Integrating Bibliometrics and Bioinformatics to Map Knowledge Structure, Trends, and Genetic Insights in Polycystic Ovary Syndrome and Tumors (2015-2024).

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine and metabolic disorder characterized by ovulatory dysfunction, hyperandrogenism, and polycystic ovarian morphology, predominantly affecting women of reproductive age. 1 The Global Burden of Disease (GBD) study reports a global age-standardized prevalence of PCOS at 1.68%, with marked geographical disparities—surpassing 7.9% in some countries. 2 Although PCOS is traditionally perceived as a disorder predominantly affecting the reproductive system, it is in fact a systemic condition encompassing metabolic, reproductive, cardiovascular, and psychological disturbances, accompanied by a spectrum of comorbidities. 3 The association between PCOS and neoplasms has garnered increasing attention, with compelling evidence from epidemiological investigations demonstrating a significantly elevated incidence of endometrial cancer, breast cancer, and ovarian cancer among affected individuals. 4 Bibliometrics, a discipline employing statistical methods to quantitatively analyze academic literature, investigates patterns in publication volume, authorship, citation networks, and keyword distribution. 5 , 6 It serves to uncover disciplinary trends, identify core research communities, assess scholarly impact, and inform scientific decision-making. Despite rapid growth in research on PCOS and cancer, the global knowledge structure, research trajectories, and frontier topics linking PCOS to cancer remain systematically underexplored. To address this gap, this study leverages the Web of Science Core Collection (WoSCC) database and employs CiteSpace, VOSviewer and Scimago Graphica to analyze and visualize scholarly outputs from 2015 to 2024. Complementarily, we overlap genes linked to PCOS and cancer are extracted from the Genecards database, followed by protein-protein interaction (PPI) network analysis to identify key targets and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to pinpoint critical signaling pathways. By synthesizing these dual perspectives, this work aims to aims to provide a macroscopic perspective and strategic guidance for future investigations into the PCOS-cancer association.

A total of 1869 publications related to PCOS and cancer were identified through a comprehensive search of WoSCC database spanning from January 2015 to December 2024. Following rigorous screening procedures, 1746 articles were ultimately included in this study. The annual publication count exhibited two distinct phases. During the first phase (2015–2020), the number of articles showed a gradual upward trend. In the second phase (2021–2024), a rapid surge in publications was observed in 2021 compared to 2020 (68 articles, a 39.3% increase), followed by a plateau in subsequent years. In terms of citations, the cumulative number of citations for these articles demonstrated an exponential growth trend ( Figure 1 ). Figure 1 Trends in Annual Publications and Total Citations. Trends in Annual Publications and Total Citations. The collaboration networks among countries/regions were clustered and visualized using Scimago Graphica ( Figure 2A ). The six collaboration clusters included the following countries/regions: Cluster 1: USA, Canada, United Kingdom, Spain, Italy, Poland, Finland, Denmark, China, and Australia; Cluster 2: Brazil and South Africa; Cluster 3:Turkey, India and Egypt; Cluster 4: Iran and malaysia; Cluster 5: Romania; Cluster 6: China Taiwan. The collaboration frequency and linkages between countries are shown in Figure 2B . China and the USA exhibited the highest international collaboration frequency. Additionally, China established close collaborations with Iran, the United Kingdom, and Canada, while the USA maintained frequent interactions with Turkey, Iran, and other countries. The overall network displayed a multi-hub structure, with key nodes such as China, the USA, Iran, and the United Kingdom, reflecting their dominant roles and