Analysis of Changes in the Expression of Selected Genes from the ABC Family in Patients with Triple-Negative Breast Cancer.
Anna Makuch-KockaJanusz KockiAnna BrzozowskaJacek BoguckiPrzemysław KołodziejAnna Bogucka-KockaPublished in: International journal of molecular sciences (2023)
Triple-negative breast cancer (TNBC) is characterized by a lack of expression of hormone receptors (estrogen and progesterone), as cancer cells also do not overexpress the HER2 receptor. Due to their molecular profile, treatments for this type of breast cancer are limited. In some cases, the pharmacotherapy of patients with TNBC is hindered by the occurrence of multidrug resistance, which is largely conditioned by proteins encoded by genes from the ABC family. The aim of our study was to determine the expression profile of 14 selected genes from the ABC family using real-time PCR in 68 patients with TNBC by comparing the obtained results with clinical data and additionally using bioinformatics tools (Ualcan and The Breast Cancer Gene Expression Miner v4.8 (bc -GenExMiner v4.8)), as well as by comparing experimental data with data in the Cancer Genome Atlas (TCGA) database. Based on the conducted studies, we found different levels of gene expression depending on the age of patients, tumor sizes, metastases to lymph nodes, cell infiltration into adipose tissue, tumor stages, or lymphovascularinvasion. The results of the presented studies demonstrate the effect of the expression level of the studied genes on the clinical course and prognosis of patients with TNBC, and suggest how profiling the expression level of genes from the ABC family may be a useful tool in determining personalized TNBC treatment.
Keyphrases
- gene expression
- poor prognosis
- genome wide
- adipose tissue
- bioinformatics analysis
- dna methylation
- genome wide identification
- single cell
- lymph node
- electronic health record
- binding protein
- end stage renal disease
- big data
- long non coding rna
- ejection fraction
- risk assessment
- chronic kidney disease
- real time pcr
- genome wide analysis
- emergency department
- skeletal muscle
- mesenchymal stem cells
- high fat diet
- transcription factor
- bone marrow
- case control
- deep learning
- insulin resistance
- peritoneal dialysis
- artificial intelligence
- patient reported