Abstract
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 BHLHE41. The alignment of multiple sites in the HIF cis-acting apparatus with RCC-susceptibility polymorphisms strongly supports a causal model in which minor variation in this pathway exerts significant effects on RCC development.
Highlights
Successive advances in genetic analysis have provided insights into the biology of cancer
We aligned extragenic renal cancer risk polymorphisms identified by genome-wide association studies, with DNA binding sites for the hypoxia inducible factor (HIF) transcription factors, which are constitutively activated in renal cancer and observed striking overlap
Detailed analysis of one overlapping polymorphism revealed that the risk allele creates a new HIF-binding site in a cell-type stage-specific enhancer of its target BHLHE41
Summary
Successive advances in genetic analysis have provided insights into the biology of cancer. To date, such analyses have focused mainly on mutations that affect the integrity of transcribed genes. Though recent studies suggest that the majority of extragenic sequences are functional, these functions are less well defined [1]. They are likely to bear a more complex relationship to gene function than that of coding sequences. This problem is compounded by the extent of variation. Without a functional framework, it is difficult to impute causality by statistical methods that are agnostic to mechanism
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