connective capabilities in international collaboration. Annual publication counts by country are presented in Figure 2C . China’s output surged rapidly after 2015, increasing from 14 articles in 2015 to 95 in 2021 and remaining high in 2024 (84 articles). In contrast, the USA maintained stable output with minimal fluctuations. National contributions to the field are detailed in Figure 2D . China’s share rose from approximately 14% in 2015 to 39% in 2024, becoming the largest contributor, while the USA declined from 38% to 17% during the same period. To further quantify research performance, key metrics (publications, total citations, and average citations) for major countries are listed in Table 2 . China ranked first in total publications (562 articles) with 11216 total citations but had a lower average citation rate (20.0 citations/article). The USA ranked second in publications (347 articles) but achieved the highest total citations (15929) and average citations (45.9 citations/article), reflecting its leading research quality and influence. Other countries, such as Australia (62.2 citations/article), France (57.4), and Italy (49.6), also demonstrated strong citation performance. Table 2 Top 10 Countries by Publication Volume in PCOS and Cancer Research Rank Country/Region Documents Citations Average Citations 1 China 562 11,216 20.0 2 USA 347 15,929 45.9 3 Italy 110 5454 49.6 4 Iran 107 2360 22.1 5 India 93 2188 23.5 6 United Kingdom 91 3917 43.0 7 Canada 66 1948 29.5 8 Australia 56 3483 62.2 9 Poland 54 1639 30.4 10 France 53 3042 57.4 Figure 2 Global contribution and collaboration in PCOS and cancer research. ( A ) Country-level collaboration network. ( B ) Chord diagram of inter-country cooperation. ( C ) Annual publication trends of top 10 countries. ( D ) Proportional contributions of top countries over time. Top 10 Countries by Publication Volume in PCOS and Cancer Research Global contribution and collaboration in PCOS and cancer research. ( A ) Country-level collaboration network. ( B ) Chord diagram of inter-country cooperation. ( C ) Annual publication trends of top 10 countries. ( D ) Proportional contributions of top countries over time. Collaboration networks among institutional affiliations were visualized using VOSviewer. Chinese universities and research institutions dominated in quantity, forming dense collaborative clusters centered around institutions such as Fudan University and Shanghai Jiao Tong University, which not only established close collaborations with domestic partners but also developed stable international linkages with universities in Iran, Sweden, the USA, and other countries ( Figure 3A ). The top 10 institutions by publication volume included Fudan University (34 articles), Tehran University of Medical Sciences (31 articles), Zhejiang University (28 articles), Shanghai Jiao Tong University (27 articles), Sichuan University (25 articles), Shandong University (23 articles), Zhengzhou University (22 articles), Karolinska Institute (21 articles), China Medical University (20 articles), and Harvard Medical School (20 articles) ( Figure 3B ). These institutions demonstrated strong research activity in the field, with their total citation counts shown in Figure 3C and Table 3 . Despite Fudan University ranking first in output, Shandong University led in academic impact with 1293 total citations. Similarly, Karolinska Institute and Harvard Medical School, despite moderate publication volumes, achieved 794 and 545 citations, respectively, highlighting their significant scholarly influence in this research domain. Table 3 Top 10 Research Institutions by Publication Volume and Citation Count Rank Organization Documents Citations Country 1 Fudan University 34 603 China 2 University of Tehran Medical Sciences 31 757 Iran 3 Zhejiang University 28 518 China 4 Shanghai Jiao Tong University 27 574 China 5 Sichuan University 25 435 China 6 Shandong University 23 1293 China 7 Zhengzhou University 22 500 China 8 Karolinska Institute 21 794 Sweden 9 China Medical University 20 243 China 10 Harvard Medical School 20 