Defining and targeting transcription factors in cancer.

A report from the Keystone Symposium on Molecular and Cellular Biology, 'Deregulation of transcription in cancer: controlling cell fate decisions', Killarney, Ireland, 21-26 July 2009

Analysis of HER2 genomic binding in breast cancer cells identifies a global role in direct gene regulation.

HER2 is a transmembrane receptor tyrosine kinase, which plays a key role in breast cancer due to a common genomic amplification. It is used as a marker to stratify patients in the clinic and is targeted by a number of drugs including Trastuzumab and Lapatinib. HER2 has previously been shown to translocate to the nucleus. In this study, we have explored the properties of nuclear HER2 by analysing the binding of this protein to the chromatin in two breast cancer cell lines. We find genome-wide re-programming of HER2 binding after treatment with the growth factor EGF and have identified a de novo motif at HER2 binding sites. Over 2,000 HER2 binding sites are found in both breast cancer cell lines after EGF treatment, and according to pathway analysis, these binding sites were enriched near genes involved in protein kinase activity and signal transduction. HER2 was shown to co-localise at a small subset of regions demarcated by H3K4me1, a hallmark of functional enhancer elements and HER2/H3K4me1 co-bound regions were enriched near EGF regulated genes providing evidence for their functional role as regulatory elements. A chromatin bound role for HER2 was verified by independent methods, including Proximity Ligation Assay (PLA), which confirmed a close association between HER2 and H3K4me1. Mass spectrometry analysis of the chromatin bound HER2 complex identified EGFR and STAT3 as interacting partners in the nucleus. These findings reveal a global role for HER2 as a chromatin-associated factor that binds to enhancer elements to elicit direct gene expression events in breast cancer cells

Interplay of cis and trans mechanisms driving transcription factor binding and gene expression evolution

Noncoding regulatory variants play a central role in the genetics of human diseases and in evolution. Here we measure allele-specific transcription factor binding occupancy of three liver-specific transcription factors between crosses of two inbred mouse strains to elucidate the regulatory mechanisms underlying transcription factor binding variations in mammals. Our results highlight the pre-eminence of cis-acting variants on transcription factor occupancy divergence. Transcription factor binding differences linked to cis-acting variants generally exhibit additive inheritance, while those linked to trans-acting variants are most often dominantly inherited. Cis-acting variants lead to local coordination of transcription factor occupancies that decay with distance; distal coordination is also observed and may be modulated by long-range chromatin contacts. Our results reveal the regulatory mechanisms that interplay to drive transcription factor occupancy, chromatin state, and gene expression in complex mammalian cell states.We thank the CRUK—CI Genomics, BRU, and Bioinformatics Cores for technical assistance and the EMBL-EBI systems team for management of computational resources. This research was supported by the European Molecular Biology Laboratory (E.S.W., D.T., J.C.M., P.F.), Cancer Research UK (B.M.S., T.F.R., F.C., C.F., A.R., D.T.O.), the BOLD ITN (B.M.S.), Darwin Fellowship (A.K.), the Wellcome Trust (WT202878/B/16/Z, WT108749/Z/15/Z) (P.F.), (WT202878/A/16/Z) (D.T.O), (WT095606) (A.C.F.-S) and (WT098051) (P.F., D.T.O.), EMBO Long-term (ALTF1518-2012) and Advanced Fellowships (aALTF1672-2014) (E.S.W.), and by the European Research Council (award 615584) and EMBO Young Investigator Programme (D.T.O.)

Rearrangement processes and structural variations show evidence of selection in oesophageal adenocarcinomas

Oesophageal adenocarcinoma (OAC) provides an ideal case study to characterize large-scale rearrangements. Using whole genome short-read sequencing of 383 cases, for which 214 had matched whole transcriptomes, we observed structural variations (SV) with a predominance of deletions, tandem duplications and inter-chromosome junctions that could be identified as LINE-1 mobile element (ME) insertions. Complex clusters of rearrangements resembling breakage-fusion-bridge cycles or extrachromosomal circular DNA accounted for 22% of complex SVs affecting known oncogenes. Counting SV events affecting known driver genes substantially increased the recurrence rates of these drivers. After excluding fragile sites, we identified 51 candidate new drivers in genomic regions disrupted by SVs, including ETV5, KAT6B and CLTC. RUNX1 was the most recurrently altered gene (24%), with many deletions inactivating the RUNT domain but preserved the reading frame, suggesting an altered protein product. These findings underscore the importance of identification of SV events in OAC with implications for targeted therapies.</p

Rearrangement processes and structural variations show evidence of selection in oesophageal adenocarcinomas

Oesophageal adenocarcinoma (OAC) provides an ideal case study to characterize large-scale rearrangements. Using whole genome short-read sequencing of 383 cases, for which 214 had matched whole transcriptomes, we observed structural variations (SV) with a predominance of deletions, tandem duplications and inter-chromosome junctions that could be identified as LINE-1 mobile element (ME) insertions. Complex clusters of rearrangements resembling breakage-fusion-bridge cycles or extrachromosomal circular DNA accounted for 22% of complex SVs affecting known oncogenes. Counting SV events affecting known driver genes substantially increased the recurrence rates of these drivers. After excluding fragile sites, we identified 51 candidate new drivers in genomic regions disrupted by SVs, including ETV5, KAT6B and CLTC. RUNX1 was the most recurrently altered gene (24%), with many deletions inactivating the RUNT domain but preserved the reading frame, suggesting an altered protein product. These findings underscore the importance of identification of SV events in OAC with implications for targeted therapies.</p

LINE retrotransposons characterize mammalian tissue-specific and evolutionarily dynamic regulatory regions.

