Expression profiling of small cellular samples in cancer: less is more

Gene expression profiling of single epidermal, basal and trichome cells of Arabidopsis thaliana

“…In particular, we confirmed that the microcapillary method is suitable for large-scale transcript expression analysis on the single-cell level (Brandt et al, 1999(Brandt et al, , 2002Kehr, 2001;Glanzer and Eberwine, 2004). Due to the high spatial resolution of our sampling technique, cell-specific transcripts could be detected subsequent to amplification and hybridization to nylon array filters (Figure 1).…”

“…Cell-type specificity in the same tissue layer might be associated with differential gene expression (Kamme et al, 2003;Glanzer and Eberwine, 2004). Our pie charts suggest small differences of gene expression in defined groups of transcripts (Figure 1).…”

Single molecule transcription profiling with AFM

“…Detection of differences and modulation in global expression patterns has yielded a deeper appreciation for the interconnected circuitries of normal and diseased tissues, and is now commonplace in biomedical research and drug discovery; global gene expression profiling is also beginning to be used in the clinical setting, to aid in disease prediction, diagnostics and treatment [3][4][5][6][7]. Importantly, there is increasing demand for expression profiling of small samples, as large amounts of material can be difficult, if not impossible, to obtain in clinical and experimental settings [8][9][10][11][12][13][14][15][16][17][18][19]. Recent methodological advances make possible the global expression profiling of minute samples from micro-dissected tissues, including single cells, thereby avoiding the confounding biological effects of tissue heterogeneity.…”

A clinical prognostic prediction of lymph node-negative breast cancer by gene expression profiles

“…Although our study showed a promising result in predicting the prognosis of breast cancer patients, however, a few critical issues concerning the microarray technology must be fully understood before such methods become a common tool in clinical application. The most important one is the heterogeneity in the tumors (Glanzer et al 2004). Current technology will not necessarily solve the problem of heterogeneity within tumors, as these data present as a composite of the whole population, providing an average snapshot (Lakhani and Ashworth 2001).…”