Noninvasive Test for Endometriosis Developed

Total ribonucleic acid (RNA) was purified from specimens, and only high-quality RNA samples were processed for hybridization to Human Genome 133 Plus 2.0 high-density oligonucleotide arrays (Affymetrix; Santa Clara, CA, USA). Menstrual cycle phase was assigned by endometrial histology reviewed by two pathologists, and confirmed by serum estradiol and P4 levels.

The team used machine learning, a computer-based technology, to analyze the gene activity of the endometrium tissue samples. With an accuracy of 90% to 100 %, a grouping system from the samples was developed. Not only could the investigators distinguish between samples from endometriosis patients and the control group but also between the endometriosis patients and those patients with other uterine disorders. They even could denote the difference between endometriosis stages.

This technique also could distinguish endometriosis at different points in the menstrual cycle. As hormone levels changed throughout the cycle, the gene expression patterns in the uterine lining of women with endometriosis were distinct from those who did not have the condition.

Based on this gene expression, a simple test eventually could be performed in the doctor's office to determine endometriosis and stage. In just minutes, a tiny, thin plastic catheter could be inserted through the cervix into the uterus to remove a sample of cells for analysis.

Louis V. DePaolo, PhD, a contributing author of the study said, “Laparoscopy involves general anesthesia and making an incision in the abdomen. These findings indicate that it may be possible to avoid the surgical procedure and diagnose endometriosis from a tissue sample obtained in the office setting without anesthesia.” The study was published on September 22, 2014, in the journal Endocrinology.

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