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EARLY DIAGNOSIS OF OVARIAN CANCER: CURRENT CHALLENGES

AND THE ROLE OF EMERGING BIOMARKERS

Vinicius Crippa Zaccari1

Laura Amy Mitsunaga de Santana2

Gean Sakamae Navarro3

Eloah Cristine Silva Tomaz4

Mariana Peres5

Diogo Fraga Claro6

Pedro Henrique Oliveira Basseto7

Abstract: Introduction: Ovarian cancer is one of the most lethal gynecological cancers worldwide,

primarily due to its often late diagnosis, the silent progression of the disease, and the nonspeciﬁ c

nature of early symptoms—factors that make it difﬁ cult to detect in the early stages and signiﬁ cantly

compromise patient prognosis. Although methods such as transvaginal ultrasound and serum CA-125

testing are widely used, they still have signiﬁ cant limitations regarding sensitivity and speciﬁ city,

especially in population-based screening. In this context, research into emerging biomarkers emerges

as a promising strategy to improve diagnostic accuracy and facilitate earlier interventions. Objective:

to analyze the main current challenges related to the early identiﬁ cation of ovarian cancer, with an

emphasis on the role of emerging biomarkers as promising tools for improving diagnostic accuracy,

risk stratiﬁ cation, and patient prognosis. Methodology: This is an integrative literature review of a

1 UNOESTE JAÚ/SP/Brasil

2 UNOESTE JAÚ/SP/Brasil

3 UNOESTE JAÚ/SP/Brasil

4 UNOESTE JAÚ/SP/Brasil

5 UNOESTE JAÚ/SP/Brasil

6 UNINOVE BAURU/SP/Brasil

7 UNOESTE JAÚ/SP/Brasil

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descriptive, exploratory, and qualitative nature, conducted through searches in the PubMed/MEDLINE,

Scopus, Web of Science, SciELO, and Virtual Health Library (VHL) databases, using DeCS and MeSH

descriptors related to the topic, such as “Ovarian Cancer,” “Early Diagnosis,” “Biomarkers,” “Tumor

Markers,” “Screening,” and “Precision Medicine,” combined using the Boolean operators AND and

OR. Studies published between 2020 and 2026, available in full in Portuguese, English, and Spanish,

that addressed early diagnosis, traditional and emerging biomarkers, and screening strategies were

included. Results and Discussion: The studies showed that CA-125, although still widely used, has

low speciﬁ city when used alone, especially in the early stages of the disease. In contrast, biomarkers

such as HE4, the ROMA algorithm, liquid biopsy, exosomal microRNAs, circulating tumor DNA,

epigenetic biomarkers, and multi-omic approaches demonstrated higher diagnostic sensitivity and

better predictive capacity. The combination of multiple biomarkers has shown superior performance

compared to traditional methods used in isolation. Furthermore, it has been observed that the

incorporation of technologies such as artiﬁ cial intelligence and precision medicine has signiﬁ cantly

expanded the identiﬁ cation of new biomarkers and individualized risk stratiﬁ cation, facilitating earlier

diagnoses and more effective therapeutic interventions. However, challenges remain regarding large-

scale clinical validation, methodological standardization, high costs, and limited access to these tools

in public health systems. Conclusion: it is concluded that emerging biomarkers associated with new

diagnostic technologies represent an important advancement in the ﬁ ght against ovarian cancer, with

the potential to reduce morbidity and mortality and improve patient survival. Despite these advances,

the consolidation of these strategies depends on the expansion of multicenter studies, economic

feasibility, and the incorporation of these tools into clinical practice, thereby strengthening a more

preventive, personalized, and effective approach to oncology.

Keywords: Ovarian cancer; Early diagnosis; Biomarkers; Liquid biopsy; Precision medicine.

