Liquid Biopsies for Ovarian Carcinoma: How Blood Tests May Improve the Clinical Management of a Deadly Disease

Artificial intelligence in the diagnosis and management of gynecologic cancer

Gynecologic cancers affect over 1.2 million women globally each year. Early diagnosis and effective treatment are essential for improving patient outcomes, yet traditional diagnostic methods often encounter limitations, particularly in low-resource settings. Artificial intelligence (AI) has emerged as a transformative tool that enhances accuracy and efficiency across various aspects of gynecologic oncology, including screening, diagnosis, and treatment. This review examines the current applications of AI in gynecologic cancer care, focusing on areas such as early detection, imaging, personalized treatment planning, and patient monitoring. Based on an analysis of 75 peer-reviewed articles published between 2017 and 2024, we highlight AI's contributions to cervical, ovarian, and endometrial cancer management. AI has notably improved early detection, achieving up to 95% accuracy in cervical cancer screening through AI-enhanced Pap smear analysis and colposcopy. For ovarian and endometrial cancers, AI-driven imaging and biomarker detection have enabled more personalized treatment approaches. In addition, AI tools have enhanced precision in robotic-assisted surgery and radiotherapy, and AI-based histopathology has reduced diagnostic variability. Despite these advancements, challenges such as data privacy, bias, and the need for human oversight must be addressed. The successful integration of AI into clinical practice will require careful consideration of ethical issues and a balanced approach that incorporates human expertise. Overall, AI presents significant potential to improve outcomes in gynecologic oncology, particularly in bridging healthcare gaps in resource-limited settings.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

Liquid biopsy in ovarian cancer: advantages and limitations for prognosis and diagnosis

Ovarian cancer (OC) is a highly fatal gynecologic malignancy, often diagnosed at an advanced stage which presents significant challenges for disease management. The clinical application of conventional tissue biopsy methods and serological biomarkers has limitations for the diagnosis and prognosis of OC patients. Liquid biopsy is a novel sampling method that involves analyzing distinctive tumor elements secreted into the peripheral blood. Growing evidence suggests that liquid biopsy methods such as circulating tumor cells, cell-free RNA, circulating tumor DNA, exosomes, and tumor-educated platelets may improve early prognosis and diagnosis of OC, leading to enhanced therapeutic management of the disease. This study reviewed the evidence demonstrating the utility of liquid biopsy components in OC prognosis and diagnosis, and evaluated the current advantages and limitations of these methods. Additionally, the existing obstacles and crucial topics for future studies utilizing liquid biopsy in OC patients were discussed.

Microfluidics engineering towards personalized oncology-a review

Identifying and monitoring the presence of cancer metastasis and highlighting inter-and intratumoral heterogeneity is a central tenet of targeted precision oncology medicine (POM). This process of relocation of cancer cells is often referred to as the missing link between a tumor and metastasis. In recent years, microfluidic technologies have been developed to isolate a plethora of different biomarkers, such as circulating tumor cells (CTCs), tumor-derived vesicles (exosomes), or cell/free nucleic acids and proteins directly from patients' blood samples. With the advent of microfluidic developments, minimally invasive and quantitative assessment of different tumors is becoming a reality. This short review article will touch briefly on how microfluidics at early-stage achievements can be combined or developed with the active vs passive microfluidic technologies, depending on whether they utilize external fields and forces (active) or just microchannel geometry and inherent fluid forces (passive) from the market to precision oncology research and our future prospectives in terms of the emergence of ultralow cost and rapid prototyping of microfluidics in precision oncology.

