RESUMO
Activation of oncogenic gene expression from long-range enhancers is initiated by the assembly of DNA-binding transcription factors (TF), leading to recruitment of co-activators such as CBP/p300 to modify the local genomic context and facilitate RNA-Polymerase 2 (Pol2) binding. Yet, most TF-to-coactivator recruitment relationships remain unmapped. Here, studying the oncogenic fusion TF PAX3-FOXO1 (P3F) from alveolar rhabdomyosarcoma (aRMS), we show that a single cysteine in the activation domain (AD) of P3F is important for a small alpha helical coil that recruits CBP/p300 to chromatin. P3F driven transcription requires both this single cysteine and CBP/p300. Mutants of the cysteine reduce aRMS cell proliferation and induce cellular differentiation. Furthermore, we discover a profound dependence on CBP/p300 for clustering of Pol2 loops that connect P3F to its target genes. In the absence of CBP/p300, Pol2 long range enhancer loops collapse, Pol2 accumulates in CpG islands and fails to exit the gene body. These results reveal a potential novel axis for therapeutic interference with P3F in aRMS and clarify the molecular relationship of P3F and CBP/p300 in sustaining active Pol2 clusters essential for oncogenic transcription.
Assuntos
RNA Polimerase II , Rabdomiossarcoma Alveolar , Humanos , RNA Polimerase II/genética , RNA Polimerase II/metabolismo , Cisteína/metabolismo , Fatores de Transcrição/metabolismo , Fator de Transcrição PAX3/genética , Rabdomiossarcoma Alveolar/genética , RNA/metabolismo , Ativação Transcricional , Ligação Proteica , Proteína Forkhead Box O1/metabolismoRESUMO
Non-coding regions amplified beyond oncogene borders have largely been ignored. Using a computational approach, we find signatures of significant co-amplification of non-coding DNA beyond the boundaries of amplified oncogenes across five cancer types. In glioblastoma, EGFR is preferentially co-amplified with its two endogenous enhancer elements active in the cell type of origin. These regulatory elements, their contacts, and their contribution to cell fitness are preserved on high-level circular extrachromosomal DNA amplifications. Interrogating the locus with a CRISPR interference screening approach reveals a diversity of additional elements that impact cell fitness. The pattern of fitness dependencies mirrors the rearrangement of regulatory elements and accompanying rewiring of the chromatin topology on the extrachromosomal amplicon. Our studies indicate that oncogene amplifications are shaped by regulatory dependencies in the non-coding genome.
Assuntos
Cromossomos Humanos/genética , Elementos Facilitadores Genéticos , Amplificação de Genes , Oncogenes , Acetilação , Sistemas CRISPR-Cas/genética , Linhagem Celular Tumoral , Sobrevivência Celular/genética , Cromatina/metabolismo , DNA de Neoplasias/genética , Receptores ErbB/genética , Receptores ErbB/metabolismo , Genes Neoplásicos , Loci Gênicos , Glioblastoma/genética , Glioblastoma/patologia , Histonas/metabolismo , Humanos , Neuroglia/metabolismoRESUMO
Great strides in gene discovery have been made using a multitude of methods to associate phenotypes with genetic variants, but there still remains a substantial gap between observed symptoms and identified genetic defects. Herein, we use the convergence of various genetic and genomic techniques to investigate the underpinnings of a constellation of phenotypes that include prostate cancer (PCa) and sensorineural hearing loss (SNHL) in a human subject. Through interrogation of the subject's de novo, germline, balanced chromosomal translocation, we first identify a correlation between his disorders and a poorly annotated gene known as lipid droplet associated hydrolase (LDAH). Using data repositories of both germline and somatic variants, we identify convergent genomic evidence that substantiates a correlation between loss of LDAH and PCa. This correlation is validated through both in vitro and in vivo models that show loss of LDAH results in increased risk of PCa and, to a lesser extent, SNHL. By leveraging convergent evidence in emerging genomic data, we hypothesize that loss of LDAH is involved in PCa and other phenotypes observed in support of a genotype-phenotype association in an n-of-one human subject.
