Normalization of acute lymphoblastic leukemia gene expression data using the cellular volume

Abstract

The development and upgrading of global gene expression analysis technologies has been widely used in biology to understand several molecular and cellular phenomena through a gene set identification and its molecular pathways that are differentially expressed in a given test situation. In addition, gene expression profile analysis has been widely used in molecular markers search for diagnosis and/or prognosis for most common diseases, including cancer. In Acute Lymphocytic Leukemia (ALL), for example, the gene expression analysis allows us to discriminate an aggressive subtype of this disease known as BCR-ABL1-like. However, gene expression values are normalized by the same RNA mass and not by the same number of cells. In other words, the fact that different tumors/leukemias have different cellular volume, therefore, amount of RNA per cell also variable, which can lead to results that are not consistent with reality, is disregarded. Because of this, important information may be lost. This work intends to develop a method for gene expression normalization according to cell volume. For this, we will use microarray data from 143 cases of ALL (B-derived and ALL-T), for which we also have an estimate of the cellular size by flow cytometry. After this new normalization process, we will discuss the characterization of different molecular types of ALL, searching for typical genes of each group and genes associated with the patient's clinical response. (AU)