Research Laboratory of Oncofertility and Onco-Gynecology

Research Laboratory of Gynecologic Oncology



Head of Laboratory — Elena Ulrikh, MD, DSc

Tasks 

Development of innovative scientific, clinical and educational practices that accumulate knowledge and experience in the priority areas of modern treatment methods for gynecological tumors, protection of reproductive function in cancer patients, personalized treatment and preservation of fertility, including in the case of malignant tumors in pregnancy.

Focus areas

The Centre conducts preclinical and clinical research, develops and implements innovative methods of fertility preservation in cancer patients, including non-drug, drug, surgical techniques and the use of reproductive technologies, including the method of ovarian tissue cryopreservation; registers cases of diagnosis and treatment of malignant tumors during pregnancy and evaluates the impact of different methods of diagnosis and treatment on maternal (obstetric and oncological) outcome and evaluates the impact on the fetus after treatment of the mother for malignant tumors during pregnancy, analyzes fertility outcomes after treatment of malignant tumors, personalizes treatment methods for cancer patients with major comorbidities and implements new educational programs.

Projects

1. Personalizing treatment for cancer patients to preserve fertility

The protocol for ovarian tissue cryopreservation that we have developed and validated in the trial takes into account the current state of the art and the results of international studies. A similar protocol is used in a number of European countries and has proven its clinical effectiveness. Our cryopreservation protocol [patent RU2974963] has demonstrated its efficacy and safety, and in 2022 ovarian tissue reimplantation using this technology was performed for the first time. A number of international initiatives are currently underway to develop recommendations for the management of patients with malignancy during pregnancy. Due to the rarity of this condition, there are currently no standardized approaches to its management. The existing experience in the management of these patients, both worldwide and at Almazov Centre, is based on clinical observations and opinions of individual experts, which requires the creation of a multicentre international automated registry of all malignant neoplasms associated with pregnancy in order to collect data, store and analyze information on the processes of diagnosis and treatment of these patients, as well as the long-term outcomes of treatment.

2. Developing a neural network algorithm for early diagnosis of female reproductive cancers (cervical cancer) based on colposcopy

There are currently a number of studies looking at the processing and analysis of medical imaging data obtained during diagnostic procedures. The development of software for automated processing and analysis of diagnostic images based on computer vision and deep learning algorithms (neural networks) seems promising. The literature provides mathematical and graphical results on the degree of trainability of networks for detecting pathological changes in the analysis of medical images. Preliminary results published in the first works of foreign authors show a high degree of reliability (up to 95%) of the results of diagnostics of cervical changes. The system we are developing for the analysis of medical images takes into account current international experience and uses similar machine learning approaches.

3. Studying the role of microbiota in the development and progression of female genital neoplasms

The detection of microorganisms in parts of the human body long considered sterile has only recently become possible thanks to the development of new sequencing technologies. As a result, we can observe in real time the emergence of new evidence for the presence of resistant microbial communities in lung, brain and tumor tissue. In the latter case, the microbiota varies considerably depending on the histological structure. The microbiota of the uterine cavity has also recently been discovered, and questions remain about its origin, 'normal' composition and changes during a woman's reproductive life.

Indeed, the study of the upper reproductive tract microbiota is at the forefront of global research. Moreover, such research is impossible without the use of the latest technological approaches, including next-generation sequencing and machine learning. In this project, we plan to use bacterial genome sequencing methods in samples with low microbial load, in line with global practice in this area.

Specialists

  • Elena Ulrikh, MD, DSC, Head of Laboratory
  • Igor Govorov, Senior Researcher
  • Elena Dikareva, Senior Researcher
  • Vitaly Pavlov, Researcher
  • Veronica Artemenko, Junior Researcher
  • Oksana Vazhenina, Junior Researcher
  • Victor Deinega, Junior Researcher
  • Eduard Komlichenko, Research Assistant
  • Dana Zhigunova, Research Assistant
  • Yulia Chekina, Research Assistant

Major publications


Contacts

Elena Ulrikh, Head of Laboratory
e-mail: ulrikh_EA@almazovcentre.ru