545 USA Figure 3 Institutional performance and collaboration in PCOS and cancer research. ( A ) Co-authorship network of research institutions. ( B ) Top 10 institutions ranked by publication volume. ( C ) Bubble chart of publications and citations by institution. Top 10 Research Institutions by Publication Volume and Citation Count Institutional performance and collaboration in PCOS and cancer research. ( A ) Co-authorship network of research institutions. ( B ) Top 10 institutions ranked by publication volume. ( C ) Bubble chart of publications and citations by institution. The collaboration networks and citation networks of publication journals were visualized using VOSviewer. In terms of journal publication volume, the top 10 journals included Frontiers in Endocrinology (51 articles), Gynecological Endocrinology (51 articles), Journal of Ovarian Research (38 articles), International Journal of Molecular Sciences (36 articles), Reproductive Sciences (32 articles), Nutrients (26 articles), Human Reproduction (24 articles), Journal of Clinical Endocrinology & Metabolism (22 articles), Molecular and Cellular Endocrinology (19 articles), and PLOS ONE (19 articles). These journals demonstrated significant academic influence in the research field, with detailed metrics including Total Citations, Total Link Strength, Impact Factor, and Average Citations per Article provided in Table 4 . Notably, Journal of Clinical Endocrinology & Metabolism , despite its moderate publication count (22 articles), high total citations (971 citations) and highest average citations per article (73 citations/article), reflecting its strong scholarly authority. The inter-journal collaboration network is shown in Figure 4A , and the bubble map illustrating journal publication volume versus citation counts is presented in Figure 4B . Table 4 Top 10 Journals by Publication Volume in PCOS and Cancer Research Rank Journal Name Publications Citations Total Link Strength IF (2023) Average Citations 1 Frontiers in Endocrinology 51 1110 53 5.2 21.8 2 Gynecological Endocrinology 51 556 70 2.0 10.9 3 Journal of Ovarian Research 38 634 80 3.8 16.7 4 International Journal of Molecular Sciences 36 2467 51 4.9 68.5 5 Reproductive Sciences 32 636 80 2.6 19.9 6 Nutrients 26 1187 24 4.8 45.7 7 Human Reproduction 24 679 46 6.0 28.3 8 Journal of Clinical Endocrinology & Metabolism 22 971 73 5.0 44.1 9 Molecular and Cellular Endocrinology 19 644 56 3.8 33.9 10 PLOS ONE 19 388 29 2.9 20.4 Figure 4 Journal visualization in PCOS and cancer research. ( A ) Co-citation network of source journals ( B ) Bubble chart of publication volume and citation count ( C ) Co-citation network of highly referenced journals. Top 10 Journals by Publication Volume in PCOS and Cancer Research Journal visualization in PCOS and cancer research. ( A ) Co-citation network of source journals ( B ) Bubble chart of publication volume and citation count ( C ) Co-citation network of highly referenced journals. Regarding cited references, the top 10 journals were The Journal of Clinical Endocrinology & Metabolism, Fertility and Sterility, Human Reproduction , PLOS ONE, Endocrinology, Human Reproduction Update, The New England Journal of Medicine, Proceedings of the National Academy of Sciences of the USA, The Journal of Biological Chemistry, International Journal of Molecular Sciences. highlighting their pivotal role in shaping interdisciplinary research on PCOS and cancer ( Figure 4C ). Detailed metrics are summarized in Table 5 . Table 5 Top Cited Source Journals in PCOS and Cancer Research Rank Journal Name Citations Total Link Strength IF (2023) JCR Quartile 1 The Journal of Clinical Endocrinology & Metabolism 5381 283,447 5 Q1 2 Fertility and Sterility 3698 186,418 6.6 Q1 3 Human Reproduction 3080 156,986 6 Q1 4 PLOS ONE 1862 95,385 2.9 Q2 5 Endocrinology 1517 95,949 3.8 Q2 6 Human Reproduction Update 1381 74,868 14.8 Q1 7 The New England Journal of Medicine 1135 68,447 96.2 Q1 8 Proceedings of the National Academy of Sciences of the USA 1076 71,029 9.4 Q1 9 The Journal of Biological Chemistry 1065 68,759 