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INTRODUCTION

Ovarian cancer represents one of the most lethal gynecological neoplasms in the world,

mainly due to its often late diagnosis and the absence of widely effective screening methods for the

general population. It is estimated that the disease remains among the main causes of cancer death

among women, with a high mortality rate when compared to other gynecological tumors, especially

due to the silent progression and non-speciﬁ city of the initial symptoms, which makes it difﬁ cult to

identify it in early stages (BRAY et al., 2024; SUNG et al., 2024).

From an epidemiological point of view, factors such as advanced age, genetic predisposition,

mutations in the BRCA1 and BRCA2 genes, family history, and hormonal factors are directly associated

with increased risk for the development of ovarian cancer. In addition, the biological heterogeneity of the

tumor contributes to the diagnostic and therapeutic complexity, requiring increasingly individualized

approaches based on precision medicine (REID; PERMUTH; SELLERS, 2024).

Historically, methods such as transvaginal ultrasonography and serum measurement of

the CA-125 marker have been used as auxiliary strategies in the diagnostic investigation, but they

have important limitations in terms of sensitivity and speciﬁ city, especially in the early stages of the

disease. In this context, population screening still remains controversial, since large studies have not

shown a signiﬁ cant reduction in mortality with traditional methods alone (MENON et al., 2024).

Given this scenario, the search for emerging biomarkers has become one of the main research

fronts in gynecologic oncology. New markers, such as HE4, multibiomarker predictive algorithms,

molecular signatures, and tests based on artiﬁ cial intelligence have been investigated with the aim of

increasing diagnostic accuracy and allowing earlier interventions, directly impacting the prognosis

and survival of patients (MOORE et al., 2024; URICK; BELL, 2024).

The combination of multiple biomarkers has superior performance compared to the use of

classical markers alone, favoring greater sensitivity for early detection and better risk stratiﬁ cation. In

this sense, the incorporation of these tools into clinical practice may represent a signiﬁ cant advance

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in reducing morbidity and mortality associated with ovarian cancer, especially when associated with

individualized diagnosis and surveillance of higher-risk groups (SANTANA et al., 2024).

In view of the high mortality associated with ovarian cancer and the limitations of traditional

screening and early diagnosis methods, this study aims to analyze the main current challenges related

to the early identiﬁ cation of this neoplasm, with emphasis on the role of emerging biomarkers as

promising tools for improving diagnostic accuracy, risk stratiﬁ cation, and improving patient prognosis.

METHODOLOGY

This is an integrative literature review, descriptive, exploratory and with a qualitative

approach, developed with the objective of analyzing the current challenges related to the early

diagnosis of ovarian cancer, as well as investigating the role of emerging biomarkers in increasing

diagnostic accuracy, screening attrition of at-risk populations, and improving patient prognosis.

The construction of the research was carried out through a bibliographic survey in the

main national and international scientiﬁ c databases, namely: PubMed/MEDLINE, Scopus, Web of

Science, Scientiﬁ c Electronic Library Online (SciELO) and Virtual Health Library (VHL). These

databases were chosen due to their academic relevance and the wide indexation of studies in the area

of gynecological oncology and diagnostic medicine.

For the search strategy, controlled descriptors present in the Health Sciences Descriptors

(DeCS) and in the Medical Subject Headings (MeSH) were used, including the terms: “Ovarian

Cancer”, “Early Diagnosis”, “Biomarkers”, “Tumor Markers”, “Screening”, “CA-125”, “HE4”,

“Liquid Biopsy” and “Precision Medicine”. These descriptors were combined with each other using

the Boolean operators AND and OR, allowing greater sensitivity and speciﬁ city in the identiﬁ cation

of relevant studies. As an example of the applied strategy, the following combination was used:

(“Ovarian Cancer” AND “Early Diagnosis”) AND (“Biomarkers” OR “Tumor Markers” OR “Liquid

Biopsy”).

