| Autor: |
Inayatullah, Mohammed, Mahesh, Arun, Turnbull, Arran K, Dixon, J Michael, Natrajan, Rachael, Tiwari, Vijay K |
| Zdroj: |
EMBO Molecular Medicine; Apr2024, Vol. 16 Issue 4, p823-853, 31p |
| Abstrakt: |
Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by extensive intratumoral heterogeneity, high metastasis, and chemoresistance, leading to poor clinical outcomes. Despite progress, the mechanistic basis of these aggressive behaviors remains poorly understood. Using single-cell and spatial transcriptome analysis, here we discovered basal epithelial subpopulations located within the stroma that exhibit chemoresistance characteristics. The subpopulations are defined by distinct signature genes that show a frequent gain in copy number and exhibit an activated epithelial-to-mesenchymal transition program. A subset of these genes can accurately predict chemotherapy response and are associated with poor prognosis. Interestingly, among these genes, elevated ITGB1 participates in enhancing intercellular signaling while ACTN1 confers a survival advantage to foster chemoresistance. Furthermore, by subjecting the transcriptional signatures to drug repurposing analysis, we find that chemoresistant tumors may benefit from distinct inhibitors in treatment-naive versus post-NAC patients. These findings shed light on the mechanistic basis of chemoresistance while providing the best-in-class biomarker to predict chemotherapy response and alternate therapeutic avenues for improved management of TNBC patients resistant to chemotherapy. Synopsis: Chemotherapy resistance is a key challenge in Triple-Negative Breast Cancer (TNBC). Combining single-cell, spatial and bulk transcriptome analysis with machine learning, we uncovered mechanisms of TNBC chemoresistance that provide biomarkers for chemotherapy response and novel avenues for therapy. Basal-epithelial subpopulations underlie chemoresistance in TNBC. Chemoresistance-associated basal-epithelial cells reside in close vicinity to stromal compartments within TNBC tumors and engage in enhanced intercellular communication. These subpopulations are defined by distinct signature genes that provide the best-in-class predictive biomarker of chemotherapy response. Drug repurposing analysis identified existing FDA-approved drugs that may benefit chemoresistant patients. Chemotherapy resistance is a key challenge in Triple-Negative Breast Cancer (TNBC). Combining single-cell, spatial and bulk transcriptome analysis with machine learning, we uncovered mechanisms of TNBC chemoresistance that provide biomarkers for chemotherapy response and novel avenues for therapy. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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