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

Multiple renal cancer susceptibility polymorphisms modulate the HIF pathway

<div><p>Un-physiological activation of hypoxia inducible factor (HIF) is an early event in most renal cell cancers (RCC) following inactivation of the von Hippel-Lindau tumor suppressor. Despite intense study, how this impinges on cancer development is incompletely understood. To test for the impact of genetic signals on this pathway, we aligned human RCC-susceptibility polymorphisms with genome-wide assays of HIF-binding and observed highly significant overlap. Allele-specific assays of HIF binding, chromatin conformation and gene expression together with eQTL analyses in human tumors were applied to mechanistic analysis of one such overlapping site at chromosome 12p12.1. This defined a novel stage-specific mechanism in which the risk polymorphism, rs12814794, directly creates a new HIF-binding site that mediates HIF-1α isoform specific upregulation of its target <i>BHLHE41</i>. The alignment of multiple sites in the HIF <i>cis</i>-acting apparatus with RCC-susceptibility polymorphisms strongly supports a causal model in which minor variation in this pathway exerts significant effects on RCC development.</p></div

Published renal cancer-associated susceptibility loci.

<p>Published renal cancer-associated susceptibility loci.</p

Allele-specific expression of <i>BHLHE41</i> is dependent on HIF-binding to rs12814794.

<p><b>A)</b> Schematic view of the chr 12p12.1 locus. The SNP rs12814794 at the HIF-binding enhancer and the intragenic SNP rs1048155 in the 3’ UTR of <i>BHLHE41</i> are indicated. <b>B)</b> Allele-specific qPCR experiments for rs1048155 using genomic DNA (gDNA) or complementary DNA (cDNA) derived from primary tubular cells of an individual heterozygous for rs1048155 and homozygous (AA) for rs12814794. Cells were exposed to 1 mM DMOG or left untreated. The allelic ratios B/A for signals from untreated or DMOG treated cDNA normalized to gDNA are shown on the right. No difference in allelic expression is measured at the intragenic SNP (ns, non-significant). The blue bar indicates the allelic ratio of gDNA. <b>C)</b> In these cells <i>BHLHE41</i> expression is not induced by DMOG. Expression levels of <i>BHLHE41</i> were normalized to the housekeeping gene HPRT and to values from the untreated control. Expression qPCR was performed in technical quadruplicates on one biological sample. Values are mean ± standard deviation. <b>D)</b> Allele-specific qPCR using gDNA and cDNA from an individual homozygous for the G allele at the HIF-binding enhancer. No difference in allelic expression is measured at the intragenic SNP. <b>E)</b> <i>BHLHE41</i> expression is induced in these cells by 1 mM DMOG. Expression qPCR was performed in technical quadruplicates on one biological sample. Values are mean ± standard deviation. <b>F)</b> Allele specific qPCR for gDNA and cDNA using PTC from an individual heterozygous for both SNPs. A significant shift in the allelic ratio of the intragenic SNP rs1048155 is detectable in DMOG treated cells. Mann-Whitney-Wilcoxon test: p<0.005. <b>G)</b> <i>BHLHE41</i> expression is induced by 1 mM DMOG. Expression qPCR was performed in technical quadruplicates on one biological sample. Values are mean ± standard deviation.</p

Allele specific HIF-binding at the rs12814794 associated enhancer.

<p><b>A)</b> rs12814794 defines a one base pair exchange (A>G) which creates a HIF-binding motif (AC<u>G</u>TG). <b>B)</b> Allele-specific qPCR for rs12814794 from DNA fragments isolated in HIF-ChIP experiments (HIF-1α and HIF-1β) or input DNA from primary renal tubular cells (PTC, n = 4 individuals). DNA from individuals homozygous for the AA or GG genotype were used as positive controls. <b>C)</b> Quantification of the two different alleles (A or G) at rs12814794 in the ChIP-seq reads from HIF-1α and HIF-1β immunoprecipitations (PTC #1 <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006872#pgen.1006872.g003" target="_blank">Fig 3</a>). <b>D)</b> Allele-specific qPCR for rs12814794 from DNA fragments isolated in FAIRE experiments or input DNA from primary renal tubular cells (PTC). DNA from individuals homozygous for the AA or GG genotype were used as positive controls. <b>E)</b> Quantification of the two different alleles (A or G) for rs12814794 present in reads from the FAIRE-seq experiment (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006872#pgen.1006872.g003" target="_blank">Fig 3a</a>: FAIRE track for PTC#1) and sequencing of the input. <b>F)</b> Allele-specific qPCR for rs12814794 from HIF-ChIP (HIF-1α, HIF-2α and HIF-1β) experiments in RCC L13 cells. DNA from control serum immunoprecipitations or input DNA from RCC L13 was used as controls. DNA from homozygous individuals (AA or GG) were used as controls for the two genotypes.</p

Non-random association between RCC GWAS loci and HIF-binding sites.

<p>4 RCC GWAS loci overlapped with 6 HIF ChIP-seq peaks. <b>A)</b> To assess the significance of this overlap, the expected number of co-localization events was calculated by randomly shuffling the GWAS loci around the genome. This was repeated 100,000 times and the frequency distribution for the number of shuffled GWAS sites that overlapped a HIF-binding site was plotted. The probability of observing 4 or more GWAS loci overlapping a HIF ChIP-seq peak is 1x10^-4 <b>B)</b> Conversely, HIF ChIP-seq peaks were randomly shuffled amongst all potential enhancer sites (as defined by the H3K27ac, H3K4me3, H3K4me1 in the same cell line 786-O), repeated 100,000 times and the frequency distribution for the number of shuffled HIF-binding sites that overlapped a GWAS site was plotted. The probability of observing 6 or more HIF-sites overlapping the GWAS sites is 9x10^-5.</p