). Some of these activities also require the complex to interact with nuclear receptors ( 25 ). The functional relationship of MYC with BRG1 and with the SWI/SNF complex is well estab-lished. For example, MYC physically interacts with the SWI/SNF component, SMARCB1 ( 26 ), and BRG1 is required to regulate the expression of MYC and MYC target genes ( 16 , 27 ). In tumors carrying BRG1 mutations, this regulation is abolished, thereby preventing cell differentiation and pro-moting cell growth ( 16 ). Here, we provide evidence that BRG1 also regulates the levels of MAX , stimulated by the presence of glucocorticoids. In virtue of this regulation, and as part of the SWI/SNF complex, BRG1 would be directly recruited to the 5′-UTR of MAX to facilitate the access of the glucocorticoid receptor to the MAX promoter, thereby activating its expres-sion. This constitutes the fi rst demonstration of a direct

Figure 5. Mutation profi le of MGA and of MYC - and BRG1 -related genes in lung cancer. A, inactivating MGA alterations in lung cancer cell lines (from http://www.broadinstitute.org/ccle/ ). The last column indicates whether MGA has been resequenced in our laboratory. B, chromatogram depicting muta-tions at MGA in the indicated lung cancer cell lines. Normal controls are also included. Arrows indicate the nucleotide changes. C, schematic represen-tation of the co-occurrence analysis of alterations at the indicated genes in a panel of 180 lung cancer cell lines. Information has been gathered from different sources, including our current and previous ( 1 , 15 ) results, and publicly available databases (i.e., http://cancer.sanger.ac.uk/ and http://www.broadinstitute.org/ccle/ ). Red and white squares indicate the presence and absence of alterations, respectively. Gray squares indicate that no data were available. Bar graph, left, indicates the frequency of alterations and the distribution between the two main lung cancer types. A detailed list including the identity of each cell line and exhaustive information on specifi c mutations is provided in Supplementary Table S4.

Cell line

A B

C

H2291 NSCLC R2291QfsX44 Yes

H22

91C

ontr

ol

LOU

-NH

91C

ontr

ol

c.6870delG(p.R2291QfsX44)

T

T T T T T T T T T

C C CA

A AA

A AC C C

C C CCC C C

C C

CCC

T T T T T T T T T

c.2188+G>A(p.V730_splice)

Yes

No

No

No

SCLCNSCLC

0 10 20 30

p.G809_splice

p.V730_splice

p.R1053*

Hom. deletion

NSCLC

NSCLC

SCLC

SCLC

H650

LOUNH91

CORL279

DMS153

MYCBRG1MYCLMGA

MYCNARID1A

MAXSMARCB1

PBRM1

Type Protein change Resequenced






functional connection between these two tumor suppressors. In addition to glucocorticoid receptor, the SWI/SNF complex interacts with other nuclear receptors, such as estrogens, retinoic acid, and vitamin D3 receptors ( 25 , 28 , 29 ). There-fore, we cannot rule out the possibility that the activation of these other receptors also infl uences the expression levels of MAX in an SWI/SNF–dependent manner.

We also noted that depletion of BRG1 triggered a strong inhibition of lung cancer cell growth. The effect was very specifi c to the MAX -defi cient cells, as growth was not affected after depleting BRG1 in a panel of lung cancer cells with amplifi ed MYC genes. Regardless of the mechanism underly-ing this specifi c and dramatic impairment in the growth of MAX -defi cient cells after BRG1 depletion, it is important to highlight its potential clinical relevance. This informa-tion suggests therapeutic possibilities for the treatment of patients with SCLC, and possibly for patients with pheochro-mocytoma, with MAX-defi cient tumors.

