Single cell lineage tracing reveals clonal dynamics of anti-EGFR therapy resistance in triple negative breast cancer

Abstract

Although many primary triple negative breast cancers (TNBCs) have enhanced expression of epidermal growth factor receptor (EGFR), EGFR-targeted therapies have shown only variable and unpredictable clinical responses in TNBCs. Here we integrate cellular barcoding and single-cell transcriptomics methods to comprehensively characterize the subclonal dynamics of adaptation of TNBC cells in response to afatinib, tyrosine kinase inhibitor (TKI) that irreversibly inhibits EGFR. Integrated lineage tracing analysis on these cells uncovered a pre-existing subpopulation of cells composed of 192 clones (out of the initial 2,336) with distinct biological features, such as elevated IGFBP2 (Insulin-Like Growth Factor Binding Protein 2) expression levels. We demonstrate that IGFBP2 overexpression is sufficient to make TNBC cells tolerant to afatinib treatment by activating the compensatory IGF1-R signalling pathway. Finally, by using deep learning techniques, we devise an algorithm to predict the afatinib sensitivity of TNBC cells from the transcriptional status of identified marker genes of the afatinib response. Our findings provide a new understanding of EGFR-dependent hierarchy in TNBC.

Predicting drug response from single-cell expression profiles of tumours

“…Interestingly, the most overrepresented classes among the drugs predicted to selectively inhibit the afatinib-tolerant subpopulation were IGF1R, HDAC, and AKT/MTOR/PI3K inhibitors (Figure 3H). We have already shown that afatinib and IGF1R inhibitors have a strong synergistic effect on these cells (4), thus validating the DREEP predictions that IGF1R inhibitors should deplete the cell population that do not respond to afatinib in this cell line.…”

“…A positive or negative score means that the cell is predicted to be resistant or sensitive to bortezomib, respectively. ( F ) UMAP plot of 1,541 MDA-MB-468 cells from Pellecchia et al (4). Cells are colour-coded according to whether they belong to an afatinib-sensitive or tolerant lineage.…”

“…Next, we evaluated DREEP’s ability to identify innate drug-resistant cell populations and to suggest drug co-treatments. To this end, we used single cell data of the untreated barcoded MDA-MB-468 breast cancer cell line that we recently generated (4). This dataset includes 1,541 single cells from the untreated MDA-MB-468 cell line, each associated with a molecularly expressed barcode (i.e., lineage).…”

“…Finally, the surviving lineages were retrospectively mapped onto the single-cell sequencing data of the untreated barcoded MDA-MB-468 cells. This approach, known as “retrospective lineage tracing”, enabled the categorization of untreated MDA-MB-468 cells as either sensitive or tolerant to Afatinib and anti-EGFR treatments (4) (Figure 3F).…”

“…We show that DREEP can detect changes in drug sensitivity over time in the breast cancer cell line MCF7 and predict the emergence of drug resistance. Additionally, using molecular barcoded MDA-MB-468 cells (4), we show that our method can recognize innate drug-tolerant cell subpopulations and predict drug co-treatments that will inhibit all of them. Finally, we demonstrate that DREEP can accurately predict drug sensitivity within heterogeneous cancer cell populations of patient-derived cultures (PDCs) containing a mix of primary and metastatic cells derived from individuals with head and neck squamous cell carcinomas (23).…”