Heterogeneous Effects of Direct Hypoxia Pathway Activation in Kidney Cancer

<div><p>General activation of hypoxia-inducible factor (HIF) pathways is classically associated with adverse prognosis in cancer and has been proposed to contribute to oncogenic drive. In clear cell renal carcinoma (CCRC) HIF pathways are upregulated by inactivation of the von-Hippel-Lindau tumor suppressor. However HIF-1<b>α</b> and HIF-2<b>α</b> have contrasting effects on experimental tumor progression. To better understand this paradox we examined pan-genomic patterns of HIF DNA binding and associated gene expression in response to manipulation of HIF-1<b>α</b> and HIF-2<b>α</b> and related the findings to CCRC prognosis. Our findings reveal distinct pan-genomic organization of canonical and non-canonical HIF isoform-specific DNA binding at thousands of sites. Overall associations were observed between HIF-1<b>α</b>-specific binding, and genes associated with favorable prognosis and between HIF-2<b>α</b>-specific binding and adverse prognosis. However within each isoform-specific set, individual gene associations were heterogeneous in sign and magnitude, suggesting that activation of each HIF-<b>α</b> isoform contributes a highly complex mix of pro- and anti-tumorigenic effects.</p></div

HIF-2α overexpression in 786-O cells.

<p>(A) HIF-2<b>α</b> binding sites in the HIF-2<b>α</b> overexpressing cells were identified by peak calling and ranked on the vertical axis according to signal intensity. Heat maps of these sites (±5kb on horizontal axis) showing ChIP-seq read density for the indicated HIF subunits were generated for both the control cells (i, ii) and the cells with HIF-2<b>α</b> overexpressed (iii, iv). In contrast to re-expressed HIF-1<b>α</b>, overexpressed HIF-2<b>α</b> binds to a large number of sites (compare i and iii), without HIF-1<b>β</b> (compare iii and iv) and has little effect on the distribution of HIF-1<b>β</b> (compare ii and iv). (B) Biplot showing Principal Component Analysis (PCA) of ChIP-seq signal intensity (RPKM values) for both individual binding sites (dots) and HIF-subunits (vectors) across all HIF-binding sites identified in control cells and in HIF-2<b>α</b> overexpressing cells. Sites binding endogenous HIF-2<b>α</b> in control cells are shown in blue while sites binding re-expressed HIF-1<b>α</b> are shown in red, sites binding both are colored purple and the remaining sites are colored grey. PCA for HIF subunits shows that HIF-2<b>α</b> and HIF-1<b>β</b> co-vary more closely in the control cells (compare HIF2<b>α</b>(VA) and HIF1<b>β</b>(VA)) than in the overexpressing cells (compare HIF2<b>α</b>(2<b>α</b>OE) and HIF1<b>β</b>(2<b>α</b>OE)). (C) Histogram of the distance to nearest transcription start site (TSS) for HIF-2<b>α</b> binding sites in cells overexpressing HIF-2<b>α</b>. (D) HIF-2<b>α</b> binding sites in the HIF-2<b>α</b> overexpressing cells were categorized according to the class (Ensemble) of the nearest gene. The relative frequency of each class is shown by pie chart. Gene set enrichment analysis (GSEA) for the set of genes nearest to (E) HIF-2<b>α</b> binding sites in the control cells and (F) newly identified HIF-2<b>α</b> binding sites in the overexpressing cells, when genes are ranked according to fold-change and significance in mRNA expression following overexpression of HIF-2<b>α</b> (horizontal axis).</p

HIF-1α and HIF-2α binding genes confer opposing prognosis in kidney cancer.

<p>(A) The genes nearest to re-expressed HIF-1<b>α</b> (blue bars) and overexpressed HIF-2<b>α</b> (red bars) binding sites were defined and examined for enrichment amongst genes annotated in different cancers using the Human Disease Ontology database (<a href="http://www.disease-ontology.org/" target="_blank">http://www.disease-ontology.org</a>).–log10 Binomial p-values are plotted for each set of HIF-binding genes in each type of cancer. Grey bar denotes p = 0.05 (-log10, 1.3) level of significance. HIF-2<b>α</b> nearest binding genes are consistently more significantly enriched amongst cancer-associated genes than are HIF-1<b>α</b> binding genes. (B) Differential HIF-1<b>α</b> binding genes or (C) differential HIF-2<b>α</b> binding genes were filtered for significant associations with overall survival and used to generate a weighted gene predictor of prognosis for each set of genes. Patients were then divided into those with above or below median values for each gene predictor and subjected to Kaplan-Meier survival analysis. The Cox proportional hazard model indicated a significant protective effect for patients with above median gene predictor values based on the HIF-1<b>α</b> binding genes. Conversely, patients with above median values for the HIF-2<b>α</b> binding gene predictor had a significantly worse prognosis.</p

Preferential distribution of AP-1 binding motifs at HIF-2α versus HIF-1α binding loci.