The reconstitution of MAX in SCLC cells triggered the expression of neural-related and glycolysis/carbohydrate metabolism-related transcripts, some of which are well-established targets of MYC ( 17, 18 ). Because it has been speculated that some SCLCs arise from neuroendocrine cells ( 4 ), the upregulation of neural-related genes upon MAX reconstitution may refl ect the activation of prodif-ferentiation programs. Genes encoding glycolysis enzymes (e.g., LDHA , HK2 , PDK1 , PKM2 , and PGK1 ) are targets of MYC and are commonly overexpressed in cancer cells ( 18 ). Conversely, the levels of these glycolysis-related genes were lower in the sh BRG1 cells than in the control cells. It is

intriguing that the reconstitution of a tumor suppressor, MAX , activates the expression of genes that are typically upregulated in cancer cells. Although additional research is likely to provide an explanation for these observations, we can speculate in the meantime that a substantial increase (i.e., after reconstitution of MAX) or decrease (i.e., after depletion of BRG1) of glycolysis enzymes, in a predomi-nantly tumor-genetic context, triggers an energetic imbal-ance, with dire consequences for cell viability. In support of this concept, the rescue of cell viability observed in MAX–sh BRG1 cells but not MAX-reconstituted or BRG1-depleted cells is accompanied by a reversion in the expression of glycolysis- and neural-related genes toward the profi le of the control cells.

MAX was believed to be essential to the oncogenic func-tion of MYC ( 30 ). However, in Drosophila , an Myc mutant lacking the Max-interaction domain still retained partial activity ( 31 ). These observations, coupled with the existence of MAX inactivation in pheochromocytomas ( 9 ) and now in SCLC, imply that some MYC activities are independent of its heterodimerization with MAX. Here, we found that most of the MYC targets that were upregulated by MAX were inversely associated with the gene expression signatures of sh BRG1 cells and of embryonic lungs from mice overexpressing Nmyc and Cmyc . In contrast, there was a direct association with the expression profi le after BRG1 reconstitution in lung cancer cells ( 16 ). These fi ndings imply that BRG1, MAX, and MYC orchestrate the transcriptional regulation of a common set of genes and suggest that MYC represses cell differentiation–related transcripts in a MAX-independent manner. Figure 6

Figure 6. Schematic model for depicting some possible scenarios of the interplay among BRG1 (or the SWI/SNF complex), MYC, and MAX to regulate the transcriptional programs of normal differentiated cells and for cancer cells with alterations at the indicated genes. White boxes, genes involved in cell differentiation; black boxes, genes involved in cell stemness; blue circles, MAX-interacting proteins.

Normal differentiatedcell

MAX-deficient

BRG1 (or SWI/SNF)-deficient

MYC-amplified

SWI/SNF

SWI/SNF

MAX

Closed chromatin

MAX

SWI/SNF

MAX

MAX

MAX MAX -Low levels of any of the MYC genes.-Chromatin accessibility in prodifferentiation genes.-MAX-mediated transactivation of prodifferentiation genes.-No MYC-mediated transactivation of stemness-related genes

-Moderate levels of any of the MYC genes.-Chromatin accessibility.-No MAX-mediated transactivation of prodifferentiation genes-MYC-mediated transactivation of stemness-related genes.

-Moderately high levels of any of the MYC genes.-No chromatin accessibility in prodifferentiation genes.-No MAX-mediated transactivation of prodifferentiation genes.-MYC-mediated transactivation of stemness-related genes.

-Very high levels of any of the MYC genes.-Chromatin accessibility.-MYC-mediated repression of prodifferentiation genes.-MYC-mediated transactivation of stemness-related genes.

Closed chromatin

MYC

MYCMYC

MYCMYC

MYC

MYC

MYC

MYC

MYC

MYC

MYC

MYC

MYC

MYC MYC

MYC MYCMYC

MYCMYCMYC

MYC

MYC

MYC

MYCX

X

X

X






depicts a model that speculates about the different scenarios that could take place in the context of MAX , MYC , or BRG1 genetic alterations in a cancer cell ( Fig. 6 ).

Finally, through a search of public cancer databases, we discovered recurrent inactivation at the MAX dimerization protein, MGA , which was mutually exclusive with alterations of members of the SWI/SNF complex and with MAX and MYC . Thus, MGA is a tumor-suppressor gene in lung cancer and is probably another cog on the SWI/SNF–MYC func-tional axis. In this regard, it is important to highlight that in recent RNA interference screening, Brg1 , Max , and Mga were identifi ed as repressors of germ-cell gene expression in murine embryonic stem cells. This is additional evidence of a functional connection of these proteins with the control of cell differentiation ( 32 ).

In conclusion, our current genetic and molecular fi ndings provide powerful evidence that MAX is a tumor-suppressor gene involved in SCLC development. We propose that the abnormal function of the SWI/SNF–MYC axis, arising from genetic alterations of any of its components, prevents cell dif-ferentiation and constitutes an acquired ability of the cancer cells that should be added to the Hanahan and Weinberg model ( 33 ).

