CASE STUDY Harnessing Multi-Omic Technologies to Reveal Novel
Non-Coding Regulatory Elements in Cancer Genomes
Coupling CRISPR, single-cell RNA sequencing, and Hi-C technologies revealed novel noncoding regulatory elements that contribute to oncogenic transcriptional programming and cellproliferation of ER+ breast cancer cells.

Breast cancer is the most common cancer among women, withmore than 2 million new cases reported in 2020, according to theWorld Health Organization1. In about 70% of breast cancer cases,
the transcription factor Estrogen Receptor Alpha (ERS1) is a prime
oncological driver contributing to tumor growth and diseaseprogression2. Estrogen Receptor (ER) can bind directly to DNA oralter transcriptome programming by engaging other transcription
factors (TF), producing genes such as CCND1, which regulates
CDK kinases and can cause alterations to the cell cycle.

Multi-Omic Approachto Understanding Estrogen Receptor
15,000 putative transcriptional
regulatory elements (TREs)

Hi-C

Through RNA analysis, ER was found to regulate approximately
3,000 genes; however, RNA analysis alone cannot elucidate
which of these genes or regulatory elements contribute tocell proliferation or other functions necessary for an oncogenicphenotype.

Challenge: Mapping the Cistrome 		of Cancer Cells
To overcome the limitations of RNA analysis, scientists havedeveloped an approach that couples CRISPR-Cas9, scRNA-seq,
and Hi-C technologies to help screen genes and transcriptional
regulatory elements (TREs) and reveal their mechanisms as wellas contributions to cancer progression.
Researchers from Novartis Institute for Biomedical Researchin Basel, Switzerland, harnessed the power of Arima Hi-C andCROP-seq to perform a comprehensive survey, screening TREs
associated with ER+ breast cancer. By combining CRISPR screenswith epigenetic profiling, the team was able to map the cistromeof cancer cells.

CRISPR-based
screening

scRNA-seq

CROP-seq

Identification of critical ER target genes anda novel potential biomarker of breast cancer
Figure 1. Lopes et al. employed a novel framework including Arima Hi-C technology forcharacterizing how oncogenic transcription factors can engage specific transcriptional regulatory
elements to impose their pathogenic program3.

“Hi-C is a powerful tool for conducting genome-wideanalyses. We used Hi-C to narrow down the window of
the scRNA-seq data and were able to successfully dissecta transcriptional regulatory network and identify thefunction of non-coding elements of cancer cells.”­– Giorgio G. Galli, PhD, Group Leader, Oncology Drug Discovery
Biology, Novartis Institutes for Biomedical ResearchApproach: Dissecting the TranscriptionalRegulatory Networks of ER+ Breast Cancer
Cells
The Drug Discovery Team at Novartis performed a cellproliferation–based CRISPRi screening to identify criticalregulatory elements contributing to ESR1 and CCND1 expression.
In addition, Hi-C experiments were used to confirm DNADNA interactions between genetic elements and ESR1 orCCND1. Based on this, researchers identified several criticaltranscriptional regulatory elements which contribute to ESR1 andCCND1 expression in ER+ breast cancer cells.

Hi-C data is a powerful high throughput method to obtain thefunctional contributions of TREs on oncogenic programming.
Through this multi-omic technique, the Novartis team was able
to unveil the network of critical transcription factors of ER. The
results demonstrate that perturbing GATA3_+1.1Mb downregulates GATA3 expression, a known cofactor of ER, and thus
contributes to ER+ breast cancer proliferation. Hi-C analysis also
discovered that TFAP2C is linked to a region ~30kb upstreamof its transcription start site — this region is denoted as atranscriptional enhancer of TFAP2C, or TET. Lower levels of TFAP2C
are associated with a better patient prognosis and have beenfound to mainly regulate metabolic genes and a small subset ofcritical ER targets.

Previous ChIP-seq analysis revealed 15,000 ER binding sites, themajority of which have never been assessed for their functional
contributions to oncogenic programming and cell proliferation. To
that end, researchers designed a comprehensive CRISPR libraryand screened the ER binding sites for functional significance.
Notably, GATA3 was enriched at enhancers, while H3K27ac wasonly enriched at promoters. However, the CRISPR screen revealed
that only a couple of elements —1.65% of the tested regions —were required for ER-driven oncogenic programming.
To further dissect the transcriptional regulatory networks ofER+ breast cancer cells, researchers created 3D genome maps
using the Arima-HiC kit coupled with CROP-seq and functionalgenomics analysis. CROP-seq (CRISPR droplet sequencing)combines the power of CRISPR technologies with the highresolution functional analysis of scRNA-seq. Arima-HiC kitscomplement these methods by capturing the 3D genome foldingof cells. Together, these methods reveal how genes interact witheach other and how misfolding and misregulation can lead tocancer cell growth. This approach of combining CROP-seq andFigure 2. Hi-C 3D genome maps help reveal TFAP2C as a critical target gene of ER throughinteractions between TFAP2C and the Transcriptional Enhancer of TFAP2C (TET) 3.

To further uncover the critical role of TFAP2C in ER+ breastcancer, a knockdown was created using shRNAs targeting
TFAP2C and ESR1, which strongly impacted cell growth.
RNA-seq analysis showed 258 genes commonly regulated byTFAP2C and ESR1. The results demonstrate that ER triggers theexpression of TFAP2C and other TFs that play a critical role in theoncogenic programming of ER+ breast cancer cells.

Impact: Improved Understanding ofTranscriptional Regulation in Cancer
In this study, Novartis scientists investigated the transcriptional
regulatory networks of the ER cistrome at both the genome-scaleand single-cell level using a multi-omic approach, harnessing
the power of CRISPR screens, scRNA-seq, and Hi-C technologies.
Importantly, this study observed that only a small subset of ER
binding sites are implicated in cell fitness. Systematic analysesof regulatory networks revealed the interaction between ER anddownstream TFs previously unknown, such as TFAP2C, and thecontribution of TREs enriched in GATA3 and H3K27Ac signals.
Combining Hi-C, CRISPR, and RNA-seq is a powerful approach
to characterizing oncogenic transcriptional regulatory elements
and revealing unknown factors within transcriptional networks.
Furthermore, this approach can be applied in other models toadvance understanding of transcriptional regulation in cancer
and influence more robust diagnosis techniques, future drug
targets, and novel treatment methods.

Figure 3. Model depicting the cross-talk between Estrogen Receptor, TET, and TFAP2C inactivating downstream target genes 3.

Technology
Arima genome-wide HiC+enables 3D genome mapping
to identify how spatial
relationships in DNA structure
can impact gene regulationand disease processes.

References
1.

Breast Cancer. (2021). WHO Fact Sheet.

2.

Lei, J. T., et al. (2019). ESR1 alterations and metastasis in estrogen receptor
positive breast cancer. Journal of Cancer Metastasis and Treatment. 5,38.

3.

Lopes, R., et al., (2021). Systematic dissection of transcriptional regulatory
networks by genome-scale and single-cell CRISPR screens. Science advances,7(27), eabf5733.

Figure 4. The newly expanded understanding of the estrogen receptor regulatory network inbreast cancer cells 3.

Learn MoreWebinar: Next Generation
Epigenomics for Oncology:
Dissecting Noncoding Regulatory
Elements in Cancer Genomes

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