PapersFlow Research Brief
Ovarian cancer diagnosis and treatment
Research Guide
What is Ovarian cancer diagnosis and treatment?
Ovarian cancer diagnosis and treatment is the clinical and pathological process of detecting, staging, and biologically characterizing ovarian malignancies and then selecting surgery, systemic therapy, and risk-informed prevention strategies to reduce morbidity and mortality.
The research literature on ovarian cancer diagnosis and treatment spans 116,544 works (5-year growth: N/A)."Ovarian cancer statistics, 2018" (2018) estimated 22,240 new U.S. ovarian cancer cases and 14,070 U.S. ovarian cancer deaths in 2018, underscoring the high fatality burden. "Integrated genomic analyses of ovarian carcinoma" (2011) profiled 489 high-grade serous ovarian cancers across multiple molecular layers (mRNA, microRNA, promoter methylation, DNA copy number), establishing a molecular framework that informs biomarker-driven approaches to therapy selection.
Research Sub-Topics
BRCA1 BRCA2 Mutations Ovarian Cancer
Researchers study germline BRCA1/2 mutations' role in hereditary ovarian cancer risk, penetrance estimation, and mutation carrier screening protocols. Population studies combine case series to quantify lifetime risks and modifier effects.
Genomic Profiling High-Grade Serous Ovarian Carcinoma
This area performs integrated multi-omics analyses of TCGA cohorts to identify somatic mutations, copy number alterations, and molecular subtypes in high-grade serous ovarian cancer. Studies correlate genomics with chemotherapy response and survival.
Ovarian Cancer Biomarker Discovery
Investigators validate serum biomarkers like CA-125, HE4, and multi-omics panels for early detection, recurrence monitoring, and differential diagnosis from benign conditions. Prospective trials assess sensitivity and specificity in screening populations.
Platinum Chemotherapy Resistance Mechanisms
Research elucidates molecular pathways including homologous recombination deficiency, ABC transporters, and epigenetic changes conferring resistance to platinum-based therapy in ovarian cancer. Functional genomics identifies synthetic lethal targets.
PARP Inhibitor Therapy Ovarian Cancer
Clinical and translational studies evaluate PARP inhibitors like olaparib in BRCA-mutated and HRD-positive ovarian cancers, exploring combination strategies and resistance evolution. Biomarker-stratified trials guide FDA approvals.
Why It Matters
Ovarian cancer is often lethal because diagnosis frequently occurs after disease has progressed, so practical improvements depend on better risk stratification, accurate classification, and treatment selection. Population-level burden is explicit in "Ovarian cancer statistics, 2018" (2018), which projected 22,240 new diagnoses and 14,070 deaths in the United States in 2018—numbers that motivate both earlier detection strategies and more effective therapies. Genomic characterization has direct clinical relevance: Bell et al. (2011) in "Integrated genomic analyses of ovarian carcinoma" analyzed 489 high-grade serous tumors across gene expression, microRNA, methylation, and copy-number alterations, providing a basis for aligning patients to molecularly informed trials and for interpreting why responses differ across seemingly similar cases. Inherited-risk evaluation is also consequential for prevention and clinical decision-making: Antoniou et al. (2003) in "Average Risks of Breast and Ovarian Cancer Associated with BRCA1 or BRCA2 Mutations Detected in Case Series Unselected for Family History: A Combined Analysis of 22 Studies" and Kuchenbaecker et al. (2017) in "Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers" supply evidence used to counsel mutation carriers about ovarian cancer risk and to justify intensified surveillance and risk-reducing strategies in appropriate patients.
Reading Guide
Where to Start
Start with "Ovarian cancer statistics, 2018" (2018) because it provides concrete incidence and mortality counts (22,240 new U.S. cases; 14,070 U.S. deaths in 2018) that frame why diagnostic and therapeutic decisions matter clinically and publicly.
