Exploring the interplay between LDHA and ABCC1 in breast cancer using computational approach.

BACKGROUND

Drug resistance is the major cause of the high death rates in Breast cancer (BC), which continues to be the most frequent disease among women. Chemoresistance is significantly mediated by drug efflux transporters, including ATP-binding cassette transporter ABCC1, and glycolytic enzymes, especially lactate dehydrogenase A (LDHA). Improving treatment results requires an understanding of the expression patterns, genetic changes, and prognostic importance of ABCC1 and LDHA.

OBJECTIVE

Breast Cancer This study aims to elucidate the role of and in BC prognosis, tumor progression, and treatment resistance using integrated bioinformatics and in-silico approaches.

METHODOLOGY

To investigate the expression and correlation between LDHA and ABCC1, in-silico analysis was done using a range of bioinformatics tools, such as UALCAN, TIMER 2.0, Bc GeneExminer, DISCO, and others, were used. GeneMANIA and STRING databases were used to explore gene–gene and protein–protein interaction networks, while KM Plotter evaluated survival correlations. Functional enrichment and pathway analyses were conducted using Enrichr for Gene Ontology (GO) and KEGG pathways. For therapeutic targeting, structure-based molecular docking was performed using AutoDock Vina, where selected anticancer compounds were docked against LDHA and ABCC1 to identify potential inhibitors.

RESULTS

Our research indicates that the expression levels of LDHA and ABCC1 are elevated in several malignancies including Breast Cancer. The elevated expression levels of LDHA and ABCC1 significantly correlate with worse overall survival. Expression analysis of and genes in relation to LDHA and ABCC1 mutations in Breast Cancer samples revealed that higher ENO1 expression is observed in mutant samples, while ESR1 expression is significantly reduced, suggesting an association with altered metabolic and hormonal pathways. Furthermore, NHI-2 and Sulfinpyrazone were found as the potential chemical that targets LDHA and ABCC1 through in-silico studies.

CONCLUSION

This study highlights the oncogenic significance of LDHA and ABCC1 in Breast Cancer progression and therapy resistance. The in-silico identification of NHI-2 and sulfinpyrazone as potential inhibitors supports a novel dual-targeting strategy to simultaneously disrupt metabolic and drug efflux pathways, which could enhance therapeutic efficacy and overcome resistance in Breast Cancer. Further experimental validation is warranted to confirm these findings and facilitate clinical translation.