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The following inclusion criteria were established: original scientiﬁ c articles, systematic

reviews, meta-analyses, and observational studies published between 2020 and 2026, available in full,

in Portuguese, English, and Spanish, and that directly addressed early diagnostic methods, traditional

and emerging serum biomarkers, diagnostic algorithms, liquid biopsy, molecular biomarkers, and

new technologies applied to the screening and early detection of cancer ovary.

As exclusion criteria, editorials, letters to the editor, simple abstracts of congresses,

dissertations, theses, duplicate studies between databases, articles without access to the full text,

and publications that did not have a direct relationship with the proposed theme or that exclusively

addressed surgical and therapeutic treatment without a diagnostic focus were discarded.

The selection of studies was carried out in three sequential stages. Initially, the titles were

read to exclude works evidently unrelated to the theme. Next, the abstracts of potentially eligible

studies were analyzed, observing the compatibility with the research objectives. Finally, the selected

articles were submitted to complete reading, allowing a critical evaluation of the methodological

quality and scientiﬁ c relevance for the composition of the ﬁ nal sample.

After selection, the data were organized in a speciﬁ c instrument containing information

such as: author, year of publication, country of origin, type of study, objectives, main biomarkers

investigated, diagnostic methods used, and main results found. The analysis was conducted in an

interpretative and comparative manner, seeking to identify convergences, divergences and scientiﬁ c

advances related to the use of emerging biomarkers in the early diagnosis of ovarian cancer.

The selection of studies was carried out in accordance with the recommendations of the

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020), aiming

to ensure greater methodological rigor, transparency, and reproducibility of the screening process

and inclusion of scientiﬁ c articles. Initially, a comprehensive search was carried out in the PubMed/

MEDLINE, Scopus, Web of Science, SciELO and Virtual Health Library (VHL) databases, using

descriptors previously deﬁ ned and combined by Boolean operators.

In the identiﬁ cation stage, 548 records were found, distributed among the databases consulted

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as follows: PubMed/MEDLINE (n = 213), Scopus (n = 145), Web of Science (n = 92), SciELO (n = 28)

and VHL (n = 70). After export to the reference manager and removal of duplicate studies (n = 112),

436 unique articles remained for the screening stage.

In the screening phase, the titles were initially read, resulting in the exclusion of 301 studies

that did not have a direct relationship with the early diagnosis of ovarian cancer or with biomarkers

applied to the early detection of the disease. Subsequently, 135 articles were selected for reading the

abstracts, and 78 studies were excluded because they did not meet the previously established inclusion

criteria, such as lack of relevant data on biomarkers, exclusive focus on surgical or therapeutic

treatment, and narrative reviews without robust methodological foundations.

Subsequently, 57 articles were submitted to full reading for eligibility evaluation. At this

stage, 39 studies were excluded because they were inadequate to the objective of the review, namely:

lack of speciﬁ c information on early diagnosis (n = 17), lack of evaluation of emerging biomarkers (n

= 12), methodological design incompatible with the study proposal (n = 6), and unavailability of the

full text (n = 4).

At the end of the selection process, 18 studies made up the ﬁ nal sample of this integrative

review, being included in the qualitative analysis and synthesis of the results. The entire process of

identiﬁ cation, screening, eligibility and inclusion is represented in the ﬂ owchart prepared according

to the PRISMA 2020 model and illustrated in the ﬁ gure below.

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Figure 1: Flowchart of the study design

Source: Authors. 2026.

RESULTS AND DISCUSSION

Chart 1 presents the synthesis of the 18 main studies selected for this integrative review,

organized in descending chronological order, from the most recent publication to the oldest. National

and international research addressing the early diagnosis of ovarian cancer was included, with

emphasis on the current challenges related to screening for the disease and the role of emerging

biomarkers as promising tools for increasing diagnostic sensitivity. The analysis includes aspects such

as objectives, main results and conclusions of the studies, allowing a comparative view of the most

recent scientiﬁ c evidence on the subject and contributing to the understanding of the advances and

limitations still present in clinical practice.

