Numerical analysis of intracellular amino acid profiles of breast cancer cells with K-Ras or PI3K mutation in response to kinase inhibitors

• Published in: BMC cancer 2018-11, Vol.18 (1), p.1109-1109, Article 1109
• Main Authors: Jeong, Jaesik, Seo, Kwangok, Kim, Eung-Sam
• Format: Article
• Language: English
• Subjects: 1-Phosphatidylinositol 3-kinase; Amino acid profile; Amino acids; Amino Acids - analysis; Amino Acids - metabolism; Antineoplastic Agents - pharmacology; Antineoplastic Agents - therapeutic use; Breast cancer; Breast Neoplasms - drug therapy; Breast Neoplasms - genetics; Cancer cells; Cancer metabolism; Care and treatment; Cell Line, Tumor; Cluster analysis; Composition; Cytoplasm - drug effects; Cytoplasm - metabolism; Development and progression; Drug Screening Assays, Antitumor; Genomics; Health aspects; Humans; Information processing; Intracellular; K-Ras protein; Kinase inhibitor; Kinase inhibitors; Kinases; Metabolites; Metabolome - drug effects; Metabolomics; Metabolomics - methods; Mutation; Phosphatidylinositol 3-Kinases - genetics; Principal Component Analysis; Protein Kinase Inhibitors - pharmacology; Protein Kinase Inhibitors - therapeutic use; Proto-Oncogene Proteins p21(ras) - genetics; Studies
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-018-4972-7

Various efforts to understand the relationship between biological information and disease have been done using many different types of highthroughput data such as genomics and metabolomics. However, information obtained from previous studies was not satisfactory, implying that new direction of studies is in need. Thus, we have tried profiling intracellular free amino acids in normal and cancerous cells to extract some information about such relationship by way of the change in IFAA levels in response to the treatment of three kinase inhibitors. We define two measures such as relative susceptibility (RS) and relative efficacy (RE) to numerically quantify susceptibility of cell line to treatment and efficacy of treatment on cell line, respectively. We applied principal component analysis (PCA) to the intracellular free amino acids (IFAAs) of isogenic breast cells with oncogenic mutation in K-Ras or PI3K genes to investigate the change in IFAA levels in response to the treatment of three kinase inhibitors. Two-dimensional plot, which was graphically represented by using the first two principal components (PCs), enabled us to evaluate the treatment efficacy in cancerous cells in terms of the quantitative distance of two IFAA profiles from cancerous and normal cells with the same treatment condition. The biggest change in metabolic states in K-Ras mutant cell was caused by REGO for both treatment time (RS=2.31 (24 h) and 1.64 (48 h)). Regarding RE, REGO was the most effective on K-Ras/PI3K mutant cell line for treatment time 24h (RE=1.28) while PI3K inhibitor had good effect on K-Ras mutant cell line for 48h (RE=1.1). Numerical study on the link between amino acid profile and cancer has been done in two different dimensions. We then summarized such link in terms of two new metrics such as RS and RE, which we first define in this work. Although our study based on those metrics seems to work, we think that the usefulness of the metrics in cancer study of this kind need to be further investigated.