Mass spectrometry and serum pattern profiling for analyzing the individual risk for endometriosis: promising insights?
OBJECTIVE
To evaluate whether distinct patterns of serum proteins in symptomatic women are of value to predict endometriosis before laparoscopy.


METHODS
Prospective exploratory cohort study.


METHODS
Tertiary care center.


METHODS
A total of 91 consecutive symptomatic patients suffering from dysmenorrhea, dyspareunia, chronic pelvic pain, or unexplained infertility.


METHODS
Collection of serum samples and a standardized protocol for patients' history before laparoscopic diagnosis.


METHODS
Protein expression was analyzed by mass spectrometric analysis according to surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) standards. The analysis of data was performed using a genetic algorithm (ClinProTools 2.0 software) and a rule-based decision-tree algorithm (XLminer software).


RESULTS
A total of 90 out of 91 samples were eligible for analysis. At laparoscopy, 51 of 90 patients (56.7%) exhibited endometriosis and 39 of 90 (43.3%) were disease free. Analyzing the serum samples, the software revealed a unique selection of mass peaks between 2,000 and 20,000 Da, which allowed for discrimination between patients suffering from endometriosis and control subjects. Overall recognition capacity was 70.8%, exhibiting a sensitivity of 81.3% (95% confidence interval [CI] 66.5-92.5) and a specificity of 60.3% (95% CI 46.1-74.2]) using the genetic algorithm, and a sensitivity of 78.4% and a specificity of 59.0% using the rule-based decision-tree algorithm.


CONCLUSIONS
These findings provide direct evidence that screening for serum protein patterns using SELDI-TOF MS before laparoscopy might be of discriminative value in the prediction of disease and partly confirms recently published data. However, in this prospective setting, we found both low sensitivity and low specificity, which disqualifies the screening for serum protein patterns by SELDI-TOF MS as a "quick fix" diagnostic test.
Department of Obstetrics and Gynecology, RWTH Aachen University, Aachen, Germany. mwoelfler@ukaachen.de
Monika M
MM
Wölfler
Kristina
K
Schwamborn
Daniela
D
Otten
Daniela
D
Hornung
Haiyuan
H
Liu
Werner
W
Rath
D000328:Adult; D001798:Blood Proteins / Q000378:metabolism*; D004715:Endometriosis / Q000097:blood* / Q000145:classification / Q000473:pathology*; D005260:Female; D006801:Humans; D007422:Intestines / Q000473:pathology; D010535:Laparoscopy; D013058:Mass Spectrometry / Q000379:methods*; D008875:Middle Aged; D010053:Ovary / Q000473:pathology; D018579:Patient Selection; D010529:Peritoneal Cavity / Q000473:pathology; D012307:Risk Factors; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D055815:Young Adult
D001798:Blood Proteins