4 Q2 10 International Journal of Molecular Sciences 1061 50,782 4.9 Q1 Top Cited Source Journals in PCOS and Cancer Research The collaboration networks among authors were analyzed using VOSviewer, revealing multiple stable collaborative clusters with distinct modular structures. For example, Chavarro Jorge E, Chen Zi-jiang, and Zhang Jing occupied central positions in separate collaborative cores ( Figure 5A ). In terms of publication count ( Figure 5B and Table 6 ), Yang Jing (12 articles) and Asemi Zatollah (11 articles) ranked highest, followed by Chen Zi-jiang, Grynberg Michael, Li Li, and Li Yan (8 articles each). Arlt Wiebke, Azziz Ricardo, Chavarro Jorge E, and Du Toit Therina each published 7 articles. Among the top 10 authors, four were Chinese scholars: Yang Jing, Chen Zi-jiang, Li Li, and Li Yan. Further analysis of the author collaboration network ( Figure 5C ) identified Azziz Ricardo, Fauser BCJM, and Escobar-Morreale HF as central nodes, indicating their strong academic influence. Citation metrics for these authors are shown in Figure 5D . Azziz Ricardo led with 435 co-citations, followed by Legro RS (262 co-citations), Fauser BCJM (252 co-citations), Escobar-Morreale HF (240 co-citations), and Diamanti-Kandarakis E (239 co-citations). Despite moderate publication volumes, these scholars exhibited significant dissemination power and structural influence within the academic network. Table 6 Top 10 Most Prolific Authors in PCOS and Cancer Research Rank Author Documents Citations Average Citations 1 Yang, Jing 12 278 23.2 2 Asemi, Zatollah 11 315 28.6 3 Chen, Zi-jiang 8 115 14.4 4 Grynberg, Michael 8 286 35.8 5 Li, Li 8 247 30.9 6 Li, Yan 8 144 18.0 7 Arlt, Wiebke 7 544 77.7 8 Azziz, Ricardo 7 1351 193.0 9 Chavarro, Jorge E. 7 266 38.0 10 Du Toit, Therina 7 219 31.3 Figure 5 Author productivity and collaboration in PCOS and cancer research. ( A ) Co-authorship network of active authors. ( B ) Top 10 authors ranked by number of publications. ( C ) Collaboration clusters based on co-authorship links. ( D ) Top 10 authors ranked by total citation counts. Top 10 Most Prolific Authors in PCOS and Cancer Research Author productivity and collaboration in PCOS and cancer research. ( A ) Co-authorship network of active authors. ( B ) Top 10 authors ranked by number of publications. ( C ) Collaboration clusters based on co-authorship links. ( D ) Top 10 authors ranked by total citation counts. Through CiteSpace visualization and cluster analysis of the keyword co-occurrence network, 14 keyword clusters were identified ( Figure 6A ). Specific information and timelines of each cluster are as follows: Cluster #0 (fertility preservation) includes representative keywords such as fertility preservation and carcinoma, primarily active in recent years; #1 (endometrial cancer) contains endometrial cancer and metabolic syndrome, concentrated around 2016; #2 (gene expression) focuses on granulosa cells, estrogen receptor, and follicular fluid; #3 (cardiovascular disease) involves terms like oxidative stress, androgen, and insulin resistance, with peak activity around 2017; #4 (body composition) includes type 2 diabetes mellitus and mechanisms; #5 (polycystic ovary syndrome), as the core cluster, covers prostate cancer, obesity, and hyperandrogenism; #6 (ovarian granulosa cells) contains keywords such as management, therapy, and PCOS; #7 (ovarian reserve) addresses themes like inflammation, syndrome PCOS, and adipose tissue; #8 (breast cancer risk) incorporates postmenopausal women, receptor, endometriosis, activation, expression, and proliferation; #9 (granulosa cell) focuses on apoptosis, breast cancer, disease, and associated polycystic ovary syndrome; #10 (breast cancer) is an independent cluster; #11 (polycystic ovarian syndrome) includes polycystic ovary syndrome, associated, and disease; #12 (anti-müllerian hormone) exclusively contains anti-müllerian hormone and health; #13 (ovarian function) features cancer, gene, and identification ( Figure 6B ). Figure 6 Keyword visualization in PCOS and cancer research. ( A ) Co-occurrence clustering