Skip to main content
Back to timeline
CancerSource publication:

The Evolving Role of Immunotherapy in Ovarian Cancer: From Empirical Use Toward Biology-Driven Combination and Precision Strategies

Synopsis

This review synthesizes the clinical evidence and resistance mechanisms for immunotherapy in ovarian cancer, noting that single-agent immune checkpoint inhibitors achieve objective response rates generally below 15% in recurrent disease, that the clearest added benefit appears in chemotherapy-based combinations for PD-L1-positive platinum-resistant disease (e.g., in ENGOT-ov65/KEYNOTE-B96, median overall survival 18.2 vs 14.0 months in the CPS >=1 population, HR 0.

Source-provided article image: The evolving role of immunotherapy in ovarian cancer.
FIGURE 1 ·

Schematic illustrating the spectrum of tumor immune phenotypes and therapeutic strategies to reprogram the TME in ovarian cancer. ( Left ) The cold tumor microenvironment is characterized by immune cell exclusion, hypoxia, dense ECM, and nutrient deficiency and is dominated by immunosuppressive cell populations, including MDSCs, M2‐like TAMs, and Tregs. ( Right ) In contrast, hot tumors display increased immune cell infiltration, activation of cytotoxic lymphocytes, normalized vasculature, reduced ECM density, and improved metabolic conditions. ( Center ) The intermediate immune‐excluded phenotype is defined by the presence of immune cells at the tumor periphery with limited intratumoral penetration, often associated with stromal barriers, vascular dysfunction, and persistent metabolic constraints. Therapeutic strategies aimed at promoting the transition from cold or immune‐excluded tumors to hot tumors include immune checkpoint inhibitors, targeting of immunosuppressive cell populations, stromal remodeling, and metabolic modulation as well as emerging approaches involving the microbiome and neural–tumor interactions. CTL indicates cytotoxic T lymphocyte; CTLA‐4, cytotoxic T‐lymphocyte–associated protein 4; ECM, extracellular matrix; IDO1, indoleamine 2,3‐dioxygenase 1; LAG‐3, lymphocyte‐activation gene 3; MDSC, myeloid‐derived suppressor cell; NK, natural killer cell; PD‐L1, programmed death‐ligand 1; TAMs, tumor‐associated macrophages; TIM‐3, T‐cell immunoglobulin and mucin domain–containing 3; TME, tumor microenvironment; Tregs, regulatory T cells; VEGF, vascular endothelial growth factor.

PubMed

Interpretation

The review compiles randomized and early-phase trial results of immune checkpoint inhibitors across lines of therapy in ovarian cancer, indicating limited single-agent PD-1/PD-L1 activity while chemotherapy combinations show overall survival benefit in platinum-resistant, PD-L1-positive populations. Relative to prior narratives treating immunotherapy as a cross-tumor breakthrough, this work stratifies evidence by first-line, platinum-sensitive relapse, and platinum-resistant settings, distinguishing which combinations yielded positive versus negative results. Based on multiple phase 3 randomized trials (e.g., IMagyn050, JAVELIN 100, ATHENA-COMBO, ATALANTE, ANITA, NINJA, ENGOT-ov65/KEYNOTE-B96) and early-phase single-arm studies, with specific median PFS, OS, HR, and p values reported.

The review proposes classifying ovarian cancer into cold, immune-excluded, and hot immune phenotypes, using this to explain immunotherapy resistance and to guide combination strategies. It frames resistance around the presence and spatial distribution of tumor-infiltrating lymphocytes, extending the problem from a single-marker level to the microenvironment level. A conceptual and mechanistic review, citing observations such as approximately half of high-grade serous carcinomas showing significant intratumoral T-cell infiltration as an independent predictor of improved outcome, without new primary data.

The review argues that PFS benefit from PARP inhibitor plus immune checkpoint inhibitor combinations in the first-line setting is largely driven by the PARP inhibitor, with immunotherapy contributing minimally or possibly detrimentally. It compares KEYLYNK-001, FIRST, DUO-O, and ATHENA-COMBO, offering a reinterpretation of each component's contribution within combination regimens. Grounded in multiple phase 3 trial results, including numerically inferior PFS with the addition of nivolumab to rucaparib in ATHENA-COMBO (15.0 vs 20.2 months, HR 1.3) and modest PFS improvement without OS benefit in FIRST.

The review systematically organizes early clinical data and ongoing trials for adoptive cell therapies, vaccines, dendritic cell therapy, and oncolytic viruses. It presents these early-stage approaches alongside phase 3 checkpoint inhibitor evidence, outlining a roadmap expanding from T-cell-centered approaches to NK cells, bispecific antibodies, and neoantigen vaccines. Mainly based on phase 1/2 single-arm trials and registered ongoing trials, such as the unconfirmed ORR of 33% and disease control rate of 67% for CLDN6-targeted CAR-T plus RNA vaccine in BNT211-01, and PFS and OS signals for DCVAC in SOV01/SOV02.

Perspective

This review is intended for clinical oncologists and translational researchers, applicable to understanding the current evidence landscape and trial design logic for immunotherapy in epithelial ovarian cancer (especially high-grade serous carcinoma); its conclusions pertain to specific lines of therapy, biomarker states, and histologic subtypes, serving to guide patient selection and combination regimen design rather than providing a uniform treatment pathway for direct application.

Several open questions remain: the optimal strategy for patients progressing after PARP inhibitor or bevacizumab maintenance is not yet established; the predictive value of markers such as PD-L1, tumor mutational burden, microsatellite instability-high, and immune-cell infiltrates is still being evaluated; the immunomodulatory effects of antibody-drug conjugates and the integration of multimodal data by artificial intelligence for response prediction require prospective validation; additionally, as a review, this article provides no new primary data, and the specific content of Figure 1, Figure 2, and supplementary Table S1 is presented here through figure legends and textual descriptions within the scope of this reading.

Sources