ArticleNature communications2024
Proteomic landscape of epithelial ovarian cancer.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed.
- Nanotherapeutics for enhanced treatments for ovarian cancer: a comprehensive minireview.Drug delivery · 2026Review
- Cell-Type-Resolved Proteomics Reveals Distinct Immune and Metabolic Programs Between Primary and Recurrent Ascites in HGSOC.Proteomics. Clinical applications · 2026Article
- The phosphoproteome of ovarian carcinoma delineates signaling signatures and potentially druggable targets across histotype stages.NPJ precision oncology · 2026Article
- Integrative Analysis of Gene and Protein Expression Data Reveals Novel Clusters for Ovarian Cancer Prognosis.International journal of molecular sciences · 2026Article
- Prognostic analysis of epithelial ovarian cancer patients with normal CA125 level: a population-based comparative study.Scientific reports · 2026Article
- Article
- Extracellular vesicle and particle biomarkers in cancer: a machine learning blueprint for liquid biopsy.Journal of nanobiotechnology · 2026Review
- A comparative analysis of serum and tissue proteomic profiles in non-small cell lung cancer patients with or without brain metastasis.Cell death discovery · 2026Article
- Analysing cell death patterns to predict outcomes and treatment options in patients with high-grade serous ovarian carcinoma.Scientific reports · 2026Article
- Deep spatial transcriptomic profiling of ovarian clear cell carcinoma in the real-world setting.Journal of ovarian research · 2026Article
- Molecular and cellular landscapes of the immune microenvironment and multiomic biomarker-sets in platinum-resistant recurrent ovarian cancers.Journal of ovarian research · 2026Review
- Dose-response relationship between ascites volume and survival in high-grade serous ovarian cancer: a prospective cohort study.Gland surgery · 2026Article
- Article
- Evolution of Multivalent Aptamer Corona for High-Throughput Multiplexed Detection of Multiple Cancers.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Metastatic organotropism in peritoneal metastasis: Paget's hypothesis revisited.Clinical and experimental medicine · 2026Review
- Proteomic analysis of ovarian carcinoma reveals diagnostic and prognostic biomarkers with histotype- and stage-specificity.Journal of ovarian research · 2026Article
- Anatomical precision in the omics era: a proposed framework for selective para-aortic lymphadenectomy in epithelial ovarian cancer.Frontiers in medicine · 2026Review
- Spatial proteomics of ovarian cancer precursors delineates early disease changes and drug targets.Molecular systems biology · 2026Article
- A machine learning-based framework for prognostic prediction and tumor microenvironment characterization of locally advanced cervical cancer with concurrent chemoradiotherapy.NPJ precision oncology · 2025Article
- Machine learning-guided deconvolution of plasma protein levels.Molecular systems biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.