Pseudo-temporal dynamics of chemoresistant triple negative breast cancer cells reveal EGFR/HER2 inhibition as synthetic lethal during mid-neoadjuvant chemotherapy
In the absence of targetable hormonal axes, chemoresistance for triple-negative breast cancer (TNBC) often compromises patient outcomes. To investigate the underlying tumor dynamics, we performed trajectory analysis on the single-nuclei RNA-seq (snRNA-seq) of chemoresistant tumor clones during neoad...
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Veröffentlicht in: | iScience 2023-02, Vol.26 (2), p.106064, Article 106064 |
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Zusammenfassung: | In the absence of targetable hormonal axes, chemoresistance for triple-negative breast cancer (TNBC) often compromises patient outcomes. To investigate the underlying tumor dynamics, we performed trajectory analysis on the single-nuclei RNA-seq (snRNA-seq) of chemoresistant tumor clones during neoadjuvant chemotherapy (NAC). It revealed a common tumor trajectory across multiple patients with HER2-like expansions during NAC. Genome-wide CRISPR-Cas9 knock-out on mammary epithelial cells revealed chemosensitivity-promoting knock-outs were up-regulated along the tumor trajectory. Furthermore, we derived a consensus gene signature of TNBC chemoresistance by comparing the trajectory transcriptome with chemoresistant transcriptomes from TNBC cell lines and poor prognosis patient samples to predict FDA-approved drugs, including afatinib (pan-HER inhibitor), targeting the consensus signature. We validated the synergistic efficacy of afatinib and paclitaxel in chemoresistant TNBC cells and confirmed pharmacological suppression of the consensus signature. The study provides a dynamic model of chemoresistant tumor transcriptome, and computational framework for pharmacological intervention.
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•Integrative model of pseudo-temporal dynamics in chemo-resistant TNBC is proposed•Chemo-resistant cell signatures are predictive of survival in bulk cohorts•Consensus signature is derived to predict FDA-approved drugs to synergize with paclitaxel•Afatinib efficacy is predicted and validated in TNBC cell lines by suppressing EGFR
Oncology; Cellular therapy; Computational bioinformatics |
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ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2023.106064 |