Funder: Helmholtz SocietyFunder: European Molecular Biology Laboratory; doi: http://dx.doi.org/10.13039/100013060BACKGROUND: To investigate the mechanisms driving regulatory evolution across tissues, we experimentally mapped promoters, enhancers, and gene expression in the liver, brain, muscle, and testis from ten diverse mammals. RESULTS: The regulatory landscape around genes included both tissue-shared and tissue-specific regulatory regions, where tissue-specific promoters and enhancers evolved most rapidly. Genomic regions switching between promoters and enhancers were more common across species, and less common across tissues within a single species. Long Interspersed Nuclear Elements (LINEs) played recurrent evolutionary roles: LINE L1s were associated with tissue-specific regulatory regions, whereas more ancient LINE L2s were associated with tissue-shared regulatory regions and with those switching between promoter and enhancer signatures across species. CONCLUSIONS: Our analyses of the tissue-specificity and evolutionary stability among promoters and enhancers reveal how specific LINE families have helped shape the dynamic mammalian regulome

Adaptation to AI therapy in breast cancer can induce dynamic alterations in ER activity resulting in estrogen independent metastatic tumours

PURPOSE: Acquired resistance to aromatase inhibitor therapy is a major clinical problem in the treatment of breast cancer. The detailed mechanisms of how tumour cells develop this resistance remain unclear. Here, the adapted function of ER to an estrogen-depleted environment following AI treatment is reported. EXPERIMENTAL DESIGN: Global ER-ChIPseq analysis of AI resistant cells identified steroid-independent ER target genes. Matched patient tumour samples, collected before and after AI treatment, were used to assess ER activity. RESULTS: Maintained ER activity was observed in patient tumours following neoadjuvant AI therapy. Genome-wide ER-DNA binding analysis in AI resistant cell lines identified a subset of classic ligand dependent ER target genes which develop steroid independence. Kaplan Meier analysis revealed a significant association between tumours which fail to decrease this steroid independent ER target gene set in response to neoadjuvant AI therapy, and poor disease-free and overall survival (n=72 matched patient tumour samples, p=0.00339 and 0.00155 respectively). The adaptive ER response to AI treatment was highlighted by the ER/AIB1 target gene, early growth response 3 (EGR3). Elevated levels of EGR3 were detected in endocrine resistant local disease recurrent patient tumours in comparison to matched primary tissue. However, evidence from distant metastatic tumours demonstrates that the ER signalling network may undergo further adaptations with disease progression as estrogen-independent ER target gene expression is routinely lost in established metastatic tumours. CONCLUSIONS: Overall, these data provide evidence of a dynamic ER response to endocrine treatment which may provide vital clues for overcoming the clinical issue of therapy resistance

Network analysis of SRC-1 reveals a novel transcription factor hub which regulates endocrine resistant breast cancer.

Steroid receptor coactivator 1 (SRC-1) interacts with nuclear receptors and other transcription factors (TFs) to initiate transcriptional networks and regulate downstream genes which enable the cancer cell to evade therapy and metastasise. Here we took a top-down discovery approach to map out the SRC-1 transcriptional network in endocrine resistant breast cancer. First, rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) was employed to uncover new SRC-1 TF partners. Next, RNA sequencing (RNAseq) was undertaken to investigate SRC-1 TF target genes. Molecular and patient-derived xenograft studies confirmed STAT1 as a new SRC-1 TF partner, important in the regulation of a cadre of four SRC-1 transcription targets, NFIA, SMAD2, E2F7 and ASCL1. Extended network analysis identified a downstream 79 gene network, the clinical relevance of which was investigated in RNAseq studies from matched primary and local-recurrence tumours from endocrine resistant patients. We propose that SRC-1 can partner with STAT1 independently of the estrogen receptor to initiate a transcriptional cascade and control regulation of key endocrine resistant genes

Pervasive lesion segregation shapes cancer genome evolution

Cancers arise through the acquisition of oncogenic mutations and grow through clonal expansion. Here we reveal that most mutagenic DNA lesions are not resolved as mutations within a single cell-cycle. Instead, DNA lesions segregate unrepaired into daughter cells for multiple cell generations, resulting in the chromosome-scale phasing of subsequent mutations. We characterise this process in mutagen-induced mouse liver tumours and show that DNA replication across persisting lesions can produce multiple alternative alleles in successive cell divisions, thereby generating both multi-allelic and combinatorial genetic diversity. The phasing of lesions enables the accurate measurement of strand biased repair processes, quantification of oncogenic selection, and fine mapping of sister chromatid exchange events. Finally, we demonstrate that lesion segregation is a unifying property of exogenous mutagens, including UV light and chemotherapy agents in human cells and tumours, which has profound implications for the evolution and adaptation of cancer genomes.This work was supported by: Cancer Research UK (20412, 22398), the European Research Council (615584, 682398), the Wellcome Trust (WT108749/Z/15/Z, WT106563/Z/14/A, WT202878/B/16/Z), the European Molecular Biology Laboratory, the MRC Human Genetics Unit core funding programme grants (MC_UU_00007/11, MC_UU_00007/16), and the ERDF/Spanish Ministry of Science, Innovation and Universities-Spanish State Research Agency/DamReMap Project (RTI2018-094095-B-I00)