Quantitative PCR on 5 genes reliably identifies CTCL patients with 5% to 99% circulating tumor cells with 90% accuracy

• Published in: Blood 2006-04, Vol.107 (8), p.3189-3196
• Main Authors: Nebozhyn, Michael, Loboda, Andrey, Kari, Laszlo, Rook, Alain H., Vonderheid, Eric C., Lessin, Stuart, Berger, Carole, Edelson, Richard, Nichols, Calen, Yousef, Malik, Gudipati, Lalitha, Shang, Meiling, Showe, Michael K., Showe, Louise C.
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Dermatitis, Atopic - diagnosis; Dermatitis, Atopic - genetics; Dermatitis, Atopic - pathology; Dermatitis, Exfoliative - diagnosis; Dermatitis, Exfoliative - genetics; Dermatitis, Exfoliative - pathology; Gene Expression Regulation, Leukemic; Hematology; Humans; Immunobiology; Investigative techniques, diagnostic techniques (general aspects); Medical sciences; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Predictive Value of Tests; Reverse Transcriptase Polymerase Chain Reaction - methods; Sezary Syndrome - diagnosis; Sezary Syndrome - genetics; Sezary Syndrome - pathology; Skin Neoplasms - diagnosis; Skin Neoplasms - genetics; Skin Neoplasms - pathology; Tumor Burden - genetics
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2005-07-2813

We previously identified a small number of genes using cDNA arrays that accurately diagnosed patients with Sézary Syndrome (SS), the erythrodermic and leukemic form of cutaneous T-cell lymphoma (CTCL). We now report the development of a quantitative real-time polymerase chain reaction (qRT-PCR) assay that uses expression values for just 5 of those genes: STAT4, GATA-3, PLS3, CD1D, and TRAIL. qRT-PCR data from peripheral blood mononuclear cells (PBMCs) accurately classified 88% of 17 patients with high blood tumor burden and 100% of 12 healthy controls in the training set using Fisher linear discriminant analysis (FLDA). The same 5 genes were then assayed on 56 new samples from 49 SS patients with blood tumor burdens of 5% to 99% and 69 samples from 65 new healthy controls. The average accuracy over 1000 resamplings was 90% using FLDA and 88% using support vector machine (SVM). We also tested the classifier on 14 samples from patients with CTCL with no detectable peripheral involvement and 3 patients with atopic dermatitis with severe erythroderma. The accuracy was 100% in identifying these samples as non-SS patients. These results are the first to demonstrate that gene expression profiling by quantitative PCR on a selected number of critical genes can be employed to molecularly diagnosis SS.