Artigo Acesso aberto Revisado por pares

Serum Circulating Human mRNA Profiling and Its Utility for Oral Cancer Detection

2006; Lippincott Williams & Wilkins; Volume: 24; Issue: 11 Linguagem: Inglês

10.1200/jco.2005.03.7598

ISSN

1527-7755

Autores

Yang Li, David Elashoff, Myungshin Oh, Uttam K. Sinha, Maie A.R. St. John, Xiaofeng Zhou, Elliot Abemayor, David T. Wong,

Tópico(s)

RNA Research and Splicing

Resumo

Purpose The purpose of this study is to explore the presence of informative RNA biomarkers from human serum transcriptome, and evaluate the serum transcriptome diagnostics for disease detection. Oral squamous cell carcinoma (OSCC) was selected as the proof-of-concept disease. Patients and Methods Blood samples were collected from patients (n = 32) with primary T1/T2 OSCC and matched healthy patients (n = 35). Circulating RNA was isolated from serum and linearly amplified using T7 polymerase. Microarrays were applied for profiling transcriptome in serum from 10 cancer patients and controls. The differential gene expression was analyzed by combining the present calls, t tests, and fold-change statistics. Quantitative polymerase chain reaction (PCR) was used to validate the selected candidate RNA markers identified by microarray. Receiver operating characteristic curve and classification models were exploited to evaluate the diagnostic power of these markers for OSCC. Results Human serum circulating mRNAs were presented by reverse transcriptase PCR. Microarray identified 2,623 ± 868 probes assigned present calls in OSCC (n = 10) versus 1,792 ± 165 in healthy patients (n = 10), indicating a higher complexity of serum transciptome in OSCC patients (P = .002, Wilcoxon test). Three hundred thirty-five serum RNAs exhibited significantly differential expression level between the two groups (P < .05, t test; fold ≥ 2). Five cancer-related gene transcripts were consistently validated by quantitative PCR on serum from OSCC patients (n = 32) and controls (n = 35). The best combination of biomarkers yielded a receiver operating characteristic curve value of 88%, sensitivity (91%), and specificity (71%) in distinguishing OSCC. Conclusion The utility of serum transcriptome diagnostics is successfully demonstrated for OSCC detection. This novel concept could be developed as an adjunctive tool for disease diagnosis.

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