Gene microarray technology is an epoch-making new molecular biology technology developed in the mid-1990s, which integrates technologies related to many disciplines such as molecular biology, immunology, biophysics, biochemistry, microelectronics, computer science, and statistics. Compared with other techniques for analyzing gene expression profiles such as RNA blotting, cDNA library sequence determination, gene expression sequences, etc., it has obvious advantages that it can analyze thousands of genes simultaneously and in parallel in experiments, and it also has the characteristics of fast speed, high integration and low contamination. 1, gene chip technology detection principle and classification Gene chip is also known as DNA chip or cDNA microarray (cDNA-microarry). Its basic principle is the complementary hybridization of probe and target gene, that is, a certain amount of nucleic acid fragments (cDNA, EST or oligonucleotide) as probes, by the robot at high speed, they are fixed in high density, according to the pre-set regular location-like arrangement on the support, such as slides, silicon wafers, nylon membrane and organic biosynthetic surface and made of DNA microarray, used to detect whether the sample to be tested The DNA microarrays are used to detect the presence of complementary sequences in the sample to be tested. The mRNA in the sample to be tested is extracted, and the fluorescence-labeled cDNA is obtained through the reverse transcription reaction process, and the DNA microarray containing thousands of genes is hybridized to the DNA microarray. To compare the differences in gene expression in two different cell lines or different tissue sources, mRNA is extracted from two different cell lines or different tissue sources. The reverse transcription reaction is labeled with different colors of fluorescence, mixed in equal amounts, and then hybridized with DNA microarrays containing thousands of genes, and the slides are scanned by laser confocal scanning. The relative expression levels of each gene in different cell lines are deduced by comparing the intensity of the two fluorescences on each dot matrix. Gene microarray technology mainly includes four steps: microarray preparation, sample preparation, hybridization reaction and detection of signal and analysis of results. There are many ways to classify gene microarrays, which can be divided into two major categories in terms of fabrication: namely, in situ synthesis method and micro-matrix method or synthetic spot sample. The in situ synthesis method applies photo-etching technology in semiconductors to DNA synthesis chemistry to synthesize oligonucleotides onto the surface of a solid substrate, producing tens of thousands of different oligonucleotide arrays in an area of a few square centimeters, with each oligonucleotide fragment representing a specific gene that exists at a specific location on the DNA chip. And there are two types of cDNA chips and oligonucleotide chips according to the length of the probes spotted on the vector [2]. 2, gene chips in gynecology applications With the implementation of the Human Genome Project and the arrival of the post-genomic era, life sciences have gradually gained attention. The in-depth development of molecular biology has made scientists realize the importance of gene regulation in the phenomenon of life. Studying diseases from the level of genes is the only way to find the root cause of diseases, and it also helps the prevention and treatment of diseases. Gene chips have shown a wide application prospect with their fast, high-throughput, simultaneous and accurate analysis of thousands of gene information. In the field of medicine, gene chips have been widely used in research on disease etiology, disease diagnosis, disease treatment, gene pharmacy and new drug screening. 2.1 Application of gene chips in gynecological tumors In recent years, the use of gene chips for tumor research has become a hot spot, which can analyze the gene expression of several hundred tumor samples simultaneously on a single chip [3]. It provides a powerful tool for studying the abnormal expression of related genes in the process of tumor occurrence and development and tumor diagnosis and treatment. It has been applied in the study and treatment of many tumors in gynecology. 