Current Understanding on Why Ovarian Cancer Is Resistant to Immune Checkpoint Inhibitors

The standard treatment of ovarian cancer (OC) patients, including debulking surgery and first-line chemotherapy, is unsatisfactory because of recurrent episodes in the majority (~70%) of patients with advanced OC. Clinical trials have shown only a modest (10-15%) response of OC individuals to treatment based on immune checkpoint inhibitors (ICIs). The resistance of OC to therapy is caused by various factors, including OC heterogeneity, low density of tumor-infiltrating lymphocytes (TILs), non-cellular and cellular interactions in the tumor microenvironment (TME), as well as a network of microRNA regulating immune checkpoint pathways. Moreover, ICIs are the most efficient in tumors that are marked by high microsatellite instability and high tumor mutation burden, which is rare among OC patients. The great challenge in ICI implementation is connected with distinguishing hyper-, pseudo-, and real progression of the disease. The understanding of the immunological, molecular, and genetic mechanisms of OC resistance is crucial to selecting the group of OC individuals in whom personalized treatment would be beneficial. In this review, we summarize current knowledge about the selected factors inducing OC resistance and discuss the future directions of ICI-based immunotherapy development for OC patients.

Expression level of CD117 (KIT) on ovarian cancer extracellular vesicles correlates with tumor aggressiveness

Ovarian cancer is known to be the most lethal malignancy among all gynecological cancers affecting a large number of women worldwide. The treatment of ovarian cancer is challenging due to the high recurrence rate of the disease and is further complicated by acquired chemoresistance. Most ovarian cancer deaths are the result of the metastatic spread of drug-resistant cells. The theory of cancer stem cells (CSC) suggests that both tumor initiation and progression are driven by a population of undifferentiated capable of self-renewal, tumor initiation and development of chemoresistance. The CD117 mast/stem cell growth factor receptor (KIT) is the most commonly used marker for ovarian CSCs. Here, we analyze the correlation between CD117 expression and histological tumor type in ovarian cancer cell lines (SK-OV-3 and MES-OV) and in small/medium extracellular vesicles (EVs) isolated from the urine of ovarian cancer patients. We have demonstrated that the abundance of CD117 on cells and EVs is correlated with tumor grade and therapy resistance status. Moreover, using small EVs isolated from ovarian cancer ascites, it was shown that recurrent disease is characterized by a much higher abundance of CD117 on EVs than primary tumor.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Circulating tumor DNA: current challenges for clinical utility

Cancer cells shed naked DNA molecules into the circulation. This circulating tumor DNA (ctDNA) has become the predominant analyte for liquid biopsies to understand the mutational landscape of cancer. Coupled with next-generation sequencing, ctDNA can serve as an alternative substrate to tumor tissues for mutation detection and companion diagnostic purposes. In fact, recent advances in precision medicine have rapidly enabled the use of ctDNA to guide treatment decisions for predicting response and resistance to targeted therapies and immunotherapies. An advantage of using ctDNA over conventional tissue biopsies is the relatively noninvasive approach of obtaining peripheral blood, allowing for simple repeated and serial assessments. Most current clinical practice using ctDNA has endeavored to identify druggable and resistance mutations for guiding systemic therapy decisions, albeit mostly in metastatic disease. However, newer research is evaluating potential for ctDNA as a marker of minimal residual disease in the curative setting and as a useful screening tool to detect cancer in the general population. Here we review the history of ctDNA and liquid biopsies, technologies to detect ctDNA, and some of the current challenges and limitations in using ctDNA as a marker of minimal residual disease and as a general blood-based cancer screening tool. We also discuss the need to develop rigorous clinical studies to prove the clinical utility of ctDNA for future applications in oncology.

Potential clinical utility of liquid biopsies in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is the most lethal gynecologic malignancy worldwide. One of the main challenges in the management of OC is the late clinical presentation of disease that results in poor survival. Conventional tissue biopsy methods and serological biomarkers such as CA-125 have limited clinical applications. Liquid biopsy is a novel sampling method that analyzes distinctive tumour components released into the peripheral circulation, including circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), cell-free RNA (cfRNA), tumour-educated platelets (TEPs) and exosomes. Increasing evidence suggests that liquid biopsy could enhance the clinical management of OC by improving early diagnosis, predicting prognosis, detecting recurrence, and monitoring response to treatment. Capturing the unique tumour genetic landscape can also guide treatment decisions and the selection of appropriate targeted therapies. Key advantages of liquid biopsy include its non-invasive nature and feasibility, which allow for serial sampling and longitudinal monitoring of dynamic tumour changes over time. In this review, we outline the evidence for the clinical utility of each liquid biopsy component and review the advantages and current limitations of applying liquid biopsy in managing ovarian cancer. We also highlight future directions considering the current challenges and explore areas where more studies are warranted to elucidate its emerging clinical potential.

