Fertility Preservation in the Era of Immuno-Oncology: Lights and Shadows.
Erica SilvestrisStella D'OronzoEaster Anna PetraccaClaudia D'AddarioGennaro CormioVera LoizziStefano CanosaGiacomo CorradoPublished in: Journal of personalized medicine (2024)
In recent years, immuno-oncology has revolutionized the cancer treatment field by harnessing the immune system's power to counteract cancer cells. While this innovative approach holds great promise for improving cancer outcomes, it also raises important considerations related to fertility and reproductive toxicity. In fact, most young females receiving gonadotoxic anti-cancer treatments undergo iatrogenic ovarian exhaustion, resulting in a permanent illness that precludes the vocation of motherhood as a natural female sexual identity. Although commonly used, oocyte cryopreservation for future in vitro fertilization and even ovarian cortex transplantation are considered unsafe procedures in cancer patients due to their oncogenic risks; whereas, ovarian stem cells might support neo-oogenesis, providing a novel stemness model of regenerative medicine for future fertility preservation programs in oncology. Recent scientific evidence has postulated that immune checkpoint inhibitors (ICIs) might in some way reduce fertility by inducing either primary or secondary hypogonadism, whose incidence and mechanisms are not yet known. Therefore, considering the lack of data, it is currently not possible to define the most suitable FP procedure for young patients who are candidates for ICIs. In this report, we will investigate the few available data concerning the molecular regulation of ICI therapy and their resulting gonadal toxicity, to hypothesize the most suitable fertility preservation strategy for patients receiving these drugs.
Keyphrases
- stem cells
- childhood cancer
- big data
- palliative care
- end stage renal disease
- ejection fraction
- public health
- middle aged
- prognostic factors
- young adults
- type diabetes
- transcription factor
- mental health
- epithelial mesenchymal transition
- machine learning
- adipose tissue
- metabolic syndrome
- minimally invasive
- squamous cell
- climate change
- replacement therapy
- weight loss
- deep learning
- smoking cessation
- chemotherapy induced