2.1.1 Gene microarray and ovarian cancer Ovarian cancer is one of the three major tumors of the female genitalia, and it is usually found at an advanced stage with poor prognosis because of atypical symptoms. Despite the continuous improvement of clinical treatment, it still cannot significantly improve its prognosis. Therefore, how to detect and diagnose ovarian cancer at an early stage and establish effective treatment is the key to improve the prognosis of ovarian cancer. Currently, it is believed that ovarian carcinogenesis is mostly caused by intracellular changes in a series of genetic genes, such as p53, c-erbβ-2, c-myc, k-ras family and RHOGDI2, but the changes and deletions of these genes cannot yet explain the diversity of ovarian cancer tissue types, such as whether it is plasmacytosis, mucinous carcinoma, clear cell type carcinoma or endometrioid carcinoma, and also It also cannot explain the biological behavior of ovarian cancer such as metastasis and sensitivity to chemotherapy. Therefore, a multifaceted study to investigate the genetic alterations from a molecular perspective may lead to significant breakthroughs in early diagnosis, early treatment and improved prognosis of ovarian. Ovarian carcinogenesis is the result of polygenic and progressive alterations in precursor ovarian surface epithelial cells. Arnold et al. studied gene expression in ovarian cancer using a cDNA microarray containing 588 genes and found that compared to the immortalized ovarian surface epithelial cell line HOSE17.1, the ovarian cancer cell lines OAW42, PEO1 and JAM showed intercellular mucus molecule 1 ( ICAM-1) expression was significantly reduced. Both mRNA and protein expression levels of ICAM-1 were reduced in most ovarian cancer cell lines and primary tumors compared to normal ovarian epithelium. osteopontin is an acidic calcium-binding phosphoglycoprotein present in human body fluids and is a mediator of inflammatory response and tumor formation. osteopontin was screened by Kim et al. by gene microarray in 99 cases of invasive and junctional ovarian cancers of various umbilical cord types, and the results showed that the sensitivity of osteopontin for predicting early and advanced ovarian cancer The sensitivity of osteopontin in predicting early and advanced ovarian cancer was 80% and 85%, respectively. Although prospective studies are needed to clarify the sensitivity and specificity of preoperative testing of osteopontin and prostasin levels in patient serum, preliminary studies suggest that detection of osteopontin and prostasin expression levels by gene microarray may be useful for early diagnosis of ovarian cancer. Tapper et al. applied cDNA microarrays containing 588 genes to analyze gene expression during the progression of plasmacytic ovarian cancer and showed that the most striking difference in adenocarcinoma compared with benign adenoma was that RHOGDI2 (Rho GDP-dissociation inhabitor 2) was upregulated regardless of the stage of the tumor. The most striking difference between adenomas and adenocarcinomas is that RHOGDI2 (Rho GDP-dissociation inhabitor 2) is upregulated regardless of tumor stage, and RHOGDI2 is located in human gene 12p123, which is involved in ovarian carcinogenesis. Sawiris et al. constructed a specialized cDNA microarray containing 516 genes to study ovarian cancer and called this small specialized microarray Ovachip. And this small microarray has many advantages. They used Ovachip to discover many differentially expressed genes in ovarian cancer and found two major groups of genes namely the up-regulated IGF2 group and the down-regulated CAK group. The IGF group mainly includes insulin-like growth factor (IGF-2), checkpoint suppressor (CHES1), cisplatin resistance-associated protein (CRA), cell cyclin-dependent kinase (CDK6 ), TGF-β2, etc. The expression of IGF2 may be related to the regulation of cell cycle checkpoints and the acquisition of drug resistance. the CAK group mainly includes CDK7 and its regulatory subunit cytokine H, AXL receptor tyrosine kinase (AXL), S100 calcium-binding protein A2 (S100A2), and selenium-binding protein 1 (SELENBP1). Identifying and detecting changes in ovarian cancer gene expression profiles not only helps in early diagnosis and pathological genotyping and prognosis, but also in clinical and chemotherapeutic drug screening. Gene microarrays as a high-density integrated analysis tool provide many valuable information in ovarian cancer drug therapy and chemotherapeutic drug screening. The problem of insensitivity to chemotherapy for ovarian cancer is often encountered in clinical practice, which is mainly due to genetic differences, such as drug response genes, resulting in different responses to drugs. Or the development of drug resistance genes leading to drug insensitivity. The protein molecules related to drug resistance in tumor cells are mainly P-glycoprotein class, dihydrofolate reductase (DHFR), glutathione-S-transferase (GST), cyclin, adenylate synthase