High dimensionality reduction by matrix factorization for systems pharmacology

The extraction of predictive features from the complex high-dimensional multi-omic data is necessary for decoding and overcoming the therapeutic responses in systems pharmacology. Developing computational methods to reduce high-dimensional space of features in in vitro, in vivo and clinical data is essential to discover the evolution and mechanisms of the drug responses and drug resistance. In this paper, we have utilized the matrix factorization (MF) as a modality for high dimensionality reduction in systems pharmacology. In this respect, we have proposed three novel feature selection methods using the mathematical conception of a basis for features. We have applied these techniques as well as three other MF methods to analyze eight different gene expression datasets to investigate and compare their performance for feature selection. Our results show that these methods are capable of reducing the feature spaces and find predictive features in terms of phenotype determination. The three proposed techniques outperform the other methods used and can extract a 2-gene signature predictive of a tyrosine kinase inhibitor treatment response in the Cancer Cell Line Encyclopedia.

System analysis of the regulation of the immune response by CD147 and FOXC1 in cancer cell lines

CD147, encoded by BSG, is a highly glycosylated transmembrane protein that belongs to the immunological superfamily and expressed on the surface of many types of cancer cells. While CD147 is best known as a potent inducer of extracellular matrix metalloproteinases, it can also function as a key mediator of inflammatory and immune responses. To systematically elucidate the function of CD147 in cancer cells, we performed an analysis of genome-wide profiling across the Cancer Cell Line Encyclopedia (CCLE). We showed that CD147 mRNA expression was much higher than that of most other genes in cancer cell lines. CD147 varied widely across these cell lines, with the highest levels in the ovary (COLO704) and stomach (SNU668), intermediate levels in the lung (RERFLCKJ, NCIH596 and NCIH1651) and lowest levels in hematopoietic and lymphoid tissue (UT7, HEL9217, HEL and MHHCALL3) and the kidney (A704 and SLR20). Genome-wide analyses showed that CD147 expression was significantly negatively correlated with immune-related genes. Our findings implicated CD147 as a novel regulator of immune-related genes and suggest its important role as a master regulator of immune-related responses in cancer cell lines. We also found a high correlation between the expression of CD147 and FOXC1, and proved that CD147 was a direct transcriptional target of FOXC1. Our findings demonstrate that FOXC1 is a novel regulator of CD147 and confirms its role as a master regulator of the immune response.