METHODS

Lung Tumor Specimens and Cancer Cell Lines Lung cancer cell lines representative of the most common lung

histopathologies were included (Supplementary Table S1). Cell lines were obtained from the American Type Culture Collection, grown under recommended conditions, and maintained at 37°C in a humidifi ed atmosphere of 5% CO 2 /95% air. All cells tested negative for Mycoplasma infection. The cells lines were authenticated by geno-typing for TP53 and other known mutations (e.g., BRG1/SMARCA4 and STK11 ). The genotyping of the mutations was done before starting the experiments or, in some particular cases, also during the experimental part of the study. The genotyping was done using direct Sanger sequencing of PCR products, as indicated previously ( 1 ). The mutations found were in agreement with those provided in public databases, as indicated in Supplementary Tables. Most samples were from the National Cancer Center Biobank at the National Cancer Center Hospital (Tokyo, Japan). Four samples were obtained from the Biobanco del SSPA (Sistema Sanitario Público de Andalucía, Spain). Genomic DNA and total RNA were extracted by standard protocols. The study was approved by the relevant Institutional Review Boards and ethics committees.

Screening for MAX Gene Alterations: Sanger Direct Sequencing and MLPA

To extract genomic DNA, freshly frozen tissue from tumors was meticulously dissected to ensure enriched material containing at least 40% tumor cells. Approximately 10- to 20-μm sections were collected and placed in 1% SDS/proteinase K (10 mg/mL) at 58°C overnight. Digested tissue was then subjected to phenol–chloroform extrac-tion and ethanol precipitation following standard protocols. For mutation screening of the MAX gene, exons 1 to 5 (NM_002382.3) and MGA (exons 1–23; NM_001164273.1) were amplifi ed from 30 ng of genomic DNA extracted from all tumors. Cycle sequencing of PCR products was carried out using Big Dye Terminator chem-istry (Applied Biosystems) with an ABI PRISM 3700 DNA Analyzer (PerkinElmer Life Sciences, Inc.). All of the variants identifi ed in the study were confi rmed by resequencing of independent PCR products. MLPA technique was used to determine the presence of intragenic

homozygous deletions at MAX in the lung primary tumors. The MLPA protocol used here has been described elsewhere ( 12 ). In short, 100 ng of genomic DNA was denatured for 5 minutes at 98°C, after which 3 μL of the probe mixture was added. The sample DNA and P429-A1 MLPA probe mixture was heated at 95°C for 1 minute and then incubated at 60°C for 16 hours, followed by a ligation step (Ligase-65 enzyme; MRC-Holland). Subsequently, a 10-μL mix-ture was added containing deoxynucleotide triphosphates (dNTP), Taq polymerase, and one unlabeled and one 6-carboxyfl uorescein amidite–labeled (FAM) universal PCR primer in each reaction. PCR was carried out for 35 cycles, and the fragments were analyzed with an ABI model 3130XL capillary sequencer (Applied Biosystems) using GeneScan 500 LIZ size standard (Applied Biosystems). MLPA fragment analysis and comparative analysis were performed using CoffalyserNET software ( 34 ).

Expression Vectors and Lentiviral Production Two main forms of MAX have been described: the short and

long forms, containing 151 and 160 amino acids, respectively ( 35 ). These arise by alternate mRNA splicing that inserts nine amino acids between residues 12 and 13 of the short form of MAX. Here, we cloned the short form (NM_145112.2) because it was the more abundant transcript in the tumors and lung cancer cell lines tested and was functionally equivalent to the long form. Human wild-type MAX was cloned into the Eco RI and Not I restriction sites of the vector pLVX–IRES–ZsGreen1 (Clontech Laboratories, Inc.). All constructs were verifi ed by automatic sequencing. Short hairpin RNAs (shRNA) were purchased from SIGMA-MISSION (LentiExpress Technology; Sigma-Aldrich) as a glycerol stock of 5 pLKO plasmids carrying BRG1-specifi c shRNA sequences. Two of these shRNAs had previ-ously been shown to deplete BRG1 expression effi ciently and specifi -cally (depleted BRG1 but not BRM expression; ref. 16 ). A scramble shRNA (Sigma MISSION shRNA non-mammalian control SHC002) was used as a control. The lentiviruses were generated within the 293T packaging cells. Lentiviruses carrying MAX constructs were generated using Lenti-X (LentiExpress Technology; Clontech Labora-tories), following the manufacturer’s recommendations. The lentivi-rus carrying the sh BRG1 and scrambled shRNAs, were cotransfected with each construct and the packaging plasmids psPAX and pMD2.6 (Sigma-Aldrich). After 48 hours, 293T fi ltered supernatants were col-lected and subconfl uent cells were infected with harvested virus and selected with puromycin for 72/96 hours.