Key Papers Explained
For disease framing, Torre et al. (2018) in "Ovarian cancer statistics, 2018" quantifies the U.S. burden. For biology that underpins modern treatment thinking, Bell et al. (2011) in "Integrated genomic analyses of ovarian carcinoma" establishes multi-omic heterogeneity from 489 high-grade serous tumors. For inherited-risk and prevention counseling, Antoniou et al. (2003) in "Average Risks of Breast and Ovarian Cancer Associated with BRCA1 or BRCA2 Mutations Detected in Case Series Unselected for Family History: A Combined Analysis of 22 Studies" and Kuchenbaecker et al. (2017) in "Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers" provide the BRCA1/2 risk evidence base, with Ford et al. (1998) in "Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families" adding penetrance/heterogeneity context. For diagnostic classification language, Tavassoli and Devilee (2003) in "Pathology and Genetics of Tumours of the Breast and Female Genital Organs" anchors histopathology and genetics conventions used to interpret tumor type and grade.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
A practical frontier implied by the provided core papers is tighter integration of multi-omic tumor profiling (Bell et al., 2011) with standardized pathologic classification (Tavassoli and Devilee, 2003) and inherited-risk modeling (Antoniou et al., 2003; Kuchenbaecker et al., 2017) to produce unified, clinic-ready decision pathways. Another advanced direction is translating population-level burden (Torre et al., 2018) into subtype-specific prevention and treatment strategies by linking epidemiologic counts to molecularly defined disease entities.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | Integrated genomic analyses of ovarian carcinoma | 2011 | Nature | 7.9K | ✓ |
| 2 | Revised 2003 consensus on diagnostic criteria and long-term he... | 2003 | Human Reproduction | 5.9K | ✕ |
| 3 | Integrated genomic characterization of endometrial carcinoma | 2013 | Nature | 5.6K | ✓ |
| 4 | Average Risks of Breast and Ovarian Cancer Associated with BRC... | 2003 | The American Journal o... | 3.6K | ✓ |
| 5 | Ovarian cancer statistics, 2018 | 2018 | CA A Cancer Journal fo... | 3.6K | ✓ |
| 6 | Ovarian Cancer | 1993 | — | 3.2K | ✕ |
| 7 | Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and... | 1998 | The American Journal o... | 3.0K | ✓ |
| 8 | Revised FIGO staging for carcinoma of the vulva, cervix, and e... | 2009 | International Journal ... | 2.8K | ✕ |
| 9 | Pathology and Genetics of Tumours of the Breast and Female Gen... | 2003 | International Agency f... | 2.8K | ✕ |
| 10 | Risks of Breast, Ovarian, and Contralateral Breast Cancer for ... | 2017 | JAMA | 2.7K | ✓ |
In the News
FDA Grants Breakthrough Therapy Designation to ...
1. Lilly's sofetabart mipitecan receives U.S. FDA's breakthrough therapy designation for the treatment of certain patients with platinum-resistant ovarian cancer. News release. Eli Lilly and Compan...
Suvemcitug plus chemotherapy in women with platinum-resistant recurrent ovarian cancer: the SCORES randomized, double-blinded, phase 3 trial
Ovarian cancer (OC) is the most lethal gynecological malignancy, with 324,938 new cases and 206,834 deaths in 2022 globally 1 . Platinum-based chemotherapy plus paclitaxel with or without bevacizum...
FDA Grants Breakthrough Therapy Designation to R-DXd ...
The FDA has granted breakthrough therapy designation to raludotatug deruxtecan (R-DXd), a potential first-in-class CDH6-directed antibody-drug conjugate (ADC), for the treatment of adult patients w...
OvarianVax Funding Announcement
Over a decade of research by Professor Ahmed at Oxford, funded by Ovarian Cancer Action, has led to this. Scientists discovered that immune cells in the fallopian tubes, where most ovarian cancers ...
