Differential gene expression analysis of palbociclib-resistant TNBC via RNA-seq

Abstract

Purpose: The management of triple-negative breast cancer (TNBC) remains a significant clinical challenge due to the lack of effective targeted therapies. Inhibitors of the cyclin-dependent kinases 4 and 6 (CDK4/6) are emerging as promising therapeutic agents against TNBC; however, cells can rapidly acquire resistance through multiple mechanisms that are yet to be identified. Therefore, determining the mechanisms underlying resistance to CDK4/6 inhibition is crucial to develop combination therapies that can extend the efficacy of the CDK4/6 inhibitors or delay resistance. This study aims to identify differentially expressed genes (DEG) associated with acquired resistance to palbociclib in ER- breast cancer cells.

Methods: We performed next-generation transcriptomic sequencing (RNA-seq) and pathway analysis in ER- MDA-MB-231 palbociclib-sensitive (231/pS) and palbociclib-resistant (231/pR) cells.

Results: We identified 2247 up-regulated and 1427 down-regulated transcripts in 231/pR compared to 231/pS cells. DEGs were subjected to functional analysis using Gene Ontology (GO) and the KEGG database which identified many transduction pathways associated with breast cancer, including the PI3K/AKT, PTEN and mTOR pathways. Additionally, Ingenuity Pathway Analysis (IPA) revealed that resistance to palbociclib is closely associated with altered cholesterol and fatty acid biosynthesis suggesting that resistance to palbociclib may be dependent on lipid metabolic reprograming.

Conclusion: This study provides evidence that lipid metabolism is altered in TNBC with acquired resistance to palbociclib. Further studies are needed to determine if the observed lipid metabolic rewiring can be exploited to overcome therapy resistance in TNBC.

Keywords: CDK4/6 inhibitors; Metabolism reprogramming; Palbociclib; TNBC; Therapy resistance.

Fig. 1

Differential expression heatmap visualization of ER− 231/pS compared to 231/pR cells. Next-generation transcriptomic RNA sequencing (RNA-seq) was performed and the raw expression of genes is shown as a heatmap. Replicate samples are clustered. Red and yellow indicate lower and higher gene expression, respectively

Fig. 2

Enriched biological processes (BP) analysis of ER− palbociclib-resistant breast cancer cells

Fig. 3

IPA analysis of ER− palbociclib-resistant breast cancer cells. A higher −log(B–H p-value) shown on the left Y axis represents more significant pathways. The ratio (right Y axis) refers to the number of genes from the dataset that map to the pathway divided by the total number of genes that map the canonical pathway from the IPA database. p_val ≤ 0.05; q_val ≤ 0.05; |log₂FC|≥ 1

Fig. 4

Metabolic pathway analysis of ER− palbociclib-resistant breast cancer cells. A higher −log(p-value) shown on the left Y axis represents more significant pathways. The ratio (right Y axis) refers to the number of genes from the dataset that map to the pathway divided by the total number of genes that map the canonical pathway from the IPA database. p_val ≤ 0.05; q_val ≤ 0.05; |log₂FC|≥ 1

Fig. 5

Protein expression correlates with DEGs identified by RNA-seq. Cells were treated with either vehicle control (Ctrl) or 500 nM palbociclib (Palbo), harvested after 24 h and immunoblotted with the indicated antibodies. a MDA-MB-231 cells. b MFM-223 cells. Quantitative densitometry analysis is shown relative to the actin protein normalized to palbociclib-sensitive control-treated cells