of keywords. ( B ) Timeline evolution of high-frequency keywords. ( C ) Top 20 keywords with strongest citation bursts. Keyword visualization in PCOS and cancer research. ( A ) Co-occurrence clustering of keywords. ( B ) Timeline evolution of high-frequency keywords. ( C ) Top 20 keywords with strongest citation bursts. In terms of keyword bursts ( Figure 6C ), keywords with bursts initiating in 2015 include tumor necrosis factor (8.92), impaired glucose tolerance (6.07), quality of life (5.81), cardiovascular risk (5.65), in vitro fertilization (5), diabetes mellitus (4.72), breast cancer (3.96), serum (3.92), metabolic syndrome (3.92). Bursts starting in 2017 include overian reserve (4.81) and bone mineral density (4.81). Necrosis factor alpha (6.02), nfκb (4.35) and association (4.03) emerged in 2019; pathogenesis (4.1) and hormone (3.96) appeared in 2020. 2021 include mechanisms (4.66) and 2022 include apoptosis (5.38), gut microbiota (4.59) and infertility (3.94). Polycystic ovary syndrome is the most frequent keyword (863 occurrences), occupying a central position, while in vitro fertilization has the highest centrality score (1.49), indicating its role as a bridging topic across research directions. Additionally, ovarian reserve, breast, and chemotherapy exhibit high network centrality ( Table 7 ). Table 7 Top Keywords by Frequency and Centrality Rank Keyword Count Keyword Centrality 1 Polycystic ovary syndrome 863 In vitro fertilization 1.49 2 Women 407 Ovarian reserve 0.95 3 Insulin resistance 301 Breast 0.83 4 Cancer 246 Chemotherapy 0.82 5 Expression 213 Fertility drugs 0.82 6 Breast cancer 195 Cohort 0.76 7 Risk 182 Cardiovascular disease 0.58 8 Oxidative stress 146 Follow up 0.58 9 Endometrial cancer 126 Estrogen 0.55 10 Metabolic syndrome 119 Assisted reproductive technology 0.54 Top Keywords by Frequency and Centrality Target genes associated with PCOS and endometrial carcinoma were retrieved from the GeneCards database, yielding 876 and 623 candidate genes, respectively. A total of 250 overlapping genes were identified between PCOS and endometrial carcinoma. A PPI network was constructed using these overlapping genes, comprising 208 nodes and 1148 edges ( Figure 7A ). The top 20 hub targets ranked by connectivity included: TP53 (56), BRCA1 (52), SRC (42), CTNNB1 (38), ATM (36), PIK3CA (36), AKT1 (34), EGFR (33), KRAS (33), PIK3R1 (33), STAT3 (33), BRCA2 (31), RAD51 (31), HRAS (29), NRAS (28), PIK3CD (28), PIK3R2 (28), EP300 (26), MSH2 (26), and PTPN11 (26) ( Figure 7B ). Figure 7 PPI Network Analysis of Shared Genes Between PCOS and Endometrial Carcinoma. ( A ) Visualization of the PPI network. ( B ) Top 20 hub targets ranked within the PPI network. PPI Network Analysis of Shared Genes Between PCOS and Endometrial Carcinoma. ( A ) Visualization of the PPI network. ( B ) Top 20 hub targets ranked within the PPI network. KEGG enrichment analysis of overlapping genes between PCOS and endometrial carcinoma identified 160 signaling pathways. After excluding human disease-related pathways, 86 pathways remained. The top 10 pathways ranked by ascending P-value were: PI3K-Akt signaling pathway, MAPK signaling pathway, Cellular senescence, FoxO signaling pathway, Ras signaling pathway, Rap1 signaling pathway, Signaling pathways regulating pluripotency of stem cells, ErbB signaling pathway, Thyroid hormone signaling pathway, and Focal adhesion ( Figure 8A ). These top 10 pathways were associated with 95 genes. Based on their connectivity to the pathways, the top 20 prioritized genes included: MAPK1, AKT3, AKT2, AKT1, HRAS, MAP2K1, RAF1, MAP2K2, PIK3R2, KRAS, PIK3CA, PIK3R1, PIK3CD, NRAS, EGF, EGFR, IGF1, IGF1R, SOS1, and MYC ( Figure 8B ). Figure 8 KEGG Enrichment Analysis of Shared Genes Between PCOS and Endometrial Carcinoma. ( A ) Top 10 enriched pathways (bubble plot). ( B ) Association between the top 10 pathways and target genes. KEGG Enrichment Analysis of Shared Genes Between PCOS and Endometrial Carcinoma. ( A ) Top 10 enriched pathways (bubble plot). ( B ) Association between the top 10 pathways and target genes.

