Loading
Life sciences · Review
Frontiers in Oncology · October 13, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Review.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
Poly (ADP-ribose) polymerase inhibitors (PARPi) have revolutionized the management of high-grade serous ovarian cancer (HGSOC). Yet, current treatment decisions remain almost exclusively guided by static BRCA/homologous recombination deficiency (HRD) genotyping. This paradigm is increasingly challenged by a profound eligibility–benefit gap: real-world data show 93.4% of patients are PARPi-eligible, but only 22.0% achieve meaningful 2-year progression-free survival benefit, compounded by 10–30% HRD test failure rates, inability to capture dynamic resistance evolution, and negligible predictive value in the ~50% of HGSOC that are homologous recombination-proficient. This narrative review, based on literature up to June 2026, systematically evaluates functional biomarkers that complement BRCA/HRD testing by assessing real-time tumor biology. To our knowledge, this is the first review to integrate these biomarkers into a unified whole-disease-course framework accounting for evidence level, assay cost, and global resource setting. RAD51 immunohistochemistry directly visualizes homologous recombination repair capacity, achieving 95% accuracy in predicting PARPi response in preclinical patient-derived xenograft models and demonstrating robust predictive value in prospective clinical cohorts. The KELIM model, derived from early CA-125 kinetics and evaluated in >12,000 patients within prospective trial and registry datasets, provides a no-additional-assay-cost, tissue-independent readout of chemosensitivity with potential for broad, low-cost global deployment. Circulating tumor DNA enables noninvasive longitudinal monitoring of resistance, potentially preceding radiographic progression by weeks to months. Exploratory immune and artificial intelligence-based multimodal markers further refine response stratification. We propose deployment of these biomarkers at four critical clinical nodes—diagnosis, post-chemotherapy, maintenance, and progression—to guide therapy selection dynamically. By transitioning from static genotype-based eligibility to real-time functional phenotyping, this integrated strategy aims to close the eligibility–benefit gap and advance adaptive precision oncology for ovarian cancer globally. As a narrative review, this work aims to offer forward-looking conceptual frameworks and stimulate future research rather than to establish high-level clinical evidence or formal guidelines.