Questioning the utility of pooling samples in microarray experiments with cell lines

• Published in: The International journal of biological markers Vol. 21; no. 2; pp. 67 - 73
• Main Authors: LUSA, L, CAPPELLETTI, V, PIEROTTI, M. A, GARIBOLDI, M, FERRARIO, C, DE CECCO, L, REID, J. F, TOFFANIN, S, GALLUS, G, MCSHANE, L. M, DAIDONE, M. G
• Format: Journal Article
• Language: English
• Published: Milano Wichtig 01.04.2006
• Subjects: Analytical, structural and metabolic biochemistry; Antineoplastic Agents, Hormonal - pharmacology; Biological and medical sciences; Biomarkers; Breast Neoplasms - genetics; Cell Line, Tumor; Computational Biology - methods; Fundamental and applied biological sciences. Psychology; Gene Expression Profiling - methods; Gene Expression Regulation, Neoplastic; Humans; Image Processing, Computer-Assisted; Investigative techniques, diagnostic techniques (general aspects); Medical sciences; Nucleic Acid Hybridization; Oligonucleotide Array Sequence Analysis - methods; Quality Control; Toremifene - pharmacology; Antineoplastic agent; Sample pooling; Antiestrogen; DNA chip; Biochemistry; Breast cancer; Antihormone; Malignant tumor; Affymetrix GeneChips; Mammary gland diseases; Cell line; DNA microarrays; MCF-7 cell line; Clinical biology; Established cell line; Toremifene; Molecular biology; Non steroid compound
• ISSN: 0393-6155; 1724-6008
• DOI: 10.1177/172460080602100201

We describe a microarray experiment using the MCF-7 breast cancer cell line in two different experimental conditions for which the same number of independent pools as the number of individual samples was hybridized on Affymetrix GeneChips. Unexpectedly, when using individual samples, the number of probe sets found to be differentially expressed between treated and untreated cells was about three times greater than that found using pools. These findings indicate that pooling samples in microarray experiments where the biological variability is expected to be small might not be helpful and could even decrease one's ability to identify differentially expressed genes.