Ovarian Cancer Research Grant Programs | OCRA
KVIA-TV ABC-7 News El Paso recently spotlighted the groundbreaking work of OCRA-funded researcher Daniel Heller, PhD of Memorial Sloan Kettering Cancer Center, whose research lab is working to deve...
Code & Tools
This project aims to classify ovarian cancer histopathology images using the EfficientNetB3 model. By leveraging state-of-the-art deep learning tec...
## Installation Guide OVision Installation Guide.pdf ( back to top ) ## Usage OVision - 3 click process to get results to aid create prognost...
precision oncology system for patient selection and guiding ovarian cancer treatment.
A deep learning based library for segmentation of high grade serous ovarian cancer on CT images.
We introduce a novel diagnostic algorithm and an R package, OvRSeq, for comprehensive RNA sequencing-based characterization of HGSOC samples. Lever...
Recent Preprints
Therapeutic landscape of ovarian cancer: recent advances ...
Ovarian cancer ranks as the seventh most common malignancy and the eighth leading cause of cancer-related death in women worldwide. Most patients are diagnosed at an advanced stage, resulting in po...
Artificial intelligence for ovarian cancer diagnosis via ...
**Background:**Early and accurate detection of ovarian cancer (OC) remains clinically challenging, prompting exploration of artificial intelligence (AI)-based ultrasound diagnostics. This systemati...
Advances in ovarian cancer: biological insights, therapeutic innovations, and future perspectives
Ovarian cancer (OC) remains a highly lethal gynecologic malignancy characterized by substantial molecular heterogeneity and diagnostic challenges. Although many reviews examine specific aspects of ...
the randomized phase 2 SOLACE2 trial
## Abstract
International Journal of Gynecological Cancer: Home Page
The International Journal of Gynecological Cancer (IJGC) serves as the primary educational and informational publication on topics related to the detection, prevention, diagnosis, and treatment of ...
Latest Developments
Recent developments in ovarian cancer diagnosis and treatment research include the launch of a Phase II clinical trial for an ovarian cancer vaccine targeting early recurrence, which is a significant milestone in the field as of early 2026 (uwcvi.org). Additionally, new treatments such as FDA-approved drugs like Elahere for advanced ovarian cancers and promising clinical trials involving targeted therapies, PARP inhibitors, antibody-drug conjugates, and immunotherapies are advancing the field (cancer.gov; ovarian.org).
Sources
Frequently Asked Questions
What is the difference between ovarian cancer diagnosis and ovarian cancer screening?
Ovarian cancer diagnosis refers to evaluating a patient with symptoms or findings to confirm malignancy and define disease type and extent, whereas screening refers to testing asymptomatic people to detect cancer earlier. The provided papers emphasize disease burden (e.g., Torre et al., 2018) and molecular classification (Bell et al., 2011) rather than establishing a population screening test.
How does genomic profiling inform ovarian cancer treatment selection?
Bell et al. (2011) in "Integrated genomic analyses of ovarian carcinoma" characterized 489 high-grade serous ovarian cancers using mRNA, microRNA, promoter methylation, and DNA copy-number data, demonstrating substantial molecular heterogeneity. That heterogeneity is used clinically to motivate biomarker-driven stratification and to interpret variable treatment responses among patients with the same histologic diagnosis.
Which papers in the provided list are most relevant for inherited risk assessment in ovarian cancer?
Antoniou et al. (2003) in "Average Risks of Breast and Ovarian Cancer Associated with BRCA1 or BRCA2 Mutations Detected in Case Series Unselected for Family History: A Combined Analysis of 22 Studies" and Kuchenbaecker et al. (2017) in "Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers" are directly focused on BRCA1/2-associated cancer risks. Ford et al. (1998) in "Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families" provides additional context on heterogeneity and penetrance relevant to counseling.
Which references support the pathologic classification framework used in ovarian cancer diagnosis?
