Disentangling oncogenic amplicons in esophageal adenocarcinoma.

Esophageal adenocarcinoma is a prominent example of cancer characterized by frequent amplifications in oncogenes. However, the mechanisms leading to amplicons that involve breakage-fusion-bridge cycles and extrachromosomal DNA are poorly understood. Here, we use 710 esophageal adenocarcinoma cases with matched samples and patient-derived organoids to disentangle complex amplicons and their associated mechanisms. Short-read sequencing identifies ERBB2, MYC, MDM2, and HMGA2 as the most frequent oncogenes amplified in extrachromosomal DNAs. We resolve complex extrachromosomal DNA and breakage-fusion-bridge cycles amplicons by integrating of de-novo assemblies and DNA methylation in nine long-read sequenced cases. Complex amplicons shared between precancerous biopsy and late-stage tumor, an enrichment of putative enhancer elements and mobile element insertions are potential drivers of complex amplicons' origin. We find that patient-derived organoids recapitulate extrachromosomal DNA observed in the primary tumors and single-cell DNA sequencing capture extrachromosomal DNA-driven clonal dynamics across passages. Prospectively, long-read and single-cell DNA sequencing technologies can lead to better prediction of clonal evolution in esophageal adenocarcinoma.

Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia.

Intestinal metaplasia in the esophagus (Barrett's esophagus IM, or BE-IM) and stomach (GIM) are considered precursors for esophageal and gastric adenocarcinoma, respectively. We hypothesize that BE-IM and GIM follow parallel developmental trajectories in response to differing inflammatory insults. Here, we construct a single-cell RNA-sequencing atlas, supported by protein expression studies, of the entire gastrointestinal tract spanning physiologically normal and pathologic states including gastric metaplasia in the esophagus (E-GM), BE-IM, atrophic gastritis, and GIM. We demonstrate that BE-IM and GIM share molecular features, and individual cells simultaneously possess transcriptional properties of gastric and intestinal epithelia, suggesting phenotypic mosaicism. Transcriptionally E-GM resembles atrophic gastritis; genetically, it is clonal and has a lower mutational burden than BE-IM. Finally, we show that GIM and BE-IM acquire a protumorigenic, activated fibroblast microenvironment. These findings suggest that BE-IM and GIM can be considered molecularly similar entities in adjacent organs, opening the path for shared detection and treatment strategies. SIGNIFICANCE: Our data capture the gradual molecular and phenotypic transition from a gastric to intestinal phenotype (IM) in the esophagus and stomach. Because BE-IM and GIM can predispose to cancer, this new understanding of a common developmental trajectory could pave the way for a more unified approach to detection and treatment. See related commentary by Stachler, p. 1291. This article is highlighted in the In This Issue feature, p. 1275.

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.

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

BACKGROUND: 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.

Comparative analysis of the AIB1 interactome in breast cancer reveals MTA2 as a repressive partner which silences E-Cadherin to promote EMT and associates with a pro-metastatic phenotype.

Steroid regulated cancer cells use nuclear receptors and associated regulatory proteins to orchestrate transcriptional networks to drive disease progression. In primary breast cancer, the coactivator AIB1 promotes estrogen receptor (ER) transcriptional activity to enhance cell proliferation. The function of the coactivator in ER+ metastasis however is not established. Here we describe AIB1 as a survival factor, regulator of pro-metastatic transcriptional pathways and a promising actionable target. Genomic alterations and functional expression of AIB1 associated with reduced disease-free survival in patients and enhanced metastatic capacity in novel CDX and PDX ex-vivo models of ER+ metastatic disease. Comparative analysis of the AIB1 interactome with complementary RNAseq characterized AIB1 as a transcriptional repressor. Specifically, we report that AIB1 interacts with MTA2 to form a repressive complex, inhibiting CDH1 (encoding E-cadherin) to promote EMT and drive progression. We further report that pharmacological and genetic inhibition of AIB1 demonstrates significant anti-proliferative activity in patient-derived models establishing AIB1 as a viable strategy to target endocrine resistant metastasis. This work defines a novel role for AIB1 in the regulation of EMT through transcriptional repression in advanced cancer cells with a considerable implication for prognosis and therapeutic interventions.

Pervasive lesion segregation shapes cancer genome evolution.

Cancers arise through the acquisition of oncogenic mutations and grow by clonal expansion1,2. Here we reveal that most mutagenic DNA lesions are not resolved into a mutated DNA base pair 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 characterize 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 multiallelic and combinatorial genetic diversity. The phasing of lesions enables 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.

A high-content RNAi screen reveals multiple roles for long noncoding RNAs in cell division.

Genome stability relies on proper coordination of mitosis and cytokinesis, where dynamic microtubules capture and faithfully segregate chromosomes into daughter cells. With a high-content RNAi imaging screen targeting more than 2,000 human lncRNAs, we identify numerous lncRNAs involved in key steps of cell division such as chromosome segregation, mitotic duration and cytokinesis. Here, we provide evidence that the chromatin-associated lncRNA, linc00899, leads to robust mitotic delay upon its depletion in multiple cell types. We perform transcriptome analysis of linc00899-depleted cells and identify the neuronal microtubule-binding protein, TPPP/p25, as a target of linc00899. We further show that linc00899 binds TPPP/p25 and suppresses its transcription. In cells depleted of linc00899, upregulation of TPPP/p25 alters microtubule dynamics and delays mitosis. Overall, our comprehensive screen uncovers several lncRNAs involved in genome stability and reveals a lncRNA that controls microtubule behaviour with functional implications beyond cell division.

