Gene expression in the cell cycle of human T‐lymphocytes: II. Experimental determination by DNASER technology

Abstract

Human lymphocytes gene expression before and after PHA stimulation is monitored by DNASER technology, a novel bioinstrumentation entirely constructed in our laboratories as previously reported. The validity of the DNASER measurements is confirmed by standard fluorescence microscopy equipped with CCD. The human lymphocytes gene expression here experimentally probed using commercially available DNA microarrays such as Human Starter, appears compatible both with independent bioinformatic prediction and with existing experimental data, pointing to MYC as the key gene in the G0-G1 transition induced by PHA in resting lymphocytes. It does not escape our notice that in cell biology and cancer research DNASER technology based on microarray constructed with few leader genes identified from bioinformatics represents a meaningful cost-effective route alternative to massive frequently misleading molecular genomics.

Gene expression in the cell cycle of human T lymphocytes: I. Predicted gene and protein networks

“…Prediction of leader genes was found compatible with both our original experimental data obtained using commercially available DNA microarrays such as Human Starter, as well as with existing experimental data [Nicolini et al, 2005].…”

LeaderGene: A Fast Data-mining Tool for Molecular Genomics

“…This theoretical prediction was validated with a DNA microarray gene expression analysis on human T lymphocytes stimulated with PHA to enter cell cycle, 24, 48 and 72 hours after the stimulation [2,6]. We chose a commercial array, displaying only 161 genes (among whom, 3 leader genes were displayed: MYC, CDK4 and CDC2), in order to limit experimental complications that may arise using a mass scale or a pangenomic microarray.…”

“…DNA microarrays have emerged as one of the most promising methods for the analysis of gene expression [1][2][3][4]. This technique allows the study of an immense amount of genes (over 10,000) with only one experiment and therefore can draw a picture of a whole genome.…”

“…This technique allows the study of an immense amount of genes (over 10,000) with only one experiment and therefore can draw a picture of a whole genome. Anyway, the huge number of data coming out from microarray experiments may often raise experimental complications and difficulties in the analysis [2]. Moreover, the greatest part of genes displayed on an array is often not directly involved in the cellular process being studied.…”

“…In this way, it becomes possible to draw and to update maps of the major biological control systems, and to integrate them in a concise manner to discern common patterns of interactions between gene expression and their correlated coding of proteins. These findings may lead to an ad hoc and therefore more significant experimentation [2,4,6]. However, at present this complex process is performed manually.…”