Panel of Genes Transcriptionally Up-regulated in Squamous Cell Carcinoma of the Cervix Identified by Representational Difference Analysis, Confirmed by Macroarray, and Validated by Real-Time Quantitative Reverse Transcription-PCR

• Published in: Clinical chemistry (Baltimore, Md.) Vol. 51; no. 1; pp. 27 - 34
• Main Authors: Sgarlato, Gregory D, Eastman, Catharine L, Sussman, Howard H
• Format: Journal Article
• Language: English
• Published: Washington, DC Am Assoc Clin Chem 01.01.2005; American Association for Clinical Chemistry; Oxford University Press
• Subjects: Analytical, structural and metabolic biochemistry; Biological and medical sciences; Carcinoma, Squamous Cell - metabolism; Cell morphology; Cervix Uteri - metabolism; Female; Fundamental and applied biological sciences. Psychology; Gene Expression Profiling; Humans; Investigative techniques, diagnostic techniques (general aspects); Medical sciences; Oligonucleotide Array Sequence Analysis; Reverse Transcriptase Polymerase Chain Reaction; Tissues; Up-Regulation; Uterine Cervical Neoplasms - metabolism; Squamous cell carcinoma; Regulation(control); Gene; Clinical biology; Genetics; Biochemistry; Malignant tumor; Molecular biology; Real time; Reverse transcription polymerase chain reaction; Quantitative analysis
• ISSN: 0009-9147; 1530-8561
• DOI: 10.1373/clinchem.2004.038620

Background: The Pap smear is currently the most widely used method of screening for squamous cell carcinoma of the cervix (SCCC). Because it is based on cell morphology, it is subject to variability in interpretation. Sensitive molecular markers capable of differentiating cancerous samples from noncancerous ones would be beneficial in this regard. Methods: We performed representational difference analysis (RDA) using paired, noncancerous (normal) and cancerous (disease) tissues taken from the same specimen obtained from a single patient with a confirmed diagnosis of SCCC. Linearly amplified cDNA from normal and diseased tissues of the original patient and seven others were hybridized to DNA macroarrays containing the candidate gene transcript fragments. Real-time quantitative reverse transcription-PCR was used to validate the macroarray results. Results: RDA identified a candidate pool of 65 transcript fragments up-regulated in diseased tissue compared with normal tissue. Forty-one transcripts were found to be up-regulated in diseased compared with normal tissue in at least one half the patients by macroarray hybridization. Eleven of those genes were selected for real-time quantitative reverse transcription-PCR analysis, and all were confirmed as transcriptionally up-regulated in cancer compared with normal tissue in at least one half the patients. Conclusions: RDA using tissues from a single patient identified gene fragments confirmed to be transcriptionally up-regulated in SCCC both in the original patient and in seven others. The confirmed genes have a variety of functions and also have the potential to serve as diagnostic or prognostic markers.