The data collection for this study was conducted on April 3, 2025, through the WoSCC ( https://www.webofscience.com/wos/woscc/ ), with the search parameters configured as follows: databases were set to Science Citation Index Expanded (SCI-EXPANDED) and Social Sciences Citation Index (SSCI); the timeframe spanned from January 1, 2015, to December 31, 2024; document types were limited to research articles and reviews; and the language was restricted to English. The specific keyword combinations and detailed search strategy are provided in Table 1 . The exported data were saved in plain text format and tab-delimited format to meet the input requirements of CiteSpace (6.4.R1) and VOSviewer, respectively. Table 1 Literature Search Strategy Set Results Search Query #1 16692 TS = (“Polycystic Ovary Syndrome” OR “PCOS” OR “Polycystic Ovarian Syndrome” OR “Ovary Syndrome, Polycystic” OR “Syndrome, Polycystic Ovary” OR “Ovarian Syndrome, Polycystic” OR “Polycystic Ovary Syndrome 1” OR “Sclerocystic Ovarian Degeneration” OR “Ovarian Degeneration, Sclerocystic” OR “Sclerocystic Ovary Syndrome” OR “Stein-Leventhal Syndrome” OR “Stein Leventhal Syndrome” OR “Syndrome, Stein-Leventhal” OR “Sclerocystic Ovaries” OR “Ovary, Sclerocystic” OR “Sclerocystic Ovary” OR “Ovarian Dysfunction” OR “Androgen Excess” OR “Hyperandrogenism” OR “Chronic Anovulation” OR “Polycystic Ovarian Morphology” OR “Polycystic Ovary Disease” OR “Insulin Resistance Syndrome”) #2 2220761 TS = (“Cancer” OR “Neoplasm” OR “Malignancy” OR “Tumor” OR “Carcinoma*” OR “Oncogenesis” OR “Oncology” OR “Metastasis” OR “Endometrial Cancer” OR “Endometrial Neoplasm*” OR “Uterine Cancer” OR “Uterine Neoplasm*” OR “Ovarian Cancer” OR “Ovarian Neoplasm*” OR “Breast Cancer” OR “Breast Neoplasm*” OR “Gynecologic Cancer” OR “Gynecologic Neoplasm*” OR “Hormone-dependent Cancer” OR “Hormone-related Malignancy” OR “Reproductive Cancer” OR “Reproductive Neoplasm*”) #3 1869 #1 AND #2 Literature Search Strategy CiteSpace 6.4.R1 was used to construct literature co-citation networks and analyze keyword clustering and evolution. 7 The data retrieved from WoSCC were imported into CiteSpace, with parameters set as follows: time slicing spanned from 2015 to 2024 (annual slices), threshold selection used the g-index (K=10), network optimization applied the Pathfinder algorithm to prune slice networks followed by secondary pruning after merging the networks, and visualization metrics linked node diameter to frequency of occurrence and line width to co-occurrence strength. VOSviewer 1.6.19 was utilized to process collaboration networks and co-occurrence analysis. 8 WoSCC export files were converted to UTF-8 encoding, and the network layout was optimized using the Linlog modularity algorithm. In the visualized networks, node size was proportional to either document count (publications) or citation count. Scimago Graphica 1.0.25 was primarily employed to visualize country/region collaboration networks. 9 The GML-formatted country collaboration table obtained from VOSviewer was imported into Scimago Graphica, with parameters configured as follows: the label menu corresponded to “Country” and the cluster menu corresponded to “String”. The generated country collaboration network mapped node diameter to national publication volume and line thickness to inter-country collaboration frequency. WPS Excel 2023 was used for basic statistical analysis, creating visualizations such as donut charts, bar charts, and column charts based on the extracted data. High-relevance genes were retrieved from the GeneCards database ( https://www.genecards.org/ ) using the keywords “Polycystic Ovary Syndrome” and “Endometrial Cancer” 10 Genes with a relevance score >25 were selected. Overlapping high-score genes shared between both diseases were identified as candidate genes. The intersecting genes was obtained through the Bioinformatics.com.cn platform ( http://www.bioinformatics.com.cn/ ). 11 , 12 Overlapping genes were imported into the STRING database ( https://cn.string-db.org/ ) 13 with the following parameters: Organism: Homo sapiens; Minimum interaction score: High confidence (0.700); Disconnected nodes hidden. The PPI network was exported in TSV format and visualized using Cytoscape software (version 3.7.2, https://cytoscape.org/ ). 14 , 15 The overlapping genes were subjected to KEGG pathway analysis using the clusterProfiler package 16 , 17 (v4.6.2) on R 4.4.2 ( https://www.r-project.org/ ). Significant pathways were filtered using the Benjamini-Hochberg method (FDR<0.05). Disease-related pathways were excluded. The top 10 enriched pathways were selected to construct a “gene-pathway” regulatory network, which was visualized in Cytoscape.