Lamprey immunity protein enables detection for bladder cancer through recognizing N-hydroxyacetylneuraminic acid (Neu5Gc)-modified as a diagnostic marker and exploration of its production mechanism

Previous studies have demonstrated that Neu5Gc is highly expressed in breast, ovarian, prostate, colon and lung cancers, but not in normal human cells. The presence of Neu5Gc is important for prognosis and is associated with aggressiveness, metastasis, and tumor grade. However, increased Neu5Gc in bladder cancer remains unclear. LIP from lamprey binds the carbohydrate receptor of N-glycolylneuraminic acid (Neu5Gc). The combination of Neu5Gc and LIP suggested that it might be used as a diagnostic tool for the detection of Neu5Gc tumor antigen. Here, the classical animal model of bladder cancer was successfully induced by MNU bladder perfusion. The ELISA results showed that the expression level of Neu5Gc in the urine of normal rats was 94.96 ± 21.01ng/mg, and that of bladder cancer rats was 158.28 ± 34.86 ng/mg. In addition, the results of SNA and LIP immunohistochemistry demonstrated the high expression of Neu5Gc in bladder cancer. After the addition of Neu5Gc to BIU-87 and SV-HUC-1 cells, transcriptomic sequencing and real-time quantitative PCR analysis demonstrated that the gene expression of Neu5Gc synthesis pathway was significantly increased. These data suggest that LIP provides a new tool for the detection of biological samples, especially urine from patients with bladder cancer or suspected cancer, and that revealing the mechanism of abnormal glycosylation can provide theoretical basis for clinical studies.

Applications of artificial intelligence (AI) in ovarian cancer, pancreatic cancer, and image biomarker discovery

BACKGROUND

Artificial intelligence (AI), including machine learning (ML) and deep learning, has the potential to revolutionize biomedical research. Defined as the ability to "mimic" human intelligence by machines executing trained algorithms, AI methods are deployed for biomarker discovery.

OBJECTIVE

We detail the advancements and challenges in the use of AI for biomarker discovery in ovarian and pancreatic cancer. We also provide an overview of associated regulatory and ethical considerations.

METHODS

We conducted a literature review using PubMed and Google Scholar to survey the published findings on the use of AI in ovarian cancer, pancreatic cancer, and cancer biomarkers.

RESULTS

Most AI models associated with ovarian and pancreatic cancer have yet to be applied in clinical settings, and imaging data in many studies are not publicly available. Low disease prevalence and asymptomatic disease limits data availability required for AI models. The FDA has yet to qualify imaging biomarkers as effective diagnostic tools for these cancers.

CONCLUSIONS

Challenges associated with data availability, quality, bias, as well as AI transparency and explainability, will likely persist. Explainable and trustworthy AI efforts will need to continue so that the research community can better understand and construct effective models for biomarker discovery in rare cancers.

Role of Circulating Biomarkers in Platinum-Resistant Ovarian Cancer

Ovarian cancer (OC) is the second most common cause of death in women with gynecological cancer. Considering the poor prognosis, particularly in the case of platinum-resistant (PtR) disease, a huge effort was made to define new biomarkers able to help physicians in approaching and treating these challenging patients. Currently, most data can be obtained from tumor biopsy samples, but this is not always available and implies a surgical procedure. On the other hand, circulating biomarkers are detected with non-invasive methods, although this might require expensive techniques. Given the fervent hope in their value, here we focused on the most studied circulating biomarkers that could play a role in PtR OC.

