HCA Data Explorer

A single-cell atlas of breast cancer cell lines to study tumour heterogeneity and drug response

Updated January 26, 2023

Breast Cancer (BC) patient stratification is mainly driven by tumour receptor status and histological grading and subtyping, with about twenty percent of patients for which absence of any actionable biomarkers results in no clear therapeutic intervention to apply. Here, we evaluated the potential of single-cell transcriptomics for automated diagnosis and drug treatment of breast cancer. We transcriptionally profiled 35,276 individual cells from 32 BC cell-lines covering all main BC subtypes to yield a Breast Cancer Single Cell Atlas. We show that single cell transcriptomics can successfully detect clinically relevant BC biomarkers and that atlas can be used to automatically predict cancer subtype and composition from a patient’s tumour biopsy. We found that BC cell lines harbour a high degree of heterogeneity in the expression of clinically relevant BC biomarkers and that such heterogeneity enables cells with differential drug sensitivity to co-exist even within a genomically stable isogenic cell line. Finally, we developed a novel bioinformatics approach named DREEP (Drug Response Estimation from Expression Profiles) to automatically predict responses to more than 450 anticancer agents starting from single-cell transcriptional profiles. We validated DREEP both in-silico and in-vitro by selectively inhibiting the growth of the HER2-deficient subpopulation in the MDAMB361 cell line. Our work shows that transcriptional heterogeneity is common, dynamic and that its plasticity plays a relevant role in determining drug sensitivity. Moreover, our Breast Cancer Single Cell Atlas and DREEP approach are a unique resource for the BC research community and to advance the use of single-cell sequencing in the clinic. Overall design: Single-cell sequencing of 32 breast cancer cell-lines

Gennaro GambardellaTelethon Institute of Genetics and Medicine (TIGEM)gambardella@tigem.it
Gennaro Gambardella (Experimental Scientist)1
1Telethon Institute of Genetics and Medicine (TIGEM)
Brittney D Wick

To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/6663070f-fd8b-41a9-a479-2d1e07afa201
None
GEO Series Accessions:INSDC Project Accessions:INSDC Study Accessions:

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Analysis Portals

None

Project Label

breastCancerCellLinesAtlas

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

breast

Organ Part

7 organ parts

Selected Cell Types

Unspecified

Disease Status (Specimen)

5 disease statuses

Disease Status (Donor)

5 disease statuses

Development Stage

human adult stage

Library Construction Method

Drop-seq

Nucleic Acid Source

single cell

Paired End

true

Analysis Protocol

analysis_protocol_1

File Format

3 file formats

Cell Count Estimate

35.3k

Donor Count

32
fastq.gz68 file(s)txt.gz1 file(s)xlsx1 file(s)