and oncogene products c-erbβ-2, ras, c-myc, etc. If the presence of relevant genes or drug resistance genes is detected by microarray technology before chemotherapy, the drug and treatment can be selected to avoid the effect of treatment due to drug insensitivity. Huang et al. performed gene profiling of various tumor tissues by microarray and found that ovarian tissues showed significantly high expression of upregulated binding factor, an RNA polymerase І-specific transcription factor, which, together with transcription factor SLI constituted a ribosomal RNA gene catalyst. Further microarray analysis was used to identify the inactive X chromosome-specific transcript (XIST) as the most significantly down-regulated gene expressed in recurrent ovarian cancer, and further clinical observations showed that the expression level of XIST was significantly correlated with paclitaxel (TAX) sensitivity, and thus XIST could be used as a potential predictor of TAX chemotherapy sensitivity in ovarian cancer, and to clarify the developmental process of TAX resistance Lamendola et al. used different concentrations of TAX to act on ovarian SKOV-3 subcell lines, and found that multidrug resistance 1 transcript expression was not elevated in SKOV-3 (0.003TR) compared to the parent SKOV-3 by cDNA microarray combined with self tissue mapping analysis (SOM), while it was elevated in SKOV-3 (0.03TR) and SKOV-3 ( 0.3TR) showed high expression. SOM analysis could clarify the changes of related transcriptional genes, including cell growth and maintenance, cell structure, signal transduction, inflammatory response and other gene families. Therefore, cDNA microarray combined with its own tissue mapping analysis could clarify the developmental process of TAX resistance, which is expected to be an effective method for the screening of selected gene families after early drug resistance phenotypes. To understand the complex network of TAX-induced apoptotic channels and the mechanism of drug resistance, Sugimura et al. examined TAX and carboplatin (CBDCA)-treated ovarian cancer cell lines (KF) and other TAX-resistant cell lines (KFTX) by cDNA microarray technology, and showed that TAX upregulated Caspases-1, -2, -3, 4, -6, -9, – 10 expression, while no change or down-regulation was observed in KFTX, while bag-1 and hsc70 were significantly up-regulated, and neither p53 nor bcl-2 was up-regulated. Therefore, it is suggested that p53-independent mitochondrial channels and enhanced response-induced channels play critical roles in TAX-induced apoptosis in ovarian cancer cell lines, and inhibition of these channels and up-regulation of bag-1 and hsc70 expression can lead to TAX drug resistance. Wenjing Zhang et al. applied gene microarray technology to investigate the differences in gene expression profiles between human ovarian cancer paclitaxel-resistant cell line OC3/Tax300 and its sensitive cell line OC3, and to screen drug resistance-related genes. The results showed that 234 genes were significantly differentially expressed, of which 217 genes were down-regulated and 17 genes were up-regulated; the down-regulated genes were mainly EBV-encoded nuclear protein (EBNA-3) and signaling protein (COP9), and the up-regulated genes were mainly tyrosine kinase (JAK2), heat shock proteins (HSPs), reduced coenzyme nicotinamide adenine dinucleotide (NADH ), etc. It may provide a new way to further explore the mechanism of drug resistance in ovarian cancer tumor cells. 2.1.2 Gene chips and cervical cancer Cervical cancer is a common malignant tumor in women, and like other malignant tumors, its occurrence and development are the result of abnormal structural and functional alterations of multiple genes inside and outside the cell. Previous studies were often limited to one or a few genes, and could not provide a more comprehensive understanding of the whole cancer process. Then gene microarray may meet this requirement due to its large throughput and simultaneous detection. Liu Kaijiang et al. applied cDNA expression profiling microarrays containing 2048 full-length human genes to analyze the gene expression profiles of three cervical cancer cases in clinically resected Uyghur women and three cervical cancer cases in Han women and their own normal cervical tissue specimens, and both found specific genes that were down- and up-regulated in expression. It helps in early diagnosis, and it is now clear that HPV infection is necessary for the development of cervical cancer. The new Bethesda system recommends HPV testing as an adjunct to the traditional Pap smear. Cho et al. performed HPV genotype testing using a newly designed HPV DNA