Some SWI/SNF subunits are preferentially mutated.

<p><b>A.</b> The average frequency of nonsynonymous SWI/SNF subunit mutations (for the 18 tumor diagnoses analyzed) is indicated superimposed on a schematic depiction of the SWI/SNF complex. Mutations preferentially hit the <i>SMARCA4</i> enzymatic subunit and several targeting subunits (<i>ARID1A</i>, <i>ARID1B</i>, <i>PBRM1</i>, and <i>ARID2</i>). <b>B.</b> Heatmap (color scale indicated) depicting the number of nonsynonymous mutations found in each SWI/SNF subunit gene from the exome datasets analyzed. Note that some tumor types show selective mutation of single SWI/SNF subunits, e.g. <i>ARID1A</i> in ovarian clear cell carcinoma (CCC) and gastric cancer, while most other tumor types do not. For simplification, only those SWI/SNF subunits and tumor types having mutations are shown.</p

SWI/SNF mutations are deleterious and widespread across human cancers.

<p><b>A.</b> Bar graph depicts the frequency of nonsynonymous mutations in SWI/SNF (<i>right</i>; counting mutations in any of 20 subunit genes) and <i>TP53</i> (<i>left</i>) for each of the 18 tumor diagnoses surveyed. The average frequency of the 18 tumor diagnoses is indicated in red. The small number of samples with mutations in two different SWI/SNF subunits was not double-counted. <b>B.</b> The frequency distribution by mutation class is indicated for SWI/SNF subunit genes (<i>right</i>) and for all exome-sequenced genes (<i>left</i>). Note, the class distribution of SWI/SNF mutations is significantly skewed towards deleterious mutations (<i>P</i> = 1.0×10⁻¹⁸, chi-square test). Refer to Methods for a detailed description of these data.</p

Exome studies analyzed.

<p>Exome studies analyzed.</p

SWI/SNF mutations are not mutually exclusive of mutations in other commonly mutated genes.

<p>For each panel, rows correspond to tumor samples and columns correspond to genes. Within the matrices, blue corresponds to a nonsynonymous mutation while grey corresponds to no reported mutation. The rows are ordered first based on the SWI/SNF mutational status and second on the cancer subtype (annotated in alternating black and brown text, <i>left</i>). <b>A.</b> The mutational status of the 189 most-highly mutated genes across the exome studies, in relation to SWI/SNF mutational status. The 189 genes are rank-ordered from left to right, from those most mutationally-inclusive to those most mutationally-exclusive with SWI/SNF mutations. <b>B.</b> Zoomed-in view of the mutational status of the four most-exclusive gene mutations (<i>FAT2</i>, <i>NEB</i>, <i>CSMD1</i>, <i>SF3B1</i>); none reach statistical significance. Additional discussion is provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055119#pone.0055119.s004" target="_blank">Text S1</a>. <b>C.</b> Zoomed-in view of the mutational status of select cancer genes. These genes are denoted by an asterisk in panel <i>A</i>. Additional discussion is provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055119#pone.0055119.s004" target="_blank">Text S1</a>.</p

Co-occurrence of mutated SWI/SNF subunits.

<p>Heatmaps depict the mutation status of each SWI/SNF subunit gene in each tumor sample, shown for the seven tumor types with the highest frequency of SWI/SNF mutations. Rows and columns represent tumor samples and SWI/SNF subunit genes, respectively. Blue indicates the presence of a nonsynonymous mutation. Samples with mutations in two different SWI/SNF subunits are identified by a red arrow. <i>TP53</i> mutations are also indicated, as are <i>EZH2</i> activating mutations for the DLBCL study (<i>lower left</i> panel).</p

Integration of RNAseq, ChIPseq and TCGA data.