Assuntos
Perda Auditiva Neurossensorial/genética , Neoplasias da Próstata/genética , Serina Proteases/genética , Translocação Genética/genética , Adulto , Idoso , Animais , Estudo de Associação Genômica Ampla , Células Germinativas/patologia , Perda Auditiva Neurossensorial/patologia , Humanos , Masculino , Camundongos , Camundongos Knockout , Fenótipo , Neoplasias da Próstata/patologiaRESUMO
Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC whole-genomes from 10 cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g., TERT and CDH10) and survival (e.g., CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217, and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. In conclusion, the screen for significant mutation patterns coupled with correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.
RESUMO
Sustained expression of the estrogen receptor-α (ESR1) drives two-thirds of breast cancer and defines the ESR1-positive subtype. ESR1 engages enhancers upon estrogen stimulation to establish an oncogenic expression program. Somatic copy number alterations involving the ESR1 gene occur in approximately 1% of ESR1-positive breast cancers, suggesting that other mechanisms underlie the persistent expression of ESR1. We report significant enrichment of somatic mutations within the set of regulatory elements (SRE) regulating ESR1 in 7% of ESR1-positive breast cancers. These mutations regulate ESR1 expression by modulating transcription factor binding to the DNA. The SRE includes a recurrently mutated enhancer whose activity is also affected by rs9383590, a functional inherited single-nucleotide variant (SNV) that accounts for several breast cancer risk-associated loci. Our work highlights the importance of considering the combinatorial activity of regulatory elements as a single unit to delineate the impact of noncoding genetic alterations on single genes in cancer.
Assuntos
Neoplasias da Mama/genética , Receptor alfa de Estrogênio/genética , Mutação , Polimorfismo de Nucleotídeo Único , Sistemas CRISPR-Cas , Linhagem Celular Tumoral , Feminino , Regulação Neoplásica da Expressão Gênica , Humanos , Células MCF-7 , Sequências Reguladoras de Ácido Nucleico , Fatores de Transcrição/metabolismoRESUMO
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.
Assuntos
Neoplasias da Mama/genética , Proteínas de Transporte/genética , Proteínas de Ciclo Celular/genética , Cromossomos Humanos Par 6/genética , Receptor alfa de Estrogênio/genética , Sequência de Bases , Neoplasias da Mama/metabolismo , Proteínas de Transporte/metabolismo , Proteínas de Ciclo Celular/metabolismo , Receptor alfa de Estrogênio/metabolismo , Feminino , Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Estudos de Associação Genética , Predisposição Genética para Doença , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único , Ligação Proteica , Fatores de RiscoRESUMO
BACKGROUND: The discovery of breast cancer subtypes and subsequent development of treatments aimed at them has allowed for a great reduction in the mortality of breast cancer. But despite this progress, tumors with similar characteristics that belong to the same subtype continue to respond differently to the same treatment. Five subtypes of breast cancer, namely intrinsic subtypes, have been characterized to date based on their gene expression profiles. Among other characteristics, subtypes vary in their degree of intra-subtype heterogeneity. It is not clear, however, whether this heterogeneity is shared across all tumor traits. It is also unclear whether individual traits can be highly heterogeneous among a majority of homogeneous traits. RESULTS: We employ network theory to uncover gene modules and accordingly consider them as tumor traits, which capture shared biological processes among the subtypes. We then use the ß-diversity metric from ecology to quantify the heterogeneity in these gene modules. In doing so, we show that breast cancer heterogeneity is contained in gene modules and that this modular heterogeneity increases monotonically across the subtypes. We identify a core of two modules that are shared among all subtypes which contain nucleosome assembly and mammary morphogenesis genes, and a number of modules that are specific to subtypes. This modular heterogeneity, which increases with global heterogeneity, relates to tumor aggressiveness. Indeed, we observe that Luminal A, the most treatable of subtypes, has the lowest modular heterogeneity whereas the Basal-like subtype, which is among the hardest to treat, has the highest. Furthermore, our analysis shows that a higher degree of global heterogeneity does not imply higher heterogeneity for all modules, as Luminal B shows the highest heterogeneity for core modules. CONCLUSIONS: Overall, modular heterogeneity provides a framework with which to dissect cancer heterogeneity and better understand its underpinnings, thereby ultimately advancing our knowledge towards a more effective personalized cancer therapy.