"Pathology and Genetics of Tumours of the Breast and Female Genital Organs" (2003) provides a pathology-and-genetics reference framework used for tumor classification. Rubin and Stephen (1993) in "Ovarian Cancer" is a highly cited general reference that can be used to orient clinicians to diagnostic and therapeutic fundamentals.
What is the role of staging in ovarian cancer treatment planning, and which paper addresses staging systems?
Staging organizes disease extent to guide prognosis estimation and treatment planning, including decisions about surgery and systemic therapy intensity. Pecorelli (2009) in "Revised FIGO staging for carcinoma of the vulva, cervix, and endometrium" is a key FIGO staging reference in gynecologic oncology; while not ovarian-specific in title, it is commonly consulted alongside ovarian staging guidance in practice.
Which paper provides a concrete, citable estimate of ovarian cancer burden in the United States?
Torre et al. (2018) in "Ovarian cancer statistics, 2018" estimated that in 2018 there would be approximately 22,240 new ovarian cancer cases and 14,070 ovarian cancer deaths in the United States. Those figures are frequently used to justify research priorities in diagnosis, prevention, and treatment.
Open Research Questions
- ? Which molecular aberration patterns identified in "Integrated genomic analyses of ovarian carcinoma" (2011) best stratify high-grade serous ovarian cancer into treatment-responsive versus treatment-refractory subgroups when applied prospectively?
- ? How should BRCA1/2 risk estimates from "Average Risks of Breast and Ovarian Cancer Associated with BRCA1 or BRCA2 Mutations Detected in Case Series Unselected for Family History: A Combined Analysis of 22 Studies" (2003) and "Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers" (2017) be integrated with family history and mutation characteristics to optimize individualized prevention pathways?
- ? Which tumor classification elements emphasized in "Pathology and Genetics of Tumours of the Breast and Female Genital Organs" (2003) are most predictive of clinically meaningful molecular subtypes described in "Integrated genomic analyses of ovarian carcinoma" (2011)?
- ? What is the minimal molecular testing set that preserves most of the clinically actionable heterogeneity observed in the multi-omic design of "Integrated genomic analyses of ovarian carcinoma" (2011) while remaining feasible for routine diagnostics?
- ? How can population burden estimates such as those in "Ovarian cancer statistics, 2018" (2018) be decomposed by biologically defined subtypes (as in Bell et al., 2011) to better target prevention and early-detection research?
Recent Trends
The provided corpus shows sustained, large-scale attention to ovarian cancer diagnosis and treatment (116,544 works; 5-year growth: N/A), with highly cited anchors spanning epidemiology, genomics, pathology, and inherited risk.
Recent emphasis within the provided papers is the move from histology-only characterization toward multi-omic tumor definition: Bell et al. in "Integrated genomic analyses of ovarian carcinoma" analyzed 489 high-grade serous tumors across mRNA, microRNA, methylation, and copy-number alterations, a design that supports subtype-aware clinical reasoning.
2011In parallel, risk stratification for prevention and management has been strengthened by BRCA1/2-focused evidence syntheses and prospective estimates, including Antoniou et al. in "Average Risks of Breast and Ovarian Cancer Associated with BRCA1 or BRCA2 Mutations Detected in Case Series Unselected for Family History: A Combined Analysis of 22 Studies" and Kuchenbaecker et al. (2017) in "Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers".
2003Research Ovarian cancer diagnosis and treatment with AI
PapersFlow provides specialized AI tools for your field researchers. Here are the most relevant for this topic:
AI Literature Review
Automate paper discovery and synthesis across 474M+ papers
Deep Research Reports
Multi-source evidence synthesis with counter-evidence
Paper Summarizer
Get structured summaries of any paper in seconds
AI Academic Writing
Write research papers with AI assistance and LaTeX support
Start Researching Ovarian cancer diagnosis and treatment with AI
Search 474M+ papers, run AI-powered literature reviews, and write with integrated citations — all in one workspace.