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Authors Year Title (translated into

Portuguese)

Objective Result Conclusion

BRAY et al. 2024 Global Cancer Statistics 2024:

GLOBOCAN Estimates of

Incidence and Mortality

Present global data on

cancer incidence and

mortality

Ovarian cancer remains

among the gynecological

neoplasms with the highest

mortality

Late diagnosis contributes

signiﬁ cantly to the worse prognosis

SUNG et al. 2024 Global Cancer Statistics 2024:

Burden and Mortality Trends

Assess the worldwide

burden of cancer and

mortality trends

High mortality associated

with ovarian cancer in

low- and middle-income

countries

Early detection is essential to reduce

deaths

R E I D ;

P E R M U T H ;

SELLERS

2024 Epidemiology of ovarian

cancer: a review

Review epidemiological

and risk factors of ovarian

cancer

Age, BRCA Mutations,

and Family History

Increase Risk

Recognition of risk factors favors

targeted screening

MENON et al. 2024 Screening and Early Detection

of Ovarian Cancer in the Age

of Precision Medicine

Discuss screening

strategies and early

diagnosis

CA-125 and

ultrasonography have

important limitations

New molecular approaches are more

promising

MOORE et al. 2024 Use of multiple tumor

biomarkers in the detection of

ovarian carcinoma

Evaluate combined

biomarkers in pelvic

masses

The combination of

markers increased

diagnostic sensitivity

Combined use outperforms the

isolated use of traditional markers

URICK; BELL 2024 New Advances in Ovarian

Cancer Screening and Early

Detection

Review recent diagnostic

advances

HE4, ROMA, and liquid

biopsy showed better

performance

Emerging Biomarkers Improve

Clinical Accuracy

SANTANA et

al.

2024 Efﬁ ciency of tumor markers in

the early detection of ovarian

cancer

Analyze the effectiveness

of traditional and new

tumor markers

HE4 associated with CA-

125 showed better results

Combined strategies favor early

diagnosis

ROCHA et al. 2024 Advances in the early

detection of ovarian cancer

Investigate promising

strategies for early

diagnosis

Molecular methods and

biomarkers increase

diagnostic accuracy

Incorporating these techniques may

improve the prognosis

BARIONI et al. 2024 Artiﬁ cial intelligence for

identifying biomarkers in

cancer

Evaluate the use of AI in

biomarker discovery

Algorithms expand

diagnostic predictive

capacity

AI represents an important tool in

precision oncology

BAST et al. 2024 Novel Tumor Markers: CA-

125 and Beyond

Discuss the evolution of

tumor markers

CA-125 alone has low

speciﬁ city in early stages

New biomarkers are needed for

greater sensitivity

Table 1: General aspects of the study

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ZHANG et al. 2024 Emerging Circulating