This study comprehensively, scientifically, and systematically analyzed the research landscape and frontiers of PCOS and cancer based on bibliometrics, visualization analysis, and bioinformatics, while identifying potential targets and pathways linking PCOS to endometrial cancer. Our research observed that global interest in PCOS and cancer-related studies has significantly increased over the past decade, with research hotspots predominantly focused on endometrial cancer. Further bioinformatics investigations revealed that the PI3K/AKT signaling pathway may play the most critical role in the association between PCOS and endometrial cancer.

In the past, research on the comorbid conditions of PCOS primarily focused on infertility, 18 type 2 diabetes, 19 obesity, 20 non-alcoholic fatty liver disease, 21 and depression. 22 The association between PCOS and cancer has received increasing attention in recent years. The long-term anovulation and progesterone deficiency in PCOS patients may be key factors contributing to the development of endometrial cancer, breast cancer, and ovarian cancer. 23 A nationwide Danish cohort study, utilizing a national database and including 1,719,452 women, found that women with PCOS had a threefold higher risk of endometrial cancer compared to women without PCOS. Among these, women of reproductive age exhibited an even greater risk, reaching nearly sixfold higher than the control group. 24 Women with PCOS have an increased overall risk of breast cancer, and subgroup analyses revealed that this risk elevation was confined to postmenopausal women. 25 A study utilizing the National Inpatient Sample database revealed that women with PCOS exhibited a nearly four-fold higher risk of endometrial cancer compared to those without the condition, while no significant increase in ovarian or cervical cancer risk was observed. 26 A meta-analysis demonstrated that, after excluding postmenopausal women, individuals with PCOS had a more than five-fold increased risk of endometrial cancer compared to those without the syndrome. 27 The aforementioned studies confirm a significant association between PCOS and malignancies, particularly highlighting its strong linkage with endometrial cancer risk. Bibliometric analysis reveals that publications investigating the association between PCOS and neoplasms exhibited a steady growth trend from 2015 to 2021, with a notable surge in 2021 followed by stabilization, indicating sustained academic attention to this field in recent years. China and the United States dominate the global publication output, with China demonstrating a rapid increase in annual publications, whereas the US maintains a stable production volume. The comparatively lower influence of Chinese academic publications relative to other nations may be associated with the nation’s research evaluation system, which historically emphasized quantitative output over qualitative impact. At the institutional level, Chinese institutions account for the majority of high-yield organizations. Fudan University leads in publication volume, yet Shandong University demonstrates disproportionately higher influence within this domain. Author-level analysis further indicates that the most influential researchers in this field typically maintain moderate publication volumes. These findings collectively suggest a non-linear relationship between quantity and quality in PCOS-cancer research. High-impact institutions and authors likely prioritize research depth and innovation, strategically allocating resources to cultivate seminal studies with enduring academic value rather than pursuing indiscriminate productivity. Among journals, Frontiers in Endocrinology and Gynecological Endocrinology rank first in publication volume related to PCOS and cancer. However, their citation impact markedly lags behind International Journal of Molecular Sciences . Reference analysis identifies The Journal of Clinical Endocrinology & Metabolism as the most frequently cited source in foundational literature, underscoring its pivotal role in shaping the intellectual framework of PCOS-cancer research. Keyword-based analysis revealed that endometrial cancer is a major research focus in the field of PCOS and cancer-related studies, garnering increasing attention. Based on this finding, we retrieved PCOS and endometrial cancer-associated gene targets from the Genecards database and identified overlapping genes as potential shared molecular targets for subsequent analysis. We then performed PPI network analysis to pinpoint key hub genes, followed by KEGG pathway enrichment analysis to elucidate critical signaling pathways. The PPI analysis identified the top 20 hub genes, including: TP53, BRCA1, SRC, CTNNB1, ATM, PIK3CA, AKT1, EGFR, KRAS, PIK3R1, STAT3, BRCA2, RAD51, HRAS, NRAS, PIK3CD, PIK3R2, EP300, MSH2, and PTPN11. Among these gene targets, TP53, BRCA1, BRCA2, ATM, MSH2, EP300 are key tumor suppressor genes, and mutations in these genes lead to abnormal cell cycle regulation, impaired DNA repair, and other cellular functions. 