Abstract
Since the conception of precision medicine has been put forward in oncology, this idea has been popularized and applied in many specialties. Significant progress has been made toward personalizing the entire process, including diagnosis, treatment planning, and embryo identification, and combining large-scale genetic information data and knowledge discovery can offer better prospects in reproductive medicine. This work reviews the application of precision medicine and possibilities in reproductive medicine and gynecologic cancer diagnosis and treatment. The limitations and challenges of precision medicine in this area remain to be discussed.
Highlights
Infertility is defined as the inability to achieve clinical pregnancy after 1 year of regular unprotected intercourse and can affect up to 14% of couples of reproductive age (Zegers-Hochschild et al, 2009)
Starting from oncology, precision medicine has already permeated into various fields of medicine
Precision has always been a criterion in every procedure, including etiology-oriented examination, specific diagnosis, identifying healthy embryos, window of implantation (WOI), and accurate implantation
Summary
Infertility is defined as the inability to achieve clinical pregnancy after 1 year of regular unprotected intercourse and can affect up to 14% of couples of reproductive age (Zegers-Hochschild et al, 2009). Mutated allele revealed by sequencing with aneuploidy and linkage analyses (MARSALA) combines NGS and single-cell whole-genome amplification methodologies to allow embryo diagnosis with single-molecule precision and benefits couples who desire to avoid transmitting their genetic diseases to their offspring (Yan et al, 2015) This technology allows the simultaneous direct observation of aneuploidy, targeted mutation sites, and their linked SNPs. MARSALA improved the precision of PGD prominently and streamlined the PGD/PGS procedure. A genomic tool named the endometrial receptivity array (ERA), based on a customized microarray, was developed, and a specially trained bioinformatic prediction computer algorithm was created to identify the WOI timing of the endometrium when it is receptive to blastocyst adhesion This genetic tool is designed to identify endometrial receptivity by comparing the genetic profile of a test sample with patients of LH+7 controls in natural cycles and patients on day 5 of P administration (P+5) after E2 priming in hormonal replacement therapy (HRT) cycles. The etiologies can be divided by organs into ovulation disorders [polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), etc.], tubal
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