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Diagnostics
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Advances in Diagnosis of Ovarian Cancer
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Advances in Diagnosis of Ovarian Cancer

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 1268

Editor

Dr. Samrita Dogra

E-Mail Website
Guest Editor
Department of Obstetrics and Gynecology, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
Interests: ovarian cancer; gynecological cancers; exosomes; tumor microenvironment; drug resistance; chemotherapy; tumor metabolism; drug screening; tumor organoids; cancer metastatsis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue, titled “Advances in Diagnosis of Ovarian Cancer”, will provide a comprehensive overview of the latest advancements and developments in the field of ovarian cancer diagnosis. Ovarian cancer, being a highly lethal gynecological malignancy, poses significant challenges in early detection and diagnosis due to its anatomical location. This Special Issue will address these challenges by showcasing cutting-edge research and innovative techniques that have the potential to improve the accuracy and timeliness of ovarian cancer diagnosis.

Highlights of the Special Issue will include the following:

  1. Advancements in Biomarkers: This Special Issue will feature articles discussing the discovery and validation of novel biomarkers for ovarian cancer. These biomarkers, which can be detected in blood, urine, or tissue samples, have the potential to facilitate earlier diagnosis and more personalized treatment plans.
  2. Molecular Diagnostics: Advances in molecular diagnostic technologies, such as next-generation sequencing, will be explored in depth. These technologies enable researchers to identify genetic alterations that drive ovarian cancer development and progression, providing insights into disease mechanisms and potential therapeutic targets.
  3. Imaging Modalities: This Special Issue will also cover recent advancements in imaging technologies, including high-resolution ultrasound, CT, MRI, and PET scans. These imaging techniques play a crucial role in detecting ovarian cancer, staging the disease, and monitoring treatment response.
  4. Early Detection Strategies: Given the importance of early diagnosis in improving ovarian cancer survival rates, this Special Issue will discuss novel strategies for early detection. These may include risk assessment models, population screening programs, and the integration of multiple diagnostic modalities.
  5. Clinical Implications and Future Directions: Finally, this Special Issue will examine the clinical implications of these advancements and explore future research directions. This will include the potential for precision medicine approaches, development of new diagnostic tools, and optimization of existing diagnostic algorithms.

In summary, this Special Issue, titled “Advances in Diagnosis of Ovarian Cancer”, will serve as a valuable resource for researchers, clinicians, and healthcare professionals interested in the latest developments in ovarian cancer diagnosis. By highlighting innovative research and technologies, this Special Issue will help to improve outcomes for patients affected by this devastating disease.

Dr. Samrita Dogra
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ovarian cancer diagnosis
  • early detection
  • biomarkers
  • molecular diagnostics
  • imaging technologies
  • precision medicine
  • innovative methods
  • treatment monitoring
  • prognosis assessment

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Published Papers (1 paper)

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Research

22 pages, 26122 KB  
Article
Multi-Omics Profiling in a Symptomatic Cohort Identifies Coordinated Biomarker Signatures in Ovarian Cancer Serum
by Rachel Culp-Hill, Charles M. Nichols, Shannon Kilkenny, Mattie Goldberg, Enkhtuya Radnaa, Maria Wong, Moisés Zapata, Kian Behbakht, Benjamin G. Bitler, Anna Jeter, Vuna S. Fa, Kim Ekroos and Abigail McElhinny
Diagnostics 2026, 16(14), 2143; https://doi.org/10.3390/diagnostics16142143 - 8 Jul 2026
Viewed by 710
Abstract
Background/Objectives: Ovarian cancer (OC) is a leading cause of cancer-related mortality in women, largely driven by late-stage diagnosis. Five-year survival is just 30% for advanced-stage (III-IV) disease but exceeds 90% for early-stage disease, underscoring the critical need for effective early detection tools. Current [...] Read more.
Background/Objectives: Ovarian cancer (OC) is a leading cause of cancer-related mortality in women, largely driven by late-stage diagnosis. Five-year survival is just 30% for advanced-stage (III-IV) disease but exceeds 90% for early-stage disease, underscoring the critical need for effective early detection tools. Current standard-of-care biomarkers show limited sensitivity for early-stage OC and lack specificity in symptomatic populations. Most biomarker studies in OC serum evaluate single molecular classes or compare OC to healthy controls, limiting understanding of coordinated biological alterations in circulating proteins, lipids, and metabolites in clinically relevant populations. Methods: We performed integrated multi-omics profiling of serum from a retrospective, case–control cohort of women presenting with vague abdominal symptoms (VAS), including early- and late-stage OC, borderline tumors, benign gynecologic conditions including adnexal masses, GI disorders, and healthy controls. Protein biomarkers were quantified by ELISA, lipidomic profiling was performed by untargeted LC-MS, and ganglioside and metabolomic profiling were performed by semi-targeted LC-MS with metabolite annotation performed against a curated reference library. Results: Consistent with known limitations for early-stage OC detection, CA125 and HE4 levels overlapped substantially with benign gynecologic conditions. Additional proteins also showed limited separation in their expression between early-stage OC and symptomatic controls. In contrast, OC showed unique lipid and metabolite profiles: phospholipids and glycerolipids were decreased, and sphingolipid composition was altered. Borderline and benign conditions exhibited lipid profiles that fall between healthy and OC groups, suggesting a continuum of metabolic changes rather than distinct states between OC and non-OC controls. Sphingolipid alterations included changes in ceramides and sphingomyelins, along with broader dysregulation of ganglioside profiles, including an elevated GD2;O2-to-GD1;O2 ratio. Metabolic profiling showed decreased amino acids and enriched cysteine metabolism in OC, consistent with altered redox balance, along with changes in fatty acids and acyl-carnitines, suggesting altered lipid metabolism and inflammatory mechanisms. Lower levels of glycolytic and TCA cycle intermediates in OC suggested altered mitochondrial metabolism and energetic reprogramming. Pairwise comparisons revealed a gradient of significance between groups, with differences between OC and healthy controls across lipid classes (LPC, PC, PE, TG, SM), gangliosides (GD1, GD2, GD2/GD1 ratio), and metabolites (amino acids, Cys/CySS, TCA cycle); borderlines occupied an intermediate space. Integration of these datasets revealed coordinated cross-omics relationships, identifying links between metabolite, lipid, and protein features. Together, these connections highlight structured, system-level alterations related to lipid remodeling, redox balance, immune signaling, and energy metabolism that no single modality would have revealed in isolation. Conclusions: This study presents an integrated analysis of the lipidome, gangliosome, metabolome, and protein biomarkers within a single clinically relevant symptomatic cohort enriched with multiple stages and subtypes of OC. This multi-omics framework demonstrates that molecular alterations in OC are biologically interconnected across molecular classes. While these findings are discovery-based and require independent validation prior to clinical application, they support the development of clinically deployable multi-omics biomarker strategies for early detection and potential pathways for therapeutic intervention. Full article
(This article belongs to the Special Issue Advances in Diagnosis of Ovarian Cancer)
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