28–30 SRC encodes a non-receptor tyrosine kinase, which is activated by phosphorylating tyrosine residues of the corresponding target proteins to activate MAPK, STAT, PI3K/AKT, EGFR, and other tumor-associated signaling pathways. 31 , 32 CTNNB1 affects tumor progression by regulating the Wnt/β-catenin signaling pathway. 33 PIK3CA, AKT1, PIK3CD, PIK3R2 encode key proteins in the PI3K/AKT signaling pathway, which is critically involved in tumorigenesis. 34 The epidermal growth factor receptor (EGFR) orchestrates tissue homeostasis through regulating cellular proliferation, differentiation, migration, and apoptosis, while functioning as a central oncogenic driver that promotes tumorigenesis, disease progression, and therapeutic resistance across multiple cancer types. 35 In the KEGG enrichment analysis, the PI3K/AKT signaling pathway was significantly enriched, indicating its central involvement in both PCOS and endometrial cancer. The PI3K/AKT signaling pathway plays a critical role in insulin resistance, hyperandrogenism, and abnormal follicular development in PCOS, participating in the entire disease progression. 36 , 37 The PI3K/AKT signaling pathway serves as a central regulatory hub in tumorigenesis and cancer progression by modulating critical cellular processes including proliferation, survival, metabolic reprogramming, inflammatory responses, and angiogenesis, with PI3K inhibitors and AKT inhibitors having advanced to clinical trial phases for anticancer therapeutic development. 38–42 Furthermore, the PI3K/AKT signaling pathway regulates key targets and pathways identified through PPI network analysis and KEGG enrichment, thereby driving tumorigenesis. Regarding the impact on key targets, the PI3K/AKT pathway phosphorylates and activates MDM2 (an E3 ubiquitin ligase), thereby promoting ubiquitination-mediated degradation of p53 and reducing its protein stability. 43 AKT phosphorylates BRCA1 at Serine 694, which inhibits its binding to BARD1, thereby impairing DNA damage repair capacity and concurrently promoting tumor cell migration, invasion, and epithelial-mesenchymal transition. 44 AKT phosphorylates β-catenin at Serine 552, preventing its degradation by GSK3β and promoting nuclear translocation and Wnt signaling activation, thereby enhancing tumor stemness and metastasis. 45 , 46 In terms of signaling pathway interactions, the PI3K/AKT and MAPK pathways form a complex regulatory network through upstream crosstalk, direct phosphorylation, negative feedback loops, and transcriptional synergy, collectively driving tumor proliferation, survival, metastasis, and therapy resistance. 47 , 48 Compensatory activation between these pathways represents a major cause of failure in targeted cancer therapies. Concurrently, phosphorylation-mediated activation of AKT induces the inactivation of FoxO proteins via phosphorylation, thereby abolishing the tumor-suppressive effects of the FoxO signaling pathway. 49–51 In summary, the PI3K/AKT signaling pathway plays a pivotal role in both PCOS and endometrial carcinogenesis.

This study inevitably has several limitations. First, the methodology exclusively utilized WoSCC as the sole data source, which may compromise the comprehensiveness of findings due to the exclusion of materials from major biomedical repositories such as PubMed, Scopus, and Embase. Second, the selection criteria were confined to articles and review papers, potentially overlooking valuable insights contained in alternative publication formats like conference proceedings and technical reports. Future research should prioritize international collaboration across three critical dimensions: investigating the dynamic interplay between PCOS-associated metabolic dysregulation and tumor microenvironment evolution, validating the clinical efficacy of PI3K/AKT pathway-targeted therapies, and developing multi-omics risk prediction models to refine personalized cancer surveillance protocols for PCOS populations. Such an integrative approach bridging mechanistic exploration and clinical implementation could establish novel paradigms for precision medicine in PCOS-related oncopathology.