The Impact of Myomectomy on IVF Outcomes

Grouping and blinding method This is a national multicenter, randomized controlled study. Competitive enrollment is performed among all centers. The study group received IVF after myomectomy and the control group was directed to IVF after the routine evaluation, probably including diagnostic laparoscopy. In this study, 792 patients were randomly divided into 2 groups with 396 patients in each group according to centralized random system. A random sequence is generated with a random block size of a block size of 4.

Collection of clinical data and samples Data and samples are collected according to Case Report Form (CRF) form, including randomized information, epidemiologic and clinical information. Evaluation of infertility history and details, imaging results, ovarian reservation and surgical findings are of special interest and detailed recorded.

Samples of peripheral blood, cervical exfoliated cells, endometrial exfoliated cells, endometrial biopsy and myoma in study group are collected for multi-omics analysis. The process of sample harvest shouldn't interfere or deteriorate the surgical and IVF treatment.

IVF treatment: the IVF regimen should include detailed records of the downregulation plan, number of cycles, frozen or fresh blastocysts, ①Study group: IVF treatment is performed 6 months after myomectomy, and patients should be followed up for 1 year after the start of IVF. If the endometrium is exposed during myomectoy, IVF treatment is performed 12 months after myomectomy. It should be noted that the time for postoperative contraception should be recorded, and also the time interval between myomectomy and IVF.

②Control group: IVF treatment was performed immediately after relevant evaluation, and follow-up for 1 year after the start of IVF.

Genomic feature examination and bioinformatics analysis

1. Endometrial receptive array (ERA) is a molecular diagnostic test based on microarray technology, which divides endometrial biopsy into receptive, pre receptive, or proliferative types based on the expression of 238 selected genes. ER Map/ER Stage is based on the expression of 184 genes involved in maternal immune response related to endometrial proliferation and embryo implantation.
2. Methylation sequencing: Extract DNA related to peripheral blood, tissue, and cells, and accurately quantify DNA concentration using Qubit 2.0. The total amount of DNA detected should not be less than 1ug. Library construction: After passing the sample detection, 1 µ g of sample genomic DNA was mixed with unmethylated lambda DNA using the Biouptor system, and then fragmented to an average size of approximately 250bp. After fragmentation, the purified random fragmented DNA was then repaired, passivated and phosphorylated with a mixture of T4 DNA polymerase, Klenow fragment and T4 polynucleotide kinase. The blunt DNA fragment was then 3 'adenosylated with Klenow fragment (3' -5'exo -), and then linked to the linker connecting 5 '- methyl Cytosine instead of Cytosine using T4 DNA ligase. After completing each step, use magnetic beads to purify DNA. Then, use ZYMO EZ DNA methylation gold kit to convert unmethylated Cytosine to Uracil according to instructions. Finally, use JumpStart Taq DNA polymerase for PCR amplification, and then use magnetic beads to purify the PCR product to obtain the final library. Library quality inspection: After the construction of the library is completed, preliminary quantification is carried out using Qubit2.0, and the library is diluted to 1ng/ul. Then, the insert size of the library is tested using Agilent 2100. After the insert size meets expectations, the effective concentration of the library is accurately quantified using qPCR method (effective concentration of the library>2nM) to ensure library quality. Online sequencing: After passing the library detection, different libraries are pooled according to the effective concentration and target offline data volume requirements, and then sequenced on the Illumina Nova platform using the PE150 sequencing strategy. After that, quality control of original offline data, sequence comparison, calculation of methylation level, identification and statistics of differential methylation region (DMR) were carried out.

Urinary protein detection and bioinformatics analysis

1. Protein separation technology: two-dimensional gel electrophoresis (2DE), two-dimensional fluorescence differential electrophoresis (2D-DIGE), isoelectric focusing electrophoresis (IEF), liquid chromatography; Multidimensional chromatography (MDC) (including size exclusion chromatography, ion exchange chromatography, reverse phase high performance chromatography, hydrophobic interaction chromatography, etc.), and multidimensional liquid chromatography (MDLC).
2. Protein identification technology: primary mass spectrometry: according to different ion sources, it can be divided into matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) and electric spray mass spectrometry (ESI MS); Secondary mass spectrometry: peptide mass fingerprint (PMF); New technology: Stable nuclide signature bio mass spectrometry (SIAMS).
3. Identification of protein peptide segments: amino and carboxyl end analysis, such as Edman; Mass spectrometry, including peptide fragment mass spectrometry and tandem mass spectrometry.
4. Protein interactions: Immunoprecipitation technology, Yeast two hybrid system, Protein chip technology.

Metabolomics and Bioinformatics Analysis

1. The endometrium tissue was immediately frozen in liquid nitrogen after being isolated, and then the tissue was stored at -80 ℃, ground and crushed, and extracted with cold organic Liquid-liquid extraction. Attention must be paid to avoiding metabolic changes before and during sampling. Perform metabolomics analysis on collected cells, tissues, blood, and urine.
2. Metabolite extraction: The most commonly used method in metabolite extraction is to precipitate protein with organic solvents, and extract the supernatant through high-speed centrifugation or ultrafast filtration to remove protein precipitation. Concentrate using freeze-drying or nitrogen blowing, and dissolve the residue in a complex solvent.
3. Sample detection: Take a certain amount of redissolved supernatant and use Thermo Vanquish UHPLC ultra-high performance liquid chromatography system and Thermo Q Active HF-X mass spectrometry platform for machine detection.
4. Data processing: After the mass spectrometry detection is completed, the offline data (. raw) file is imported into the search software for simple screening of retention time, mass charge ratio, and other parameters. Then, according to the retention time deviation, quality deviation and signal strength deviation, signal to noise ratio, minimum signal strength and other information of different samples, peak alignment and peak extraction are carried out. At the same time, the peak area is quantified, and then the target ions are integrated to predict the Molecular formula and compare with the database to obtain the identification and quantitative results of the data. Therefore, non targeted metabolomics databases and search software play a decisive role in the experimental results. However, LC-MS has very few public databases, and most of them are platform built databases. The commonly used databases include HMDB, METLIN, and some self built libraries.
5. Information analysis: Principal component analysis, differential metabolite analysis, etc.