<p>In addition to a hypoxia response element (HRE) motif, analysis of sites binding endogenous and overexpressed HIF-2<b>α</b> also identified an AP-1 motif. For each site, the maximum normalized log likelihood ratio for the AP-1 motif in red and the HRE motif in blue is plotted on the vertical axis as a bar chart. A smooth spline cubic fit line is overlaid to show the trend. The smoothing parameter is automatically determined using a ‘leave-one-out’ cross validation as implemented by the Smooth.spline function in R. Sites were categorized as binding (A) re-expressed HIF-1<b>α</b>, (B) overexpressed HIF-2<b>α</b> and ranked according to the HIF-1<b>β</b> signal at each site. Spline fit curves are overlaid (solid/dashed lines) to indicate overall trends across both forward and reverse strands. (A) Sites binding re-expressed HIF-1<b>α</b> show specific enrichment (positive score) for the HRE motif that decreases as the HIF-1<b>β</b> signal falls. In contrast, these same sites show depletion of the AP-1 motif. (B) Sites binding overexpressed HIF-2<b>α</b> show enrichment of the HRE motif that declines more steeply as the HIF-1<b>β</b> signal falls. In contrast to sites binding re-expressed HIF-1<b>α</b>, those binding overexpressed HIF-2<b>α</b> show enrichment of the AP-1 motif that increases (and exceeds that seen for the HRE) as the HIF-1<b>β</b> signal falls.</p

HIF-1α re-expression in 786-O cells.

<p>(A) HIF-1<b>α</b> binding sites in the HIF-1<b>α</b> re-expressing cells were identified by peak calling and ranked on the vertical axis according to signal intensity. Heat maps of these sites (±5kb on horizontal axis) showing ChIP-seq read density for the indicated HIF subunits were generated for both the control cells (i, ii) and the HIF-1<b>α</b> re-expressing cells with HIF-1<b>α</b> re-introduced (iii-v). The pattern of HIF-2<b>α</b> binding is minimally affected by the re-expression of full-length HIF-1<b>α</b> (compare i and iii). Sites binding re-expressed HIF-1<b>α</b> are largely co-occupied by HIF-1<b>β</b> (compare iv and v). (B) Biplot showing Principal Component Analysis (PCA) of ChIP-seq signal intensity (RPKM values) for both individual binding sites (dots) and HIF-subunits (vectors) across all HIF-binding sites identified in control cells and in HIF-1<b>α</b> re-expressing cells. Sites binding endogenous HIF-2<b>α</b> in control cells are shown in blue while sites binding re-expressed HIF-1<b>α</b> are shown in red, sites binding both are colored purple and the remaining sites are shown in grey. PCA for each subunit shows high co-variance between HIF-2<b>α</b> binding in the control cells and in the HIF-1<b>α</b> re-expressing cells (compare HIF2<b>α</b>(VA) and (HIF2<b>α</b>(1<b>α</b>RE)). This indicates only minimal change in the HIF-2<b>α</b> binding as a consequence of the HIF-1<b>α</b> re-expression. Conversely, the HIF-1<b>β</b> vector changes dramatically with HIF-1<b>α</b> re-expression (compare HIF1<b>β</b>(VA) with HIF1<b>β</b>(1<b>α</b>RE)) and aligns closely with the vector for re-expressed HIF-1<b>α</b> (HIF1<b>α</b>(1<b>α</b>RE)). The individual binding sites in the control and HIF-1<b>α</b> re-expressing cells (blue and red dots) aligned closely with their respective PCA vectors. (C) Histogram of the distance to nearest transcription start site (TSS) for HIF-1<b>α</b> binding sites in cells re-expressing HIF-1<b>α</b>. (D) HIF-1<b>α</b> binding sites in the re-expressing cells were categorized according to the class (Ensemble) of the nearest gene. The relative frequency of each class is show by pie chart. (E) Gene set enrichment analysis (GSEA) for the set of genes nearest to HIF-1<b>α</b> binding sites when genes are ranked according to fold-change and significance in mRNA expression following re-expression of HIF-1<b>α</b> (horizontal axis).</p

Hydroxylation of HIFα and the chemical structures of IOX4 and other PHD inhibitors used in this study.

<p><b>(a)</b> Prolyl-hydroxylation (as catalyzed by the PHDs) of HIFα. <b>(b)</b> Structures of the dihydropyrazoles (<b>1</b> and <b>IOX4</b>) in comparison to structures of 2-oxoglutarate (<b>2OG</b>), <i>N</i>-oxalylglycine (<b>NOG</b>) (a catalytically inactive analogue of 2OG), dimethyloxalylglycine (<b>DMOG</b>) (a cell-permeable ester derivative of NOG) and <b>IOX2</b> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref009" target="_blank">9</a>]. Chemical structures of previously reported PHD inhibitors (compound <b>2</b>, bicyclic isoquinolinyl inhibitor <b>IOX3</b> and bicyclic naphthalenylsulfone hydroxythiazole <b>BNS</b>) used in this study are also shown.</p

Comparison of the binding modes of PHD inhibitors.