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.

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.

Adaptation to AI Therapy in Breast Cancer Can Induce Dynamic Alterations in ER Activity Resulting in Estrogen-Independent Metastatic Tumors.

PURPOSE: Acquired resistance to aromatase inhibitor (AI) therapy is a major clinical problem in the treatment of breast cancer. The detailed mechanisms of how tumor cells develop this resistance remain unclear. Here, the adapted function of estrogen receptor (ER) to an estrogen-depleted environment following AI treatment is reported. EXPERIMENTAL DESIGN: Global ER chromatin immuno-precipitation (ChIP)-seq analysis of AI-resistant cells identified steroid-independent ER target genes. Matched patient tumor samples, collected before and after AI treatment, were used to assess ER activity. RESULTS: Maintained ER activity was observed in patient tumors 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 that develop steroid independence. The Kaplan-Meier analysis revealed a significant association between tumors, which fail to decrease this steroid-independent ER target gene set in response to neoadjuvant AI therapy, and poor disease-free survival and overall survival (n = 72 matched patient tumor 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 tumors in comparison with matched primary tissue. However, evidence from distant metastatic tumors demonstrates that the ER signaling network may undergo further adaptations with disease progression as estrogen-independent ER target gene expression is routinely lost in established metastatic tumors. CONCLUSIONS: Overall, these data provide evidence of a dynamic ER response to endocrine treatment that may provide vital clues for overcoming the clinical issue of therapy resistance. Clin Cancer Res; 22(11); 2765-77. ©2016 AACR.

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.

Coassociation of estrogen receptor and p160 proteins predicts resistance to endocrine treatment; SRC-1 is an independent predictor of breast cancer recurrence.

PURPOSE: This study investigates the role of the p160 coactivators AIB1 and SRC-1 independently, and their interactions with the estrogen receptor, in the development of resistance to endocrine treatments. EXPERIMENTAL DESIGN: The expression of the p160s and the estrogen receptor, and their interactions, was analyzed by immunohistochemistry and quantitative coassociation immunofluorescent microscopy, using cell lines, primary breast tumor cell cultures, and a tissue microarray with breast cancer samples from 560 patients. RESULTS: Coassociation of the p160s and estrogen receptor alpha was increased in the LY2 endocrine-resistant cell line following treatment with tamoxifen in comparison with endocrine-sensitive MCF-7 cells. In primary cultures, there was an increase in association of the coactivators with estrogen receptor alpha following estrogen treatment but dissociation was evident with tamoxifen. Immunohistochemical staining of the tissue microarray revealed that SRC-1 was a strong predictor of reduced disease-free survival (DFS), both in patients receiving adjuvant tamoxifen treatment and untreated patients (P < 0.0001 and P = 0.0111, respectively). SRC-1 was assigned a hazard ratio of 2.12 using a Cox proportional hazards model. Endocrine-treated patients who coexpressed AIB1 with human epidermal growth factor receptor 2 had a significantly shorter DFS compared with all other patients (P = 0.03). Quantitative coassociation analysis in the patient tissue microarray revealed significantly stronger colocalization of AIB1 and SRC-1 with estrogen receptor alpha in patients who have relapsed in comparison with those patients who did not recur (P = 0.026 and P = 0.00001, respectively). CONCLUSIONS: SRC-1 is a strong independent predictor of reduced DFS, whereas the interactions of the p160 proteins with estrogen receptor alpha can predict the response of patients to endocrine treatment.

Cyclooxygenase-2 predicts adverse effects of tamoxifen: a possible mechanism of role for nuclear HER2 in breast cancer patients.

Cyclooxygenase-2 (COX-2) is associated with breast tumour progression. Clinical and molecular studies implicate human epidermal growth factor receptor 2 (HER2) in the regulation of COX-2 expression. Recent reports raise the possibility that HER2 could mediate these effects through direct transcriptional mechanisms. The relationship between HER2 and COX-2 was investigated in a cohort of breast cancer patients with or without endocrine treatment. A tissue microarray comprising tumours from 560 patients with 10-year follow-up was analysed for HER2, ERK1/2, polyoma enhancer activator 3 (PEA3) and COX-2 expression. Subcellular localisation of HER2 was assessed by immunofluorescence and confocal microscopy. Expression of markers examined was analysed in relation to classic clinicopathological parameters and disease-free survival in the presence and absence of tamoxifen. COX-2 expression associated with both membranous and nuclear expression of HER2 (P=0.0033 and P<0.00001 respectively). No association was detected between COX-2 and either ERK1/2 or PEA3 (P=0.7 and P=0.3 respectively). None of the markers were found to be independently prognostic. Membrane HER2, nuclear HER2 and COX-2, however, were all found to predict poor disease-free survival in patients on endocrine treatment (P=0.0017, P=0.0003 and P=0.0202 respectively). Moreover, patients who were positive for COX-2 predicted adverse effects of tamoxifen (P=0.0427). These clinical ex vivo data are consistent with molecular observations that HER2 can regulate COX-2 expression through direct transcriptional mechanisms. COX-2 expression correlates with disease progression on endocrine treatment. This study supports a role for COX-2 as a predictor of adverse effects of tamoxifen in breast cancer patients.