A new “atlas” of the human ovary provides information that could lead to treatments that restore ovarian hormone production and the ability to have biologically related children, according to engineers at the University of Michigan.
This deeper understanding of the ovary means that researchers could create artificial ovaries in the laboratory using tissues stored and frozen before exposure to toxic medical treatments such as chemotherapy and radiation. Currently, surgeons can implant previously frozen ovarian tissue to temporarily restore hormone and egg production. However, this doesn’t work for long because very few follicles (the structures that produce hormones and transport eggs) survive through reimplantation, the researchers say.
The new atlas reveals the factors that allow a follicle to mature, as most follicles wither without releasing hormones or an egg. Using new tools that can identify which genes are expressed at the single-cell level within a tissue, the team was able to locate the ovarian follicles that carry the immature precursors of eggs, known as oocytes.
“Now that we know which genes are expressed in oocytes, we can test whether affecting these genes could result in the creation of a functional follicle. This can be used to create an artificial ovary that could eventually be transplanted back into the body,” Ariella said. Shikanov, a U-M associate professor of biomedical engineering and corresponding author of the new study in Scientific advances.
Most follicles, called primordial follicles, remain dormant and are located in the outer layer of the ovary, called the cortex. A small portion of these follicles are periodically activated and migrate to the ovary, to a region known as the growth cluster. Only a few of those growing follicles produce mature eggs that are released into the fallopian tubes.
With the ability to guide follicle development and adjust the ovarian environment, the team believes the engineered ovarian tissue could function much longer than unmodified implanted tissue. This means patients would have a longer window of fertility, as well as a longer period in which their bodies produce hormones that help regulate the menstrual cycle and support muscular, skeletal, sexual and cardiovascular health.
“We’re not talking about using a surrogate mother or artificial insemination,” said Jun Z. Li, associate chair of the U-M Department of Computational Medicine and Bioinformatics and co-corresponding author of the study. “The magic we are working on is being able to make an immature cell mature, but without knowing what molecules drive that process, we are blind.”
The UM team used a relatively new technology, called spatial transcriptomics, to track all of the gene activity (and where it occurs) in tissue samples. They do this by reading strands of RNA, which are like notes taken from the strand of DNA, revealing which genes are being read. Working with an organ procurement organization, UM researchers performed RNA sequencing of ovaries from five human donors.
“This was the first time we were able to target ovarian follicles and oocytes and perform transcription analysis, which allows us to see which genes are active,” Shikanov said.
“The majority of ovarian follicles, already present at birth, never enter the growth pool and eventually self-destruct. These new data allow us to begin to understand what makes a good egg: what determines which follicle will grow, ovulate, be fertilized and become a baby.”
The UM work is part of the Human Cell Atlas project, which seeks to create “maps of all the different cells, their molecular characteristics and where they are located, to understand how the human body works and what goes wrong in diseases.”
Shikanov, Li and U-M collaborators like Sue Hammoud, U-M associate professor of human genetics and urology, are mapping other parts of the female reproductive system, including the uterus, fallopian tubes and ovaries. Other contributors include Andrea Suzanne Kuliahsa Jones, formerly of UM and now at Duke University, and D. Ford Hannum, a graduate student research assistant in bioinformatics at UM.
The research was partially funded by the Chan Zuckerberg Initiative. Additional financial support was provided by the National Institutes of Health.