<p>Views from crystal structures of PHD2 complexed with <b>1</b> (<b>a</b>), <b>IOX3</b> (<b>b</b>), <b>2</b> (<b>e</b>) and <b>NOG</b> (<b>h</b>) Compound <b>1</b> coordinates the active site metal in a bidentate manner via the nitrogens of its pyridine (<i>trans</i> to His374 N<i>ε</i>2) and pyrazolone (<i>trans</i> to the Asp315 O<i>δ</i>1) rings as shown in <b>a</b>. A model of <b>IOX4</b> binding based on that of <b>1</b> (<b>d</b>) and the overlay of <b>a</b> and <b>d</b> (<b>g</b>) are shown for comparison. This coordination mode enables <b>1</b> to competitively inhibit PHD2 with respect to 2OG (as observed with the other inhibitors described here); the triazole ring of <b>1</b> is located in the 2OG C-5 carboxylate binding site whilst the carboxylate side chain of <b>1</b> makes electrostatic interaction with another arginine, R322 (1 carboxylate O–NH1 R322, 2.9 Å) that is located at the entrance of the active site; R322 is directly involved in substrate binding (P564/HIF1α CODD O–NH1 R322/PHD2, 2.6 Å; P564/CODD O–NH1 R322/PHD2, 2.8 Å) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref039" target="_blank">39</a>]. Compare <b>a</b>, <b>b</b> and <b>c</b> for differences in binding modes between <b>1</b> and <b>IOX3</b>; <b>a</b>, <b>e</b> and <b>f</b> for differences between <b>1</b> and <b>2</b>; <b>a</b>, <b>h</b> and <b>i</b> for differences between <b>1</b> and <b>NOG</b>. PDB ID: 4BQX (PHD2.IOX3) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref009" target="_blank">9</a>], 4BQW (PHD2.IOX2) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref009" target="_blank">9</a>]; 3HQR (PHD2.NOG.CODD) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref039" target="_blank">39</a>].</p

IOX4 induces HIFα in mice.

<p>(<b>a</b>) Immunoblots showing HIF1α and HIF2α induction in various mouse tissues (liver, brain, kidney, heart) after 1 h treatment at equimolar concentrations of <b>IOX2</b> (37.7 mg/kg), <b>IOX4</b> (35 mg/kg) or dimethyl <i>N</i>-oxalylglycine <b>DMOG</b> (75 mg/kg). (<b>b-c</b>) Immunoblot showing dose-dependent induction of HIF1α and HIF2α in the mouse liver (<b>b</b>) and in the mouse brain (<b>c</b>) after 1 h treatment by various doses of <b>IOX4</b> (17.5 to 70 mg/kg) in comparison to vehicle control and <b>DMOG</b> (160 mg/kg). n.s.: non-specific; l.e.: long exposure.</p

Selectivity profiling of the dihydropyrazoles 1 and IOX4 against a panel of human 2OG-dependent dioxygenases.

<p>The IC₅₀ values obtained reveal the selectivity of dihydropyrazoles <b>1</b> and <b>IOX4</b> for PHD2 in comparison with <b>IOX2</b> and <b>NOG</b>. Assays were carried out as previously reported [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref009" target="_blank">9</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref018" target="_blank">18</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref019" target="_blank">19</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132004#pone.0132004.ref038" target="_blank">38</a>].</p><p>PHD2: HIF-prolyl hydroxylase-2, JMJD1A (KDM3A): Lysine-specific demethylase 3A, JMJD2A (KDM4A): Lysine-specific demethylase 4A, JMJD2C (KDM4C): Lysine-specific demethylase 4C, JMJD2E (KDM4E): Lysine-specific demethylase 4E, JMJD3 (KDM6B): Lysine-specific demethylase 6B, FBXL11 (KDM2A): Lysine-specific demethylase 2A, JARID1C (KDM5C): Lysine-specific demethylase 5C, BBOX: γ-butyrobetaine hydroxylase, FIH: factor inhibiting HIF, FTO: fat mass and obesity associated protein.</p><p>Selectivity profiling of the dihydropyrazoles 1 and IOX4 against a panel of human 2OG-dependent dioxygenases.</p

Selective Small Molecule Probes for the Hypoxia Inducible Factor (HIF) Prolyl Hydroxylases

The hypoxia inducible factor (HIF) system is central to the signaling of low oxygen (hypoxia) in animals. The levels of HIF-α isoforms are regulated in an oxygen-dependent manner by the activity of the HIF prolyl-hydroxylases (PHD or EGLN enzymes), which are Fe­(II) and 2-oxoglutarate (2OG) dependent oxygenases. Here, we describe biochemical, crystallographic, cellular profiling, and animal studies on PHD inhibitors including selectivity studies using a representative set of human 2OG oxygenases. We identify suitable probe compounds for use in studies on the functional effects of PHD inhibition in cells and in animals