Identification of biomarkers for cervical cancer in peripheral blood lymphocytes using oligonucleotide microarrays

Oligonucleotide microarrays are increasingly being used to identify gene expression profiles that associated with complex genetic diseases. Peripheral lymphocytes communicate with cells and extracellular matrixes in almost all tissues and organs in human body, suggesting that the gene expression profiles in peripheral lymphocytes may reflect the presence of disease in the body. This study aimed to identify molecular biomarkers for cervical cancer in peripheral blood lymphocytes by using oligonucleotide microarrays.

Total RNA was extracted from peripheral blood lymphocytes of 24 early stage cervical cancer patients and 18 healthy controls. We used 22K Human Genome microarrays to profile peripheral blood lymphocytes from 4 early stage cervical cancer patients and compared their gene expression profiles with those from 3 healthy controls. Differentially expressed genes would be identified if they had adjusted P values of less than 0.05 and a groupwise average fold change greater than 1.5 or less than 0.67. Then the selected 5 genes were validated in the remaining 20 early stage cervical cancer patients and the 15 healthy controls by using real-time reverse-transcription polymerase chain reaction (RT-PCR).

Genes identified by the gene selection program expressed differently between the blood samples of the early stage cervical cancer patients and those of the healthy controls. To validate the gene expression data, 5 genes were analyzed by real-time RT-PCR. In three of the 5 identified genes, tenasin-c (TNC), nuceolin (NCL), and enolase 2 (ENO2) showed a significant up-regulation in the blood samples of the early stage cervical cancer patients versus that of the healthy controls.

The up-regulation of TNC, NCL, and ENO2 in peripheral blood may be used to identify novel blood biomarkers for detecting cervical cancer in a clinically accessible surrogate tissue, and thus to provide a possibility to develop a noninvasive and predictive diagnosis for the disease.