microarray and compared the results to Pap smear results according to the new Bethesda system. The microarray contained 22 specific oligonucleotide probes, of which 15 were high-risk and 7 were low-risk types. The HPV DNA microarray was combined with the Pap smear diagnosis in a comparative study of 685 cervicovaginal swabs. The results showed that the HPV positivity rate was 31.9% in 414 controls, while the positivity rate was 78.6% in 271 cancer cases. HPV subtypes 16, 18 and 58 are the main causes of cervical cancer, and low-grade squamous intraepithelial lesion is a lesion caused by co-infection with multiple HPV subtypes and is more common in young women (40 years old).Oh et al. established an HPV DNA microarray containing 15 high-risk and 12 low-risk types, applying three HPV-positive cell lines (Hela, Caski and SiHa cells ) and two HPV-negative cell lines (C33A and A549 cells) showed that the microarray was able to detect the known HPV types present in these cell lines well, and the detection limit was more than 100 times higher than that of the PCR method, and the microarray was highly specific and reproducible. There have also been attempts to replace cytological screening with HPV testing, and studies have shown that hybridization capture as well as HPV microarrays are feasible as screening tools, and their sensitivity does not differ from liquid-based cytology. Thus, HPV DNA microarrays can be used as a powerful screening tool for large-scale epidemiological investigations, allowing early detection of high-risk HPV infection and targeted treatment, significantly reducing the incidence of cervical cancer. Peng Min et al. used gene microarray technology to analyze primary cervical cancer specimens in order to explore the variation of oncogene expression in the cervical cancer genome, and as a result, a total of 11 proto-oncogenes or suppressor genes with differential expression were screened in the tissue of primary cervical cancer specimens, accounting for 3.4% of the candidate genes, including 7 genes with significantly decreased expression and 4 up-regulated genes. This can provide a basis and clues for studying the pathogenesis of cervical cancer. In addition, gene chips have been used in tumor pathological typing studies, and Fujimoto et al [21] used microarrays containing 1700 cancer-related genes to analyze two different morphologies of SKG-IIIa and SKG-IIIb cells from the same cervical cancer patient with the aim of detecting tissue type-specific cancer-related genes, screening 10 genes (IGFB3, IAP The 10 genes (IGFB3, IAP, TM1CEA, EPLG8, IFIG, CAD13, SNO, AMLEV1, TGFB2 and PLP) were screened and confirmed by semi-quantitative RT-PCR in 9 cervical cancer cell lines, among which IGFB3, IAP and CAD13 were mostly expressed in squamous cancer cell lines, which might be related to the histomorphological differences of cervical cancer; while IFIG, SNO and transforming growth factor (TGF)β2 were expressed in both squamous and adenocarcinoma cell lines, which may be associated with cervical carcinogenesis. The diagnostic form of TBS for cervical cancer has been established in most regions, and there is no better method for the management of patients reported with atypical squamous epithelial cells. Some authors [22] applied microarrays and confirmed by immunoblotting that, in comparison with HPV-negative normal cervical epithelium, cervical cancer specimens with high-risk HPV infection had ERBB2, KIT, FLT1, MYCN, RAS, CDKN2A CCND1, NME1, NME2, MET, FGF7, FGFR2, STAT1 and anti-apoptotic (e.g., Bcl-2), and cytoarchitecture-related genes were upregulated, whereas the expression of some members of the TGF receptor and integrin, IL-1, and insulin-like growth factor binding protein families were downregulated. Therefore it is feasible to obtain cervical cells via cell brushing and analyze the characteristics of gene expression by gene expression arrays to clearly distinguish malignant tumors from normal cervical squamous epithelium. 2.1.3 Gene microarray and endometrial cancer Kabbarah et al [23] used RNA from 800-4400 cells obtained by microisolation of alcohol-fixed, paraffin-embedded uterine specimens for gene microarray expression profiling. The results identified a number of known aberrantly expressed genes and unknown aberrantly expressed genes in endometrial cancer and confirmed that Amd1, which has increased expression in other tumors, was also increased in mouse endometrial cancer RNAs, making the microarray useful for the diagnosis of early microscopic lesions in endometrial cancer. Using gene microarray technology containing 4096 cDNA clones, Zhou Huaijun et al. compared the gene expression profiles of two endometrial adenocarcinoma tissues and their corresponding normal tissues to explore candidate genes for endometrial adenocarcinoma, and the results showed that the two specimens co-expressed a total of 350 differential genes, among which 33 genes were significantly up-regulated by Ratio>3 and 44 genes were significantly down-regulated by Ratio<0.3. 