Biology subjects

Berrett, K. C.

Publications and source records attributed to Berrett, K. C..

7 recordsLinked to original sources

bioRxiv2021

A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology

Model systems that recapitulate the complexity of human tumors and the reality of variable treatment responses are urgently needed to better understand cancer biology and to develop more effective cancer therapies. Here we report development and characterization of a large bank of patient-derived xenografts (PDX) and matched organoid cultures from tumors that represent some of the greatest unmet needs in breast cancer research and treatment. These include endocrine-resistant, treatment-refractory, and metastatic breast cancers and, in some cases, multiple tumor collections from the same patients. The models can be grown long-term with high fidelity to the original tumors. We show that development of matched PDX and PDX-derived organoid (PDxO) models facilitates high-throughput drug screening that is feasible and cost-effective, while also allowing in vivo validation of results. Our data reveal consistency between drug screening results in organoids and drug responses in breast cancer PDX. Moreover, we demonstrate the feasibility of using these patient-derived models for precision oncology in real time with patient care, using a case of a triple negative breast cancer with early metastatic recurrence as an example. Our results uncovered an FDA-approved drug with high efficacy against the models. Treatment with the PDxO-directed therapy resulted in a complete response for the patient and a progression-free survival period more than three times longer than her previous therapies. This work provides valuable new methods and resources for functional precision medicine and drug development for human breast cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC="FIGDIR/small/433268v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@134d5cdorg.highwire.dtl.DTLVardef@1c0a419org.highwire.dtl.DTLVardef@556a4forg.highwire.dtl.DTLVardef@1b68c9c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design

BackgroundPooling cells from multiple biological samples prior to library preparation within the same single-cell RNA sequencing experiment provides several advantages, including lower library preparation costs and reduced unwanted technological variation, such as batch effects. Computational demultiplexing tools based on natural genetic variation between individuals provide a simple approach to demultiplex samples, which does not require complex additional experimental procedures. However, these tools have not been evaluated in cancer, where somatic variants, which could differ between cells from the same sample, may obscure the signal in natural genetic variation. ResultsHere, we performed in silico benchmark evaluations by combining raw sequencing reads from multiple single-cell samples in high-grade serous ovarian cancer, which has a high copy number burden, and lung adenocarcinoma, which has a high tumor mutational burden. Our results confirm that genetic demultiplexing tools can be effectively deployed on cancer tissue using a pooled experimental design, although high proportions of ambient RNA from cell debris reduce performance. ConclusionsThis strategy provides significant cost savings through pooled library preparation. To facilitate similar analyses at the experimental design phase, we provide freely accessible code and a reproducible Snakemake workflow built around the best-performing tools found in our in silico benchmark evaluations, available at https://github.com/lmweber/snp-dmx-cancer.

bioinformatics↗

bioRxiv2020

Estrogen receptor alpha mutations in breast cancer cells cause gene expression changes through constant activity and through secondary effects

While breast cancer patients with tumors that express estrogen receptor (ER) generally respond well to hormone therapies that block ER activity, a significant number of patients relapse. Approximately 30% of these recurrences harbor activating mutations in the ligand binding domain (LBD) of ER, which have been shown to confer ligand-independent function. However, much is still unclear regarding the effect of mutant ER beyond its estrogen independence. To investigate the molecular effects of mutant ER, we developed multiple isogenic ER mutant cell lines for the most common LBD mutations, Y537S and D538G. These mutations induced differential expression of thousands of genes, the majority of which were mutant allele-specific and were not observed upon estrogen treatment of wildtype cells. These mutant-specific genes showed consistent differential expression across ER mutant lines developed in other laboratories. Wildtype cells with long-term estrogen exposure only exhibited some of these transcriptional changes, suggesting that mutant ER causes novel regulatory effects that are not simply due to constant activity. While ER mutations exhibited minor effects on ER genomic binding, with the exception of ligand independence, ER mutations conferred substantial differences in chromatin accessibility. Mutant ER was bound to approximately a quarter of mutant-enriched accessible regions that were enriched for other DNA binding factors including FOXA1, CTCF, and OCT1. Overall, our findings indicate that mutant ER causes several consistent effects on gene expression, both indirectly and through constant activity.