<p>^aAmplified/highly-expressed <i>vs</i>. non-amplified/highly-expressed (FDR<10%)</p><p>Integration of RNAseq, ChIPseq and TCGA data.</p

Integrative Genomics Implicates EGFR as a Downstream Mediator in <i>NKX2-1</i> Amplified Non-Small Cell Lung Cancer

<div><p><i>NKX2-1</i>, encoding a homeobox transcription factor, is amplified in approximately 15% of non-small cell lung cancers (NSCLC), where it is thought to drive cancer cell proliferation and survival. However, its mechanism of action remains largely unknown. To identify relevant downstream transcriptional targets, here we carried out a combined NKX2-1 transcriptome (NKX2-1 knockdown followed by RNAseq) and cistrome (NKX2-1 binding sites by ChIPseq) analysis in four <i>NKX2-1</i>-amplified human NSCLC cell lines. While NKX2-1 regulated genes differed among the four cell lines assayed, cell proliferation emerged as a common theme. Moreover, in 3 of the 4 cell lines, epidermal growth factor receptor (EGFR) was among the top NKX2-1 upregulated targets, which we confirmed at the protein level by western blot. Interestingly, EGFR knockdown led to upregulation of NKX2-1, suggesting a negative feedback loop. Consistent with this finding, combined knockdown of NKX2-1 and EGFR in NCI-H1819 lung cancer cells reduced cell proliferation (as well as MAP-kinase and PI3-kinase signaling) more than knockdown of either alone. Likewise, NKX2-1 knockdown enhanced the growth-inhibitory effect of the EGFR-inhibitor erlotinib. Taken together, our findings implicate EGFR as a downstream effector of NKX2-1 in <i>NKX2-1</i> amplified NSCLC, with possible clinical implications, and provide a rich dataset for investigating additional mediators of NKX2-1 driven oncogenesis.</p></div

Combined NKX2-1 and EGFR knockdown reduces cell proliferation and MAPK/PI3K signaling.

<p>(A) Combined knockdown of NKX2-1 and EGFR reduces H1819 cell proliferation more than either alone. **, <i>P</i>-value < 0.01; ***, <i>P</i>-value < 0.001 (two tailed Student’s t-test). (B) Combined knockdown of NKX2-1 and EGFR in H1819 cells diminishes MAPK signaling (p-MAPK) and PI3K signaling (p-AKT) more than either alone. Percent residual indicated; levels normalized to α-tubulin loading control. Note, in the particular western shown, EGFR knockdown does not appear to increase NKX2-1 levels appreciably, although the increase has been reproducibly observed in multiple other experiments (e.g. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142061#pone.0142061.g004" target="_blank">Fig 4C</a>, and Figure B, Panel H in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142061#pone.0142061.s002" target="_blank">S2 File</a>). (C) NKX2-1 knockdown collaborates with EGFR inhibitor erlotinib to inhibit H1819 cell growth ***, <i>P</i>-value ≤ 0.001 (two tailed Student’s t-test).</p

NKX2-1 regulates EGFR levels, with negative feedback.

<p>(A) NKX2-1 knockdown leads to reduced EGFR protein levels quantified by western blot (% residual indicated). Levels normalized to α-tubulin loading control. (B) EGFR knockdown by siRNA reduces cell proliferation comparable to NKX2-1 knockdown (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142061#pone.0142061.g001" target="_blank">Fig 1A</a>). **, <i>P</i>-value < 0.01 (two tailed Student’s t-test). (C) EGFR knockdown leads to elevated NKX2-1 protein levels (% increase indicated; levels normalized to α-tubulin loading control), suggesting negative feedback regulation.</p

Characterization of <i>NKX2-1</i> amplified and growth-dependent NSCLC cell lines.

<p>(A) Efficient siRNA-mediated NKX2-1 knockdown in four NSCLC cell lines, demonstrated by western blot. NTC, non-targeting control. α-tubulin serves as a loading control. (B) NKX2-1 knockdown leads to significantly reduced cell proliferation, measured by WST-1 viability assay. ***, <i>P</i>-value < 0.001 (two-tailed Student’s t-test).</p