Molecular diagnosis of lymphoma: outcome prediction by gene expression profiling in diffuse large B-cell lymphoma.
This chapter describes the illness diffuse large B-cell lymphoma (DLBCL) and why research has and continues to focus on creating accurate predictors of response to treatment to allow individual risk assessment for a patient and individualization of treatment choice to maximize the chances of cure. Microarray technology has the promise to bring these objectives within reach. The first papers attempting to identify molecular signatures of response and outcome using microarray technology were generated using DLBCL samples and are described. The different types of microarray platform and data analysis tools are reviewed followed by a detailed step-by-step guide to data generation using the Affymetrix chip system from RNA extraction to laser scanning of the hybridized and stained chips.
St. Bartholomew's Hospital, London, UK.
Kim
K
Last
Silvana
S
Debarnardi
T Andrew
TA
Lister
D001185:Artificial Intelligence; D003937:Diagnosis, Differential; D020869:Gene Expression Profiling / Q000379:methods*; D015973:Gene Expression Regulation, Leukemic; D006801:Humans; D016393:Lymphoma, B-Cell / Q000175:diagnosis* / Q000235:genetics / Q000378:metabolism; D016403:Lymphoma, Large B-Cell, Diffuse / Q000175:diagnosis* / Q000235:genetics / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011379:Prognosis; D012334:RNA, Neoplasm / Q000235:genetics / Q000302:isolation & purification / Q000378:metabolism; D013223:Statistics as Topic
D012334:RNA, Neoplasm