cancer biology↗

bioRxiv2020

Regulatory Sharing Between Estrogen Receptor α Bound Enhancers

The human genome encodes an order of magnitude more gene expression enhancers than promoters, suggesting that most genes are regulated by the combined action of multiple enhancers. We have previously shown that neighboring estrogen-responsive enhancers, which are approximately 5,000 basepairs apart, exhibit complex synergistic contributions to the production of an estrogenic transcriptional response. Here we sought to determine the molecular underpinnings of the observed enhancer cooperativity. We generated genetic deletions of individual estrogen receptor (ER) bound enhancers and found that enhancers containing full estrogen response element (ERE) motifs control ER binding at neighboring sites, while enhancers with pre-existing histone acetylation/accessibility confer a permissible chromatin environment to the neighboring enhancers. Genome engineering revealed that a cluster of two enhancers with half EREs could not compensate for the lack of a full ERE site within the cluster. In contrast, two enhancers with full EREs produced a transcriptional response greater than the wild-type locus. By swapping genomic sequences between enhancers, we found that the genomic location in which a full ERE resides strongly influences enhancer activity. Our results lead to a model in which a full ERE is required for ER recruitment, but the presence of a pre-existing active chromatin environment within an enhancer cluster is also needed in order for estrogen-driven gene regulation to occur.

genetics↗

bioRxiv2019

ETV4 is necessary for estrogen signaling and growth in endometrial cancer cells

Estrogen signaling through estrogen receptor alpha (ER) plays a major role in endometrial cancer risk and progression; however, the molecular mechanisms underlying ERs regulatory role in endometrial cancer are poorly understood. In breast cancer cells, ER genomic binding is enabled by FOXA1 and GATA3, but the transcription factors that control ER genomic binding in endometrial cancer cells remain unknown. We previously identified ETV4 as a candidate factor controlling ER genomic binding in endometrial cancer cells and here we explore the functional importance of ETV4. Homozygous deletion of ETV4, using CRISPR/Cas9, led to greatly reduced ER binding at the majority of loci normally bound by ER. Consistent with the dramatic loss of ER binding, the gene expression response to estradiol was dampened for most genes. ETV4 contributes to estrogen signaling in two distinct ways; ETV4 loss impacts chromatin accessibility at some ER bound loci and impairs ER nuclear translocation. The diminished estrogen signaling upon ETV4 deletion led to decreased growth, particularly in 3D culture where hollow organoids were formed and in vivo in the context of estrogen dependent growth. Our results show that ETV4 plays an important role in estrogen signaling in endometrial cancer cells.

molecular biology↗

bioRxiv2018

Sufficiency analysis of estrogen responsive enhancers using synthetic activators

Multiple regulatory regions bound by the same transcription factor have been shown to simultaneously control a single genes expression. However, it remains unclear how these regulatory regions combine to regulate transcription. Here we test the sufficiency of promoter-distal estrogen receptor (ER)-binding sites (ERBS) for activating gene expression by recruiting synthetic activators in the absence of estrogens. Targeting either dCas9-VP16(10x) or dCas9-p300(core) to ERBS induces H3K27ac and activates nearby expression in a manner similar to an estrogen induction, with dCas9-VP16(10x) acting as a stronger activator. The sufficiency of individual ERBS is highly correlated with their necessity, indicating an inherent activation potential that is associated with the binding of RNA polymerase II and several transcription factors. By targeting ERBS combinations, we found that ERBS work independently to control gene expression when bound by synthetic activators. The sufficiency results contrast necessity assays that show synergy between these ERBS, suggesting that synergy occurs between ERBS in terms of activator recruitment, whereas directly recruiting activators leads to independent effects on gene expression.

systems biology↗

bioRxiv2018

Estrogen-independent molecular actions of mutant estrogen receptor alpha in endometrial cancer

Estrogen receptor 1 (ESR1) mutations have been identified in hormone therapy resistant breast cancer and primary endometrial cancer. Analyses in breast cancer suggests that mutant ESR1 exhibits estrogen independent activity. In endometrial cancer, ESR1 mutations are associated with worse outcomes and less obesity, however experimental investigation of these mutations has not been performed. Using a unique CRISPR/Cas9 strategy, we introduced the D538G mutation, a common endometrial cancer mutation that alters the ligand binding domain of ESR1, while epitope tagging the endogenous locus. We discovered estrogen-independent mutant ESR1 genomic binding that is significantly altered from wildtype ESR1. The D538G mutation impacted expression, including a large set of non-estrogen regulated genes, and chromatin accessibility, with most affected loci bound by mutant ESR1. Mutant ESR1 is unique from constitutive ESR1 activity as mutant-specific changes are not recapitulated with prolonged estrogen exposure. Overall, D538G mutant ESR1 confers estrogen-independent activity while causing additional regulatory changes in endometrial cancer cells that are distinct from breast cancer cells.

cancer biology↗