Provero, P. | Search bioRxiv

bioRxiv2018

Somatic mutability in cancer predicts the phenotypic relevance of germline mutations

Genomic sequence mutations in both the germline and somatic cells can be pathogenic. Several authors have observed that often the same genes are involved in cancer when mutated in somatic cells and in genetic diseases when mutated in the germline. Recent advances in high-throughput sequencing techniques have provided us with large databases of both types of mutations, allowing us to investigate this issue in a systematic way. Here we show that high-throughput data about the frequency of somatic mutations in the most common cancers can be used to predict the genes involved in abnormal phenotypes and diseases. The predictive power of somatic mutation patterns is largely independent of that of methods based on germline mutation frequency, so that they can be fruitfully integrated into algorithms for the prioritization of causal variants. Our results confirm the deep relationship between pathogenic mutations in somatic and germline cells, provide new insight into the common origin of cancer and genetic diseases and can be used to improve the identification of new disease genes.

genomics↗

bioRxiv2018

SP1 and STAT3 functionally synergize to induce the RhoU small GTPase and a subclass of non-canonical WNT responsive genes correlating with poor prognosis in breast cancer.

Breast cancer is a complex disease in which heterogeneity makes clinical management very challenging. Although breast cancer subtypes classified according to specific molecular features are associated to better or worse prognosis, the identification of specific markers predicting disease outcome within the single subtypes still lags behind. Both the non-canonical WNT and the STAT3 pathways are often constitutively activated in breast tumors, and both can induce the small GTPase RhoU gene transcription. Here we show that RhoU transcription can be triggered by both canonical and non-canonical WNT ligands via the activation of JNK and the recruitment of the SP1 transcription factor to the RhoU promoter, identifying for the first time SP1 as a JNK-dependent mediator of WNT signaling. RhoU down-regulation by silencing or treatment with JNK, SP1 or STAT3 inhibitors lead to impaired cell migration in basal-like MDA-MB-231 cells, which display constitutive activation of both the non-canonical WNT and STAT3 pathways. These data suggest that STAT3 and SP1 can cooperate to induce high RhoU expression and enhance migration of breast cancer cells. In vivo binding of both factors characterizes a group of SP1/STAT3 responsive genes belonging to the non-canonical WNT and the IL-6/STAT3 pathways. High expression of this signature is significantly correlated with poor prognosis across all profiled patients. Thus, concomitant binding of both STAT3 and SP1 defines a subclass of genes contributing to breast cancer aggressiveness, suggesting the relevance of developing novel targeted therapies combining inhibitors of the STAT3 and WNT pathways or of their downstream mediators.\n\nNovelty and ImpactThe WNT and STAT3 pathways are often activated in breast tumors, but whether they can cooperate towards aggressiveness is not presently known. Here the authors show that WNT ligands can elicit the activation of the transcription factor SP1, which cooperates with STAT3 to induce a subset of non-canonical WNT and IL-6/STAT3 genes. Expression of this gene signature correlates with bad prognosis in breast cancer, suggesting coordinated interference with both TFs as a novel therapeutic option.

cancer biology↗

bioRxiv2017

Evolutionary rewiring of the human regulatory network by waves of genome expansion

Genome expansion is believed to be an important driver of the evolution of gene regulation. To investigate the role of newly arising sequence in rewiring the regulatory network we estimated the age of each region of the human genome by applying maximum parsimony to genome-wide alignments with 100 vertebrates. We then studied the age distribution of several types of functional regions, with a focus on regulatory elements. The age distribution of regulatory elements reveals the extensive use of newly formed genomic sequence in the evolution of regulatory interactions. Many transcription factors have expanded their repertoire of targets through waves of genomic expansions that can be traced to specific evolutionary times. Repeated elements contributed a major part of such expansion: many classes of such elements are enriched in binding sites of one or a few specific transcription factors, whose binding sites are localized in specific portions of the element and characterized by distinctive motif words. These features suggest that the binding sites were available as soon as the new sequence entered the genome, rather than being created later by accumulation of point mutations. By comparing the age of regulatory regions to the evolutionary shift in expression of nearby genes we show that rewiring through genome expansion played an important role in shaping the human regulatory network.

evolutionary biology↗

bioRxiv2017

Patterns of cancer somatic mutations predict genes involved in phenotypic abnormalities and genetic diseases

Genomic sequence mutations in both the germline and somatic cells can be pathogenic. Several authors have observed that often the same genes are involved in cancer when mutated in somatic cells and in genetic diseases when mutated in the germline. Recent advances in high-throughput sequencing techniques have provided us with large databases of both types of mutations, allowing us to investigate this issue in a systematic way. Here we show that high-throughput data about the frequency of somatic mutations in the most common cancers can be used to predict the genes involved in abnormal phenotypes and diseases. The predictive power of somatic mutation patterns is largely independent of that of methods based on germline mutation frequency, so that they can be fruitfully integrated into algorithms for the prioritization of causal variants. Our results confirm the deep relationship between pathogenic mutations in somatic and germline cells, provide new insight into the common origin of cancer and genetic diseases and can be used to improve the identification of new disease genes.

genomics↗