44 genes. This indicates that the formation of endothelial adenocarcinoma is the result of malignant transformation of cells due to abnormalities in multiple transmission pathways caused by multiple gene abnormalities. The differentially expressed genes in 32 cases of endometrial cancer tissues were analyzed by gene microarray technology and the gene expression profiles were analyzed by hierarchical clustering. As a result, 12 differentially expressed genes associated with tumor metastasis were screened. The results of the hierarchical clustering analysis of 32 cases of endometrial cancer based on these 12 differentially expressed genes showed a 66% compliance rate with the surgical pathological stage. 2.1.4 Gene microarray and choriocarcinoma Choriocarcinoma is a highly malignant tumor that can metastasize to the whole body through the bloodstream at an early stage, destroying tissues and organs. With the advancement of HCG monitoring technology and chemotherapy, the prognosis of choriocarcinoma patients has been improved. Gene expression profiles differ between normal human trophoblast and choriocarcinoma cell lines, and Vegh et al [26] used cDNA microarrays containing 588 known genes for comparison. Six genes were upregulated and three genes were downregulated in choriocarcinoma cells compared to normal trophoblast cells, including heat shock protein 27 (HSP227), which is downregulated in choriocarcinoma and contributes to increased sensitivity of trophoblast tumors to chemotherapy. 2.2 Application of gene microarray in endometriosis and polycystic ovary syndrome Endometriosis (EM) is one of the most common gynecological diseases, with about 10% of women of reproductive age suffering from it. Although a lot of research has been conducted on this disease, its true etiology is still unknown and treatment is limited to surgery and some hormonal drugs, and it is prone to recurrence. Gene microarray technology provides an effective tool for achieving research goals because of its low consumption, high sensitivity and high throughput in analyzing intracellular gene expression profiles. Li Jie et al. applied a 578-point human immune-related expression profile cDNA gene microarray to screen endometriosis-associated genes. Results were obtained for 9 genes associated with endometriosis showing 2 up-regulated genes and 7 down-regulated genes. The most significant difference among the down-regulated genes was IL-12R. The gene microarray technique was more sensitive and efficient compared with the ELSA test results. Fan Yang et al. applied a gene microarray containing 1200 genes labeled with isotopic probes to explore the expression profiles of CK genes associated with EM tissues and normal uterine tissues. Among them, 15 CK and CKR genes were up-regulated, including IL21, IL22, IL26, L28, VEGFR, TGF, EGF, FGF and EPOR. Gene expression profiling microarray can effectively screen EM-related CK and CKR genes, which provides an efficient and accurate research tool to understand the disease mechanism. The prevalence of polycystic ovary syndrome (PCOS) is also relatively high, and previous studies suggest a familial clustering phenomenon in PCOS, but the exact genetic mechanism remains unclear. The application of gene microarray technology has helped to study the disease. Using human whole genome microarray U133A, Hu Zhenxing et al. used follicular granulosa cells left after in vitro fertilization-embryo transfer in patients with polycystic ovary syndrome and controls after egg retrieval to detect relevant differentially expressed genes in granulosa cells of five PCOS patients and five controls, and as a result, a total of 46 differentially expressed genes significantly associated with PCOS were screened compared with controls, of which 25 The results showed that 46 differentially expressed genes were significantly associated with PCOS compared with the control group, of which 25 were increased and 21 were decreased. These differentially expressed genes have various biological functions, such as regulation of lipid metabolism, intercellular signaling and immune inflammatory response, reflecting the diversity of clinical symptoms in PCOS patients. The application of gene microarray technology can screen to identify new genetically