Research Trends in the Early Diagnosis of Ovarian Cancer during 2001–2020: A Bibliometric Analysis

Background: Ovarian cancer (OC) is the most fatal gynecologic malignancy tumor, and early diagnosis is difficult. There are few bibliometric studies on the early diagnosis of OC. This study aims to visualize the research trends on early diagnosis of OC through a bibliometric analysis. Methods: Publications on early diagnosis of OC from the Web of Science Core Collection (WoSCC) were downloaded. We used the CiteSpace software for bibliometrics and visualization analysis of publications, authors, cited authors, countries, institutions, references, cited journals, and keywords, etc. Results: 464 institutions in 70 countries published a total of 1015 articles during 2001–2020. The number of articles increased annually. With the United States of America (USA) and China as leading contributors. University College London (UCL) and the University of Texas MD Anderson Cancer Center were the major research institutions, with a majority of top 10 institutions located in the USA. Gynecologic Oncology was the most published journal as well as the most co-cite. Usha Menon was the most frequently published author and Ian J. Jacobs was the most frequently cited author. Co-citation cluster labels revealed characteristics of 17 main clusters: CA125, proteomics, diagnostic/prognostic biomarkers, gene expression profiling, BRAF, randomized controlled trial (RCT), exosome, prognosis, epidemiology, salpingectomy, HE4, symptoms, human, ovary, the prognosis of OC, mucinous carcinoma, and tumor-associated antigens. Keywords burst detection showed that HE4, algorithm, pathway, expression, collaborative trial, RCT, serous carcinoma, and prognosis were recent research trends. Conclusions: This study used bibliometrics and visualization methods to illustrate research trends in the early diagnosis of OC during 2001–2020. In-depth study of traditional tumor markers, the discovery of DNA and non-coding RNA and exosomes, as well as gene chip, proteomics, mass spectrometry, immunohistochemistry, liquid biopsy, prophylactic Salpingectomy, and epidemiology in the diagnosis of early stage OC have important research value and application prospects. Finding more accurate biomarkers on the basis of basic and clinical studies, and carrying out larger and multi-center clinical trials, will be the focal points in the future.

ovarian cancer; early diagnosis; early detection; bibliometrics; trends; CiteSpace

[1] Stewart C, Ralyea C, Lockwood S. Ovarian Cancer: an Integrated Review. Seminars in Oncology Nursing. 2019; 35: 151–156.

[2] Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021; 71: 209–249.

[3] Reid F, Bhatla N, Oza AM, Blank SV, Cohen R, Adams T, et al. The World Ovarian Cancer Coalition Every Woman Study: Identifying Challenges and Opportunities to Improve Survival and Quality of Life. International Journal of Gynecological Cancer. 2021; 31: 238–244.

[4] Chen C, Ibekwe-SanJuan F, Hou J. The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis. Journal of the American Society for Information Science and Technology. 2010; 61: 1386–1409.

[5] Liang C, Luo A, Zhong Z. Knowledge mapping of medication literacy study: a visualized analysis using CiteSpace. SAGE Open Medicine. 2018; 6: 2050312118800199.

[6] Chen C, Chen Y. Searching for clinical evidence in CiteSpace. AMIA Annual Symposium Proceedings. 2005; 2005: 121–125.

[7] Xie P. Study of international anticancer research trends via coword and document co-citation visualization analysis. Scientometrics. 2015; 105: 611–622.

[8] Jacobs IJ, Menon U, Ryan A, Gentry-Maharaj A, Burnell M, Kalsi JK, et al. Ovarian cancer screening and mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): A randomised controlled trial. The Lancet. 2016; 387: 945.

[9] Murgan SS, Elaziz FJA, Nasr AMA, Elfaki EE, Khalil EAG. Ovarian Cancer: tumor-specific urinary micro-peptides profiling as potential biomarkers for early diagnosis. Proteomes. 2020; 8: 32.

[10] Lheureux S, Braunstein M, Oza AM. Epithelial ovarian cancer: Evolution of management in the era of precision medicine. CA: A Cancer Journal for Clinicians. 2019; 69: 280–304.

[11] Ma Y, Wang X, Qiu C, Qin J, Wang K, Sun G, et al. Using protein microarray to identify and evaluate autoantibodies to tumor-associated antigens in ovarian cancer. Cancer Science. 2021; 112: 537–549.

[12] Bast RC, Klug TL, St John E, Jenison E, Niloff JM, Lazarus H, et al. A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. The New England Journal of Medicine. 1983; 309: 883–887.

[13] Weiland F, Lokman NA, Klingler-Hoffmann M, Jobling T, Stephens AN, Sundfeldt K, et al. Ovarian blood sampling identifies junction plakoglobin as a novel biomarker of early ovarian cancer. Frontiers in Oncology. 2020; 10: 1767.

[14] Enroth S, Berggrund M, Lycke M, Broberg J, Lundberg M, Assarsson E, et al. High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer. Communications Biology. 2019; 2: 221.

[15] Whitwell HJ, Worthington J, Blyuss O, Gentry-Maharaj A, Ryan A, Gunu R, et al. Improved early detection of ovarian cancer u-ing longitudinal multimarker models. British Journal of Cancer. 2020; 122: 847–856.

[16] Manchana T, Phoolcharoen N, Tantbirojn P. BRCA mutation in high grade epithelial ovarian cancers. Gynecologic Oncology Reports. 2020; 29: 102–105.

[17] Killock D. CancerSEEK and destroy - a blood test for early cancer detection. Nature Reviews Clinical Oncology. 2018; 15: 133–133.