ChIP Assays ChIP assays were performed as previously described ( 16 ). Briefl y,

preliminary fi xation experiments were performed over a predeter-mined period. Cells were then fi xed in 1% formaldehyde for 10 minutes and fi nal conditions were chosen that yielded the best combi-nation of in vivo fi xed chromatin, high DNA recovery, and small aver-age size of chromatin fragments (an average length of 0.25–1.00 kb). Three independent ChIP experiments were performed. qPCRs were performed using SYBR Green Master Mix (Applied Biosystems). Relative enrichment was determined from a standard curve of serial dilutions of input samples. For semi-qPCR, amplifi cations were performed with 30 cycles in a total volume of 25 μL and run on 2% agarose gels. qPCR was performed using Power SYBR Green Master Mix (Applied Biosystems). The sequences of primer sets used in each case are available upon request.

Antibodies and Western Blot Analyses The following primary antibodies were used for Western blot

analyses: polyclonal anti-MAX, sc-197 antibody (Santa Cruz Bio-technology), polyclonal anti-BRG1, H88 (1:1,000; Santa Cruz Bio-technology), anti–C-MYC 9E10 (1:500; Santa Cruz Biotechnology), anti-tubulin (T6199 mouse; Sigma-Aldrich), and anti–β-actin (13854;






Sigma-Aldrich). For Western blot analyses, whole-cell lysates were collected in a buffer containing 2% SDS, 50 mmol/L Tris–HCl (pH 7.4), 10% glycerol, and protease inhibitor cocktail (Roche Applied Science). Protein concentrations were determined using a Bio-Rad DC Protein Assay kit (Life Science Research). Equal amounts of lysates (20 μg) were separated by SDS-PAGE and transferred to a polyvinylidene difl uoride (PVDF) membrane that was blocked with 5% nonfat dry milk. Membranes were incubated with the primary antibody overnight at 4°C, and then washed before incubation with species-appropriate horseradish peroxidase (HRP)–conjugated sec-ondary antibodies for 1 hour at room temperature.

Treatments Dexamethasone was used for glucocorticoid treatment. Cells were

fi rst depleted of FBS and subjected to a hormone-free medium by transfer to 10% charcoal-dextran–treated, heat-inactivated FBS for 24 hours before hormone treatment ( 16 ). Cells were then treated for 24 to 72 hours with the indicated concentrations of dexamethasone before harvesting.

MTT Assay For cell viability assays, 10 μL of a solution of 5 mg/mL MTT

(Sigma Chemical Co.) was added. After incubation for 3 hours at 37°C, the medium was discarded, the formazan crystals that had formed were dissolved in 100 μL dimethyl sulfoxide (DMSO), and absorbance was measured at 596 nm. Results are presented as the median of at least two independent experiments performed in tripli-cate for each cell line and for each condition.

Microarray Global Gene Expression Analysis RNA (100 ng) was used for the gene expression microarray analy-

sis. RNA integrity values were in the range of 9.0 to 10.0 when assayed by Lab-chip technology in an Agilent 2100 Bioanalyzer. For labeling, we used a commercial “One-Color Microarray-Based Gene Expression Analysis” version 5.5 kit and followed the manufacturer’s instructions (Agilent manual G4140-90050, February 2007). Hybridi-zation was performed on the Human Gene Expression v2 microarray 8 × 60K (Agilent microarray design ID 014850, P/N G4112F). For scanning, we used a G2505B DNA microarray scanner. Images were quantifi ed using Agilent Feature Extraction Software (v. 9.5). The cells used for microarray gene expression analysis were as follows: (i) control cells: H1417, Lu134, and Lu165 containing the control vector; (ii) H1417, Lu134, and Lu165, each containing 5′-UTR–MAX; (iii) H1417, Lu134, and Lu165, each expressing sh BRG1 ; and (iv) Lu134, expressing both 5′-UTR–MAX and sh BRG1 . To generate the lists of upregulated and downregulated transcripts for each condition, we chose the following criteria: (i) transcripts induced or repressed by a factor of at least 1.5 under each MAX or sh BRG1 condition with respect to their matched cell line carrying the empty vector, and (ii) statistical signifi cance (see below). The genes are listed in Supplementary Tables S2 and S3.