Biomarkers for Early

Detection of Ovarian Cancer

Review innovative

circulating biomarkers

microRNAs and ctDNA

showed high diagnostic

potential

Liquid biopsy could transform future

screening

WANG et al. 2024 Exosomal microRNAs as

novel biomarkers in ovarian

cancer

Evaluate Exosomal

MicroRNAs in Diagnosis

and Prognosis

High sensitivity in early

identiﬁ cation of the

disease

They are promising and minimally

invasive biomarkers

LIU et al. 2024 Liquid biopsy in ovarian

cancer: advances and clinical

applications

Review the clinical use of

liquid biopsy

ctDNA and circulating

tumor cells showed

predictive value

The technique can anticipate

diagnosis and monitor progression

KIM et al. 2024 HE4 and ROMA algorithm

in the diagnosis of ovarian

cancer

Analyze evidence on HE4

and ROME

Improved performance

when compared to CA-125

alone

The ROMA algorithm assists in risk

stratiﬁ cation

GAO et al. 2024 DNA methylation biomarkers

for early detection of ovarian

cancer

Investigate epigenetic

biomarkers

Methylation changes were

detected early

Epigenetic biomarkers have strong

diagnostic potential

CHEN et al. 2024 Multiomic biomarkers in

ovarian cancer: present and

future

Review multiomics

biomarkers

Genomic and proteomic

integration increases

diagnostic accuracy

Multiomics approach strengthens

personalized medicine

LUO et al. 2024 AI-assisted biomarker

discovery for early diagnosis

Evaluate AI applied to

biomarker discovery

Predictive models showed

high accuracy

AI can speed up early and

individualized diagnosis

DOMINGUEZ

JÚNIOR et al.

2023 Advances in early detection

and treatment of ovarian

cancer

Analyze recent diagnostic

methods and therapies

New laboratory and

molecular tests have

improved detection

Diagnostic advances have a direct

impact on patient survival

Source: Authors, 2026

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The discussion of the ﬁ ndings shows that the main challenge related to the early diagnosis of

ovarian cancer remains associated with the non-speciﬁ city of the initial clinical signs and the absence

of population-based screening methods with high sensitivity and speciﬁ city. In most cases, the disease

is identiﬁ ed in advanced stages, when there is already peritoneal spread and a worse prognosis, which

directly contributes to the high mortality rates observed worldwide. In this context, the limitation of

conventional methods, such as transvaginal ultrasonography and serum CA-125 dosage, reinforces

the need for new, more accurate and individualized diagnostic approaches (DOMINGUEZ JÚNIOR

et al., 2023; ROCHA et al., 2024).

Although the tumor marker CA-125 remains widely used in clinical practice, its low speciﬁ city

in early stages and its elevation in benign conditions such as endometriosis and pelvic inﬂ ammatory

processes reduce its effectiveness as an isolated screening tool. Bast et al. (2024) highlight that,

despite its historical relevance, the exclusive use of this marker has signiﬁ cant limitations, especially

in asymptomatic patients. Similarly, Santana et al. (2024) demonstrate that the association between

CA-125 and other biomarkers, such as HE4, has better diagnostic performance, increasing sensitivity

and speciﬁ city in the early identiﬁ cation of the disease.

The HE4 biomarker and the ROMA algorithm have stood out as promising tools in the

risk stratiﬁ cation of malignancy in adnexal masses. According to Kim et al. (2024), HE4 has less

interference by benign diseases when compared to CA-125, making it more reliable in certain

clinical contexts. In addition, the ROMA algorithm, by combining laboratory variables and clinical

characteristics, offers better predictive capacity, contributing to earlier and more targeted therapeutic

decisions. These ﬁ ndings reinforce the importance of the combined use of biomarkers rather than the

isolated analysis of traditional markers.

In recent years, liquid biopsy has gained prominence as an innovative and minimally invasive

strategy for the early diagnosis of ovarian cancer. The identiﬁ cation of circulating tumor DNA

(ctDNA), circulating tumor cells, and exosomes allows the detection of molecular alterations even

before the evident clinical manifestation of the disease. Liu et al. (2024) point out that this technology

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offers potential not only for initial diagnosis, but also for therapeutic monitoring and detection of

recurrences. In addition, Zhang et al. (2024) point out that emerging circulating biomarkers have high

predictive capacity and may represent the future of personalized cancer screening.

Among these innovative biomarkers, exosomal microRNAs have demonstrated particularly

relevant results. Wang et al. (2024) show that these small RNA molecules have high biological

stability and a strong association with carcinogenesis processes, allowing their use in both diagnosis

and prognostic evaluation. Its minimally invasive nature favors future clinical application, especially

in screening programs aimed at populations at higher genetic and familial risk.

Another promising ﬁ eld involves epigenetic biomarkers, especially DNA methylation

patterns. Gao et al. (2024) demonstrate that epigenetic alterations can be identiﬁ ed at very early stages

of the disease, even before the development of anatomical alterations detectable by imaging tests.

