EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer.

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression.

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1, ETV1, CRKL, and ID4. Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC, on the same complex amplicons such as ecDNA. We characterized a MYC-ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC's enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.

Estrogen-induced chromatin looping changes identify a subset of functional regulatory elements.

Transcriptional enhancers can regulate individual or multiple genes through long-range three-dimensional (3D) genome interactions, and these interactions are commonly altered in cancer. Yet, the functional relationship between changes in 3D interactions associated with regulatory regions and differential gene expression appears context-dependent. In this study, we used HiChiP to capture changes in 3D genome interactions between active regulatory regions of endometrial cancer cells in response to estrogen treatment and uncovered significant differential long-range interactions that are strongly enriched for estrogen receptor α (ER) bound sites (ERBS). The ERBS anchoring differential loops with either a gene's promoter or distal regions were correlated with larger transcriptional responses to estrogen compared to ERBS not involved in differential interactions. To functionally test this observation, CRISPR-based Enhancer-i was used to deactivate specific ERBS, which revealed a wide range of effects on the transcriptional response to estrogen. However, these effects are only subtly and not significantly stronger for ERBS in differential loops. In addition, we observed an enrichment of 3D interactions between the promoters of estrogen up-regulated genes and found that looped promoters can work together cooperatively. Overall, our work suggests that changes in 3D genome structure upon estrogen treatment identify some functionally important regulatory regions; however, these changes aren't required for a transcriptional response to E2 in endometrial cancer cells.

Cis-regulatory control of transcriptional timing and noise in response to estrogen.

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Estrogen Receptor Alpha Mutations, Truncations, Heterodimers, and Therapies.

Annual breast cancer (BCa) deaths have declined since its apex in 1989 concomitant with widespread adoption of hormone therapies that target estrogen receptor alpha (ERα), the prominent nuclear receptor expressed in ∼80% of BCa. However, up to ∼50% of patients who are ER+ with high-risk disease experience post endocrine therapy relapse and metastasis to distant organs. The vast majority of BCa mortality occurs in this setting, highlighting the inadequacy of current therapies. Genomic abnormalities to ESR1, the gene encoding ERα, emerge under prolonged selective pressure to enable endocrine therapy resistance. These genetic lesions include focal gene amplifications, hotspot missense mutations in the ligand binding domain, truncations, fusions, and complex interactions with other nuclear receptors. Tumor cells utilize aberrant ERα activity to proliferate, spread, and evade therapy in BCa as well as other cancers. Cutting edge studies on ERα structural and transcriptional relationships are being harnessed to produce new therapies that have shown benefits in patients with ESR1 hotspot mutations. In this review we discuss the history of ERα, current research unlocking unknown aspects of ERα signaling including the structural basis for receptor antagonism, and future directions of ESR1 investigation. In addition, we discuss the development of endocrine therapies from their inception to present day and survey new avenues of drug development to improve pharmaceutical profiles, targeting, and efficacy.

ASPSCR1-TFE3 reprograms transcription by organizing enhancer loops around hexameric VCP/p97.

The t(X,17) chromosomal translocation, generating the ASPSCR1::TFE3 fusion oncoprotein, is the singular genetic driver of alveolar soft part sarcoma (ASPS) and some Xp11-rearranged renal cell carcinomas (RCCs), frustrating efforts to identify therapeutic targets for these rare cancers. Here, proteomic analysis identifies VCP/p97, an AAA+ ATPase with known segregase function, as strongly enriched in co-immunoprecipitated nuclear complexes with ASPSCR1::TFE3. We demonstrate that VCP is a likely obligate co-factor of ASPSCR1::TFE3, one of the only such fusion oncoprotein co-factors identified in cancer biology. Specifically, VCP co-distributes with ASPSCR1::TFE3 across chromatin in association with enhancers genome-wide. VCP presence, its hexameric assembly, and its enzymatic function orchestrate the oncogenic transcriptional signature of ASPSCR1::TFE3, by facilitating assembly of higher-order chromatin conformation structures demonstrated by HiChIP. Finally, ASPSCR1::TFE3 and VCP demonstrate co-dependence for cancer cell proliferation and tumorigenesis in vitro and in ASPS and RCC mouse models, underscoring VCP's potential as a novel therapeutic target.

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression.

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1 , ETV1 , CRKL , and ID4 . Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC , on the same complex amplicons such as ecDNA. We characterized a MYC - ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC 's enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.