Past, Present, and Future of Serum Tumor Markers in Management of Ovarian Cancer: A Guide for the Radiologist

The ability to accurately detect early ovarian cancer and subsequently monitor treatment response is essential to improving survival for patients with ovarian malignancies. Several serum tumor markers (STMs)-including cancer antigen 125 (CA-125), human epididymis protein 4 (HE4), cancer antigen 19-9 (CA 19-9), and carcinoembryonic antigen (CEA)-have been used as a noninvasive method of identifying ovarian cancer in conjunction with imaging. Although current guidelines do not recommend use of STMs as screening tools for ovarian cancer, these markers have clinical utility in both diagnosis and surveillance for women with ovarian cancer. CA-125 is the most commonly used STM; its level may be elevated in several types of ovarian cancer, including epithelial cell tumors, carcinosarcoma, teratomas, and secondary ovarian malignancies. An elevated level of CA 19-9 is associated with clear cell tumors, teratomas, and secondary malignancies. CEA is most commonly associated with mucinous ovarian cancers. Finally, HE4 is being increasingly used to identify certain subtypes of epithelial ovarian cancers, particularly serous and endometrioid tumors. Diagnosis of ovarian cancers relies on a combination of CA-125 levels and US findings, which include a large adnexal mass or high-risk features, including septa and increased vascularity. CT is preferred for staging and is used along with PET and STM monitoring for surveillance. Increasingly, MRI is being used to characterize ovarian lesions that are indeterminate at US or CT. The future of STM testing involves development of "liquid biopsies," in which plasma samples are analyzed for evidence of tumors, including circulating tumor DNA or tumor cells and tumor micro-RNA. When combined with traditional imaging techniques, liquid biopsies may lead to earlier diagnosis and improved survival. An invited commentary by Shinagare is available online. ^©RSNA, 2021.

Future Screening Prospects for Ovarian Cancer

Simple Summary

Ovarian cancer (OC) has the highest mortality rate of all gynecological cancers. It is usually diagnosed in late stages (FIGO III-IV), and therefore, overall survival is very poor. If diagnosed at the early stages, ovarian cancer has a 90% five-year survival rate. Liquid biopsy has a good potential to improve early ovarian cancer detection and is discussed in this review.

Abstract

Current diagnostic tools used in clinical practice such as transvaginal ultrasound, CA 125, and HE4 are not sensitive and specific enough to diagnose OC in the early stages. A lack of early symptoms and an effective asymptomatic population screening strategy leads to a poor prognosis in OC. New diagnostic and screening methods are urgently needed for early OC diagnosis. Liquid biopsies have been considered as a new noninvasive and promising method, using plasma/serum, uterine lavage, and urine samples for early cancer detection. We analyzed recent studies on molecular biomarkers with specific emphasis on liquid biopsy methods and diagnostic efficacy for OC through the detection of circulating tumor cells, circulating cell-free DNA, small noncoding RNAs, and tumor-educated platelets.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

Extracellular Vesicles: A Novel Tool Facilitating Personalized Medicine and Pharmacogenomics in Oncology

Biomarkers that can guide cancer therapy based on patients' individual cancer molecular signature can enable a more effective treatment with fewer adverse events. Data on actionable somatic mutations and germline genetic variants, studied by personalized medicine and pharmacogenomics, can be obtained from tumor tissue or blood samples. As tissue biopsy cannot reflect the heterogeneity of the tumor or its temporal changes, liquid biopsy is a promising alternative approach. In recent years, extracellular vesicles (EVs) have emerged as a potential source of biomarkers in liquid biopsy. EVs are a heterogeneous population of membrane bound particles, which are released from all cells and accumulate into body fluids. They contain various proteins, lipids, nucleic acids (miRNA, mRNA, and DNA) and metabolites. In cancer, EV biomolecular composition and concentration are changed. Tumor EVs can promote the remodeling of the tumor microenvironment and pre-metastatic niche formation, and contribute to transfer of oncogenic potential or drug resistance during chemotherapy. This makes them a promising source of minimally invasive biomarkers. A limited number of clinical studies investigated EVs to monitor cancer progression, tumor evolution or drug resistance and several putative EV-bound protein and RNA biomarkers were identified. This review is focused on EVs as novel biomarker source for personalized medicine and pharmacogenomics in oncology. As several pharmacogenes and genes associated with targeted therapy, chemotherapy or hormonal therapy were already detected in EVs, they might be used for fine-tuning personalized cancer treatment.

