Identification and validation of a prognostic proteomic signature for cervical cancer. Gynecol Oncol 2019 Nov;155(2):324-330
Date
09/04/2019Pubmed ID
31477280Pubmed Central ID
PMC6825895DOI
10.1016/j.ygyno.2019.08.021Scopus ID
2-s2.0-85071452175 (requires institutional sign-in at Scopus site) 6 CitationsAbstract
OBJECTIVE: To date, The Cancer Genome Atlas (TCGA) has provided the most extensive molecular characterization of invasive cervical cancer (ICC). Analysis of reverse phase protein array (RPPA) data from TCGA samples showed that cervical cancers could be stratified into 3 clusters exhibiting significant differences in survival outcome: hormone, EMT, and PI3K/AKT. The goals of the current study were to: 1) validate the TCGA RPPA results in an independent cohort of ICC patients and 2) to develop and validate an algorithm encompassing a small antibody set for clinical utility.
METHODS: Subjects consisted of 2 ICC patient cohorts with accompanying RPPA and clinical-pathologic data: 155 samples from TCGA (TCGA-155) and 61 additional, unique samples (MCW-61). Using data from 173 common RPPA antibodies, we replicated Silhouette clustering analysis in both ICC cohorts. Further, an index score for each patient was calculated from the survival-associated antibodies (SAAs) identified using Random survival forests (RSF) and the Cox proportional hazard regression model. Kaplan-Meier survival analysis and the log-rank test were performed to assess and compare cluster or risk group survival outcome.
RESULTS: In addition to validating the prognostic ability of the proteomic clusters reported by TCGA, we developed an algorithm based on 22 unique antibodies (SAAs) that stratified women with ICC into low-, medium-, or high-risk survival groups.
CONCLUSIONS: We provide a signature of 22 antibodies which accurately predicted survival outcome in 2 separate groups of ICC patients. Future studies examining these candidate biomarkers in additional ICC cohorts is warranted to fully determine their clinical potential.
Author List
Rader JS, Pan A, Corbin B, Iden M, Lu Y, Vellano CP, Akbani R, Mills GB, Simpson PAuthors
Marissa Iden Iden PhD Research Scientist II in the Obstetrics and Gynecology department at Medical College of WisconsinAmy Y. Pan PhD Associate Professor in the Pediatrics department at Medical College of Wisconsin
Janet Sue Rader MD Chair, Professor in the Obstetrics and Gynecology department at Medical College of Wisconsin
Pippa M. Simpson PhD Adjunct Professor in the Pediatrics department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
AdultAntibodies, Neoplasm
Biomarkers, Tumor
Female
Humans
Kaplan-Meier Estimate
Middle Aged
Neoplasm Proteins
Proteomics
Risk Factors
Uterine Cervical Neoplasms