Statistical and Bioinformatic Analysis Data were analyzed using a χ 2 test or a two-tailed Student unpaired-

samples t test. Group differences were presented as mean and SDs. Differences were considered statistically signifi cant for any value of P < 0.05. Expression data were analyzed using the R program. Raw data were normalized by the robust multiarray average (RMA) algorithm available in Bioconductor’s affy package ( 36 ). We used limma package to obtain limma-moderated t statistics to derive the signatures of dif-ferentially expressed genes. Test P values were adjusted with respect to the false discovery rate (FDR). Test statistics with an associated value of P < 0.05 were considered to be statistically signifi cant. The lists of genes (ranked by the n -fold values of change) were subjected to

gene set enrichment analysis (GSEA; ref. 37 ) using the indicated gene expression signatures as the gene set. After Kolmogorov–Smirnov testing, our gene sets were considered signifi cantly enriched between comparison classes for values of FDR < 0.25, a widely accepted cutoff for the identifi cation of biologically relevant gene sets ( 38 ).

Disclosure of Potential Confl icts of Interest S. Savola is employed by MRC-Holland, manufacturer of commer-

cially available MLPA probemixes. No potential confl icts of interest were disclosed by the other authors.

Authors’ Contributions Conception and design: O.A. Romero, M. Sanchez-Cespedes Development of methodology: O.A. Romero, M. Torres-Diz, E. Pros, S. Savola, A. Villanueva Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): O.A. Romero, M. Torres-Diz, C. Saez, L.M. Montuenga, T. Kohno Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): O.A. Romero, M. Torres-Diz, E. Pros, A. Gomez, S. Moran, A. Villanueva, M. Sanchez-Cespedes Writing, review, and/or revision of the manuscript: O.A. Romero, M. Torres-Diz, S. Savola, C. Saez, L.M. Montuenga, M. Sanchez-Cespedes Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): O.A. Romero, M. Torres-Diz, E. Pros, S. Savola, R. Iwakawa, J. Yokota, M. Sanchez-Cespedes Study supervision: O.A. Romero, M. Sanchez-Cespedes

Acknowledgments The authors thank Patricia Cabral and Sara Verdura (Genes and

Cancer Group) at IDIBELL for technical assistance and HaciAli Yigit-top for performing the MLPA experiments.

Grant Support This work has been supported by the Spanish Ministry of Econ-

omy and Competitiveness (grant SAF2011-22897 to M. Sanchez-Cespedes), the Red Temática de Investigación del Cáncer-RTICCs (RD12/0036/0045 to M. Sanchez-Cespedes and RD12/0036/0040 to L.M. Montuenga), Red de Biobancos (RD09/0076/00085) and the European Community’s Seventh Framework Programme (FP7/2007-13 to M. Sanchez-Cespedes, L.M. Montuenga, and S. Savola), under grant agreement no. HEALTH-F2-2010-258677–CURELUNG. Addi-tional support came from a Grant-in-Aid from the Ministry of Health, Labor and Welfare for the Third-term Comprehensive 10-year Strategy for Cancer Control, Japan, to T. Kohno and J. Yokota. M. Torres-Diz is the recipient of a Fellowship (FPI) from the Spanish Ministry of Economy and Competitiveness.

Received October 28, 2013; revised December 13, 2013; accepted December 16, 2013; published OnlineFirst December 20, 2013.

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2014;4:292-303. Published OnlineFirst December 20, 2013.Cancer Discovery Octavio A. Romero, Manuel Torres-Diz, Eva Pros, et al. Programs and Is Synthetic Lethal with BRG1

SWI/SNF− Inactivation in Small Cell Lung Cancer Disrupts MYCMAX

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