CAMK2N1/RUNX3 methylation is an independent prognostic biomarker for progression-free and overall survival of platinum-sensitive epithelial ovarian cancer patients

BACKGROUND

To date, no predictive or prognostic molecular biomarkers except BRCA mutations are clinically established for epithelial ovarian cancer (EOC) despite being the deadliest gynecological malignancy. Aim of this biomarker study was the analysis of DNA methylation biomarkers for their prognostic value independent from clinical variables in a heterogeneous cohort of 203 EOC patients from two university medical centers.

RESULTS

The marker combination CAMK2N1/RUNX3 exhibited a significant prognostic value for progression-free (PFS) and overall survival (OS) of sporadic platinum-sensitive EOC (n = 188) both in univariate Kaplan-Meier (LogRank p < 0.05) and multivariate Cox regression analysis (p < 0.05; hazard ratio HR = 1.587). KRT86 methylation showed a prognostic value only in univariate analysis because of an association with FIGO staging (Fisher's exact test p < 0.01). Thus, it may represent a marker for EOC staging. Dichotomous prognostic values were observed for KATNAL2 methylation depending on BRCA aberrations. KATNAL2 methylation exhibited a negative prognostic value for PFS in sporadic EOC patients without BRCA1 methylation (HR 1.591, p = 0.012) but positive prognostic value in sporadic EOC with BRCA1 methylation (HR 0.332, p = 0.04) or BRCA-mutated EOC (HR 0.620, n.s.).

CONCLUSION

The retrospective analysis of 188 sporadic platinum-sensitive EOC proved an independent prognostic value of the methylation marker combination CAMK2N1/RUNX3 for PFS and OS. If validated prospectively this combination may identify EOC patients with worse prognosis after standard therapy potentially benefiting from intensive follow-up, maintenance therapies or inclusion in therapeutic studies. The dichotomous prognostic value of KATNAL2 should be validated in larger sample sets of EOC.

Combined detection and subclass characteristics analysis of CTCs and CTECs by SE-iFISH in ovarian cancer

Objective

Hematogenous metastasis is essential for the progression of ovarian cancer (OC), and circulating tumor cells (CTCs) are part of the metastatic cascade. However, the detection rate of CTC is low due to the use of less sensitive detection methods. Therefore, this study aimed to detect CTCs and circulating tumorigenic endothelial cells (CTECs) in patients with OC using subtraction enrichment and immunostaining and fluorescence in situ hybridization (SE-iFISH).

Methods

We enrolled a total of 56 subjects, including 20 OC patients and 36 ovarian benign tumor patients. CTCs and CTECs were captured by subtraction enrichment (SE) and counted and classified according to immunofluorescence staining of tumor markers (TMs) carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) combined with fluorescence in situ hybridization (iFISH) of chromosome 8 (Chr8) aneuploidy. The diagnostic value and subtype characteristics of CTCs and CTECs were investigated.

Results

The detection rate of CTCs by SE-iFISH was high. Compared with CA125 and HE4, Chr8 aneuploidy was the major identification feature of CTC. CTC counts in OC were statistically higher than those in benign groups. CTC and CTEC with ≥pentaploidy were detected in both groups, illustrating the poor diagnostic value of CTC or CTEC. Distributions of triploid and tetraploid CTC subtypes were significantly different, and combined detection of triploid and tetraploid CTCs showed the best diagnostic value. In contrast, the distribution of CTECs in the OC and benign groups had no statistically significant difference. Small CTCs accounted for over 1/3 of the total CTC count. We also found that small CTCs and CTECs primarily comprised triploid cells, while large CTCs and CTECs mainly comprised pentaploidy and beyond.