[18] Ishak CA, De Carvalho DD. DNA Methylation Profiling of Premalignant Lesions as a Path to Ovarian Cancer Early Detection. Clinical Cancer Research. 2020; 26: 6083–6085.

[19] Douville C, Cohen JD, Ptak J, Popoli M, Schaefer J, Silliman N, et al. Assessing aneuploidy with repetitive element sequencing. Proceedings of the National Academy of Sciences. 2020; 117: 4858–4863.

[20] Hao X, Luo H, Krawczyk M, Wei W, Wang W, Wang J, et al. DNA methylation markers for diagnosis and prognosis of common cancers. Proceedings of the National Academy of Sciences of the United States of America. 2017; 114: 7414–7419.

[21] Li H, Xu Y, Zhao D. MicroRNA-193b regulates human ovarian cancer cell growth via targeting STMN1. Experimental and Therapeutic Medicine. 2020; 20: 3310–3315.

[22] Qiao B, Wang Q, Zhao Y, Wu J. MiR-205-3p Functions as a Tumor Suppressor in Ovarian Carcinoma. Reproductive Sciences. 2020; 27: 380–388.

[23] Song KW, Zhang QG, Tan WB, Fang YN. Diagnostic signif-icance of serum miR-26b and miR-21 expressions in ovarian cancer and their associations with clinicopathological characteristics and prognosis of patients. European Review for Medical and Pharmacological Sciences. 2020; 24: 1697–1703.

[24] Wang W, Yin Y, Shan X, Zhou X, Liu P, Cao Q, et al. The Value of Plasma-Based MicroRNAs as Diagnostic Biomarkers for Ovarian Cancer. The American Journal of the Medical Sciences. 2019; 358: 256–267.

[25] Maeda K, Sasaki H, Ueda S, Miyamoto S, Terada S, Konishi H, et al. Serum exosomal microRNA-34a as a potential biomarker in epithelial ovarian cancer. Journal of Ovarian Research. 2020; 13: 47.

[26] Zhou J, Gong G, Tan H, Dai F, Zhu X, Chen Y, et al. Urinary microRNA-30a-5p is a potential biomarker for ovarian serous adenocarcinoma. Oncology Reports. 2015; 33: 2915–2923.

[27] Wang X, Yao Y, Jin M. Circ-0001068 is a novel biomarker for ovarian cancer and inducer of PD1 expression in T cells. Aging. 2020; 12: 19095–19106.

[28] Xie Z, Chen X, Li J, Guo Y, Li H, Pan X, et al. Salivary HOTAIR and PVT1 as novel biomarkers for early pancreatic cancer. Oncotarget. 2016; 7: 25408–25419.

[29] Yang M, Zhai Z, Guo S, Li X, Zhu Y, Wang Y. Long non-coding RNA FLJ33360 participates in ovarian cancer progression by sponging miR-30b-3p. OncoTargets and Therapy. 2019; 12: 4469–4480.

[30] Yang M, Zhai Z, Zhang Y, Wang Y. Clinical significance and oncogene function of long noncoding RNA HAGLROS overex-pression in ovarian cancer. Archives of Gynecology and Obstet-rics. 2019; 300: 703–710.

[31] Cheng L, Zhang K, Qing Y, Li D, Cui M, Jin P, et al. Proteomic and lipidomic analysis of exosomes derived from ovarian cancer cells and ovarian surface epithelial cells. Journal of Ovarian Research. 2020; 13: 9.

[32] Buys SS, Partridge E, Black A, Johnson CC, Lamerato L, Isaacs C, et al. Effect of screening on ovarian cancer mortality: the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Randomized Controlled Trial. Journal of the American Medical Association. 2011; 305: 2295–2303.

[33] Thigpen JT. Sensitivity and specificity of multimodal and ultrasound screening for ovarian cancer, and stage distribution of detected cancers: results of the prevalence screen of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Yearbook of Oncology. 2009; 10: 327–340.

[34] Yamamoto CM, Oakes ML, Murakami T, Muto MG, Berkowitz RS, Ng S. Comparison of benign peritoneal fluid- and ovarian cancer ascites-derived extracellular vesicle RNA biomarkers. Journal of Ovarian Research. 2018; 11: 20.

[35] Ducie J, Dao F, Considine M, Olvera N, Shaw PA, Kurman RJ, et al. Molecular analysis of high-grade serous ovarian carcinoma with and without associated serous tubal intra-epithelial carcinoma. Nature Communications. 2017; 8: 990.

[36] Kurman RJ, Shih I. The Dualistic Model of Ovarian Carcinogenesis: Revisited, Revised, and Expanded. The American Journal of Pathology. 2016; 186: 733–747.

[37] Parker WH. Bilateral oophorectomy versus ovarian conservation: effects on long-term women’s health. Journal of Minimally Invasive Gynecology. 2010; 17: 161–166.

[38] Falconer H, Yin L, Salehi S, Altman D. Association between pelvic inflammatory disease and subsequent salpingectomy on the risk for ovarian cancer. European Journal of Cancer. 2021; 145: 38–43.

[39] Trinidad CV, Tetlow AL, Bantis LE, Godwin AK. Reducing Ovarian Cancer Mortality through Early Detection: Approaches Using Circulating Biomarkers. Cancer Prevention Research. 2020; 13: 241–252.

[40] Hann KEJ, Ali N, Gessler S, Fraser LSM, Side L, Waller J, et al. Attitudes towards a programme of risk assessment and stratified management for ovarian cancer: a focus group study of UK South Asians’ perspectives. BMJ Open. 2018; 8: e021782.