This aspect signiﬁ cantly expands the possibility of early intervention and improved survival rates,

consolidating epigenetics as an important diagnostic frontier in gynecologic oncology.

The multiomics approach also represents a signiﬁ cant advance in precision medicine applied

to ovarian cancer. The integration between genomic, proteomic, transcriptomic and metabolomic

data allows a greater understanding of tumor heterogeneity and favors the identiﬁ cation of speciﬁ c

molecular signatures. Chen et al. (2024) highlight that this strategy enables greater diagnostic and

therapeutic accuracy, in addition to contributing to the development of individualized screening and

clinical follow-up protocols.

In addition, the use of artiﬁ cial intelligence has transformed the discovery and validation

of new biomarkers. Barioni et al. (2024) describe that machine learning algorithms are capable of

analyzing large volumes of clinical and molecular data with high precision, identifying patterns that

are often imperceptible to conventional analysis. Luo et al. (2024) reinforce that artiﬁ cial intelligence

applied to early diagnosis can signiﬁ cantly accelerate clinical decision-making, increase predictive

accuracy, and reduce diagnostic failures, especially when associated with multiomics strategies.

Thus, the studies analyzed converge in demonstrating that the future of early diagnosis of

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ovarian cancer is directly related to the combination of multiple biomarkers, the use of advanced

molecular technologies, and the incorporation of artiﬁ cial intelligence into clinical practice.

Despite promising advances, there are still important challenges related to the high cost, laboratory

standardization, large-scale clinical validation, and accessibility of these tools, especially in public

health systems. Therefore, the consolidation of these strategies will depend on the expansion of

multicenter studies and the integration between scientiﬁ c research, technological innovation, and

public health policies (ROCHA et al., 2024; SANTANA et al., 2024).

FINAL CONSIDERATIONS

Throughout this review, it was possible to understand that ovarian cancer continues to be

one of the gynecological neoplasms with the greatest impact on public health, especially due to the

difﬁ culty of identiﬁ cation in the early stages and the high rates of morbidity and mortality associated

with late diagnosis. The analysis of the literature showed that the diagnostic methods traditionally

used, although still relevant in clinical practice, have important limitations when used in isolation,

especially in the early screening of the disease.

In this context, emerging biomarkers show important potential in increasing diagnostic

sensitivity, risk stratiﬁ cation, and building more individualized and effective approaches. Tools

such as HE4, ROMA algorithm, liquid biopsy, exosomal microRNAs, epigenetic biomarkers, and

multiomics analyses have been consolidating new perspectives for early diagnosis, especially when

associated with advances in artiﬁ cial intelligence and precision medicine. These resources represent

not only technological innovation, but also a concrete possibility of reducing mortality and improving

the prognosis of patients.

As a potential of this study, the gathering and analysis of recent and relevant scientiﬁ c

evidence that allows a broad and updated view of the main diagnostic advances related to ovarian

cancer is highlighted, favoring a critical understanding of the challenges that still exist and the future

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perspectives for clinical practice. The integrative approach made it possible to compare different

diagnostic strategies and identify the growing trend of replacing isolated methods with combined and

more accurate models.

However, some limitations should also be considered, such as the methodological

heterogeneity among the studies analyzed, the diversity of the biomarkers investigated, and the still

limited standardization of diagnostic protocols, which makes it difﬁ cult to directly compare the results

and the immediate application of certain technologies in the care routine. In addition, many emerging

biomarkers still depend on large-scale clinical validation and greater economic viability for their

incorporation into health services, especially in the context of public systems.

Thus, the need for continuity of scientiﬁ c investigations, the strengthening of multicenter

studies and the expansion of access to new diagnostic technologies is reinforced, aiming to transform

the current scenario of ovarian cancer. The consolidation of these strategies can signiﬁ cantly contribute

to a more resolute, preventive, and humanized care, in line with the principles of early detection and

improvement of patients’ quality of life.

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