Conclusions

The application of SE-iFISH offered a more comprehensive understanding of heterogeneous CTCs and CTECs in OC. Analysis of subclass characteristics of the CTCs and CTECs according to Chr8 aneuploidy and cell size may broaden their potential clinical utility and deepen mechanistic studies in OC.

Comprehensive Serum Glycopeptide Spectra Analysis Combined with Artificial Intelligence (CSGSA-AI) to Diagnose Early-Stage Ovarian Cancer

Ovarian cancer is a leading cause of deaths among gynecological cancers, and a method to detect early-stage epithelial ovarian cancer (EOC) is urgently needed. We aimed to develop an artificial intelligence (AI)-based comprehensive serum glycopeptide spectra analysis (CSGSA-AI) method in combination with convolutional neural network (CNN) to detect aberrant glycans in serum samples of patients with EOC. We converted serum glycopeptide expression patterns into two-dimensional (2D) barcodes to let CNN learn and distinguish between EOC and non-EOC. CNN was trained using 60% samples and validated using 40% samples. We observed that principal component analysis-based alignment of glycopeptides to generate 2D barcodes significantly increased the diagnostic accuracy (88%) of the method. When CNN was trained with 2D barcodes colored on the basis of serum levels of CA125 and HE4, a diagnostic accuracy of 95% was achieved. We believe that this simple and low-cost method will increase the detection of EOC.

Clinical outcomes and safety of apatinib monotherapy in the treatment of patients with advanced epithelial ovarian carcinoma who progressed after standard regimens and the analysis of the VEGFR2 polymorphism

The aims of the present study were to investigate the clinical outcomes and safety of apatinib monotherapy in the treatment of patients with advanced epithelial ovarian carcinoma (EOC) who have progressed after standard regimens, and to analyze the vascular endothelial growth factor receptor 2 (VEGFR2) rs2071559 polymorphism. A total of 118 patients with advanced EOC who received apatinib treatment were included in the study. Tumor response was evaluated using progression-free survival (PFS) and overall survival (OS) time, and safety data were documented. Additionally, peripheral blood and peripheral blood mononuclear cell (PBMC) specimens from the patients with EOC were collected to perform the genotyping of genetic polymorphism and assess the mRNA expression of VEGFR2, respectively. The objective response rate across the 118 patients with advanced EOC was 38.98%, the disease control rate was 63.56%, the median PFS time was 4.65 months and the median OS time was 15.10 months. Regarding the polymorphism analysis, the prevalence of rs2071559 in VEGFR2 among the 118 patients with advanced EOC was recorded as the TT genotype in 72 cases (61.02%), TC genotype in 41 cases (34.75%) and CC genotype in 5 cases (4.23%), and the minor allele frequency of rs2071559 was 0.22. The distribution of the three genotypes was in accordance with the Hardy-Weinberg equilibrium (P=0.781). TC and CC genotypes were merged in the subsequent analysis. The prognosis analyses suggested that the median PFS time of patients with the TC/CC genotype and the TT genotype was 3.10 and 5.40 months, respectively (P=0.015). Moreover, the median OS time of the two genotypes was 12.60 and 17.50 months, respectively (P=0.009). However, no association was noted between genotype status of the polymorphism and adverse reactions. Additionally, the mRNA expression analysis indicated that the mRNA expression levels of VEGFR2 in PBMC specimens were significantly different between TT and TC/CC genotypes (P<0.001). The present study suggested that the clinical outcomes of patients with advanced EOC, who progressed after standard regimens and received apatinib treatment, might be influenced by the VEGFR2 rs2071559 polymorphism.