Abstract
Objective The phenotypic and pathological features of small cell cervical carcinoma (SMCC) and small small cell lung cancer (SCLC) are very similar; thus, the chemotherapy regimens used for the rare SMCC have been routinely based on regimens used for common SCLC. We set out to explore the protein expression profile similarities between these 2 cancers to prove that linking their therapeutic regimens is justified, with a secondary aim of finding tumor-specific proteins to use as additional biomarkers for more accurate diagnosis of SMCC, and potentially to use as therapeutic targets. Methods Protein expression analysis was performed for 3 cases of SMCC and 1 example each of SCLC, mucinous adenocarcinoma of the cervix (MACC), lung mucinous adenocarcinoma (MACL), and squamous cell carcinoma of the cervix (SCC). We used cancer tissue-originated spheroids (CTOS) and isobaric tags for relative and absolute quantitation (iTRAQ)-based comprehensive and quantitative protein expression profile analysis. Expression in corresponding clinical samples was verified by immunohistochemistry. Results Rather than organ of origin-specific patterns, the SMCC and SCLC samples revealed remarkably similar protein expression profiles - in agreement with their matching tumor pathology phenotypes. Sixteen proteins were expressed at least 2-fold higher in both small cell carcinomas (SMCC and SCLC) than in MACC or SCC. Immunohistochemical analysis confirmed higher expression of creatine kinase B-type in SMCC, compared with MACC and SCC. Conclusions We demonstrate a significant overlapping similarity of protein expression profiles of lung and cervical small cell carcinomas despite the significant differences in their organs of origin.
Author supplied keywords
Cite
CITATION STYLE
Egawa-Takata, T., Yoshino, K., Hiramatsu, K., Nakagawa, S., Serada, S., Nakajima, A., … Kimura, T. (2018). Small Cell Carcinomas of the Uterine Cervix and Lung: Proteomics Reveals Similar Protein Expression Profiles. International Journal of Gynecological Cancer, 28(9), 1751–1757. https://doi.org/10.1097/IGC.0000000000001354
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.