related candidate genes for PCOS. For example, Lemkin et al [33] applied cDNA microarray technology to detect the different expression of genes in mammary tissues of rats during pregnancy and lactation, and examined the genes preferentially expressed in mammary tissues during pregnancy and lactation. The results showed that carbonic acid dehydratase III was highly expressed in the mammary tissues of "virgin" and pregnant rats, and also in the mammary tissues of rats with genes associated with poor mammary epithelial development, while those genes encoding milk proteins were preferentially expressed in the mammary tissues during lactation. It is useful for understanding the molecular mechanism of lactation. Yoshioka et al. used gene microarray technology to examine the expression of genes in the uterus of rats before and after pregnancy, and analyzed 6500 genes on gene microarrays. This suggests that activation and inactivation of certain genes are necessary for successful implantation. Similar studies have shown that some genes may be involved in different stages of trophoblast invasion, such as integral proteins, MMPs and extracellular matrix proteins, and autocrine and paracrine regulators such as growth factors and cytokines that regulate cell trophoblast proliferation and differentiation in vitro. The information expressed by these genes may explain the implantation of the pregnant egg and the formation of the placenta, as well as some pathological pregnancies such as pre-eclampsia, thus providing new ideas to ensure a good pregnancy outcome. In order to investigate the differential expression of genes in embryonic congenital neural tube defects induced by gestational diabetes mellitus and to reveal the molecular mechanism of the occurrence and development of embryonic congenital neural tube defects, two groups of 70-90 days old SD rats were used to construct an animal model of embryonic congenital neural tube defects induced by gestational diabetes mellitus, and mRNA was extracted from yolk sac cells. The differentially expressed genes were detected by cDNA gene microarray. Among them, 42 genes were up-regulated (including apoptosis-related genes BAX, bcl22, HSP70, glucose2transporter 3, etc.) and 37 genes were down-regulated (including phospholipase A2, insulin2like growth factor II receptor 3, etc.). The differentially expressed genes of gestational diabetes induced embryonic congenital neural tube defects were revealed, which provided an experimental basis for effective early diagnosis and treatment of congenital neural tube defects. Using the DNA primer and probe design software DNAClub and Primer 510, Yi Guangcai designed 16 oligonucleotide probes of about 30 bp in length based on the sequences of cytomegalovirus (HCMV169), herpes simplex virus (HSV-I,II), rubella virus (RV) and Toxoplasma gondii (TOX) obtained from Genbank, and synthesized them with a simple The DNA of the tested pathogenic microorganisms and the plasmid vector DNA were cut and ligated with the same endonuclease to form the "hybrid" DNA. Then PCR amplification and fluorescent dye labeling were performed using the universal primers on the vector to amplify the product. The products were hybridized with DNA microarrays, scanned with a microarray scanner GeneTACTMUC4 (Genomic Solutions Inc), and data were processed and analyzed using the supplied software GeneTAC IntegratorMicroarray Analysis Software Version3130. and analysis. The results showed that the gene chip prepared by this method could detect five pathogenic microorganisms simultaneously, and the positive specimens detected by fluorescent quantitative PCR were detected by gene chip with basically the same results. Although gene microarray technology has not been available for a long time and there are still many limitations in the field of obstetrics and gynecology, it has shown very broad application prospects in obstetrics and gynecology. Gene microarray technology can also be used to identify genetically related genes in the early embryonic stage and provide prenatal diagnosis, which can provide a strong guarantee for the eugenics of the population. As people know more about various genes, various diseases may be understood from the genetic level to understand their development. Due to the short time of development of gene microarrays, there are still shortcomings in this technology [39], such as the need for expensive equipment; the inevitable inclusion of wrong nucleotides and impurities in synthetic probes, which reduce the specificity; and the need to improve the density of probe arrays. With the development of technology, these problems will be overcome.